New Analysis Shows ecolytiq’s Proven Impact

We are driven by our mission to create positive climate impact at ecolytiq — about helping banks empower consumers to make more sustainable choices and building a greener future. But what does that actually look like in practice? More importantly, how do we know we’re really making a difference?

In this post, we’re pulling back the curtain to share a preview of our latest research findings and upcoming Impact Report, which features scientific analyses that validate whether ecolytiq’s solution is moving the needle on household-level sustainability. And at the heart of it is our Success Greenprint — the framework we use to measure what matters.

Why Is This Important?

Impact implies causality. It’s not enough to say people are engaging more, or that emissions intensity is declining — we need to understand whether those changes are being driven by our solution.

At ecolytiq, we balance two complementary approaches to learning: our preferred method is more rigorous, focused on isolating and proving causal impact; the other is agile and exploratory, helping us spot trends and inform product design quickly. Like many organizations, we conduct regular descriptive analyses to recognize patterns and trends after the introduction of our solution. These insights are invaluable for tracking early indicators, iterating on product features, and supporting our customers.

But when it comes to our core impact – ultimately reducing greenhouse gas emissions – we know that scientific standards matter. That’s why we are invested in a more robust study design to validate whether our solution truly drives meaningful change. Together, these dual approaches allow us to build better products while ensuring we’re on the right path to real-world impact.

We’ve conducted our analyses from multiple perspectives and with more rigor than ever to account for these factors. These impact evaluations further underscore and validate our Theory of Change and the positive impact we can achieve with our solution.

The Success Greenprint: Our Impact Measurement Framework

Real impact needs to be measurable, tested, and iterated. That’s why we created the Success Greenprint — a structured methodology for measuring, evaluating, and learning (MEL) from our household-level interventions.

To build this framework, we:

• Mapped user behavior using results chains
• Identified key barriers to sustainable lifestyles
• Defined both process/output indicators (e.g., engagement) and outcome/impact indicators (e.g., spending behavior and emissions intensity)
• Chose evaluation methods based on data availability and context

What We Measured

Last year, we conducted a large-scale descriptive analysis of post-launch data across multiple implementations and geographies – with promising results. Even with a large and diverse sample, we observed a 13% reduction in emissions following the introduction of the solution, while the weekly number of transactions and spend volume increased by 10% and 6%, respectively.

To build upon these findings, we conducted deeper, bank-level analyses with banks that implemented our retail sustainability solution between 2023 and 2024. Where historical data was available, we had a clear view of how users were spending before and after the solution was introduced.

The ability to compare users with a control group allowed for a robust regression-based impact evaluation — our preferred and most scientifically rigorous method for evaluating causal relationships. In one key implementation, this enabled us to apply a difference-in-differences regression method with a staggered adoption design. This study design helped isolate the treatment effect while accounting for seasonality, income, and other individual characteristics.

In parallel, we ran exploratory and descriptive analyses on other implementations to detect broad-level patterns. We regularly evaluate other implementations across diverse user groups and geographies to test scalability – a critical enabler of our mission. Each analysis helps us validate previous findings, identify outliers, and refine our product to be more effective across contexts.

Validating Our Product Impacts: Regression-Based Insights

To isolate the true impact of ecolytiq’s solution by accounting for external variables, we conducted a regression analysis. The analysis focused on one implementation type, used historical data, and clearly defined a control group to limit confounding factors. This allowed us to run a robust, regression-based evaluation — providing our strongest evidence yet that our solution drives measurable, meaningful behavior change.

We strive to apply causality-based analysis at every opportunity to validate our solution’s impact. While this type of evaluation is resource-intensive and not always suitable in every context, it provides a much higher level of confidence that the observed changes are the result of our solution, not external factors or chance.

Note: Statistical significance indicates the probability that the observed effect occurred by chance rather than because of the intervention. For example, a 5% significance level (p < 0.05) indicates just a 5% probability that the observed effects are due to chance, providing strong evidence that our solution is making a genuine impact.

The results?

We compared 52 weeks of both pre- and post-treatment data of early adopters with the pre-opt-in data of late adopters serving as a control. We use a Difference-in-Differences approach to observe differences between the two groups so that any impacts we find are relative to the control group in the same period. After 52 weeks, we found:

• An 8% reduction in emissions per user (p < 0.05)
• A 5% reduction in emissions intensity of spending (p < 0.05)
• All while maintaining stable spending levels — no trade-off between financial wellbeing and sustainability.

Users of ecolytiq’s solution appear to be spending more sustainably and not spending less. These changes persisted over time. After 52 weeks, treatment group users had 8% lower emissions and 5% lower carbon intensity* of spending than the control group, suggesting the shifts were sustained, not short-lived.

*Carbon intensity refers to the CO₂e emissions per unit of currency (i.e., how “emissions-heavy” purchases are). For our purposes, we use EUR as our baseline currency to make figures comparable across geographies.

We also saw notable reductions in high-emissions spending categories:

• Groceries: -5% emissions (p < 0.05), -4% carbon intensity (p < 0.01)
• Transportation: -13% emissions (p < 0.10), -5% carbon intensity (not statistically significant, indicative trend)
• Living Expenses: -8% emissions (p < 0.10), -4% carbon intensity (p < 0.01)

These statistically significant reductions are linked to more sustainable consumption behaviors rather than reduced activity. In fact, users increased their number of transactions in the living category by +6% (p < 0.01) — suggesting the solution drives more thoughtful choices, not less spending.

This is powerful evidence that ecolytiq supports climate-positive behavior and helps consumers make lower-emission choices without compromising convenience or lifestyle. When further interpreting results, it should also be noted that these insights reflect users who actively opt into the solution, suggesting a higher baseline level of environmental awareness. As a result, while these trends indicate promising potential, they are most applicable to pro-environmental users and should be interpreted in this context.

Overall, this analysis offers high statistical confidence that these changes were driven by ecolytiq’s intervention — not chance, not seasonality, and not other outside factors. That’s a big deal in an industry where rigorous evaluation is often missing or anecdotal.

Overall, this analysis offers high statistical confidence that these changes were driven by ecolytiq’s intervention — not chance, not seasonality, and not other outside factors.

Testing an Alternative Implementation: Early Signals from a Broader Sample

While our regression analysis offers strong evidence of impact among sustainability-motivated users, we also explored a different implementation type — one where users were automatically enrolled, resulting in a broader and more representative sample of the general population. While there was no control group available in this instance, these descriptive insights reveal promising patterns that that suggest our solution is having a meaningful impact. After 52 weeks, we saw a: 

• 13% increase in the number of transactions
• 15% increase in transaction volume

These descriptive findings are encouraging and may suggest that even among a general user base, ecolytiq’s solution is nudging behavior in the right direction. This analysis offers early signals of potential impact and reinforces the importance of continuing to test and validate across different implementation types.

This analysis offers early signals of potential impact and reinforces the importance of continuing to test and validate across different implementation types.

What This Means for Impact and the Industry

Measuring real-world impact is one of the toughest — and most important — challenges in sustainability. In a space with few shared standards, our recent progress in data and evaluation allows us to lead the charge in taking a meaningful step forward. This allows us to demonstrate value for our customers, their clients, and the community at large.

Through a scientifically and operationally pragmatic approach — including our first statistically significant regression analysis — we’ve strengthened the case for how ecolytiq’s solution drives measurable change. These results not only validate our Theory of Change, but also support the credibility of spend-based emissions insights more broadly.

In an emerging field where transparency and trust are critical, demonstrating clear outcomes matters. And sharing what we learn is just as important. Our data is more than a proof point — it’s a contribution to a growing movement for standardized, accountable, and effective climate action. We’re using these insights to design smarter interventions and accelerate change that works in practice, not just in theory. That’s why we’re committed to sharing our findings openly and responsibly — helping to shape a stronger, more evidence-based path forward for the industry.

Our data is more than a proof point — it’s a contribution to a growing movement for standardized, accountable, and effective climate action.

What’s Next?

We’ll be publishing the full Impact Report soon — with even more findings, learnings, and next steps. But for now, we hope this gives you a window into how we think about impact: not just as a buzzword, but as something we measure, test, and improve.

Got questions about our methodology or want to collaborate on future research?
We’d love to hear from you — reach out to us at info@ecolytiq.com.

Stay tuned for the full report — and thank you for being part of our journey toward a more sustainable future.

Special Acknowledgements

We want to recognize Dr. Gracia Lanza Castillo, our in-house scientist who manages our Research function, for her incredible efforts in leading this analysis. Her expertise in Environmental Economics, Sustainability, and Climate research ensures our work remains grounded in scientific integrity and analytical rigor.

Thank you, Gracia!