Managing Retention When 75% of Your Users Can't Find Products

Most retention problems stem from users losing interest in your product. For Buen Provecho, the challenge is different: users are interested, but they open the app and can't find anything to buy. When your business model inherently creates situations where most users see empty shelves most of the time, traditional retention tactics don't work.

On the Levels Podcast, Guillermo Martinez, COO and co-founder of Buen Provecho, discussed how they think about retention when supply constraints mean disappointment is baked into the user experience—and why this makes their retention metrics look different from typical consumer apps.

The Math Problem

Buen Provecho operates in Uruguay and Argentina with around 420 stores. Sounds substantial, until you consider the geographic distribution. Seventy-five percent of their stores are in Uruguay, where 60% of the country's population lives in the capital city. The rest are scattered across Argentina's major urban areas.

Within any given city, stores publish surplus food at different times throughout the day. A bakery might have products available at 8 AM. A restaurant publishes at 4 PM. A grocery store at 8 PM. Each store typically has just a handful of items available when they do publish.

Now consider the user experience. Someone opens the app looking for nearby options. If they live more than two kilometers from participating stores, they see nothing. If they open the app between publishing windows, they see nothing. If they open the app right after power users with favorited stores have claimed inventory, they see nothing.

The result? Most users, most of the time, open the app and find limited or no available products. This is the fundamental retention challenge Buen Provecho faces.

Why Traditional Metrics Don't Apply

In typical consumer apps, daily active users and monthly active users are straightforward north star metrics. More DAU means more engagement, which typically means more revenue and better retention. Product teams optimize for maximizing these numbers.

Buen Provecho can't think this way.

"We may not be on the upper echelon of active users regarding to total users. But we are really sticky, right?"

Their approach focuses on conversion rate when users do open the app rather than frequency of opens. A user who opens the app twice per week but purchases both times is more valuable than a user who opens daily, finds nothing available six times, and makes one purchase.

This inverts the typical engagement optimization. Instead of maximizing app opens through push notifications and engagement tactics, they need to maximize the likelihood that each app open results in a purchase. That means carefully timing notifications, managing supply distribution across neighborhoods, and avoiding notification fatigue that brings users in when inventory isn't available.

The stickiness Guillermo mentions is crucial. When users do make successful purchases, they have strong positive experiences—good food at good prices, visible environmental impact, supporting local businesses. These successful transactions create lasting value that keeps users coming back even if many visits result in finding nothing available.

The Supply-First Strategy

The only real solution to retention challenges caused by supply constraints is fixing the supply side.

"So we need to extract as much as we can from our really active users, like they're really strong."

This statement reveals the strategic thinking. Since they can't dramatically increase the total user base without worsening the supply/demand imbalance, they focus on extracting maximum value from users who are already engaged and understand how the model works.

This means prioritizing features and experiences that serve active users rather than acquiring new ones. The location-based push notification system ensures that when stores publish products, users who typically shop in that area get notified. The favorites feature lets power users get instant access to stores they love. The impact dashboard reinforces the mission for users who care about waste reduction beyond just saving money.

Meanwhile, the team dedicates enormous resources to store acquisition. Getting from 420 stores to 500 stores, then 600, then 800—this is what actually solves retention because it means more products available more often in more neighborhoods.

"For example, I'd say almost all 2023 and most of 2024, we dedicated 85, 90-ish percent of our dev time resources to the app for the source."

This is a striking resource allocation. While most consumer apps dedicate the vast majority of development time to the consumer experience, Buen Provecho spent nearly 90% of their time building tools for stores. Better onboarding for stores, easier product publishing, better inventory management, clearer analytics showing stores how much money they're recovering.

Why? Because every minute spent making it easier for stores to use the platform translates directly into more supply, which is the only thing that truly fixes retention.

The Notification Balancing Act

With limited supply and a user base that outnumbers available products, notifications become a delicate balancing act. Send too many and users get frustrated by repeated disappointments. Send too few and engaged users miss opportunities to purchase.

"What we do normally is at the same time, the people that, you know, engage that notification at the same time, we don't send them another one, for example, maybe 48 or 72 hours later. We try to go for people that didn't use a notification."

This cooling period system prevents bombarding the same users repeatedly while giving everyone fair chances to see inventory. A user who receives a notification and makes a purchase gets a break for 48-72 hours. The next batch of notifications goes to different users, distributing opportunity more equitably.

This approach trades off maximum immediate conversion for better long-term retention. They could notify everyone every time a store publishes, which would maximize short-term sales but quickly burn out users who consistently find nothing available. Instead, they rotate through their user base, accepting lower conversion rates on any individual notification in exchange for keeping more users engaged over time.

The system also tries to learn from non-engagement. Users who receive notifications but don't open the app might receive different messaging or be notified about different store types to find better matches. The goal is finding the right product-user fit rather than just blasting everyone with everything.

Geographic Density Matters

Retention rates vary significantly based on where users live. Someone in central Montevideo surrounded by dozens of participating stores has a fundamentally different experience than someone in a residential neighborhood with three nearby stores.

"Our average user goes around two kilometers to pick up a product."

This two-kilometer radius becomes crucial for retention. Users who live in areas with five or more stores within two kilometers have enough options that they can usually find something available when they open the app. Users with only one or two nearby stores often find nothing available and gradually stop checking.

This geographic concentration creates a chicken-and-egg problem for expansion. New neighborhoods start with few stores, which means poor user experience and low retention. But stores don't want to join in neighborhoods with few users because there isn't enough demand. Breaking into new areas requires coordinated expansion, onboarding several stores simultaneously to create viable density.

The successful strategy involves identifying neighborhoods where they already have clusters of users, even if no stores are active yet, and then heavily recruiting stores in those specific areas. This concentrated approach works better than scattered store acquisition across the entire city.

The Organic Growth Advantage

Given the retention challenges created by supply constraints, Buen Provecho has learned that organic growth serves them better than paid acquisition.

"We try to keep it organic for quite a bit, like six plus months because it was just growing like small time, but just keep growing and the users were recruiting."

Organic users who discover the app through word-of-mouth or social media tend to have more realistic expectations. They've heard about the model from a friend or seen content that explains how it works. They understand they won't always find products available, and they're more patient about checking back at different times.

Paid acquisition users arrive with expectations shaped by the ad copy rather than realistic understanding of the model. If the ad emphasizes "discount food" without properly explaining availability constraints, users expect something closer to traditional food delivery. First-time users who encounter empty inventory often uninstall immediately.

This is why their viral TikTok moment, while exciting in raw numbers, created retention problems. Thousands of users arrived with high expectations but limited understanding of how surplus food availability actually works.

The Long Game on Supermarkets

The real breakthrough for retention will come from landing major supermarket chains. Unlike individual restaurants and bakeries, supermarket chains offer several advantages for improving user experience.

"We needed to go to big stock stores, retailers, supermarkets, those kinds of things."

Supermarkets have more consistent surplus throughout the day rather than single publishing windows. They have multiple locations, often several stores in the same city, increasing the likelihood users find something nearby. They carry diverse product categories, so users can find different types of products on different visits. And supermarkets are familiar, trusted brands that reduce concerns about food quality and safety.

Landing supermarket partners has taken longer than Buen Provecho hoped, as discussed in their decision to refuse strategic investment. But this patience in pursuing the right partnerships rather than accepting compromised terms will pay off in dramatically improved retention once those partnerships activate.

A single supermarket chain with 20-30 locations can transform the user experience in a city, providing enough consistent supply that most users can find something available whenever they check.

Accepting Different Success Metrics

Perhaps the most important lesson from Buen Provecho's approach is that retention doesn't have to look like typical consumer app metrics to represent success.

Their MAU/DAU ratio is lower than food delivery apps. Their average session frequency is lower than social apps. Their percentage of users who open the app weekly is lower than habit-forming productivity tools.

But none of those comparisons matter because Buen Provecho isn't trying to be those things. They're trying to efficiently match sporadic surplus food supply with users who want affordable food while reducing waste. The metrics that matter are conversion rate when products are available, user satisfaction with purchases made, and lifetime value of users who understand and work within the model's constraints.

Building engagement features that work for this kind of business requires different thinking than standard implementations of streaks or points systems. A streak that requires daily usage doesn't make sense when products aren't available daily. Points that reward frequency of visits rather than successful purchases would be counterproductive. The engagement mechanics need to align with the reality of supply constraints rather than fighting against them.

Key Takeaways

• Supply constraints require different retention metrics as focusing on conversion rate per session matters more than maximizing session frequency
• Resource allocation reflects what drives retention with 85-90% of development time spent on store tools rather than consumer features
• Notification cooling periods trade immediate conversion for long-term retention by preventing users from experiencing repeated disappointments
• Geographic density determines experience quality as users need multiple nearby stores to have consistently good experiences
• Organic growth creates more realistic expectations than paid acquisition for models with inherent availability constraints

Listen to the full conversation with Guillermo Martinez on the Levels Podcast to hear more about managing growth and retention in a supply-constrained marketplace.