How to Improve Customer Retention with Product Analytics

By now, everyone working on a product knows that retaining a user is easier and healthier for your business than letting the bucket leak while you chase user growth. The discipline of strategies deployed to retain users is called customer retention and the team is often termed the success or retention team. The customer retention team plays a significant role in keeping your active customers engaged and satisfied.

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In the olden days, the go-to tactic for retention used to be loyalty programs with discounts or offering free access to premium features. But it just isn’t enough anymore. Today, customers only care about a personalised and customised retention strategy, and that is the reason behind this article.

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Any and all personalisation begins with a deep understanding. It’s easy to do when you have 10 or 20 customers or to be hunch-driven when you have a small, fairly similar set of users. But if your user base is in thousands or more and is diverse, we would recommend using an analytics tool to understand your users by segmenting them, making cohorts, and then running personalised campaigns backed by a deep understanding. It will help you build a reliable and evidence-backed strategy to keep your customers retained.

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This post will share a detailed guide on customer retention and analytics with tips on how you can improve customer retention rates using your behavior data.

What Is Customer Retention Analytics?

Customer retention analytics is how you can identify, track, and evaluate key metrics that reflect customer loyalty. It helps you dig into the who and why behind customer retention to understand the factors that drive customer churn. It determines how many customers are loyal to your product and will likely continue purchasing from you.

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Customer retention analytics tells you:

• The possible reasons why your customers churn.
• The key determinants - demographics, behaviors, and events indicating at-risk customers.
• Feature ideas or product ideas that would encourage retention and reduce churn.
• The impact of churn on your bottom line.

Types of Analytics Techniques to Improve Customer Retention Rates

Customer analytics helps you monitor and track your customer behavior so that you can understand their requirements and expectations better. Here are different ways you can gauge your customers with retention analytics.

1. Descriptive

Descriptive analytics provides detailed insights into customer behavior based on historical data. Analyzing what has happened in the past helps you identify patterns and trends in customer behavior. It also helps you understand how satisfied your customers are.

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You can learn about:

• Which product features are the most popular among customers.
• Which customer segments are utilizing your product the most.
• Which customer segments are the most profitable.
• Which customers are satisfied with your product.

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2. Diagnostic

Diagnostic analytics offers valuable insights into why a specific event or trend occurred. It aims to uncover the root causes behind a particular event and provide insights for better decision-making. It is often considered the next step after conducting a descriptive analysis.

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It helps you understand:

• The reasons why certain events occurred.
• The variations in customer behavior and business performance over a given period.

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By giving insights into what has previously happened and why it has happened, you can form hypotheses and run excellent product experiments to improve product efficiency.

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3. Periodic

Periodic analytics measures customer retention and churn over a given period. It involves identifying and monitoring customer activity and determining their engagement with your product. This period could be anywhere between days, weeks, or even months.

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The main goal of periodic analytics is to identify churn before it happens. It is sometimes referred to as periodic survival analysis, which tells whether a particular customer was active or inactive during a specific period.

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4. Retrospective

Retrospective analytics measures when customers churn and provide intelligent insights to avoid these possible churns. It analyzes customer inactivity in the historical data so that you can clearly understand where to direct your retention efforts.

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It measures the time the customers have been inactive to determine the rate at which customers churn.

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5. Prescriptive

Prescriptive analytics uses product and customer data to identify the best action or strategy for specific customer interactions moving forward.

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It answers questions like:

• What should we do?
• What is the best course of action for this problem?
• What can be done next to support a particular strategy?

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Prescriptive analytics aims to increase efficiency by offering insights into various possible outcomes and identifying the worst-case scenarios for your product. Thus helping you make decisions based on highly analyzed facts rather than just instincts.

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6. Predictive

Predictive analytics analyzes current and historical data to predict future events and trends. It predicts specific customer actions and helps you with data-driven decision-making. Further, it shares insights on the customers who are likely to stay and the ones who will churn.

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By identifying potential customer churn early, you can take proactive measures to retain them.

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Top 4 Benefits of Improving Customer Retention

Customer retention analytics gives intelligent insights into your customer behavior and helps you make data-driven product decisions. Besides this, retention analytics offers a host of other benefits that are crucial for sustainable product-led growth.

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Let us briefly explore each of them.

#1. Lowers Customer Acquisition Costs (CAC)

Retaining an existing customer is much cheaper than acquiring a new one. The cost of acquiring a new customer can be five times higher than retaining an existing one.

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Customer retention analytics help you identify your target customers better. It offers insights into ideal customer segments likely to spend with your business. You can then concentrate on converting those customers instead of targeting the wrong ones.

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Further, customer retention analytics offers valuable insights into your existing customer behavior. This information can be used to devise excellent strategies to engage and retain customers.

#2. More Upsell/Cross-Sell Opportunities

By analyzing customer data, you can identify relevant cross-selling and upselling opportunities for creating personalized offers and increasing revenue. You can use customer analytics data to learn more about your customers' preferences, pain points, and purchasing behavior to recommend complementary products or higher-priced alternatives. After all, selling to existing customers is much easier than selling to new ones.

#3. Offers Quality Insight into High-Performing Sales Channels

Customer retention analysis offers insights into the top-performing customer acquisition channels—for example, affiliates, pay-per-click campaigns, social media, etc. By focusing your efforts on channels that promise excellent retention rates, you unlock new opportunities for selling your product. You can track crucial sales metrics to measure your sales performance and focus your efforts on the high-potential channel that generates and retains maximum customers.

#4. Fosters Customer Loyalty

Customer retention analytics gives you thorough insights to understand when and why customers leave. It helps you identify the friction points in your product and reveals critical trends that could be potential churn risks. Doing so enables you to avoid these risks and convince your customers to stay. It also helps you build an excellent product to deliver better customer experiences.

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Build strong customer relationships by engaging customers personally and offering excellent service. Ensure that your product addresses their pain points. This will increase the customer's lifetime value and foster a sense of loyalty among your customers.

How to Improve Customer Retention in 8 Steps

Here is a step-by-step guide on leveraging product data to improve customer retention and grow revenue.

#1. Calculate Current Retention Rates

Calculating customer retention rates is the first step. It will help you know how many customers are sticking with your product and how many are leaving. The higher the retention rate, the better it is. It shows that many of your customers see value in your product.

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Customer Retention Rate = [(Number of Customers at the end of the period - Number of New Customers gained during the period) / Number of Customers at the beginning of the period]  * 100

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Here are simple steps to follow to improve your customer retention rates:

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• Start by asking yourself what customer retention means to your business. Is it about increasing revenue generation? Is it about building better customer relationships? Is it about the number of customers who continue to use your product? The answers to these questions will help you define your retention goal.
• Divide your customers into different groups according to their demographics, behavior, and other factors. Track how they use your product over time to analyze their product usage patterns and purchasing behavior.
• Analyze the customer journey with your product to know more about the features they love, the features they do not use, and so on. This will help you duplicate similar experiences for new customers.

#2. Select Retention Metrics to Track

The next step is identifying the various customer retention metrics to help you with your goals. Some of the critical metrics you need to track include:

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• Customer Retention Rate - Measures how many customers you have retained over a period of time.
• Customer Churn Rate - Measures how many customers stop doing business with you.
• Revenue Churn Rate - Measures how much revenue is lost from existing customers.
• Repeat Purchase Ratio - Measures how many customers return to make another purchase.
• Customer Lifetime Value - Measures the revenue generated by a certain customer.
• Net Promoter Score (NPS) - Measures how likely your customers would refer your product to others.

#3. Create Cohorts Based on Timeframe and Persona

Utilize customer data to segment customers into various groups and monitor their behavior to identify engaged customers and those that are highly likely to churn. Grouping customers into cohorts will help you identify characteristics and behaviors that could lead to churn or protect against it.

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Cohorts feature in Houseware allows you to build separate cohorts based on their demographics, their sign-up date, their first purchase, and other events. It allows you to identify high-value customer segments more likely to spend money on your product. You can then deliver targeted messages to these segments and optimize your product experiences.

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Moreover, 71% of customers expect companies to invest in personalized interactions. Start delivering personalized experiences and boosting customer satisfaction with segmentation and cohort analysis.

#4. Conduct Funnel Analysis to Track User Behavior

Funnel analysis can help you understand the specific journey or paths your customers take to perform actions with your product. It involves mapping and analyzing a series of events that occur with your customers when using your product.

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Use Houseware Funnels to define a customer retention funnel containing the following four stages to track your customer behavior.

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• Active new customer - A new customer actively engaging with your product.
• Active repeat customer - An existing customer who continues to engage with your product.
• Risk of churn customer - A customer showing signs of disengagement or whose activity with your product is reduced.
• Dormant customer - A customer who has not engaged with your product in a long time.

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Conduct a funnel analysis to understand your customer behavior and identify the potential barriers to customer loyalty. Based on the findings, prioritize your product development efforts and design a product your customers want.

#5. Identify Behaviors Indicating Churn Risk

Now that you have divided customers into various cohorts and learned to track their behavior, it is time to monitor and examine specific behaviors within each cohort to reveal the patterns that could potentially lead to churn. Dig deeper to analyze where and how these customers decide to leave.

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At this point, you can invest in some customer retention strategies (to be discussed later in the post) to channel your efforts into retaining clients.

#6. Capture At-Risk Users

Now that you have identified the behaviors associated with churn, you can compare these behaviors with individual customers and capture the ones at high risk of churning.

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Monitor their journeys using the Flows feature in Houseware to track every step of their progress. Identify various touchpoints throughout their journey and devise strategies that could help them with efficient product usage. Set up in-app events to motivate them to use your product and track it in the Flows dashboard. This will help you engage the at-risk customers and encourage them to use your product, improving customer retention rates.

#7. Calculate Customer Maturity and Health Score

Customer maturity score indicates the potential of a business to meet its customers' needs and expectations. Monitoring customer maturity scores will reveal which customers will likely make the most of your product.

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Similarly, a customer health score helps you gauge your customer relationship. It tells you if your customers are happy with your product, indicating high or low customer retention scores.

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• Healthy - Your customers are doing great. You can connect with them for upselling or cross-selling.
• At Risk - This customer is on the verge of churning. You must engage them with your product.
• Might Churn - This customer needs immediate attention. You ought to take proactive measures to avoid churn.

#8. Implement Retention Strategies

Invest in any of the below-mentioned retention methods to improve customer retention rates.

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• Build an engaging product onboarding experience for your customers. Ensure that this onboarding module subtly introduces them to all the product features. You can also embed this workflow with tutorials on utilizing each feature effectively.
• Utilize a product analytics tool like Houseware to monitor customer behavior regularly and analyze patterns and trends in their behavior. Craft your product strategy to offer personalized support to your customers.
• Enhance customer engagement by providing them with educational resources to make product use easier. For example, video tutorials, guides, how-to articles, and more.
• Start a customer loyalty program offering them rewards for a variety of actions. For instance, early access to new features, free limited-time access to premium features, or a points system that can be utilized for certain discounts on product pricing.
• Leverage other marketing platforms to connect with dormant or inactive customers. For example, send a 'we miss you' email or share an engaging survey to gather their feedback about your product.
• Ask your customers to share their feedback to learn more about their experiences with your product. Leverage this feedback to improve your product.

How Houseware Can Help You Improve Customer Retention

Customer retention analytics begins by collecting accurate customer data from all sources. The more information you have, the better it is. Houseware, a warehouse-native platform, resides in your existing data warehouse, eliminating the need for manual data transfers or ETL data transfer pipelines. It captures your historical data to evaluate customer behavior and offers various ways to improve customer retention rates. It generates accurate insights for monitoring customer retention data.

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For instance, Houseware offered Quizizz, our all-in-one platform to track, manage, monitor, and evaluate their product and customer data. Houseware consolidated all their crucial data into flexible dashboards. After implementation, the Quizizz team was able to leverage the power of data to optimize their product and shorten their data-to-insight lifecycle.

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It helped them gain clear visibility into customer behavior patterns and take measures to boost engagement. Quizizz noticed a 2.5x increase in user activation rate during one of their product experiments. Their team also leveraged Houseware to evaluate existing customer behavior to drive proactive conversations and facilitate increased customer retention.

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Interested in knowing how to improve customer retention metrics and analytics with Houseware? Book a demo to find out.