Retention modeling

According to HBR, the cost of acquiring a new customer is 5-25 times more expensive than retaining your existing ones.

Whereas, a 5% increase in customer retention leads to 25% - 95% more profit.

Retention modeling helps you gather the necessary data to measure and act on metrics such as lifetime value and retention, so you can reap the rewards of a loyal customer base.

“We knew we should be shipping a large volume of experiments but we didn’t know-how. The first few experiments we tried missed the mark. But then we started working with Speero who came in and helped us with tooling, research, statistics, and the processes needed to run experimentation at scale."
Daniel Layfield, Growth Product Manager at Codecademy

What are the benefits of retention modeling?

Quite often, businesses get the majority of their revenue and profit from a small percentage of visitors or customers. Those are the customers that buy frequently or subscribe to more expensive plans, for longer.
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With a retention model, you can identify such customers, and detect traits of future high-value customers. Then, you can work on attracting and retaining them.
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This service is for SAAS, lead generation, and ecommerce businesses.

What will my retention modeling project look like?

Discovery

Every business is different and so are their most valuable customer segments. We’ll work closely with your team to understand the nuances of your business, customers, and goals.

Data collection infrastructure audit

It’s likely that your business already has a good amount of really useful data. Unfortunately, this is often spread across multiple tools and platforms, some important data points are missing, and sometimes others aren’t 100% accurate. We’ll audit your data analytics tools, and make the necessary fixes and improvements. More importantly, we’ll break the silos by sending data from all relevant sources into a data warehouse.

Retention analysis

Having all this customer data is great, but it’s rather useless without the analysis to find useful insights hidden inside. We’ve worked with all kinds of businesses so we know exactly which customer retention metrics will provide the most value. Taking a deep dive into your customer data will help us identify the problems and opportunities holding back these metrics.

Execution

There are several ways we can help put the insights discovered into action;
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• A/B testing to validate retention or customer lifetime value improvements.
• Conducing ResearchXL to gain qualitative insights into your customers motivations.

Retention Modeling Case Studies

$1.5 million in additional revenue

For Procter & Gamble brand, Native, by experimenting and improving their customer experience.

0-100 experiments

We helped MongoDB embed an experimentation culture that took them from no testing to running 100 tests per year.

$2M additional revenue

A single research-backed recommendation for RevZilla delivered $2M in annualized revenue.

“I’d gone on your site and read everything. I thought these guys know what they are talking about. We had previously engaged with some of the biggest UX and CRO agencies in the country but it felt like they hadn’t even been on our website. Speaking to you guys, you’d already identified some issues on our very first call. We knew we were talking to the right people.”

Alexander Robinson, Director, PMO at RevZilla

Retention Modeling FAQs

What is a retention model?

A retention model provides you with the data to monitor, report and analyze customer churn, retention, and customer lifetime value throughout your customer journey.

How do you conduct retention analysis?

We start by validating your current customer data sources to make sure all the necessary data is being tracked and is trustworthy. Then, we push and pull all this data into a data warehouse for more advanced analysis. It’s all about finding patterns and correlations that high-value customers have in common.

What are the stages of modeling customer retention?

• Get to know the business and the customer
• Make sure you have access to all the data you need and that this data is accurate
• Analyze the data, find what’s common for high-value customers
• Turn insights into actions

Let’s kick things off.
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