How Creating a Customer-Centric Culture Led to Increased Conversions

Insight/Action/Outcome: Users who downloaded the rebuy mobile app often wanted to know their device’s value, but had to navigate several screens to receive an estimate for selling their device to rebuy. Using data from Amplitude Analytics, the product team created a link on the home page asking users if they wanted to know the value of their device. Taking them straight to that questionnaire increased the number of users grading Samsung phones by 30% and phones by 11%, giving the company more stock to resell online. The tile also caught the interest of users who weren’t initially interested in selling their device, creating additional conversions.

Some businesses call themselves data-driven, but they only look at the numbers, which only reveal part of their reality. At rebuy, we’re following an approach that combines talking to our customers and looking at the numbers, which is incredibly powerful and helps us stand out in the eCommerce space.

I am passionate about eCommerce. I love connecting with end users to understand their needs and find ways to serve them better. Making things easier for them is the heart and soul of product development, and I strive to put our customers first.

I came to rebuy, a Berlin-based retailer that facilitates a circular economy, to create a culture around customer-centricity. We buy used electronics and media products from our customers, refurbish and resell them, giving new life to products and diverting them from the landfill. We have almost 500 employees, and our 15-person product team includes product managers and designers, UX researchers, and writers.

I’ve spent most of my career in the eCommerce space in different industries, and I keep hearing about companies wanting to be close to the customer but not doing anything to make it happen. Marrying customer conversations with data helps us understand what’s happening to the customer, sparking creativity that allows us to explore exciting new possibilities and make decisions that help us get us closer to our customers.

But sometimes getting closer to customers is easier said than done.

Reducing unnecessary complexity

Back in 2014, I was working for an Argentinian startup that used Google Analytics (GA) to optimize our mobile app. It worked well at the beginning, but eventually the results didn’t offer the level of detail we needed. We weren’t alone. Many companies start with GA because they see it as an easy option, but now it feels like it’s from a different era. It was tough to understand what was tracked, what was not, and how to find it. If you know what answer you need, you can get it in GA, but playing with the data and exploring what you don’t know becomes super complicated.

Some companies struggle with GA because of poor implementation and lose sight of their data, but that wasn’t the case at rebuy. We had a solid GA setup, but it still didn’t offer what we wanted. Its complex nature meant that people went to find out one or two things without going any further. The first thing I said when I came to rebuy was, “Google Analytics is not going to help us get the data culture we want here.”

When I worked at the startup and started exploring alternatives to GA, I came across Amplitude Analytics, and I’ve used it at multiple companies since. Amplitude Analytics became my go-to platform because of its user-friendly interface and its exploration capabilities. If a platform is too hard to use, people don’t bother. But Analytics makes it easy for people to ask questions upon questions, helping us learn more about why our customers do what they do.

I pitched Amplitude to our CTO based on my past positive experiences, and he agreed with my choice. I knew our product team was on board, but other departments used GA, too. And since GA offers many out-of-the-box solutions, I was worried that some of these departments wouldn’t be happy with such a significant change. But once they saw how Amplitude worked, it was an easy conversation. We decided to move everything over to Analytics and Experiment, including the data we use for reporting.

Features that everyone uses

We needed to move quickly. Some of our core business processes depend on this data, and we could not interrupt ingesting sessions and tracking users. The Amplitude team accommodated our tight schedule, and we went from signing the contract to the first iteration of our tracking system in two months.

Amplitude has helped rebuy create a culture that encourages everyone in the company to make data-driven decisions. Today, our primary use cases are measurement and exploration. Our commercial, marketing, and product teams use Analytics to see how many people are looking at our pages, the items users are viewing, and see conversion rates. Our product and product design teams use Analytics to develop hypotheses about user behaviors and turn to Experiment to test them. Our designers (who aren’t usually into data) poke around in Analytics to see how design elements affect user behavior. Even our pricing team uses Experiment to test different prices to increase profitability.

I use Segmentation and Funnel Analysis Charts daily. I also use the Journeys feature to dive deep into transitions along a user path. If I see a significant drop at one step in our funnel, I can zoom in and see what users do after dropping out. Knowing when potential customers leave our funnel impacts how we adjust our product development and marketing efforts.

Unexpected insights and outcomes

Adopting Analytics and Experiment has led to some unexpected outcomes.

We took data from Analytics and fed it to Experiment to run A/B tests about the number of questions we ask when users offer to sell us their used electronics. We assumed the more detailed questions would lead to fewer conflicts (when the assessment the customer makes about the goods for resale differs from our experts’ in-facility assessment). But regardless of the number of questions we asked, the number of conflicts between the customer’s assessment and the assessment of our experts remained the same. This led us to rethink the kinds of questions we asked.

Another such insight was that users who downloaded our mobile app often wanted to know the value of their mobile device. But they had to navigate several screens to get an estimate and sell their device to us. Using data from Analytics, we created a link on the home page asking users if they wanted to know the value of their device. Taking them straight to our device questionnaire increased the nuber of users grading Samsung phones by 30% and phones by 11%, giving us more stock to resell online. The tile also caught the interest of users who weren’t initially interested in selling their device, creating additional conversions.

Another obvious but counterintuitive insight was that our homepage is not the most important page on our website. Many of our customers follow an ad or a web search and end up on another landing page. Analytics allowed us to see that, while our homepage is often the primary destination, we must optimize every page so that every customer journey starts and ends smoothly, no matter where our users originate.

Unified Analytics and Experiment provide quantitative data we can combine with qualitative data for deeper insights into customer behavior. We’re currently focusing on monetization and micro-conversions at every step of our funnel, and Amplitude is the starting point for these meaningful conversations. We begin with quantitative data from Amplitude to see where our customers are dropping off. We then conduct in-depth customer interviews to validate these insights and determine whether they apply to our entire user base or specific customer segments.

The opposite can also happen. I recently spoke with a colleague who conducted customer interviews about some of our current campaigns. The users he spoke to were excited about these offers, but Analytics revealed that most of our customers weren’t, and the impact of these campaigns on our bottom line was negligible.

Reducing operational dependencies

One of my primary goals in bringing Amplitude to rebuy was reducing operational dependencies. We used GA along with an open-source A/B testing framework to run randomized tests. Our engineers were proficient at setting up A/B tests, but our product team couldn’t easily explore the resulting data to determine the significance or impact of the metrics recorded. If you weren’t a data scientist or statistician, you couldn’t do anything with the numbers. Experiment liberated our product and marketing teams because anybody can now make sense of A/B test results. The easy-to-understand charts and graphs mean they don’t need help interpreting the numbers, which saves our data science teams time while unblocking experimentation for product and marketing teams.

Our previous platform was also limited to transactional data. We could see everything leading up to a sale or a purchase, but nothing past that. Analytics and Experiment allow us to see what happens after a customer completes a transaction. What customer segment is returning products? What was their journey through our funnel? It’s a work in progress, but we can now look at post-transactional data and connect the dots to what happened during the sale or purchase process.

Amplitude helps us build for maximum impact

We need to learn what works and what doesn’t as fast as we can, and Amplitude enables us to step up our efforts. Adoption is exponential, and queries have skyrocketed. I ran over 14,000 Amplitude queries in the last year. I’m not proficient in SQL, so I would have needed to work with a data scientist from our BI team to answer those queries without Analytics. Using GA and an open-source A/B testing platform would take more time, and I would’ve only achieved a fraction of what I can do with Analytics and Experiment.

Now that customer data and A/B experiments are just a click away in an easy-to-interpret dashboard, teams have become hungry for information and use data to their maximum benefit.

We have more than 50 active Amplitude users at our central office, and we’ve seen a massive change in product team behavior. We were always interested in data, but gathering BI was arduous, and waiting for our data scientists to respond stifled our curiosity. Now that customer data and A/B experiments are just a click away in an easy-to-interpret dashboard, teams have become hungry for information and use data to their maximum benefit.

I don’t like building things for the sake of it. I value results and strive to have an impact on our customers and our business. Analytics and Experiments provide data that accelerates the product development cycle, giving us the foundational blocks to boost the metrics that matter to the company by identifying where to best invest our resources.

Thanks to Amplitude, we have increased conversion rates and adds to cart. We have optimized our app and website. And we now have the tools and the data culture to thoroughly map our funnel and analyze our user journeys, creating experiences to delight our customers and maximize our bottom line.