How Olio increased subscription revenue by 50% with self-serve analytics

Olio is a community sharing app designed to reduce waste, both at home and across businesses. Through the app, users can give away or sell almost anything to neighbors. It started as a food sharing platform in the UK, where the idea was simple: if you had food you weren’t going to eat before it expired, you could pass it on to someone nearby. Olio has since grown well beyond household food. Today, volunteers collect unsold stock from retailers like Tesco and Sainsbury’s at the end of each day and redistribute it through the app, and users can give away and sell household items to their local community. Available across most countries, with its primary user base in the UK, Olio is used by millions of people looking to share more and waste less.

Olio has a lean data team and a growing need for answers. As the app scaled, questions from product, marketing, and engineering all funneled through one analyst. The company turned to Mixpanel to change that, building out a self-serve analytics layer that the whole company now uses directly. The impact showed up across the board: a pricing experiment that revealed Olio could maximise revenues by reducing its subscription pricing led to a ~50% increase in subscription revenue, while faster bug detection through Mixpanel alerts protected both ad and subscription income before issues could compound.

As Olio scaled, getting data to the people who needed it became the bottleneck:

• All data requests bottlenecked through a single analyst: Data requests from product, marketing, and engineering all queued behind a single person. Getting answers was slow, and experimentation was harder than it needed to be.
• Backend data showed what, not why: The data warehouse could flag that signups had dropped, but couldn’t explain where users were falling off or what was breaking. Investigating meant manual testing and guesswork.
• No early warning system: When something went wrong in a critical flow, like signup or ad delivery, the team had no way to catch it fast. Issues surfaced only after they’d already had an impact.

Olio adopted Mixpanel to give every team direct access to product data, without needing to go through the data team.

Key changes:

• Self-serve through Lexicon: Using Mixpanel Lexicon, Ivar Struijker Boudier, Senior Product and BI Analyst at Olio, translated backend event names into plain language and added screenshots of the app screens that trigger each event. A marketing manager or product lead can now understand exactly what they’re looking at without asking for help.
• Cross-team adoption: Product managers monitor new feature performance directly. Marketing builds audience cohorts in Mixpanel and syncs them to Airship for targeted campaigns. Engineers inspect funnel drop-offs and individual user profiles to diagnose bugs.
• Proactive alerting: Olio set up Mixpanel alerts on key metrics such as signup conversion and ad delivery. When something drops below the normal range, Ivar gets notified immediately, before it becomes a bigger problem.
• A/B testing at the variant level: The team uses feature flags to split users across test variants, then measures conversion and flow differences in Mixpanel to decide whether new features are worth keeping.

Mixpanel enabled Olio to increase revenue, improve campaign effectiveness, and detect critical issues faster.

1. A 50% lift in subscription revenue

For years, Olio’s subscription pricing had been set and left alone. When the team finally tested it in Mixpanel, running about 8 or 9 different price combinations and tracking conversion across variants, they found they’d been charging too much. Lowering the price brought more users over the threshold of being willing to pay, and subscription revenue went up by around 50%.

“We found out we were charging too much previously. That was sort of a blocker for users.”

– Ivar Struijker Boudier, Senior Product and BI Analyst, Olio

2. Clearer campaign performance

During a New Year campaign, marketing used Mixpanel to look past app opens. Opens were up a few percent. Transactional activity (actual listing creation and item requests) was up around 25%. That gap changed how the team interpreted success and how they planned future campaigns.

3. Revenue protection through fast bug detection

When Olio’s reward ads stopped showing reliably, Mixpanel alerts caught it fast. The revenue impact would have been double: fewer ad impressions and fewer subscriptions, since the friction that drives upgrades had disappeared.

“Without Mixpanel, that may have taken us longer to figure out.”

– Ivar Struijker Boudier, Senior Product and BI Analyst, Olio

The same applied earlier when a broken onboarding step was stopping new users from completing sign-up. Backend data showed something was wrong but not where. Mixpanel’s funnel view showed the exact drop-off point.

4. A leaner, faster data culture

Mixpanel is now used daily across product, marketing, and engineering, without running everything through the data team. Product managers check feature performance on release day. Marketing targets campaigns using cohorts built directly in Mixpanel. Engineers debug by inspecting individual user profiles. And when something unexpected shows up in the metrics, alerts make sure Ivar knows before the rest of the business does.

Approach

Olio started as a food sharing platform in the UK and has since grown into something broader: you can give away or sell almost anything through the app, and volunteers redistribute unsold food from retailers like Tesco and Sainsbury’s every day. Running that at scale, across millions of users, with a lean team, means everyone has to stay close to the data. For most of Olio’s life, that wasn’t really the case.

A one-person data team 

Data questions funneled through Ivar. The data was there. Getting to it just meant asking him.

Getting to self-serve meant making Mixpanel usable for non-analysts. Ivar did it through Lexicon, translating backend event names into plain language and attaching screenshots of the app screens that trigger each event. A marketing manager doesn’t need to know what a backend event string means. They can see the screen it maps to.

“It just makes it more than a tool that’s used by data people,” Ivar says. “It just becomes a self-serve tool, which is super valuable.”

When the data tells you something’s broken 

A few years back, Olio noticed users were creating accounts but not completing onboarding. On the backend, nothing pointed clearly to a cause. In Mixpanel, the drop-off was obvious: users were getting stuck at a specific step, likely something broken in the location selection screen. “If you have the data already there in Mixpanel, then that’s just immediately visible, and you can do something about it,” Ivar says. An intermittent bug that doesn’t trigger every time is hard to catch by walking through flows yourself.

That same alerting paid off when Olio’s reward ads stopped showing reliably. Non-subscribers see a short ad before they can make a request; it’s both a revenue source and an incentive to subscribe. When the ads broke, the impact was double: fewer ad impressions and fewer subscriptions. Mixpanel caught it quickly. “Without Mixpanel, that may have taken us longer to figure out,” says Ivar.

Testing the price they’d been assuming was right 

Olio has offered a paid subscription for around 5 years. For most of that time, the price was set and left alone. When the team finally tested it in Mixpanel, running about 8 or 9 different price combinations and tracking conversion across variants, they found they’d been charging too much. Lowering the price brought more users over the threshold of being willing to pay, and subscription revenue went up by around 50%.

“We found out we were charging too much previously. That was sort of a blocker for users,” says Ivar. Without Mixpanel, that assumption might have sat unchallenged for another 5 years.

Knowing what the front page is actually doing 

Last year, Olio introduced carousels on the app’s home screen: horizontal rows of listings users swipe through. The top carousel gets the most eyes; below the fold, engagement drops. When the team reordered those carousels, Mixpanel showed clearly how much traffic followed. “The product team had to be more thoughtful about making those changes,” Ivar says. “And they knew they had to be more thoughtful because they’d seen the Mixpanel data. Without that, they probably would still be making those changes all the time.”

Campaigns that actually move the needle 

Marketing builds audience cohorts in Mixpanel and syncs them directly to Airship for targeted communications. During a New Year campaign, the team looked past app opens. Opens were up a few percent. Transactional activity (listing creation and item requests) was up around 25%. That gap changed how the team interpreted success and planned future campaigns.

What’s next 

Olio is in the early stages of international expansion, running pilots in markets outside the UK. The person leading those pilots isn’t a data expert, and Mixpanel is what makes that workable: they can filter by market and see new signups and active users directly.

Session replay is now available for React Native apps, and Ivar wants to explore it. There’s also interest in connecting Mixpanel to Olio’s BigQuery data warehouse in both directions. For now, the setup is doing what Olio most needs: keeping the whole company close to data, without everything going through one person.