Customer Cohort Analysis is a subset of behavioural analytics that take a range of data from a larger set of data over a period of time. Rather than looking at all the customers as one unit, it separates them into a related smaller group based on various sorts of attributes for analysis.
But have you ever wondered about the difference between customer cohort analysis and user cohort analysis? In this blog post, we will elaborate on the differences between both and the benefits it gives to a product or brand.
A brief on – Customer Cohort Analysis
As mentioned above, cohort analysis segregates data into related smaller groups and it highlights how user groups can engage with a product, particularly about enhancing retention. Similarly, Customer Cohort Analysis narrows down the scope of the customer that generates revenue for the product, irrespective of the source such as signing up a subscription, or watching an ad, or making a purchase. Customer cohort analysis utilizes data to categorize the customers who drive revenue to support you, to understand the value of your product that needs an additional nudge to become a high-value customer. This analysis lets you get insights on the level of engagement from the high-value customers.
Do you wonder why you need to concentrate mainly on the high-value customer?
They are your potential customers, by focusing more on fulfilling their needs or tailoring the products as per their needs, you can gain more loyalty and increased brand value. Customer cohort analysis lets you get this insight.
How to run a Customer cohort analysis?
To execute a Customer cohort analysis you should first define the cohort group by choosing the users who performed in your revenue-generating event such as making a purchase, or watching an ad, or making a subscription.
Based on your company’s revenue model, you can add those who subscribe at any tier level or focus on who has made a repeat purchase.
Once you have defined the cohort, look for the attributes or behaviours they have in common, because identifying the similarities can provide instant opportunities to offer more of what the high-value customers value and nudge low-performing customers who may value those features to upgrade.
How Customer Cohort Analysis Differs from User Cohort Analysis?
The user cohort analysis gives insights on the complete user base, whether they pay for your service or not. Likewise, it doesn’t let you know anything about how to increase a high-value customer base and establish your revenue generation, unlike the customer cohort analysis.
Companies can benefit from the complete user base analysis, as it helps in making decisions on the nuances that keep customers coming back. These analyses can get you the lists for fast-growing businesses but do not show light on the data.
Here is a real-time example of the impact of customer cohort analysis
When Groupon was launched, it attracted a massive number of users who showed interest in the bargain, but were not loyal to the company. The churn rates were high and most of the users were less likely to make repeat purchases unless they get heavy discounts. However, cheap rates ate the profit margin of the Groupon shared with the merchant, so they changed the business model. In this case, the customer cohort analysis could have been a boon if they had analyzed the experiences and behaviours of the repeat customers, rather than focusing on the wider user base. They could have narrowed down the requirements of the repeat customers and cut down on the high-churn user rates.
Le-Monde, a French newspaper, took advantage of customer cohort analysis to define their high-impact readers. They made an analysis of their data to define what content interests more for revenue-driving users. They also tested the balance between the free content (accessible to all) and paid content (available for revenue-driving customers) to best incentivize subscriptions. The analysis gave them insights on where to nudge a customer. By utilizing this analysis, and understanding what made more subscriptions, the company was able to boost their subscription up to 20%. They also optimize their customer experience and enhance renewals.
What Customer Cohort Analysis Can Do for You
When you are able to narrow down your analysis to your high-value customers, you will be able to make cost-effective decisions. Executing customer cohort analysis enables you to focus more on the profitable part of the customer segment and drive high-value in their life cycle. With the help of the cohort analysis, a brand can improve acquisition, activation, onboarding, returning user experience, and adoption of new products or features.
You can customize these for your high-value users and find multiple ways to enhance them for non-revenue-driving customers.
This kind of analysis is valuable due to the specificity of the information it provides. It allows companies to find answers to targeted questions by analyzing only the relevant data. Here are some things this process can help you do.
– Know-how user behaviors affect your business. Cohort analysis allows you to see how actions those in the cohort took or didn’t take translate into changes in business metrics, such as acquisition and retention.
– Understand customer churn. You can marshal your data to assess your hypotheses regarding whether one customer action or attribute leads to another, such as whether sign-ups related to a specific promotion encourage greater churn.
– Calculate customer lifetime value. Analyzing cohorts based on acquisition time period, such as grouping customers by the month they signed up, allows you to see how much customers are worth to the company over time. You can then further group these cohorts by time, segment, and size to assess which acquisition channels lead to the best customer lifetime value (CLV).
– Optimize your conversion funnel. Comparing customers who engaged in various ways at given times with your sales process can allow you to see how user experience throughout the digital marketing funnel translates to value in your customers.
– Create more effective customer engagement. As you see patterns in how various cohorts engage with your company, SaaS website and the product – you can take steps that will encourage all customers to take various actions more efficiently.
How appICE helps in increasing customer retention rates
appICE analysis empowers brands with data that aids in measuring and driving user retention. You will have various benefits using appICE, one of the key advantages is the virtual data representation. You don’t have to skim through rows and columns of data to make sense of your customer behavior. appICE gives a glance at your cohort analysis in a graphical form that requires no further interpretation.
Cohort Analysis can provide all manner of useful insight into what works best to engage, convert, and retain customers. It’s something savvy business owners should return to, frequently, as you seek to answer both basic and complex questions about your company’s progress and growth.