Improving Customer Retention with Cohort Analysis: A Complete Guide for Businesses
Written by
Sukanya Bhan
Sukanya Bhan

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Improving Customer Retention with Cohort Analysis: A Complete Guide for Businesses

Published : September 11, 2023

Businesses and marketing campaigns everywhere are searching for the magic formula to keep customers coming back.

The truth is, there’s no single magic button. However, there’s a powerful tool that can help unlock the secrets of customer and retention rates: Cohort Analysis. Don’t get intimidated by all the users’ jargon – this guide is here to break things down in layman’s terms.

Improve customer retention with cohort analysis

What is Cohort Analysis?

In the simplest terms, a cohort is a group of people who share a common characteristic over a certain period of time.

In the world of business analytics, this often refers to a group of customers who made their first purchase during a specific time frame.

Cohort Analysis, then, is the study of the behaviors of these cohorts how different groups over a time period.

Imagine you run a monthly book subscription box. The cohort for January would be everyone who subscribed in that month.

By studying this January cohort with different cohorts and monthly cohorts over the next several months, you can see how many of them renew their subscription, how many purchase additional items, and how many drop-offs.

Why is Cohort Analysis Important for Customer Retention?

  • Customized Insights

Diving deep into cohort analysis allows businesses to segregate their customers into distinct groups based on shared characteristics or experiences. These cohorts provide invaluable insights into customer behavior over specific time frames.

Consider the scenario where a cohort from February exhibits a markedly higher retention rate. Could this be attributed to a special Valentine’s Day promotion, or maybe a seasonal product launch?

With cohort analysis, it’s easier to discern patterns and insights specific to each group, allowing businesses to replicate successes and rectify missteps.

In essence, cohort analysis transforms raw data into actionable strategies, making it an indispensable tool for businesses aiming for precision in their decision-making.

  • Product Feedback

Cohort analysis isn’t just about numbers—it’s a direct line to customer sentiment. When you observe that a particular cohort’s engagement or retention levels plummet right after a new product release or an update, it sends a clear message.

Perhaps the product didn’t resonate well, maybe there were unexpected bugs, or the changes made were not in line with customer expectations. Rather than making assumptions, cohort analysis offers tangible evidence of where a product stands in the eyes of its users.

It’s like having a continuous feedback loop, ensuring that businesses remain agile and responsive to user needs.

  • Lifecycle Understanding

Every customer is on a unique journey, and cohort analysis is the compass that helps businesses navigate these varying pathways.

Whether a customer is a newbie just exploring the offerings or a seasoned patron familiar with every nook and cranny, cohort analysis maps out where each group is in its lifecycle.

By doing so, it empowers businesses to tailor their marketing and engagement strategies. For instance, new users might benefit more from introductory offers and onboarding content, while loyal customers might appreciate loyalty rewards or advanced feature tutorials.

Recognizing and catering to these diverse stages not only ensures that each customer feels seen and valued but also significantly enhances retention strategies.

Types of Cohort Analysis for Customer Retention

Customer retention cohort analysis isn’t one-size-fits-all. There are three primary types we focus on: acquisition, the behavioral analytics, and predictive cohort analyses. Here’s a closer look at each:

1. Acquisition Cohorts: Segmenting by First Impressions

In acquisition cohort analysis, users are grouped based on specific acquisition milestones. This could be when they first sign up for a service or when they upgrade to a premium version.

By employing this analysis, businesses can discern long-term retention trends for each group. It’s like comparing how different batches of customers stick around over time. Plus, it offers insights into the results of acquisition strategies and marketing campaigns.

2. Behavioral Cohorts: Actions Speak Louder

This method clusters users based on certain actions they have (or haven’t) taken within a defined period. Think of categorizing users according to whether they’ve ticked off the onboarding tasks.

The strength of behavioral cohort analysis lies in its detail. It goes beyond showing how many users stay—it delves into the ‘why’. Such deep dives can unveil the underlying reasons for user retention or drop-off.

3. Predictive Cohorts: A Glimpse into Tomorrow

Enter the realm of foresight with predictive cohorts. These are segments of users deemed likely to exhibit particular behaviors down the line, such as discontinuing a service. This forecasting prowess comes from machine learning models that feed on historical user data.

What makes predictive cohort analysis exciting? It’s the proactive approach it offers. Businesses can anticipate user actions and strategize accordingly. For instance, they might engage users with tailored in-app messages, turning potential drop-offs into renewed interest or upsell opportunities.

4 Ways of Using Cohort Analysis to Boost Customer Retention

1. Refine Your Marketing Strategy

Every audience segment has its unique mode of communication. Cohort analysis sheds light on these preferences.

For instance, if younger cohorts resonate more with Instagram campaigns while older groups show higher engagement through email newsletters, this insight is invaluable.

It allows businesses to not only choose the right channels but also tailor the content to suit the tastes and preferences of each cohort.

Thus, rather than deploying a blanket marketing strategy, businesses can craft nuanced campaigns that cater specifically to the dynamics of each group, ensuring a higher return on marketing investments.

2. Optimize Onboarding

The first impression counts, and for many customers, this is formed during the onboarding process.

If cohort analysis reveals that a significant chunk of users disengage shortly after their initial signup, it’s a clear indicator that the onboarding experience may be lacking. Perhaps it’s too complex, not intuitive enough, or fails to effectively showcase the product’s value.

By analyzing the sticking points for different cohorts, businesses can refine and restructure their onboarding process to make it more user-friendly, engaging, and informative, ensuring users feel equipped and motivated to continue their journey.

3. Loyalty Programs

While acquiring new customers is crucial, retaining existing ones is often more cost-effective and beneficial in the long run.

Cohort analysis can highlight which user groups are more inclined towards brand loyalty. Armed with this data, businesses can introduce tailored loyalty programs, offering exclusive benefits, discounts, or referral bonuses.

For cohorts showing higher loyalty tendencies, these programs can be a way to further deepen their connection to the brand, making them not just customers but brand advocates.

4. Customize Product Offerings

In the diverse world of consumer preferences, one size doesn’t fit all. Cohort analysis can illuminate patterns in purchasing behaviors.

For example, if a certain cohort consistently shows a preference for organic products, businesses can curate special bundles or offers catering to this interest.

Similarly, insights into the purchase patterns of different cohorts can guide upselling or cross-selling strategies.

If a cohort frequently purchases a specific type of product, businesses can recommend complementary items, creating a holistic shopping experience that caters to the user base’s tastes and needs.

4 steps to conducting a cohort analysis

1. Look at when users churn

Your users might voice their opinions, but the data timeline often speaks louder in understanding your churn issues. Pinpointing when the churn occurs lets you zoom in on potential factors triggering it.

So, how do you get this insightful timeline? Through an acquisition cohort analysis.

For this, it’s crucial to craft a cohort chart. This chart should list your distinct cohorts, tally the number of users in each, and have dedicated columns for every day within your analysis period.

Cohort analysis - Netcore Cloud

Inspecting this, you’ll notice that the figures under each day represent the percentage of the original cohort, for that specific row, retained on that particular day. Quite insightful, isn’t it?

As you embark on setting up your acquisition cohort analysis, keep these pointers in mind:

  • Time period: Align your time frame with the age and dynamics of your app and its users. While days are a common choice, depending on the context, weeks or months might be more suitable.
  • Focused scope: Broad overviews can sometimes mask the finer details essential for understanding pitfalls. If necessary, segment your analysis based on common user retention stages: initial, intermediate, and advanced. This focused approach can provide clearer insights into where and why users drop off.

2. Discover the Impactful Features

Armed with your detailed acquisition cohort analysis and timeline (identifying the ‘who’ and ‘what’), it’s time to delve into the ‘why’.

Spot significant user drop-offs and flag them. Reflect on what might have triggered these declines. For instance, if you notice a 23% decline in users on day 3, ask yourself, “What’s unique about day 3? Is that when users are prompted to sync their data?”

Identifying such a correlation could mean you’ve pinpointed an issue. While it might not be the sole problem, it’s a tangible one you can address.

While this seems straightforward, in reality, your analysis will often be intricate. It’s likely you’ll need to extend this examination to every primary feature of your app.

Here’s a pitfall to avoid: Merely assessing how app engagement in the initial 30 days relates to churn. Such a broad perspective won’t provide actionable insights.

Instead, consider a more targeted question: “How does completing the app’s onboarding checklist influence churn?”

In essence, aim for specificity. Determine which exact features resonate most with your users. That’s the crux of what you’re trying to uncover.

3. Analyze Behavioral Cohorts

It would simplify matters if issues stemmed from a solitary feature, but reality isn’t always that straightforward.

More often than not, a fusion of features and user behaviors dictates cohort churn. To illustrate, users who complete your app’s onboarding checklist might be less prone to churn when prompted to sync data, unlike those who skipped the onboarding.

Such observations are just scratching the surface; countless layers of insights await your exploration.

So, how do you unravel these layers? By juxtaposing various behavioral cohorts.

For the data enthusiasts adept at pivot tables, conditional formatting, and with time to spare, a spreadsheet might suffice.

However, to expedite the process, there are specialized tools available. Amplitude, for instance, is tailor-made for swiftly generating and contrasting behavioral cohorts.

As you plunge into the ocean of data, stay anchored to your core objective: discerning the blend of behaviors and features that sway retention, be it positively or adversely.

Ultimately, your analysis should not just decipher patterns but also birth testable hypotheses to guide future strategies.

4. Refine, Reassess, and Reapply

CAUTION: The data shows users not completing the onboarding checklist experience a sharp 67% drop-off by day 10.

You might think, “Revamp everything! Pepper users with reminders from day 1 to 7!”

Hold that thought. Refrain from drastic shifts like that.

Dramatic changes can sometimes exacerbate churn rather than alleviate it. Here’s a better approach: Validate, validate, and validate again.

Your intuition might suggest more reminders could enhance onboarding. While that’s valuable insight, always corroborate with tangible data through testing.

Moreover, if one change escalates retention, don’t get complacent.

There’s a trove of hypotheses awaiting exploration. Examine each.

Why? Because sometimes, subsequent tweaks can eclipse initial successes, further minimizing churn.

So, be meticulous. Be patient. Refine your strategies, reassess the outcomes, and reapply insights, continuing this cycle until you’ve pinpointed and addressed the core issues.

Retention Cohort Analysis Example

Step into the shoes of a product manager overseeing a social media automation tool, akin to Hootsuite. Your quest? Decipher the user behavior and actions that tie them steadfastly to your software.

Let’s say you’ve got a theory: Those who integrate their social media accounts tend to stay loyal.

To validate this, you zoom in on an acquisition cohort — let’s pick those who joined in January 2023.

This cohort data is then bifurcated into two behavior-centric groups: users who’ve linked their social media and those who’ve abstained.

Your subsequent move? Trace the retention arcs of these segments over a chosen period. A pronounced disparity in their loyalty trajectories could reinforce your initial theory.

With such revelations, action beckons. Maybe weaving in a step during onboarding that advocates for account integration is the way forward. Alternatively, a gentle nudge to present users via in-app prompts might seal the deal.

Another Real-world Example

Consider an online apparel shop.

They observed a sharp decline in retention for their April cohort by the time June rolled around.

A closer examination of granular retention data revealed that this particular group predominantly purchased summer attire.

In response, the store dispatched a special offer on sun hats to this cohort in July.

The outcome? A surge in purchases and a rejuvenated retention user engagement rate for the April audience.

Tips for Effective Cohort Analysis

    Unlock the Power of Cohort Analysis with Netcore Cloud!

    In today’s dynamic business landscape, truly grasping your customers isn’t a luxury—it’s an imperative. Cohort Analysis offers invaluable insights into customer retention. Yet, imagine the power of those insights supercharged with precise data and a top-tier tool.

    Netcore Cloud’s cohort analysis tool offers a deep dive into customer behaviors. Harness accurate, real-time data to drive informed decisions. Elevate your retention strategies with intuitive insights.

    Why Netcore Cloud?

    • Advanced Cohort Features

    With Netcore’s state-of-the-art cohort analysis capabilities, dive deep into customer behavior. Identify patterns, understand retention drivers, and leverage insights to make data-driven decisions.

    • Tailored for Every Business

    Whether you’re an e-commerce giant or a budding start-up, Netcore’s features are versatile enough to cater to every business’s unique needs, ensuring optimal customer retention.

    • Seamless Integration

    Say goodbye to clunky interfaces. Netcore is designed for effortless integration, allowing you to focus on what truly matters: understanding and retaining your customers.

    Behaviour cohort analysis - Netcore Cloud

    Final Thoughts

    Cohort Analysis goes beyond mere numbers—it’s a window into your customers’ journey, aiming to enhance their experience. Remember, securing a new customer often costs more than cherishing an existing one. By delving into understanding cohort analysis and analytics and studying customer behaviors, not only can you boost profits, but you also cultivate enduring, meaningful relationships with your clientele.

    Why remain on the sidelines? Experience the power of detailed retention analysis firsthand. Ready to elevate your business and bolster customer retention?

    Book a demo and Visit Netcore Cloud’s customer engagement platform now. Together, let’s shape the future of customer engagement.

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    get started now
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    Written By: Sukanya Bhan
    Sukanya Bhan
    Manager- Marketing Projects