Ever wondered why some companies attract tons of new customers but can’t keep them around?

Or why others have die-hard loyalists but struggle to grow their audience? Balancing customer acquisition and retention is like walking a tightrope—it’s tricky but absolutely essential for long-term success.

In this article, we'll dive into why finding that sweet spot between bringing in new customers and keeping existing ones happy is so important. We'll explore research findings, discuss how to understand customer value when resources are tight, and look at strategies like dual-path experiments to optimize your efforts.

Related reading: Designing experiments to improve user retention.

The importance of balancing customer acquisition and retention

When businesses chase after new customers and forget about the ones they already have, things can go downhill fast. Not only can profitability suffer in the long run, but customer loyalty takes a hit, too. According to a study by Ovchinnikov et al. (2014), when there's limited capacity, adding more customers doesn't always add more value. In fact, the value of each new customer can decrease depending on how many you already have and the mix of customers you're working with. So, pouring all your resources into acquisition while ignoring retention might not be the best move.

But swinging too far in the other direction isn't great either. If you focus only on keeping your current customers happy, you might miss out on growing your market and bringing in fresh faces. Reinartz, Thomas, and Kumar (2005) talk about this balance and introduce a framework for balancing resources between acquisition and retention to maximize profitability. They point out how crucial it is to figure out the right way to split your marketing budget between the two.

Finding that sweet spot is especially challenging for startups. A user in a Reddit discussion about B2B Enterprise SaaS shared how they saw a chance to improve the user experience to boost retention. But they ran into roadblocks trying to convince leadership to pay attention to existing customers instead of just chasing new ones.

This is where effective experimentation comes into play. By testing different strategies, companies can figure out how to balance acquisition and retention efforts effectively. Tools like Statsig's ID Resolution feature make this easier. It lets businesses look at data from both logged-out and logged-in users, giving a full picture of the user journey—from that first page visit all the way to making a purchase. Understanding this journey helps in making informed decisions and building a base of high-value, long-term customers.

Understanding customer value when resources are tight

We all know that Customer Lifetime Value (CLV) is a big deal—it estimates how much profit a customer will bring over time. But here's the catch: CLV doesn't always take into account situations where you have limited capacity. In these cases, the Value of an Incremental Customer (VIC) actually goes down as you get more customers. That means you might need to rethink how you're investing, adjusting your spending based on the mix of customers you have to make the best use of your resources.

So, businesses need to strike a balance between acquisition and retention efforts, especially when resources are limited. It's important to strategically allocate marketing resources across different channels to boost customer profitability. But watch out—sometimes biases in decision-making can lead to pouring too much money into high-value customers and not enough into those who might be lower-value now but could grow over time.

Just relying on CLV information can sometimes make these biases worse. A better approach is to look at the marginal costs of acquisition and retention. By understanding these costs, you can reduce biases and improve your net revenue. Grasping the finer points of customer value and how efficiently you're spending can help you balance growth and retention, even when the market is super competitive.

Implementing dual-path experiment design

So, how do you figure out the best way to balance acquisition and retention? One effective method is using dual-path experiments. These allow you to assess both acquisition and retention strategies at the same time. By designing experiments that connect your efforts to attract new customers with how well you keep them around, you gain insights into your true profitability. This big-picture view helps you avoid getting stuck focusing only on short-term acquisition numbers.

But to make these experiments work, you have to be really careful about controlling biases. Factors like limited capacity, customer mix, and unobserved variables can mess with your measurements and lead you to spend your resources in the wrong places. Ovchinnikov et al. (2014) emphasize how important it is to consider these biases in their dynamic programming model.

Setting up dual-path experiments also means you need to balance your acquisition and retention resources strategically. Remember Reinartz, Thomas, and Kumar's (2005) framework? It helps you optimize this balance to maximize customer profitability. By figuring out the right marketing spend across different channels, you can boost your overall revenue.

A big part of this is identifying those critical activation moments—the points where new users really start to engage with your product. Lenny's Newsletter lays out a process: brainstorm potential "aha" moments, run regression analysis, and validate through targeted experiments. Combining these qualitative insights with quantitative data ensures you're focusing on the right activation metrics.

This is where Statsig can be a game-changer. With Statsig's ID Resolution feature, you can simplify the analysis of new user experiments by linking data from logged-out users to their logged-in metrics. This gives you a full view of the user journey, from initial interactions to how well they stick around. By addressing common pitfalls and ensuring your data is solid, ID Resolution helps you optimize the entire user experience.

Optimizing resources through informed experimentation

Sharing information about the marginal costs of acquisition and retention can really help reduce biases in how managers decide to spend money. When you know these costs, you can avoid overspending on customers who seem high-value and underspending on those who might be lower-value now but could become more profitable later. This approach ultimately boosts your net revenue.

Digging into experimental data gives you strategies to optimize customer profitability. By figuring out how to allocate your marketing budget between getting new customers and keeping existing ones, you can maximize the value of your customer base.

Combining what you learn qualitatively (like from user interviews) with hard numbers improves how you allocate resources. Take, for example, identifying critical activation moments—those key actions that correlate with long-term retention. Lenny's Newsletter suggests methods like regression analysis to pinpoint these moments. This helps you focus your efforts where they'll have the biggest impact.

Using online controlled experiments is a powerful way to make decisions when developing websites or apps. Even small changes, when tested properly, can lead to big improvements in metrics like revenue and retention.

It's important to follow best practices for product experimentation. This includes thoughtful experiment design, consistent monitoring, and careful analysis. By paying attention to the right metrics and truly understanding the effects of your changes, you can make data-driven decisions to optimize your products and enhance retention.

Closing thoughts

Balancing customer acquisition and retention isn't easy, but it's crucial for sustainable growth. By understanding the true value of both new and existing customers and using informed experimentation, businesses can allocate resources more effectively. Tools like Statsig make it easier to analyze data and make decisions that optimize the entire user journey.

If you're looking to dive deeper into this topic, check out the resources linked throughout this post. And feel free to explore Statsig's blog for more insights on experimentation and user engagement strategies.

Hope you found this helpful!