Add Data to Cart: How Ankorstore Ended Data Bottlenecks with Amplitude

Insight/Action/Outcome: When Ankorstore needed to switch to a self-service data culture, they needed a strategic analytics partner—and Amplitude was the clear choice. Ankorstore has gained both visibility and velocity across their organization, from enriching marketplace data to leadership being able to self-serve data-driven answers. One experiment even boosted add-to-cart rates 7%. Removing data bottlenecks has raised their revenue and helped them grow.

Every team wants data, and they want it yesterday. But hiring an analyst for every squad isn’t realistic, and it’s hard to scale a cohesive data unit alongside the rest of the business.

At Ankorstore, we figured out a way to do both.

Ankorstore is a European B2B marketplace connecting more than 300,000 retailers, grocery stores, coffee shops, and other concept stores with makers of authentic products and brands that ecommerce giants don’t offer.

A thriving marketplace requires matching the right brands with the right retailers. To do that, we track typical ecommerce metrics like product discovery, searches, views, and add-to-cart rates. We launch new features weekly to improve key touchpoints so retailers can find their ideal products faster and brands reach more buyers.

Stakeholders understandably want to know what’s working, what isn’t, and why—but it used to be hard to pin down those answers.

A shopping list for the next phase

For one thing, our data function was very service-oriented. Stakeholders would request reports, but it took analysts days or even weeks to prepare and interpret data models. With business intelligence scattered across different squads, we lacked harmonization and governance.

In a marketplace like ours, we can’t afford to wait weeks to know if something’s working. We wanted to shift from a service ticket approach to one that placed more value on self-service, giving teams everything they needed to make fast, fact-based decisions on their own.

We started evaluating product analytics partners, including Amplitude, Pendo, Heap, and Mixpanel. Amplitude stood out for a few reasons:

• Platform maturity. Amplitude supports a range of use cases, from simply measuring traffic to more advanced analytics such as retention and survival analysis. The ability to connect data in different ways and perform more advanced reporting appealed to us, along with the Amplitude team’s knowledge of the product, marketing, and data landscape.
• A solid reputation. We wanted to work with a state-of-the-art company that had significant market presence. As we expanded our internal capabilities, we would also benefit from an expanded talent pool. Hiring people fluent in the platform’s UI meant they could start having an impact quickly, crafting data points and accelerating feature development.
• A collaborative spirit. Amplitude understood our business context and our desired use cases. Post-sale, their engineers helped us design event collections and develop the right analytical workflows. Having a dedicated CSM and French-speaking support made for a smooth rollout and ensured adoption across all teams.

Pendo wasn’t as mature and didn’t have a comparable market penetration. Heap had been bought by ContentSquare, and we weren’t confident in its product evolution and future development. Mixpanel was a strong contender, but ultimately, we felt that the Amplitude sales and CSM teams were better positioned to support our goals.

The only way we could evolve was to work with a strategic partner who would help us ensure our data was well-modeled, governed, and actionable as we grew. Amplitude was that partner.

Contextualizing data without any heavy lifting

We unlocked the full power of Amplitude Analytics through an integration with Twilio Segment, which we use to enrich and streamline event data.

When a user views a product on our marketplace, the event payload might only include a product or user ID. To understand what’s happening, though, we need context: product category, stock level, price range, and so on. If we overload the front or back end with that information, it would negatively impact the user experience.

Using JavaScript functions, Segment queries our internal APIs in real time, fetches the additional context, and enriches each event before feeding it into Amplitude. We have high-quality, contextualized data with minimal effort down the line.

Along with Analytics, we also used Data Replay from Twilio Segment to level-set our situation from the start. When we launched Amplitude, stakeholders wanted to compare new insights with historical performance. Data Replay allowed us to backfill 13 months of historical data, and having that data built immediate trust in the platform.

AI-focused, product-led growth? It’s in the bag

Putting the right platforms in place lays the foundation for using AI to accelerate how we build, ship, and measure features. Our developers leverage LLMs and tools like Cursor and Claude Code to generate and refine code. This step has accelerated feature delivery dramatically, from weeks to days. Because those features are instrumented directly into Amplitude, we can measure their impact almost immediately.

For example, as we craft new lead generation features, we use the OpenAI web search API to collect the retailers and brands metadata, contact details, and product info for potential brand partners. The API responses arrive already formatted and integrate directly into our systems. Having these details means we can craft more high-quality products that deliver more value to users.

Another standout example was when we enriched our product catalog using generative AI. We created two cohorts in Amplitude Feature Experimentation: one that saw the original catalog and another exposed to the AI-enriched version. In the cohort exposed to the AI-enriched version, we noted a 7% uplift in add-to-cart rate, directly translating to an increase in top-line revenue.

Amplitude gives us end-to-end visibility into how these features perform. From the moment they’re shipped, we understand how the product is performing, if it fits our users’ expectations, and if it’s driving the change we want. Our newfound ability to learn and iterate quickly allows us to lean into more product-led growth.

Data-literate teams that help themselves

With Amplitude, data bottlenecks no longer block our teams. Anyone can tap into Amplitude’s user-friendly UI to explore user journeys, test hypotheses, and track feature success independently. It’s driven greater data literacy, and product managers, developers, and even executives explore data and answer questions in minutes.

One of my favourite examples came during an eight-day event critical to our yearly performance. Our chief product and technology officer (CPTO) wanted to know whether to highlight brands or products on the homepage to maximize engagement. Within five minutes, he had opened Amplitude, built a funnel report, and began to adapt the value proposition. No waiting for analysts, no SQL queries. Simply insights on demand.

Developers and engineers use data to make small-scale product improvements, but this use case demonstrates that even top leaders can be hands-on in Amplitude. They use it to make the big decisions that help Ankorstore grow.

The right visibility to highlight our partners

If we lost Amplitude tomorrow, we’d lose not just visibility, but velocity. With less time spent answering day-to-day questions, our data team focuses on designing the right data models and making sure events are tracked correctly from the start.

Our biggest achievement so far hasn’t just been the increased revenue, but the end of our data bottlenecks. We now have more information at our fingertips to better match entrepreneurs and independent retailers, and it’s that engine that powers our entire marketplace.