As the EU invests in AI gigafactories, France is confronting the land, water and energy behind digital growth. The challenge is to use AI where it creates genuine value without treating natural resources as unlimited.

On 10 July 2026, the Grenoble Administrative Court suspended the building permit for an artificial intelligence computer centre near Valence.

The project would require more than 60 MW of electrical power at full capacity. The court found that an environmental impact assessment should have been carried out and identified serious doubts about whether the installation complied with local planning rules. The decision is temporary, pending a final ruling. [1]

Twelve days later, ADEME published a position paper on the environmental effects of generative and agentic AI. It highlighted rising demand for data centres, energy, hardware, land and water, alongside the difficulty of measuring these impacts, given that leading providers disclose so little about their models and infrastructure. [2]

Then, on 30 July, the European Union launched a call for up to seven AI gigafactories. The programme could receive up to €10 billion in European and national public funding and is expected to mobilise at least €20 billion in private investment. Its purpose is to strengthen Europe’s computing capacity and technological sovereignty. [3]

Together, these decisions bring a less visible part of AI growth into focus. Data centres are built in real territories, where land, electricity and water are shared with communities and ecosystems.

Europe has legitimate reasons to seek technological sovereignty, but forecasts of future demand should not be enough on their own to justify additional infrastructure. They should open a wider discussion about which uses create genuine value, where new capacity can be built responsibly and what environmental limits should apply.

Europe’s AI ambition is becoming physical

Technological sovereignty is usually discussed in terms of model ownership, data residency, security, and regulation.

• Can European organisations rely on foreign providers for critical infrastructure?
• Where is their data processed?
• Which jurisdiction controls the service?
• Can European startups compete without depending entirely on American hyperscalers?

These concerns are legitimate, but sovereignty also has a physical layer that receives far less attention.

Advanced AI requires computing capacity. That capacity depends on processors, servers, electricity, cooling systems, suitable land and network connections.

The EU’s gigafactory programme is designed to expand this foundation. The selected sites will combine advanced processors, cloud technologies, high-speed connectivity and energy-efficient data centres. They will support the training, fine-tuning and inference of advanced models for startups, SMEs, researchers, industry and public authorities. [3]

Companies cannot build competitive AI products without access to infrastructure, but bringing more computing capacity into Europe also brings its constraints closer to European territories.

Why France can still be a strategic location

There is also a legitimate environmental argument for locating some capacity in France. RTE notes that French electricity production is more than 95% decarbonised, meaning that workloads hosted in France may have a lower operational carbon footprint than equivalent activity powered by more carbon-intensive grids. The distinction, however, is whether new French capacity replaces activity elsewhere or simply adds to total global demand. [16]

The sovereignty question therefore becomes more demanding: Can Europe expand AI capacity without treating energy, water and land as invisible inputs?

The answer will shape more than environmental policy. It will influence where infrastructure can be built, how quickly capacity becomes available, what providers charge and which companies can afford to compete.

The territorial cost of computing capacity

Land cannot be treated as a neutral surface available for digital expansion. The Office français de la biodiversité notes that soils host close to 60% of terrestrial biodiversity and that artificialisation damages their biological, hydrological and climatic functions, while destroying and fragmenting habitats.

New infrastructure should therefore prioritise existing industrial and already artificialised sites before consuming natural, agricultural or forest land. [9]

Water reveals the measurement gap

AI’s water footprint has become one of the most visible parts of the infrastructure debate.

Data centres may use water directly for cooling. Water is also involved indirectly through electricity generation and the manufacture of processors, servers and other equipment.

But the numbers are easy to misuse because they often measure different things. These categories are not interchangeable:

• Water withdrawn from a local supply
• Water consumed and not returned to the same system
• Potable water used for cooling
• Indirect water associated with electricity production
• Training or inference
• Operational use or the full lifecycle

ARCEP reported that the French data centres covered by its environmental survey withdrew 681,000 cubic metres of water in 2023, primarily drinking water. That represented a 19% annual increase, although ARCEP notes that the total remains modest compared with withdrawals for other activities. [4]

The French competition authority estimates that the electricity consumed by data centres is associated with more than 5.2 million cubic metres of indirect water withdrawals each year. [5]

National averages can hide local pressure

National totals can appear modest while local pressure remains significant. Water availability varies by season and river basin, and withdrawals during dry periods occur when rivers, wetlands, soils and vegetation may already be under stress. Water scarcity affected 28% of EU territory and 32% of its population during at least one season in 2023. [10]

Data centres are not currently France’s largest water or electricity users. ARCEP describes their direct water withdrawals as modest compared with other activities, while RTE estimates that data centres account for around 2% of French electricity consumption today. The concern is therefore not that they represent the country’s dominant environmental pressure, but that their resource demand is rising quickly, new facilities are becoming considerably larger and local impacts can be concentrated in particular territories and river basins. [4][16]

Why AI-specific figures remain unavailable

The two figures describe different parts of the system. More importantly, neither represents AI alone.

Data centres also support cloud services, websites, financial systems, streaming, storage and conventional enterprise software. Public facility-level reporting cannot currently isolate the water used by one model, product or marketing workflow.

This is why simple statements such as “AI consumed this much water in France” are unreliable.

Why litres per prompt can mislead

Turning an AI interaction into a bottle or glass of water makes an invisible system easier to imagine.

It can also create false precision.

The footprint of a response depends on factors including:

• The model and its size
• Length and complexity of the task
• Number of model calls
• Hardware
• Data-centre location
• Cooling system
• Electricity mix
• Boundaries of the assessment

Mistral offers one of the few public, model-specific examples.

Its lifecycle assessment estimates that a 400-token response from Le Chat, excluding the user’s device, is associated with 1.14 grams of CO₂ equivalent and 45 millilitres of water consumption. [6]

The figure is meaningful within the specific model, infrastructure and methodology assessed by Mistral, but it cannot be generalised to ChatGPT, Claude, Gemini or every Le Chat interaction.

Mistral also acknowledges that environmental accounting for large language models remains incomplete. Hardware data is limited, methodologies are not yet fully standardised, and providers do not all measure the same boundaries.

Without context, environmental efficiency risks becoming another vague product badge.

Growth teams influence which demand gets scaled

Growth teams may not control data-centre cooling or processor manufacturing, but their decisions influence the demand placed on that infrastructure.

They help decide:

• Which tools enter the stack
• Which processes are automated
• How many model calls a workflow makes
• Whether every visitor receives live personalisation
• How much content is generated
• How widely automated outreach is deployed
• Whether complex models are used for simple tasks
• Whether an underperforming experiment continues to run

These choices affect both commercial efficiency and infrastructure demand.

The French competition authority estimates that electricity represents approximately 30% to 50% of a data centre’s operating costs. It also argues that AI frugality could become a competitive factor by enabling providers, including smaller companies, to offer efficient services at lower cost. [5]

AI changes the economics of software usage

Once built, a conventional software feature may cost very little each time it is used. An AI feature creates variable costs whenever a model is called, particularly when it uses a large model, generates rich media or chains several steps together.

Growth teams already decide which activities receive budget, automation and scale. That same discipline can reduce unnecessary ecological demand by limiting duplicated outputs, excessive model calls, real-time personalisation with no proven benefit and large models used for simple tasks.

Commercial efficiency still matters, but it should support a wider objective: creating useful outcomes without treating infrastructure as limitless.

When efficiency increases consumption

Generative AI has lowered the time and monetary cost of producing many marketing outputs.

A team can create more campaign concepts, email variations, advertisements and landing-page drafts than it could produce manually.

This can improve experimentation and execution, but it can also encourage teams to scale output before proving its value.

ADEME specifically warns that AI assessments must account for indirect effects, including rebound effects. When a process becomes more efficient and accessible, total usage may rise enough to offset part of the original saving. [2]

Growth has seen this pattern before: more advertising inventory did not guarantee better acquisition, automation did not necessarily improve nurturing, and a larger volume of content did not automatically create authority or organic demand. AI can amplify the same mistakes at much greater speed.

Content

Producing 100 articles instead of ten is not a growth result.

If the additional content repeats existing ideas, competes for the same search intent or attracts irrelevant traffic, production has scaled while demand has not.

Outbound

AI can research accounts and generate personalised messages at considerable volume.

If targeting is poor, it simply makes irrelevant outreach look more polished. The business creates more activity, model usage and reputational risk without producing more qualified conversations.

Agents

One customer request may trigger planning, retrieval, reasoning, verification and generation across several model calls.

What matters is not the number of actions performed, but the proportion of tasks completed correctly and with proportionate resources.

When production becomes cheaper, the risk is not simply that companies create more. It is that they create more without becoming more useful.

Efficiency needs an ecological boundary

Improving energy efficiency per request will not be enough if the total number of requests, features and facilities continues to rise. A more efficient system can still increase overall pressure when it is deployed everywhere, including where it adds little value.

Growth teams therefore need to assess necessity before optimisation. Before asking how cheaply or efficiently a workflow can run, they should ask whether it needs AI, whether a simpler system can perform the task, and whether the outcome justifies the additional demand.

From cost per token to cost per useful outcome

Tokens are valuable for technical monitoring and billing.

A cheaper model call is not automatically a better decision if the result requires extensive correction, creates a poor customer experience or fails to influence revenue.

Commercial cost per useful outcome

Cost per Useful Outcome offers a more useful starting point by connecting the full operational cost of a workflow to a verified result. The principle is not new. It applies familiar unit-economics thinking to AI workflows, while tracking resource intensity alongside financial and operational costs.

It can improve commercial discipline, but it should sit within clear ecological limits. A workflow may perform well financially and still be unacceptable if it depends on avoidable infrastructure, unnecessary land artificialisation or additional withdrawals in a water-stressed territory.

The calculation should include: Platform and API costs + implementation + human review + correction and failure costs

divided by: Verified successful outcomes

The successful outcome depends on the use case. It could be:

• Qualified meeting
• Incremental conversion
• Activated user
• Retained customer
• Accurately resolved request
• Completed internal task
• Creative asset that improved campaign performance

The outcome must be defined before the workflow is expanded.

Resource intensity per useful outcome

Environmental and technical indicators should be tracked alongside the commercial calculation, not mixed into the same unit.

Depending on the data available, these could include:

• Model calls per successful outcome
• Tokens or compute per outcome
• Energy per outcome
• Water estimates supplied by the provider
• Percentage of work routed through smaller models
• Human corrections per outcome
• Quality of the vendor’s environmental disclosure

The objective is to make a better commercial decision about whether each use case merits continued investment.

What resource-aware growth looks like

Resource-aware growth requires the same discipline already expected in acquisition, experimentation and revenue operations.

Begin with a defined problem

“We need an AI agent” is not a business case.

“We need to reduce the time Sales spends researching accounts without lowering research quality” is one.

A clear problem makes it possible to compare the AI-supported workflow with the existing process.

Establish a baseline

Before implementation, measure:

• Time required
• Current cost
• Output quality
• Error rate
• Conversion or completion rate

Without a baseline, adoption is easily confused with improvement.

Prove incrementality

Use control groups, phased deployment or before-and-after analysis to determine whether AI changed the outcome.

A generated landing-page variation that performs no better than the original has not created incremental growth.

Match the model to the task

Not every activity requires the largest available model.

Classification, extraction, routing and structured rewriting may be handled effectively by smaller or specialised systems.

A more resource-intensive model is justified when it materially improves accuracy, commercial performance or risk management.

Build stopping rules

AI workflows can expand automatically, which makes operational limits essential.

These may include:

• Usage budgets
• Maximum calls per task
• Model-routing rules
• Confidence thresholds
• Human review requirements
• Content-volume limits
• Performance thresholds below which an experiment stops

Ask vendors better questions

Buyers may not receive complete environmental data today, but they can still ask:

• Where are workloads processed?
• Can the model or processing region be selected?
• Are smaller models available?
• Does the system use model routing?
• Is usage visible by workflow?
• Has the provider published lifecycle or inference data?
• What does its methodology include?
• Which impacts remain estimated?

The ability to answer clearly can become part of vendor trust.

What should Europe require before scaling further?

The EU already requires data centres with installed IT power demand of at least 500 kW to report energy and water indicators to a European database.

The framework covers total energy and water use, Power Usage Effectiveness, Water Usage Effectiveness and waste-heat reuse. Public information is currently published at aggregated Member State and EU levels. [7][8]

The Commission is also preparing a wider Data Centre Energy Efficiency Package, including a common European rating scheme and future minimum performance standards. [7]

This does not yet provide workload-level transparency. A buyer cannot use the database to identify the water footprint of its chatbot or campaign.

Energy and water efficiency are moving from an internal infrastructure concern towards reporting, procurement and competition.

From reporting to responsible infrastructure decisions

Europe now has an opportunity to define the conditions under which additional capacity is acceptable. Rather than treating every forecast of AI demand as a reason to build, policymakers, providers and buyers should ask:

• Can an existing industrial or artificialised site be reused?
• Is the proposed location already exposed to water stress?
• Has a complete environmental assessment been carried out?
• Would the facility replace existing foreign capacity or simply add to total demand?
• How will habitats, soils and ecological corridors be protected?
• Could smaller models or fewer calls deliver the same outcome?
• Can users disable generative features they do not need?
• Are energy, water, hardware and lifecycle impacts reported transparently?

A credible provider should be able to explain which models it uses, where workloads run, how tasks are routed, what its assessment includes and how efficiency changes across use cases.

The French competition authority has already identified frugality as a potential competitive parameter that can influence price, quality and innovation. [5]

These conditions could help Europe develop an AI model shaped by greater transparency, resource restraint and territorial responsibility, rather than measuring success only through capacity.

FAQ

Does every AI prompt consume the same amount of water?

No. The result depends on the model, task, hardware, location, cooling technology, electricity source and assessment methodology. A number calculated for one provider should not be generalised to all AI interactions.

Did the French court suspend the Alixan project because of water consumption?

No. The court found that the project required an environmental impact assessment and identified serious doubts about compliance with planning rules. The decision is an interim suspension, not a final cancellation. [1]

Are France’s data-centre water figures specific to AI?

No. Data centres support many digital activities. Current public reporting does not isolate AI workloads from the rest of a facility’s operations. [4][5]

Should companies use less AI?

The better goal is selective and measurable use. Companies should identify where AI creates meaningful value, choose an appropriate model and stop expanding workflows that produce activity without useful results.

Why should growth teams care?

Growth teams influence which workflows are deployed, how frequently models are called and whether those systems continue to scale. These decisions affect margins, customer experience and infrastructure demand.

Can efficiency become a competitive advantage for European AI?

Potentially. Efficient models, regional infrastructure, transparent methodologies and auditable reporting can support lower costs, stronger procurement cases and greater trust. European origin alone is not enough.

Conclusion

July 2026 has made the tension surrounding Europe’s AI ambitions unusually visible. A French court suspended an AI infrastructure permit because the required environmental assessment had not been carried out, ADEME called for greater transparency and lifecycle measurement, and the EU launched its call for up to seven AI gigafactories, backed by up to €10 billion in potential public funding and at least €20 billion in expected private investment. [1][2][3]

These developments are unfolding within a wider ecological reality. Earth Overshoot Day fell on 30 July, while France was experiencing its third official heatwave of the summer and nearly 495,000 hectares had been mapped as burned across the EU in 2026. These events were not caused by AI infrastructure, but they show how heavily land, water and energy systems are already being tested. Additional data-centre capacity can increase that pressure, particularly in water-scarce regions and during periods of extreme heat. [11][12][13]

AI can support research, medicine, accessibility, conservation and everyday work. Its usefulness should encourage more careful decisions about which applications deserve to scale and what each new facility asks of land, water and energy.

Water must remain a public and ecological priority

Water is both a human right and a shared ecological resource. French law gives priority to essential human needs while requiring the protection of aquatic ecosystems and natural water systems. These principles should define the conditions under which industrial and digital uses are authorised, particularly during droughts and heatwaves. [14][15]

Europe still has an opportunity to regulate before rising demand becomes difficult to challenge. This means careful siting, full environmental assessments, transparent lifecycle information, smaller or specialised models where they are sufficient, and the ability to refuse projects whose public value does not justify their local ecological cost.

Where growth teams can make a difference

Growth teams influence which applications become normal, which experiments continue and which automated processes multiply. Measuring useful outcomes can help distinguish applications that genuinely improve people’s work or lives from those that mainly produce more volume.

AI is already part of our economic and social systems, which makes strong regulation essential. European leadership should be judged not only by the computing capacity it builds, but by the care with which it decides what deserves scarce land, water and energy.

💌 If you want more essays on ethical growth, trust-led marketing and practical B2B growth systems, you can join Conscious Growth Dispatch here.

Sources

[1] Grenoble Administrative Court, Suspension du projet de Datacenter à Alixan, 10 July 2026. The court temporarily suspended the permit for an AI computer centre requiring more than 60 MW at full capacity.

[2] ADEME, IA générative, comment quantifier les impacts ?, 22 July 2026. ADEME reviews the direct and indirect environmental effects of generative and agentic AI and recommends standardised measurement, greater transparency and attention to rebound effects.

[3] European Commission Representation in France, L’UE lance un appel d’offres pour les giga-fabriques d’IA, 30 July 2026. The call supports up to seven gigafactories with up to €10 billion in public funding and at least €20 billion in expected private investment.

[4] ARCEP, Enquête annuelle Pour un numérique soutenable, 17 April 2025. ARCEP reports that the French data centres covered by its survey withdrew 681,000 cubic metres of water in 2023, primarily drinking water.

[5] Autorité de la concurrence, Étude sur les enjeux concurrentiels liés à l’impact énergétique et environnemental de l’intelligence artificielle, 17 December 2025. The study covers energy costs, direct and indirect water use, environmental transparency and AI frugality as a competitive parameter.

[6] Mistral AI, Our contribution to a global environmental standard for AI, 22 July 2025. Mistral reports the lifecycle footprint of Mistral Large 2 and the estimated marginal impact of a 400-token Le Chat response.

[7] European Commission, Energy performance of data centres, accessed 31 July 2026. The page explains the European reporting database, its water and energy indicators and the planned Data Centre Energy Efficiency Package.

[8] European Union, Commission Delegated Regulation (EU) 2024/1364, 14 March 2024. The regulation establishes reporting requirements and sustainability indicators for data centres with installed IT power demand of at least 500 kW.

[9] Office français de la biodiversité, Lutter contre l’artificialisation des sols. The OFB explains that soils host close to 60% of terrestrial biodiversity and that artificialisation damages their biological, hydrological and climatic functions.

[10] European Environment Agency, Water scarcity conditions in Europe, updated 2026. Water scarcity affected 28% of EU territory and 32% of its population during at least one season in 2023.

[11] Global Footprint Network, Earth Overshoot Day 2026 falls on July 30, 5 June 2026. The calculation estimates that humanity is using ecological resources and services 73% faster than Earth can regenerate them, equivalent to 1.73 Earths.

[12] Météo-France, Orages et fortes chaleurs à l’est, 30 July 2026. Météo-France confirms that the heatwave beginning on 28 July was the third national heatwave of summer 2026. It followed two earlier summer heatwaves and an exceptionally early May heat episode that did not meet the national heatwave threshold.

[13] European Forest Fire Information System, EFFIS Statistics Portal, accessed 31 July 2026. EFFIS had mapped approximately 495,000 hectares burned across EU countries during 2026, including 91,057 hectares in France. The figures are updated regularly and principally cover fires of approximately 30 hectares or more.

[14] UN-Water, Human Rights to Water and Sanitation. The United Nations recognises access to sufficient, safe, acceptable, physically accessible and affordable water for personal and domestic use as a human right.

[15] Légifrance, French Environmental Code, Articles L210-1 and L211-1. French law defines water as part of the nation’s common heritage, recognises access to drinking water for essential uses and requires the preservation of aquatic ecosystems, wetlands and natural balances.

[16] RTE, Les data centers en chiffres clés, 2026. RTE estimates that data centres currently consume around 10 TWh, approximately 2% of France’s annual electricity consumption. This could rise to between 23 and 28 TWh, around 4% of national consumption, by 2035.

The post The Hidden Cost of AI Growth appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

What B2B marketers can learn from NOUS anti-gaspi, Too Good To Go and Back Market about positioning, proof and conversion.

There is something quietly interesting about walking into a shop that sells products other retailers did not want to keep.

A packet may have a short date, a fruit may look less polished, a product might come from surplus stock, or a phone may have had a previous life before being refurbished and sold again.

The product may still have real value, while asking the customer for a little more trust before they choose it.

• Is this still good?
• Is it safe?
• Is the lower price hiding a weaker experience?
• Am I making a smart choice, or accepting a compromise?

That question is what makes anti-waste commerce such a strong marketing case study.

“Brands like NOUS anti-gaspi, Too Good To Go and Back Market sell products that need trust before they can be chosen. Their growth depends on making products with an initial trust gap feel understandable, credible and worth choosing.”

In B2B marketing, buyers also make decisions under uncertainty. They may be interested in a product, but still unsure about implementation, risk, quality, data, support, compliance or internal buy-in. In categories like this, conversion is not just persuasion. It is risk reduction.

The value of “imperfect” depends on how it is framed

A short-dated product is not automatically a bad product. A wonky vegetable is not less nutritious. A surplus item is not less useful. A refurbished phone is not necessarily less reliable.

The meaning attached to the product often matters as much as the product itself.

Modern commerce has spent years making quality feel synonymous with freshness, abundance and newness. A full shelf feels reassuring, a pristine product feels safer, and a new device often feels easier to trust than one with a previous life.

Positioning matters here because it shapes whether the customer sees imperfection as a risk or as part of the value.

Many B2B products also carry a perceived flaw. They can be complex, technical, regulated, expensive, hard to implement or difficult to compare. Weak marketing tries to smooth over that friction. Stronger marketing explains why the friction exists and what value it creates.

Anti-waste commerce has grown because it solves several tensions at once

Food waste is not a small problem. The European Commission states that more than 58 million tonnes of food waste are generated annually in the EU, with an associated market value estimated at €132 billion. [1]

In France, anti-waste and food destocking have become a more visible commercial category. Xerfi estimated that the turnover of food destocking and anti-waste specialists reached €520 million in France in 2024. [2]

Those figures explain the economic relevance of the category. The buying decision itself is more layered.

The best models make the buying decision feel both rational and emotionally acceptable. The customer can say: “I saved money, avoided waste, and still got something useful.”

It also connects with something I explored in From Scarcity to Stewardship: The New Psychology of Conscious Consumers. Responsible consumption is no longer only about values. It is also about proof, affordability, usefulness and trust.

Awareness does not remove hesitation

Most people already understand that food waste is a problem, and many consumers know that buying refurbished can reduce environmental impact. Awareness creates interest; confidence turns that interest into behaviour.

“At the moment of purchase, the buyer needs more than awareness. They need to feel that the product is safe, the price reflects real value and the sustainability message is not hiding a weaker experience.”

A similar pattern appears in B2B SaaS, fintech and marketplaces.

Buyers may understand the problem and agree with your category narrative, but they still need practical reassurance: will the product work, can the team deliver, is implementation manageable, is the data reliable, and can the decision be defended internally?

That is why the most interesting anti-waste brands do more than create demand. They design the buying experience around the hesitation itself.

NOUS anti-gaspi makes anti-waste feel like normal shopping

NOUS anti-gaspi is interesting because it brings anti-waste into a familiar retail format.

From the outside, the model is simple: sell everyday products that would otherwise risk being wasted, often at lower prices, through physical stores. The marketing challenge is more subtle. NOUS anti-gaspi sells discounted products, but its real marketing challenge is to normalise a different way of shopping.

For the model to work, customers need to feel that buying anti-waste products is not strange, risky or second best. It has to feel like a practical grocery choice.

The brand connects several layers of value at once: price, everyday usefulness, waste reduction, local shopping habits and a familiar retail experience.

According to Plan Bio, NOUS anti-gaspi raised €3 million in 2024 and reported 28 stores and €41 million in turnover for 2023. [3] In January 2026, Linéaires reported that the brand planned to open eight new stores in 2026, including a Paris opening on Boulevard Richard Lenoir, with further development planned in Paris, Bordeaux and Lyon. [4]

The exact figures will evolve, but the direction is clear: anti-waste is no longer only a niche activist behaviour. It is becoming a more structured retail proposition.

For B2B marketers, the useful lesson is about adoption. A new behaviour becomes easier to accept when it is embedded in a format the buyer already understands.

If your product asks buyers to change how they work, report, buy, analyse or decide, the experience cannot feel completely foreign. You need to make the new behaviour legible through familiar cues: clear categories, simple next steps, transparent pricing, recognisable workflows, proof points and onboarding that reduces uncertainty.

Too Good To Go makes waste reduction feel small enough to act on

Instead of putting anti-waste into a physical grocery format, it turns surplus food into a small, repeatable action. The customer opens the app, finds a nearby partner, reserves a discounted surprise bag and collects it during a specific time window.

The surprise element could have been a barrier. People do not always know exactly what they will get, and that uncertainty creates friction. Too Good To Go gives that uncertainty a structure.

Too Good To Go says it has grown to more than 120 million registered users and 180,000 active business partners and has helped save more than 500 million meals from being wasted. [5] As this is company-reported data, it should be treated as self-reported impact rather than independent verification. Still, it shows the scale of the behaviour the company is trying to build.

That is why the first action matters. It gives the customer a way to test the promise without needing to believe the whole story upfront.

Back Market shows why proof has to appear before conversion

Refurbished electronics carry one of the clearest trust problems in circular commerce.

“The value proposition is attractive: cheaper devices, less waste, less pressure to buy new. But the buyer may still worry about battery life, hidden defects, seller quality, warranty, support and what happens if the device fails.”

Back Market has to make refurbished feel safe enough to choose, with sustainability as part of the value rather than the whole argument.

The company does this through visible trust mechanisms. Its own site highlights refurbishment standards, up to 100-point quality inspections, free 30-day returns and a 1-year warranty. [6]

In 2024, The Guardian reported that Back Market had expanded to 18 countries, raised more than $1 billion and worked with around 1,700 traders and refurbishers. The same article quoted CEO Thibaud Hug de Larauze describing the “trust gap” between refurbished products and new devices. [7]

A trust gap closes when quality control, guarantees and seller standards become visible before the customer feels too much risk.

Many companies have strong operational proof, but they hide it too deep in the journey. The best evidence sits in sales decks, onboarding calls, legal documents, security questionnaires, help centres or customer success processes. By the time the buyer sees it, they may already have hesitated.

When operations answer a real objection, they should be part of the story. In B2B, that proof can come from onboarding processes, data governance, customer support, partner vetting, security standards or implementation frameworks.

Before the buyer says yes

Across these examples, the important work happens before the customer says yes.

The brand changes how the buyer interprets the perceived flaw, then adds enough proof to make the decision feel reasonable.

The pattern is simple: identify the hesitation, make the trade-off clear, show proof early, and make the first step feel low-risk. Anti-waste brands do this because they have to. B2B marketers should do it because buyers are already asking these questions before they convert.

A lot of marketing becomes too thin at exactly this stage. It jumps from claim to CTA without doing the confidence-building work in between.

A company may say it is more sustainable, more efficient, AI-powered, future-facing or built for growth, while the buyer is still wondering whether the claim is credible, what will actually change, how difficult adoption will be and whether the decision can be defended internally.

The experience still has to hold

This is also where the limits of anti-waste commerce become important. These models can easily become romantic stories about better consumption, but they are operationally difficult businesses.

Supply can be unpredictable, margins can be thin, quality may vary, and operations are often complex. There is also a deeper paradox: if society becomes better at preventing waste, businesses built around surplus need to keep evolving.

Poor quality, unclear impact or inflated claims can make consumers question whether the model truly reduces waste or whether it simply turns surplus into another polished commercial story.

Ethical intent may create the first reason to care, but repeat behaviour still depends on the experience. A weak product, a disappointing basket or an unreliable warranty quickly remind customers that mission alone cannot carry the relationship.

The brands that hold up over time combine mission with practical value. Price, convenience, reassurance, local access, guarantees and repeatable behaviour all matter.

What B2B marketers can take from this

Anti-waste commerce gives B2B marketers a useful logic: study the hesitation before trying to accelerate the conversion. A SaaS company does not need to behave like a grocery store, and a fintech platform does not need to imitate an anti-waste app.

Make the trade-off visible

B2B buyers need to understand what they are choosing.

A clear trade-off is easier to trust than a polished promise. Setup time, specialisation, structured workflows or higher pricing do not have to weaken the offer, as long as the buyer understands what each constraint protects, clarifies or helps avoid.

Turn abstract claims into customer jobs

A lot of B2B messaging starts too high up. Words like growth, innovation, efficiency, transformation and AI-powered performance may be relevant, but they often fail to explain what the buyer can actually do next.

Move proof closer to the first moment of doubt

If a buyer has to book a demo before they understand your methodology, security posture, onboarding process or customer results, the journey is asking for trust too early.

Move proof into the places where hesitation already appears: landing pages, comparison pages, FAQs, pricing pages, case studies, product explainers, demo follow-ups, nurture emails and onboarding content.

This is where anti-waste commerce connects with circular growth loops: the strongest models do not simply acquire users. They create repeat behaviours around value, trust and participation.

Growth is what happens when the customer has enough confidence to come back.

Look for trust leakage before adding more traffic

Trust leakage happens when a buyer understands the offer but still does not feel safe enough to move forward. More traffic will not fix that. The friction sits inside the proof, the reassurance, the onboarding story or the perceived risk.

This is where B2B marketers should look before assuming the problem is demand.

This is a more useful way to diagnose growth in trust-sensitive categories. Not every conversion problem is a CTA problem. Sometimes the buyer simply does not have enough confidence yet.

FAQ

What is anti-waste commerce?

Anti-waste commerce is the sale, redistribution or revalorisation of products that are still usable but at risk of being wasted, discarded or undervalued. This can include surplus food, short-date groceries, imperfect products, unsold meals, refurbished electronics and other circular commerce models.

Why are anti-waste brands relevant to B2B marketing?

Because they sell under imperfect conditions. Their products often carry a perceived flaw, which makes them useful examples for B2B categories where trust, risk and proof shape conversion.

What can SaaS companies learn from Too Good To Go or Back Market?

SaaS companies can learn how to reduce perceived risk before conversion. Too Good To Go turns a big problem into a simple, repeatable action. Back Market makes quality control and reassurance visible. Both show that trust should be designed into the customer journey, not added at the end.

Is anti-waste commerce only about sustainability?

Sustainability sits alongside price, convenience, quality reassurance, trust signals and repeat behaviour.

How can B2B marketers reduce perceived risk before conversion?

By making proof visible earlier: customer evidence, methodology, security information, onboarding clarity, transparent FAQs and operational credibility.

Conclusion

Anti-waste commerce is interesting because it begins with products that can raise doubts, then builds a buying experience around those doubts.

NOUS anti-gaspi does it through familiarity. Too Good To Go does it by making uncertainty feel small and actionable. Back Market does it by making proof visible before the customer has to take the risk.

For B2B marketers, the useful lesson is to notice where buyers hesitate before trying to accelerate the conversion. Sometimes the problem is not demand, positioning or traffic in isolation. Sometimes the buyer simply does not feel safe enough to move.

In anti-waste commerce and B2B growth, trust is part of the system that makes conversion possible.

💌 If you want more essays on ethical growth, trust-led marketing and practical B2B growth systems, you can join Conscious Growth Dispatch here.

Sources

[1] European Commission, Food waste, accessed May 2026. The Commission states that over 58 million tonnes of food waste are generated annually in the EU, with an associated market value estimated at €132 billion.

[2] Xerfi, Le marché du déstockage et de l’anti-gaspi alimentaire, published 27 June 2025. Xerfi estimates that the turnover of food destocking and anti-waste specialists reached €520 million in France in 2024.

[3] Plan Bio, L’enseigne NOUS anti-gaspi lève trois millions d’euros et ouvrira 3 magasins d’ici fin 2024, published 2024. The article reports NOUS anti-gaspi’s €3 million fundraising, 28 stores and €41 million turnover in 2023.

[4] Linéaires, NOUS anti-gaspi ouvrira 8 magasins en 2026, published 15 January 2026. The article reports the brand’s plan to open eight new stores in 2026, including a Paris opening on Boulevard Richard Lenoir.

[5] Too Good To Go, Too Good To Go Accelerates U.S. Expansion, published 27 August 2025. The company states that it has 120 million registered users, 180,000 active partners across 19 countries and more than 500 million meals saved from waste.

[6] Back Market, Back Market: refurbished tech that’s better for the planet, accessed May 2026. Back Market highlights refurbishment standards, up to 100-point quality inspection, 30-day returns and a 1-year warranty.

[7] The Guardian, “It should be a right to fix your phone”: the boss of booming secondhand tech firm Back Market, published 11 June 2024. The article discusses Back Market’s international growth, refurbisher network and the trust gap around refurbished electronics.

The post How Anti-Waste Brands Make Imperfect Products Easier to Trust appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

Education and training have become a strange category to market.

On paper, demand should be obvious. Europe needs digital skills. France needs green and AI-ready talent. Companies need to upskill people faster, retain teams longer, and adapt to changes that their internal systems were not always built to absorb. [1][2]

And yet, many education and training providers still approach growth as if the main issue were volume: more visibility, more campaigns, more form fills, more webinar registrations, and more leads to pass to Sales.

The problem is that B2B education is not a simple volume game.

“Companies are not just buying a course. They are buying a way to reduce skills risk, support transformation, and justify training spend internally.”

So the real question in 2026 is not:

How do we generate more leads?

It is:

Can we build enough trust, proof, and operational discipline to turn market need into qualified pipeline?

That is a different problem. And it requires a different system.

1. The market does not lack demand. It lacks clarity.

The need is already there.

Cedefop’s 2035 skills forecast shows a European labour market increasingly shaped by the digital and green transitions, with demand moving towards higher-level skills. [1]

In France, the OECD estimates that 30.9% of workers are exposed to generative AI, meaning at least 20% of their tasks could be done in half the time with GenAI support. In Île-de-France, that figure rises to 41.5%. [2]

This changes the role of professional training. It is no longer just an HR benefit or a catalogue of courses. It is becoming part of how companies manage productivity, retention, internal mobility, and skills shortages.

But there is a trap here.

When demand feels obvious, providers can assume the market will understand their value on its own. It usually will not.

A company may know it needs AI training, data literacy, cybersecurity awareness, management development, or green skills. That does not mean it knows which provider to trust, which format to choose, how to prove ROI, or how to align the programme with business priorities.

This is where many education brands lose momentum. Not because the market is absent, but because the path from need to decision is not clear enough.

Key idea: In B2B education, market demand does not automatically become a commercial pipeline.

2. France is not a normal lead-generation market

France adds another layer of complexity.

Professional training is shaped by funding mechanisms, certification rules, apprenticeship policy, CPF usage, OPCOs, France Compétences, and regular regulatory changes.

France Compétences reported that more than 1.3 million CPF-funded training applications were validated in 2023, for more than €2 billion committed. [3] Its 2024 activity also included revisions to apprenticeship funding levels, generating around €140 million in savings. [4]

This is not just administrative background. It changes how growth works.

When funding rules move, employers hesitate. When apprenticeship support changes, timing changes. When certification quality is scrutinised, proof matters more. When budgets are tighter, generic training promises become weaker.

In France, the go-to-market strategy for education is also funding literacy.

“A provider that only sells course features will struggle against one that helps employers understand timing, financing, compliance, skills priorities, and expected outcomes.”

That is why a simple “run ads and collect leads” model is too shallow. You cannot solve a policy-shaped, high-trust B2B market with landing pages alone.

Key idea: In France, education growth depends on understanding the funding and regulatory environment, not just the acquisition channel.

3. The buyer wants proof, not a promise

The buyer has changed, too.

HR, L&D, talent, and transformation teams are under pressure to show that learning supports business goals. LinkedIn Learning’s 2024 Workplace Learning Report found that aligning learning programmes to business strategies was L&D’s number one focus area for the second year in a row. [5]

That tells us something important.

The buyer is not only asking whether the training is good. They want to know what problem it solves, why it is worth the investment, how managers and employees will engage with it, and how it supports broader goals such as retention, internal mobility, productivity, or transformation.

This is why B2B education marketing needs to move from catalogue logic to outcome logic.

For example, the message should move from “we offer AI training” to “we help non-technical teams use AI safely and productively in their daily workflows”.

It should move from “we train digital talent” to “we help companies reduce hard-to-fill digital skills gaps through measurable upskilling pathways”.

And it should move from “we are impact-led” to “here is what changed for learners, employers, and the organisations that hired them”.

In B2B education, impact is not a positioning statement. It becomes commercially valuable only when it is evidenced.

Key idea: buyers do not only need inspiration. They need proof they can use internally.

4. Impact needs to become usable proof

This matters even more for impact-led education brands.

Impact is a strong message in France and Europe. It connects to inclusion, employability, access to skills, social mobility, and the need to bring more people into digital and green careers.

But impact alone does not convert a B2B buyer. A company needs evidence.

That evidence might include learner completion rates, skills progression, certification outcomes, employer satisfaction, job placement, internal mobility, retention impact, repeat business, sector-specific case studies, manager feedback, or business outcomes after training.

The point is not to make every education brand sound like a consultancy. The point is to make proof visible and usable across the full funnel.

A good case study should not sit quietly in a PDF. It should shape the website, sales deck, landing pages, nurture emails, retargeting, webinars, comparison pages, and AI-search visibility.

Proof is not something you add at the end. It is what makes the whole growth system more credible.

Key idea: Impact becomes powerful when it is translated into evidence that buyers can trust, share, and defend.

5. CPL is too small a metric for this category

Many organisations still judge acquisition through surface-level numbers: cost per lead, form submissions, landing-page conversion rate, webinar registrations, and download volume.

These metrics are not useless. But in B2B education, they are incomplete.

A cheap lead is not a better lead if it never becomes a serious conversation with the right buyer.

The more useful questions are usually harder:

• Which sectors convert best?
• Which skill needs create urgency?
• Which company sizes have budget?
• Which buyer personas influence the deal?
• Which content creates sales conversations?
• Which campaigns generate qualified meetings?
• Which leads become opportunities?
• Which accounts return?

This is where many education brands need a more mature growth operating system.

Not because marketing should become complicated for the sake of it. Because the buying journey already is.

An HR manager may research the topic. A business leader may own the urgency. A finance team may validate the budget. A training manager may compare providers. An OPCO or funding mechanism may influence timing. A director may make the final call.

If the CRM is messy, the segmentation is vague, and the follow-up is slow, more lead volume simply creates more waste.

Growth does not fix unclear systems. It amplifies them.

Key idea: In B2B education, the best metric is not lead volume. It is the quality of the path from demand to pipeline.

6. Seasonality is real, but trust cannot be seasonal

Education and training have natural cycles.

In France, those cycles are often linked to rentrée, apprenticeship calendars, annual training plans, HR budget cycles, funding windows, regulatory changes, and sector-specific transformation priorities.

France Travail’s BMO 2026 survey collected nearly 416,000 responses across France to analyse recruitment needs by sector and employment area. [6] That matters because training demand is often connected to hiring pressure, talent shortages, and operational planning.

But seasonality can create a bad habit: waiting too long to build demand.

“The risk is that marketing starts too late. Buyers may already be comparing options, building internal cases, or discussing providers before a campaign even goes live. When that happens, paid media and sales follow-up have to compensate for the trust that should have been built earlier.”

A stronger approach is to prepare the market before the buying window opens.

That means educating employers earlier, creating familiarity over time, and making the future sales conversation easier.

For example:

• A digital skills school could run webinars before the rentrée period to explain apprenticeship timelines, funding options, and the profiles employers can realistically recruit.
• An AI training provider could help HR teams identify which roles need upskilling before the annual budget is finalised.
• A cybersecurity provider could create sector-specific pages for finance, healthcare, or retail, where risks and compliance expectations are different.

Seasonality should shape planning. It should not become an excuse for last-minute acquisition.

Key idea: Education brands should not wait for the buying window to start building trust.

7. AI search adds a new visibility problem

B2B buyers still use Google, LinkedIn, peer recommendations, events, newsletters, and direct referrals. But AI-assisted search is becoming another layer in the research process.

A buyer might use AI search to ask which providers can support AI upskilling, how to structure a company-wide training programme, or what to look for when comparing data, cybersecurity, or digital skills providers.

This does not mean SEO is dead. It means SEO is no longer the only visibility layer.

Education brands need to be easy to understand, both for people and for AI systems. That means building a clearer content layer around:

• Clear positioning
• Structured programme pages
• Specific use cases
• Sector-focused content
• FAQs that answer real buyer questions
• Comparison pages
• Employer case studies
• Outcome data
• Recognised certifications
• Credible third-party mentions

The brands that win in AI search will not necessarily be the loudest. They will be the easiest to understand, trust, and cite.

For B2B education, this matters because a lot of the decision-making happens before a form is submitted. By the time a buyer speaks to Sales, they may already have formed an opinion.

The question is whether the brand was visible and credible during that invisible research phase.

Key idea: SEO and GEO are not just traffic channels. They are part of the trust-building layer. For a deeper look at how AI search changes brand visibility and credibility, you can read my article on GEO here.

8. What a growth operating system looks like

A serious growth operating system for B2B education brands in France and Europe needs several layers.

Market intelligence

The provider needs to understand where demand is structurally rising: AI, data, cybersecurity, green skills, industrial transformation, management, internal mobility, hard-to-fill roles, and regional labour shortages.

This should inform positioning, content, targeting, and offer design.

Segmentation

Not all companies buy training for the same reason.

• An SME may need practical support and funding clarity.
• A large group may need scale, compliance, reporting, and stakeholder alignment.
• A tech company may care most about speed and adoption.
• An industrial company may need training that fits operational constraints.
• A public-sector buyer may prioritise accessibility, procurement rules, and framework alignment.

That is why segmentation should not stop at job title. It should also consider sector, company size, maturity, skill need, urgency, funding route, and buying trigger.

Proof-led positioning

Every major claim needs evidence behind it.

Employability, transformation, inclusion, productivity, and business alignment are strong promises, but they only become credible when the reader can see what they mean in practice.

That might mean learner outcomes, placement data, career progression, before-and-after examples, access and completion data, manager feedback, operational improvements, or a clear measurement framework.

Without proof, positioning becomes decoration.

Always-on demand generation

Demand generation should not depend only on campaign peaks.

A stronger system combines SEO, GEO, paid acquisition, LinkedIn, webinars, newsletters, retargeting, partner content, lead magnets, and sales enablement.

The goal is not only to be seen. It is to educate the market before the buyer is ready.

CRM discipline

This is often the least glamorous part of growth, and one of the most important.

A B2B education provider needs clean data, clear lifecycle stages, lead scoring, source tracking, sector tagging, company-level views, and fast handover to Sales.

If the CRM cannot tell the difference between a student, an HR lead, an employer partner, an alumni contact, and an unqualified enquiry, growth becomes noisy very quickly.

Nurturing

Most buyers will not convert immediately.

Nurturing should help buyers understand the problem, compare options, build internal support, and reduce perceived risk.

The role of content is not only to attract. It is to move a serious buyer from interest to confidence.

Sales alignment

Marketing and Sales need shared definitions: what counts as an MQL, what qualifies as an SQL, what makes a meeting qualified, which accounts matter, what the expected follow-up time is, which objections come back repeatedly, and which campaigns create pipeline.

Without this alignment, marketing optimises for activity while Sales complains about quality.

Measurement beyond CPL

CPL is only one small signal.

A better dashboard would include:

• MQL to SQL conversion
• qualified meeting rate
• opportunity creation
• pipeline generated
• pipeline by sector
• pipeline by use case
• sales cycle length
• revenue influenced
• employer repeat business
• cost per qualified opportunity

This is where growth becomes commercial. Better conversion from market need to measurable business value.

Conclusion

B2B education brands in France and Europe are operating in a market full of demand, but not easy demand.

Skills shortages, AI disruption, green transition, apprenticeship funding, CPF usage, regulatory pressure, and L&D accountability all point in the same direction: companies need training, but they also need clarity, proof, and confidence. [1][2][3][4][5]

“That is why the next stage of growth in this category will not belong to the providers that simply generate the most leads. It will belong to the ones who build the strongest operating system.“

The brands that understand the market, segment the buyer, prove the outcome, build trust before the buying window, show up in search and AI-assisted discovery, maintain CRM discipline, align Marketing and Sales, and measure pipeline rather than activity.

In a high-trust, policy-shaped, skills-driven market, growth is not a campaign.

It is an operating system.

💌 If you want the next piece, you can join Conscious Growth Dispatch here.

Sources

[1] Cedefop, Skills forecast 2035: the twin transition and the demographic challenge drive demand for high-level skills, March 2025. Cedefop projects future EU labour-market shifts to be shaped by the digital and green transitions, with demand moving towards higher-level skills.

[2] OECD, Job Creation and Local Economic Development 2024, Country Note: France, November 2024. OECD estimates that 30.9% of workers in France are exposed to generative AI, rising to 41.5% in Île-de-France.

[3] France Compétences, Rapport 2024 sur l’usage des fonds de la formation professionnelle, February 2025. France Compétences reports more than 1.3 million CPF-funded training applications validated in 2023, for more than €2 billion committed.

[4] France Compétences, Publication du Rapport d’activité 2024, June 2025. France Compétences reports work on apprenticeship funding levels, including NPEC revisions that generated around €140 million in savings in 2024.

[5] LinkedIn Learning, Workplace Learning Report 2024, 2024. The report identifies aligning learning programmes to business strategies as L&D’s number one focus area for the second year in a row.

[6] France Travail, Enquête Besoins en Main-d’Œuvre 2026, 2026. France Travail’s BMO survey collects recruitment needs by sector and employment area, with nearly 416,000 responses collected for France.

The post B2B Education Needs a Growth Operating System appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

Search is now two experiences stacked on top of each other.

• The first is the classic one: a list of results, rankings, clicks.
• The second is where attention increasingly goes: an AI answer that summarises, then shows a handful of sources.

If you are a founder, your content can be used without being visited. And that changes what “visibility” means.

That is where GEO comes in.

1. GEO, in one sentence

Generative Engine Optimisation (GEO) is the practice of increasing the chance your pages are selected and cited inside AI-generated answers, while staying compatible with long-term, human-centred SEO. [1]

The term was formalised in academic work in late 2023, with a very pragmatic framing: generative engines are black boxes, so you optimise by improving the odds that your content is retrieved, understood, and considered “safe” to cite. [1]

2. Why founders should care now

AI summaries reduce friction for users. That is the whole point.

Google presents AI Overviews as a way to help people “dig deeper” and discover a wider range of sources. [4]
But when an AI summary appears, real user behaviour can shift towards fewer clicks. Pew’s research found users were less likely to click on traditional results when they encountered an AI summary. [8]

Both can be true:

• Some links inside AI answers may get high-intent clicks.
• A lot of informational intent gets satisfied without any click.

So the founder question becomes: if someone never visits your site, can they still meet your thinking, your credibility, your definitions, your proof?

Citations are now part of brand distribution.

3. How AI answers choose sources (the boring mechanics that matter)

Most AI answer systems follow the same pattern:

1. The question gets expanded (often into sub-questions)
2. The system retrieves candidate pages
3. Those pages are ranked and filtered
4. A model writes a synthesis
5. A subset of sources is shown as citations

Google is unusually explicit about one key mechanism: query fan-out. AI Overviews and AI Mode may run multiple related searches across subtopics, then pick supporting pages while generating the answer. [2]

This matters because it creates a founder-relevant opportunity: you can be cited for a sub-question even if you are not ranking #1 for the original query.

4. What the platforms officially say (and what they carefully avoid saying)

a) Google: no special GEO trick, just “be eligible” and be useful

Google’s documentation is consistent on one point: there is no special markup you add to “be in AI Overviews”. You need to be indexed and eligible to appear in Search features, then you win by having useful, reliable content. [2][3]

If you want a simple mental model for Google:

• GEO is largely “SEO done properly”, with stricter expectations on clarity and trust. [3]

If you want the long version of this idea, I broke it down here: SEO for Good: Content That Powers Purpose and Growth.

b) Microsoft: citations have become a measurable surface

Microsoft introduced AI Performance in Bing Webmaster Tools, which reports how often your site is cited across Copilot, Bing AI answers, and some partner experiences. It includes total citations, cited pages, and grounding queries. [5]

This is important even if you do not care about Bing’s market share. It is the first major platform saying, in product form, that citations are a real visibility metric.

c) ChatGPT Search: citations exist when search is used

OpenAI’s help documentation states that when ChatGPT uses search, responses contain inline citations and a “Sources” button that lists cited sources. [6]

Founder implication: you are still playing a web visibility game. Being citeable starts with being accessible, indexable, and credible.

d) Perplexity: citation-forward by design

Perplexity’s own help centre describes a workflow that searches the internet in real time and produces a summary backed by sources. [7]

In practice, this rewards pages that are easy to verify: clear definitions, primary sources, and clean structure.

5. The founder playbook: 5 moves in 30 days

This is not a content calendar. It is a visibility system. This approach fits the broader system mindset I described in How to Build a Sustainable Growth Engine Without Burning Budget (or the Planet).

a) Create 5 “source pages” you actually want to be cited for

Pick 5 topics that sit at the centre of your category, then write pages built for retrieval and citation:

• A short definition near the top
• Clear H2s that match real questions
• “How it works” and “Where it fails”
• 3–5 FAQs based on sales calls

This aligns with how Google frames success in AI search: unique, valuable content that helps people. [3]

b) Make every important page verifiable

Add:

• An author or reviewer line (real person, real role)
• A “last updated” date where the topic moves
• A sources section with primary references

This is not a trick. It is how you look serious, both to buyers and to systems trying to avoid citing nonsense.

c) Use structured data, but only when it matches visible content

Google’s guidance stays conservative here too: structured data should reflect what is actually on the page. [3]

For founders, the practical version is:

• Article markup for deep explainers
• FAQ markup only if you visibly include FAQs
• No “schema cosplay”

4) Track citations like a leading indicator, not like revenue

Use:

• Google Search Console for classic performance
• Bing Webmaster Tools AI Performance for citation visibility [5]

A citation is not a conversion. But it tells you which pages the discovery layer is willing to use.

5) Publish one asset that cannot be summarised away

AI answers compress generic content. They struggle to replace original assets.

Examples that work in B2B:

• A small benchmark (even if niche)
• A compliance checklist mapped to a specific regulation
• A dataset, glossary, or teardown that is genuinely useful

You still want to be cited, but you also want to earn the click when it matters.

6. “Without ruining your SEO” is mainly a taste and integrity problem

Bad GEO looks like content written for extraction.

Templates, inflated word counts, filler paragraphs, fake authority. That is short-term optimisation for a system that changes fast.

Good GEO is simpler:

• Clarity beats length
• Proof beats vibes
• Structure beats “thought leadership”
• Honest limits beat overconfident claims

Google’s own advice basically says the same thing in polite language. [3]

Conclusion

GEO is not a new channel. It is a new surface.

Your job as a founder is to decide what you want the surface to repeat about you, even when nobody clicks.

If you build a few pages that are genuinely source-worthy, you do not just improve your SEO. You increase the chance that the new layer of search carries your definitions, your framing, and your credibility forward.

💌 If you want the next piece, you can join Conscious Growth Dispatch here.

Sources

[1] Aggarwal et al., GEO: Generative Engine Optimization (arXiv, 2023).
[2] Google Search Central, AI features and your website (includes “query fan-out”).
[3] Google Search Central Blog, Top ways to ensure your content performs well in Google’s AI experiences on Search (May 21, 2025).
[4] Google Blog, Generative AI in Search: Let Google do the searching for you (May 14, 2024).
[5] Bing Webmaster Blog, Introducing AI Performance in Bing Webmaster Tools Public Preview (Feb 10, 2026).
[6] OpenAI Help Center, ChatGPT search (inline citations and Sources button).
[7] Perplexity Help Center, How does Perplexity work? (real-time search + cited sources).
[8] Pew Research Center, Google users are less likely to click on links when an AI summary appears in the results (Jul 22, 2025).

The post GEO: Get Cited in AI Answers appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

Dashboards lie. Traffic climbs, campaigns launch, features roll out. On the surface, everything appears to be fine. Yet underneath those tidy charts, most funnels are quietly losing value. Prospective customers get close to a first win, then drift away. Budgets evaporate. Teams work late and wonder why nothing sticks.

Here’s the uncomfortable reality: most growth problems aren’t about attracting more people. They’re about keeping the people you already have. Leaks waste money, energy, and attention. They also erode trust, which is the foundation of any sustainable brand.

The good news? You can locate your biggest losses. No specialist software. No complicated models. Just a practical audit that respects users’ time and turns waste into progress.

1) Choose a North Star that measures real value

Funnels fail when they chase shiny but hollow outcomes. Page views, impressions, and raw sign-ups look impressive yet say little about whether anyone benefited.

Start by finishing this sentence:

We succeed when __________ because users __________.

Pick a North Star where business results and user well-being overlap. Two simple examples:

• We succeed when people publish their first project because they feel genuine creative ownership.
• We succeed when new customers connect their bank account because they can see real financial insight.

💡 A clear North Star forces honest trade-offs. It keeps the team focused on value, not theatre. It also exposes where value slips away.

A broad, external sense-check helps here. A typical landing page conversion hovers around the mid-single digits across industries. Consider 6.6% a rough median baseline, not a target [1].

2) Capture your funnel as it actually behaves

Create a 30-day snapshot. Accuracy can improve later. Direction is what matters now.

If you can’t fill a row, that’s not a failure. It’s a finding. Add the gap to your instrumentation list and move on. You can only fix what you can see.

3) Put numbers on the losses

At each stage, ask two simple questions:

1. How many people fall away here?
2. What does that loss cost us in money, time, or trust?

A quick illustration:

• 10,000 qualified visits
• 15% activation
• Roughly 8,500 people don’t reach the first value

If an average customer is worth £100 over their lifetime, that equates to £850,000 of potential monthly value left on the table. More importantly, thousands of people gave you attention and left without benefit. That damages credibility and drains morale.

Fixing leakage isn’t just commercial hygiene. It’s an ethical practice.

4) Pick three focused changes that help users as well as the business

Resist the urge to fix everything. Choose three precise hypotheses you can ship now. Use a clean format:

“If we ______ then ______ because ______.”

Add one ethical filter: does this reduce friction and increase clarity for the user, not just bump a number for the quarter?

Practical experiments to start with:

a) Build trust early. If we place three client logos and one short, authentic testimonial above the fold, more people will proceed because visible proof reduces uncertainty [2]. Why it’s ethical: genuine transparency, not pressure tactics.

b) Shorten the form. If we reduce the sign-up form from seven fields to four, completion will rise because unnecessary fields create drop-off [3]. Why it’s ethical: respect for people’s time and privacy.

c) Match the message. If the landing page headline echoes the wording in our best-performing ad, more visitors will convert because expectations are met rather than disappointed [3]. Why it’s ethical: consistency avoids bait-and-switch dynamics.

d) Guide activation on Day 0. If we send a plain-text quick-start email immediately after sign-up, more users will complete setup because we meet them while motivation is high [4]. Why it’s ethical: we help people realise value promptly, without tricks.

5) Prioritise without overthinking

Use the ICE method. Score each idea from 1 to 10 for:

• Impact: How much could it move the North Star
• Confidence: How strong the evidence is
• Ease: How quickly it can be shipped

Multiply Impact by Confidence and divide by Ease. The highest scores go first. If ideas touch very different audience sizes, add Reach and use RICE. Don’t let scoring become a performance.

6) Create one page everyone reads

Forget a dozen dashboards. Build a single page that guides decisions:

• Top: your North Star and the current number
• Middle: three funnel metrics with a simple status colour for each
• Bottom: three active experiments with owner, target, and review date

This becomes the weekly agenda. No data theatre. No guessing. For product teams, external benchmarks are useful context rather than commandments. Amplitude’s public benchmark hub is a handy reference for activation and retention patterns by product type [7].

7) Run the ethics check before you ship

For every change, ask three questions:

1. Does this save the user’s time?
2. Does this make the journey clearer?
3. Does this respect attention as finite, not free?

If the answer is no, you’re not fixing a leak. You’re relocating waste. In 2025, trust remains a central growth lever. The Edelman Trust Barometer shows how trust dynamics influence behaviour across markets and sectors [5]. A funnel that protects trust reduces long-term costs.

To maintain that trust, measure the right behaviours. Generic metrics won’t tell you if people actually reached value. Track the specific micro-events that mark progress, then use them to guide design decisions [6].

8) A concrete example you can adapt

North Star: Weekly Activated Users

30-day snapshot:

• Qualified sessions: 10,000
• Activation: 15%
• Week-4 retained: 25%

Largest loss: 8,500 visitors don’t reach first value

Three active experiments:

1. Client logo strip under the hero. Target: +3 percentage points activation. Stop if bounce rises above 65%. Owner: Marketing.
2. Four-field sign-up form. Target: +2 percentage points activation. Stop if error rate doubles. Owner: Product.
3. Day-0 quick-start email. Target: +2 percentage points activation. Stop if unsubscribe exceeds 2%. Owner: Lifecycle.

Review date: two weeks from today. Decide to ship, iterate, or stop.

Why this matters

Patch the obvious holes and you’ll need less traffic to grow. Spend drops. Churn eases. Teams stop firefighting and start improving the product. Most importantly, customers experience value faster and with less friction. That’s what ethical growth looks like in practice: fewer broken promises, more durable relationships.

Start your list for this week

□ Fill the 30-day table with your best available numbers
□ Select two experiments and write short test cards
□ Book a 30-minute review in 14 days to decide
□ Assign named owners for each test

💌 Like what you just read? The rest of the series is just as bold. Join Conscious Growth Dispatch to receive the next instalments, exclusive tools, and fresh thinking on ethical business. Sign up here!

References

[1] Unbounce. “What is the average landing page conversion rate?” Q4 2024 median of 6.6% across industries.

[2] Unbounce. “Conversion Benchmark Report 2024.” Insights drawn from 57M conversions and 41K landing pages, including the role of clarity and proof.

[3] Baymard Institute. “Checkout Optimisation: 5 Ways to Minimise Form Fields.” Also see Unbounce “Landing Page Best Practices” section on message match.

[4] Braze. “Why Email Marketing Is Important for Your Cross-Channel Strategy.”

[5] Edelman. “2025 Edelman Trust Barometer. Global Report.”

[6] Nielsen Norman Group. “Unlock Powerful UX Insights with Custom Events in Analytics.”

[7] Amplitude. “Benchmark Your Digital Product Performance.”

The post Stop the Leaks: Your 60-Minute Funnel Waste Audit appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

Your monthly ethical growth marketing newsletter

For B2B founders, marketers, and lean teams who refuse to choose between growth and values.

No vanity hacks. No soulless automations. Simply practical insights into how ethical and environmentally responsible brands are scaling — and how you can, too.

Every edition delivers:

• Tactical breakdowns of real growth experiments (cold email, SEO, dark social, etc.)
• Tool and stack audits with a conscious lens (privacy, carbon impact, longevity)
• Fresh commentary on sustainable marketing trends and team design
• Smart systems, Notion dashboards, and lean campaign ideas (like “Notion dashboard: Track retention without drowning in data”)

“Whether you’re leading growth at a mission-driven startup or building a solo venture that reflects your ethics, this is built for you.”

Who this is for

You’re in the right place if:

• You’re tired of the Growth culture that rewards short-term wins over long-term trust
• You want to build systems that scale ethically
• You care about real data, thoughtful tooling, and signal over noise
• You believe sustainability, transparency, and digital responsibility aren’t optional

Subscribers include B2B founders, ethical DTC operators, growth strategists, marketers in climate, impact, SaaS, and Web3.

Recent topics covered:

• “Why ethical brands are winning the retention game”
• “Why scaling fast isn’t the flex it used to be”
• “The haunted cost of AI: How much water are your tools wasting?”
• “Cold email vs. dark social: Where should early-stage startups invest?”

Who I am

I’m Samin Ghiasi, a Paris-based growth strategist helping ethical startups build smarter systems in B2B.

I’ve helped ethical and climate-conscious startups build growth systems that scale without burning out their teams or the planet. I write, test, and work hands-on with tools and strategies that respect both people and ecosystems.

This newsletter is where I share what works (and what to skip).

Subscribe for free

If you’re ready to building sustainable, values-aligned growth, join me. Subscribe to “The Conscious Growth Dispatch”

Delivered monthly to conscious marketers. No AI filler. No sponsored junk. Just clarity, context, and strategy you can actually use.

The post Welcome to the Conscious Growth Dispatch appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

“Cold outreach isn’t dead. It’s just evolving.”

For years, cold emails were the domain of spammy subject lines and soulless automation. But in 2025, ethical brands are rewriting the rules.

Bonus post to close out the July blog series on The Growth Ethos. Subscribe here to be updated for September content!

1. Why traditional cold outreach fails (and fast)

Nearly eight in ten B2B buyers say that most of the outreach they receive feels irrelevant or misaligned with their needs [1].

The root issue isn’t just volume, it’s trust erosion. Tactics like fake “follow-ups,” misleading subject lines, or copy-paste introductions have made cold email synonymous with spam.

“Excessive bounce rates and low engagement now threaten your sender reputation more than ever.“

The real cost? Deliverability collapse, brand dilution, and teams wasting hours chasing leads that were never aligned to begin with.

2. The 3 pillars of conscious cold emailing

These aren’t constraints, they’re filters for quality. Ethical is simply smart.

3. From extractive to value-led: cold email examples

❌ The extractive version (don’t do this)

Subject: Quick call?
Hi [FirstName],
I help companies like yours scale. Got 15 minutes this week?

This lacks intent, substance, and reason to reply. No context. No relevance. Just noise.

✅ The conscious version (real tone, real intent)

Subject: Curious how you’re approaching [X]?
Hey [FirstName],
I came across your [recent project/article/post]. I work with ethical brands facing similar [challenge] and thought a short idea might support what you’re building.
Would it be helpful if I sent it over?

Key ingredients: curiosity, context, consent.

This approach acknowledges the recipient’s world before introducing yours; the foundation of respectful outreach.

4. Tooling for authenticity

The right tech stack safeguards your reputation.

• Lemlist – Enables personalisation (images, videos) at scale [2]
• Apollo – For segmentation and cleaner data
• Bouncer – Scrubs lists to prevent spam flags
• HubSpot CRM – Tracks conversations considerately

Also important: Set up your SPF/DKIM records properly. Failing to authenticate your domain can kill deliverability before you send your first email [3].

5. What ethical brands do differently

In conscious outreach, every touchpoint reflects long-term values:

• Ask permission before pitching
• Always include an opt-out (even manually)
• Use copy that has your tone of voice
• Follow up with care, not pressure
• Track engagement that signals trust, not just opens

Pro tip: Link your outreach to something useful, like a short resource or invite, not a sales deck.

6. Metrics that matter in 2025

These numbers move the needle:

• Reply rate > Open rate
• Positive response rate
• Lead-to-qualified ratio
• Reputable markers – newsletter signups, social shares, return replies
• Unsubscribe rate – yes, track it. A low opt-out rate signals relevance

7. Conscious cold emailing at scale

Ethical outreach is possible, but only when your systems reflect your support.

• Segment by behaviour and values, not just company size
• Don’t add pictures!
• Add human context to every step
• Automate reminders, not relationships
• Only send when there’s a clear reason to reach out (lead socring)

Example:

Instead of pushing a product demo in the first email, share a short audit or insight based on something they published.

E.g.: “I noticed your team launched [X feature] last month — here’s a quick teardown on how similar companies increased adoption post-launch.”

Why it works: It shows you’ve done your homework, offers insight without asking for anything, and invites a thoughtful exchange (rather than a pitch).

Build a community (yes, again)

If you’re building something meaningful, treat outreach as an extension of your product, one that is thoughtful, intentional, and clear.

Respect your reader. Provide a real contribution. And trust that the right leads will respond.

SOURCES

[1] LinkedIn B2B Trends Report 2024 – “Why most cold outreach fails”
[2] Lemlist – “How to personalise cold emails with dynamic visuals”
[3] Google Postmaster Tools – Email authentication best practices

THIS SERIES IS COMPLETE (really, this time)

This bonus post concludes The Growth Ethos — a 10-post exploration of smarter, more sustainable growth in 2025.

If you’re new here, here’s what you’ve missed:

• Part 1: Growth Marketing 101 (2025 Edition): A Conscious Marketer’s Guide
• Part 2: Why Vanity Metrics Are Dying (and What to Track Instead)
• Part 3: How to Build a Sustainable Growth Engine Without Burning Budget (or the Planet)
• Part 4: Circular Growth Loops Are the Future of Ethical Marketing
• Part 5: 6 Martech Tools Every Ethical Brand Should Be Using This Year
• Part 6: From Scarcity to Stewardship: The New Psychology of Conscious Consumers
• Part 7: Dark Social and Micro‑Communities: How Sustainable Brands Are Winning Trust
• Part 8: Sustainable Paid Media: How to Align Ads with Purpose in 2025
• Part 9: SEO for Good: Content That Powers Purpose and Growth
• Part 10: B2B : 5 modèles européens qui réinventent la concurrence

BUILD WITH INTEGRITY

Thanks for following along this summer. If you’re building your community — I’d love to stay in touch.

📬 Subscribe to the newsletter to receive new posts when the next series starts in September.

The post 🎁 Bonus: The Conscious Marketer’s Cold Email Playbook appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

🎉 10ᵉ et dernier article de la série de juillet sur The Growth Ethos. Abonnez-vous ici pour lire la suite en septembre.

Pardon, English readers! This last post is exclusively in French 🇫🇷

“Quand les valeurs guident l’action, la croissance devient un effet secondaire naturel.”

Le vrai test de ces principes ? Le B2B.
Cycles de vente longs. Parties prenantes multiples. Départements achats obsédés par le coût.

Ces cinq entreprises européennes ont repensé la croissance avec des choix radicaux : transparence totale, gouvernance partagée, sobriété stratégique.

1. Fairphone — la transparence B2B comme avantage concurrentiel

Ce qu’ils font : Au-delà de la vente de téléphones, Fairphone a construit la chaîne d’approvisionnement électronique la plus transparente d’Europe. Ils travaillent directement avec les fournisseurs de composants [2].

L’innovation B2B : Ils ont cartographié tous les fournisseurs de composants de deuxième niveau et publient des relations détaillées avec les fournisseurs, les coûts et les métriques d’impact [2]. Les équipes achats peuvent voir exactement d’où vient chaque composant.

Pourquoi c’est important pour le B2B : L’approvisionnement électronique traditionnel est une boîte noire. La transparence radicale de Fairphone crée la confiance avec les clients entreprises qui doivent respecter leurs propres exigences de reporting de durabilité.

La contrainte opérationnelle : Une transparence complète signifie qu’ils veulent “combler le fossé entre les gens et leurs produits”, mais cela implique aussi qu’ils ne peuvent pas cacher les inefficiences ou négocier agressivement.

Pourquoi ce modèle est difficile à copier ? Reconstruire les relations fournisseurs autour de la clarté plutôt que de la minimisation des coûts est complexe.

2. Les coopératives de plateforme — propriété partagée

Ce qu’elles sont : Les coopératives de plateforme utilisent un site web, une application mobile ou un protocole détenu et gouverné de manière collaborative pour faciliter la vente de biens et services, où les utilisateurs possèdent et contrôlent collectivement la plateforme [5].

L’innovation B2B : Au lieu d’extraire de la valeur des effets de réseau, ces plateformes partagent la propriété avec leurs utilisateurs professionnels. Des initiatives européennes comme Fairbnb.coop montrent comment des prestataires (les hôtes, dans ce cas) peuvent co-posséder la plateforme [3].

Enjeu spécifique pour le B2B : Les plateformes traditionnelles deviennent plus coûteuses à mesure qu’elles gagnent du pouvoir de marché. Les structures collaboratives de plateforme alignent les incitations—les améliorations bénéficient directement aux propriétaires.

La contrainte opérationnelle : La gouvernance participative est lente. Chaque décision de plateforme à besoin d’un consensus des parties prenantes, rendant le développement rapide de fonctionnalités et les pivots stratégiques beaucoup plus difficiles.

Pourquoi ce modèle est difficile à copier ? Requiert une fragmentation industrielle et un environnement réglementaire qui soutient les structures commerciales coopératives. Fonctionne mieux en UE où le droit coopératif est bien développé.

3. Quideos — rendre la finance agricole lisible

Ce qu’ils font : Plateforme de gestion des risques pour les coopératives et agriculteurs français confrontés à la volatilité des prix des matières premières. Leur modèle s’appuie sur une tarification algorithmique transparente [1].

L’innovation B2B : Transparence algorithmique complète dans la finance agricole. Les agriculteurs et coopératives peuvent voir exactement comment les prix sont calculés, quels frais sont appliqués et comment les risques sont distribués [1].

Impact sur les relations B2B : La finance agricole traditionnelle tire profit de l’opacité; banques et traders gagnent de l’argent grâce aux avantages informationnels. Quideos, en revanche, gagne de l’argent uniquement sur la valeur du service, créant la confiance avec les acheteurs qui ont souffert de prêts prédateurs.

La contrainte opérationnelle : La transparence signifie qu’ils ne peuvent pas extraire de frais cachés comme la finance agricole traditionnelle. Les revenus proviennent purement des frais de service déclarés.

Pourquoi ce modèle est difficile à copier ? Ce modèle exige des écosystèmes matures — mais là où les coopératives sont fortes, il prouve qu’une finance utile, lisible et éthique est non seulement possible, mais compétitive.

4. Coopératives énergétiques européennes — infrastructure comme gouvernance démocratique

Ce qu’elles font : Fourniture d’énergie via des réseaux de production et distribution détenus collectivement. Les clients entreprises deviennent copropriétaires de leur infrastructure énergétique [6].

L’innovation B2B : Les utilisateurs peuvent devenir membres coopérateurs, partageant à la fois la propriété et la gouvernance de leur approvisionnement énergétique. Les contrats long terme deviennent des prises de participation, alignant les intérêts entre fournisseur et client [3].

Ce que cela change dans une logique B2B : L’approvisionnement énergétique traditionnel est conflictuel, les fournisseurs maximisent les marges tandis que les clients minimisent les coûts. La propriété multipartite aligne les incitations autour de l’efficacité long terme et la stabilité du réseau plutôt que l’extraction trimestrielle.

La contrainte opérationnelle : La gouvernance limite la mise à l’échelle rapide et nécessite une consultation approfondie des parties prenantes pour les décisions stratégiques. Elle ne peut pas poursuivre une expansion de marché agressive comme les services publics traditionnels.

Pourquoi ce modèle est difficile à copier ? S’appuie sur un cadre réglementaire soutenant les coopératives énergétiques et des clients entreprises prêts à échanger la flexibilité contre la stabilité long terme et la propriété partagée.

5. UCT — l’optimisation des coûts par l’achat collectif

Ce qu’ils font : UCT est une coopérative d’achats française dédiée aux professionnels du transport et de la logistique. Elle permet à ses membres de mutualiser leurs volumes d’achats pour obtenir de meilleures conditions sur des postes clés comme le carburant, les véhicules, les pneumatiques ou les assurances [4].

L’innovation B2B : Au lieu de négocier individuellement avec les fournisseurs, les transporteurs adhérents à UCT bénéficient de la force d’un grand groupe, sans perdre leur indépendance.
Cela réduit drastiquement leurs coûts d’exploitation et améliore leur compétitivité face aux acteurs plus importants, générant des économies substantielles pour ses membres [4].

Pourquoi c’est important pour le B2B : Dans un secteur à faibles marges et forte concurrence, la mutualisation des achats permet aux petites et moyennes entreprises de transport de rester viables.
Elle offre aux clients professionnels des transporteurs (les chargeurs) une chaîne logistique plus robuste et des services à des prix plus stables et compétitifs [3].

La contrainte opérationnelle : Comme toute structure collaborative, la prise de décision peut nécessiter plus de temps et de consensus entre des membres aux besoins diversifiés. L’efficacité maximale dépend de l’adhésion aux stratégies d’achat définies.

Pourquoi ce modèle est difficile à copier ? Ce système exige une forte confiance entre des entreprises potentiellement concurrentes et une volonté de mutualiser des données ou des besoins. Il est particulièrement efficace dans les secteurs où les achats représentent une part significative des coûts d’exploitation.

Principes opérationnels spécifiques au B2B

Ces approches participatifs et transparents fonctionnent dans ces contextes car ils résolvent des problèmes que les relations commerciales traditionnelles ne peuvent pas :

La question de réplication B2B

Ces cadre opérationnel fonctionnent car ils résolvent des problèmes structurels dans les relations commerciales :

• Asymétries de confiance : Les relations impliquent souvent des déséquilibres de pouvoir significatifs. Les structures collaboratives et la transparence radicale uniformisent les règles du jeu.

• Alignement long terme : Les clients entreprises font des investissements d’infrastructure qui durent des années. La propriété partagée aligne les incitations des fournisseurs avec le succès client.
  
• Navigation réglementaire : Les industries complexes demandent souvent des réponses coordonnées à la réglementation. Les modèles participatifs de gouvernance facilitent l’alignement industriel.

• Coordination industrielle : Beaucoup de défis nécessitent des solutions à l’échelle de l’industrie. Ces structures permettent l’action collective tout en préservant la concurrence.

Ce qui est transférable aux autres marchés

• Les disciplines opérationnelles : La transparence radicale, la gouvernance partagée et la croissance contrainte créent des avantages concurrentiels que les entreprises traditionnelles ne peuvent pas facilement reproduire.

• Les solutions structurelles : La propriété coopérative et la gouvernance démocratique résolvent les problèmes de confiance et d’alignement qui existent à travers industries et géographies.

• Les relations client : Quand les clients deviennent parties prenantes, les coûts de changement augmentent dramatiquement et le développement commercial devient plus prévisible.

L’implication stratégique

La question n’est pas de savoir si ces configurations sont moralement supérieurs, mais s’ils créent des avantages concurrentiels durables que les relations d’affaires traditionnelles ne peuvent pas égaler.

Pour les entreprises B2B dans des industries avec des déficits de confiance, une complexité réglementaire ou des défis de coordination, ces approches offrent plus que de l’inspiration.

SOURCES

[1] Quideos – “Gérer le risque prix en toute transparence”
[2] Fairphone – Cartographie et initiatives de transparence de la chaîne d’approvisionnement
[3] Coopératives européennes – Structures commerciales et modèles de gouvernance coopératifs
[4] UCT (Coopérative d’achats du Transport) – Mutualisation des achats pour les professionnels du transport
[5] Coopératives de plateforme – Modèles et infrastructure numérique partagée (ex: Fairbnb.coop)
[6] Coopératives énergétiques européennes – Modèles d’approvisionnement B2B

THIS SERIES IS COMPLETE

What a journey it’s been! 🥳

This article wraps up our 10-post series on The Growth Ethos, where we’ve explored smarter, more sustainable ways to scale in 2025.

If you missed previous posts in this series, here are the links to catch up:

• Part 1: Growth Marketing 101 (2025 Edition): A Conscious Marketer’s Guide
• Part 2: Why Vanity Metrics Are Dying (and What to Track Instead)
• Part 3: How to Build a Sustainable Growth Engine Without Burning Budget (or the Planet)
• Part 4: Circular Growth Loops Are the Future of Ethical Marketing
• Part 5: 6 Martech Tools Every Ethical Brand Should Be Using This Year
• Part 6: From Scarcity to Stewardship: The New Psychology of Conscious Consumers
• Part 7: Dark Social and Micro‑Communities: How Sustainable Brands Are Winning Trust
• Part 8: Sustainable Paid Media: How to Align Ads with Purpose in 2025
• Part 9: SEO for Good: Content That Powers Purpose and Growth
• Part 10: B2B : 5 modèles européens qui réinventent la concurrence
• 🎁 Bonus: The Conscious Marketer’s Cold Email Playbook

LET’S BUILD SOMETHING BETTER

If you’ve followed along this far, merci. If you’re building with clarity, courage, and care — I’d love to connect.

📬 Subscribe to the newsletter to get each new post as it drops, directly to your inbox.

The post B2B : 5 modèles européens qui réinventent la concurrence appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

“If your metrics look strong but your growth feels fragile, you’re probably tracking the wrong signals.”

1. Time’s up for vanity metrics

We all know them: bounce rate, impressions, total followers, and CTRs without context. They make dashboards look impressive, but they rarely tell you what’s truly working.

Vanity metrics give the illusion of progress. Behind the surface, they often hide bigger issues:

• Leads that never convert
• Followers who never engage
• Traffic that never returns

Forward-thinking growth teams, especially in B2B and purpose-driven businesses, are shifting toward metrics that reflect value, momentum, and alignment.

2. What makes a metric “vanity”

It’s not always about the metric itself; it’s about what it tells you (or doesn’t).

A metric becomes vanity when:

• It doesn’t influence decisions
• It lacks context or strategic value
• It grows while your business stalls

“10,000 pageviews may look good on paper. However, if 92% of the traffic bounces and only 0.3% converts, that traffic is essentially noise.”

3. What to track instead

Here’s what growth-conscious marketers are tracking instead in 2025:

4. Metrics with meaning (especially for purpose-driven brands)

To go deeper, here are five high-signal, value-aligned metrics you should consider building into your strategy:

a. Activation rate

How many users reach their first meaningful milestone?
Example: Downloading a carbon-saving tool or completing a product demo.

b. Referral-to-signup ratio

Are users bringing others with them?
This is one of the most powerful signals of real product affinity.

c. Time-to-impact

How quickly can someone see results or value from your offer?
Shorter time = higher retention and trust.

d. Values-aligned lead %

What portion of your leads match both your ICP and your mission?
A simple lead scoring system can help track this.

e. Community contribution rate

Who isn’t just consuming, but actively sharing, commenting, or co-creating with you?

5. The bigger picture: why this shift matters

Tracking more meaningful metrics isn’t just about efficiency but clarity and alignment.

If you’re building a mission-driven brand, surface-level performance isn’t enough. Global data from PwC shows that consumers are willing to pay an average of 9.7% more for sustainably sourced products. This reinforces that sustainability-aligned growth isn’t just ethical, it’s commercially strategic.

You need indicators that tell you:

• Are we delivering something people want?
• Are we attracting the right users?
• Are we building long-term momentum or chasing short-term peaks?

Better metrics lead to better questions, better alignment, and better growth.

WHAT’S NEXT IN THIS SERIES

This is part 2 of The Growth Ethos, a 10-part blog series on how to grow with clarity, intention, and impact in 2025.

Coming next:
→ How to Build a Sustainable Growth Engine Without Burning Budget (or the Planet)

LET’S BUILD SOMETHING BETTER

If you’re rethinking how growth should look—more intentional, more ethical, more effective—this series is for you.

📬 Subscribe to the newsletter to get each new post as it drops, directly to your inbox.

The post Why Vanity Metrics Are Dying (and What to Track Instead) appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.

This is part of a 10‑part July series on The Growth Ethos. Subscribe to follow it.

This series explores how to grow with clarity and intention in 2025, focusing on designing systems that align performance with purpose and turn momentum into meaningful progress.

“Fast growth is easy to sell. Meaningful, resilient growth—the kind that lasts—is what actually matters now.”

1. Growth has evolved. So must we.

Let’s face it, growth marketing used to be about scale at any cost. Run ads, launch popups, push users through funnels.

But we’ve changed. Your audience has changed. And in the shadow of climate urgency, greenwashing fatigue, and digital burnout, your growth strategy must mature, too.

“Not just how fast can we grow, but how fairly, how sustainably, and how durably?”

According to Deloitte, 63% of European consumers now prefer brands with verified environmental impact over legacy leaders (Deloitte, 2025 Global Sustainability Consumer Survey).

2. Circular economy style

If we’re serious about sustainability, we need to rethink more than just our messaging. We need to reimagine the system itself.

• Instead of extract → convert → churn
• Build systems that recirculate value, minimise waste, and optimise retention

In 2025, the best growth marketers aren’t funnel-obsessed—they’re ecosystem builders.

Example: The Loop

Take a company like Phenix (France). They fight food waste by redistributing unsold goods to NGOs and consumers. Their growth isn’t just visible in dashboards—it lives in impact feedback, community loops, and storytelling that sustains trust.

Here’s how a circular growth loop can look:

1. Educate: Share content, tools, or newsletters that create awareness and build shared values.
   Example: “Decode your supply chain emissions in 30 seconds.”
   
2. Engage: Offer free trials or diagnostics. Make it easy, data-rich, and respectful.
   Example: “Estimate how much CO₂ you could offset by adjusting X input.”
   
3. Exchange: Capture insight, not just emails. Ask questions to learn what your audience cares about and create better products and content.
   Example: “What’s your biggest procurement risk today?”
   
4. Enrich: Show the user their impact. “By switching to us, you helped stabilise 3 commodity prices and saved 2.4t of CO₂.”
   
5. Extend: Close the loop with co-creation or advocacy. “Want to share your impact story with our community?”

This isn’t just a funnel, it’s a system designed to regenerate value.

3. The new KPIs of conscious growth

Legacy metrics no longer tell the full story. In 2025, high-performing teams track hybrid indicators that reflect both business and impact performance.

Tools like Scope3, Fathom, and Matomo help measure not just user behaviour, but do so in ways that respect privacy, consent, and environmental impact.

According to BCG and Ad Net Zero, carbon KPIs are expected to become standard benchmarks across major EU ad networks by late 2025 (BCG x Ad Net Zero, The Sustainable Media Report).

4. Winning tactics in 2025

Conscious B2B marketers aren’t just polishing mission statements. They’re upgrading their playbooks:

• Ghostbuster-level traffic cleanup: Filter out bot traffic, click farms, and fake engagement. Focus on high-intent, real users. Better funnels. Better data. Less digital noise.
• Impact-layered attribution: Don’t just ask which channel converts.
  Ask: “Which channel brings aligned, long-term customers who care about what we stand for?”
• Carbon-budgeted campaigns: Some teams now assign emissions limits to ad launches.
  Example: “We’ll greenlight this if we stay under 20g CO₂ per lead.”
  
  According to Scope3, programmatic ad emissions can vary by over 25x depending on format, publisher, and placement (Scope3, State of Sustainable Advertising 2025).

These are signs of where growth is headed: less waste, more resonance, and performance that earns its keep.

5. Real growth = shared growth

When you stop seeing users as data points and start treating them as collaborators, everything changes.

In a world where attention is scarce, honesty scales.

Where distrust is high, impact wins.

And where resources are limited, circular systems outperform linear ones—every time.

WHAT’S NEXT IN THIS SERIES

This post marks the beginning of The Growth Ethos, a 10-part blog series that explores how to build resilient and sustainable growth strategies for 2025 and beyond.

Coming next:
→ Why Vanity Metrics Are Dying (and What to Track Instead)

LET’S BUILD SOMETHING BETTER

If you’re rethinking how growth should look—more intentional, more ethical, more effective—this series is for you.

📬 Subscribe to the newsletter to get each new post as it drops, directly to your inbox.

The post Growth Marketing 101 (2025 Edition) appeared first on SAMIN GHIASI | GROWTH MARKETING CONSULTANT | FR/EN.