Selling is increasingly an exact science, where dice play an important role in ensuring commercial success.
This is because, despite the strong human role in this activity, it is increasingly the analysis of structured information that guarantees the closing of the deal and financial sustainability.
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Within this scenario, Cohort Analysis has become more important as a way to interpret not only isolated data but also its variation according to groups with common characteristics, in a given period of time.
Want to better understand how this sales metric works? Check out what Cohort Analysis is and how to use it in your company’s business strategy in the article!
What is Cohort Analysis?
To understand what is a Cohort Analysis (or Cohort Analysis), we need to understand the meaning of the word Cohort.
This is a statistical concept that refers to grouping a group of people who have in common an event that took place in the same period. We use Cohort to talk, for example, about people born in a certain year and assess some common ground.
Considering this concept, therefore, we understand that Cohort Analysis is the interpretation of indicators for a specific group, grouped according to a specific period.
When we take this metric to the sales universe, we can answer some very important questions about commercial strategies, such as:
- How did changes in the sales process impact results?
- Am I able to keep my customer engaged over time?
- What is the revenue coming from each customer group, for each campaign group?
These answers, however, are different from those obtained by only segmenting the groups.
In the case of a specific campaign, for example, using Cohort Analysis we can look at the results obtained throughout each month of the year for that specific acquisition source, noticing the evolution during the period.
Why is Cohort important?
Cohort Analysis is a valuable metric for any company profile, but especially for those that work with recurrence, as in the SaaS (Software as a Service) model.
This is because, in this case, it is even more important to maintain the client over time and to monitor the revenue brought in by him at each period.
In this regard, find out below some of the advantages of adopting Cohort Analysis in commercial management:
1. Evaluate results of strategy changes
When we talk about recurrence, customers can have very different purchasing and service usage experiences depending on their initial point of contact with the company.
Changes in the form of contracting, contract terms, website layout, trading model and the product itself can significantly affect the results that will come over time.
With a Cohort Analysis, it is possible to divide these customers into groups and periods that demonstrate how much the effect was positive or negative for each change.
2. Develop actions considering different purchasing experiences
If we assume that there are different shopping experiences and that, in general, each consumer profile will have one in particular, it is possible to use the Cohort Analysis as a starting point for more assertive actions, which ensure the closing of the deal or the maintenance of the customer inside the base.
Therefore, there is a huge advantage in making Cohort Analysis one of the sales metrics of your strategy.
Using Cohort Analysis in the Business Process
And how to use Cohort Analysis in your business process?
It may seem like a complex task (after all, it involves analyzing multiple variables), but it’s actually quite simple when you follow a step-by-step step like the one we describe below:
1. Define what you want to discover
Any data analysis needs a very clear objective to interpret. What will your Cohort Analysis be?
You can perform analyzes of this type for different purposes, such as those listed below:
- The cancellation fee for different customer profiles;
- Financial return over time for different acquisition campaigns;
- The retention rate for customers who purchased different service plans.
The important thing is to establish three variables:
- customer group
- sales metric
- time periods
2. Structure the Cohorts
Speaking of these variables, then, you need to start with your Cohort.
To define it, also know what data is available for analysis in your different databases.
Both your CRM system and other tools, such as Google Analytics, can help you in this segmentation.
Just remember: it needs to be very clear what differentiates one group from another. Some examples:
- Customer groups from each marketing campaign
- Customer groups belonging to a profile (Corporate or Individual)
- Group of customers belonging to specific regions of the country
- Among so many others that are relevant to your strategy!
3. Choose the sales metric
You can monitor the relationship between groups and different sales metrics. However, those that are related to the time factor make more sense.
Some of them:
- Customer retention or loyalty rate ;
- Cancellation or churn fee;
- LTV – long time value or customer lifetime ;
- Return on Investment;
- Average monthly purchase ticket;
- A number of sales to the customer base (Upsell or Cross-Sell).
4. Set time intervals
In general, time scales in a Cohort Analysis are monthly. But this can vary depending on your company profile.
If it is an e-commerce focused on the B2C market, for example, it may make sense to break the data into weekly or fortnightly intervals, since the sales cycle is shorter and new purchases by the same customer can happen more frequently.
If your commercial operation is focused on selling high-value solutions to the B2B market, with long trading times, it is possible to establish longer intervals, such as quarters.
5. Analyze and follow continuously
With the three variables defined and segmented, you need to continuously monitor the data. You can do this in Excel spreadsheets or, if this functionality exists, in your CRM system.
Also, don’t forget to look at the historical series. Here is the most important information for you to establish new trading strategies.
6. Take action on the data
All monitored sales metrics need to be evaluated with a “what can be done better going forward?” look. It couldn’t be different with Cohort Analysis.
Keep in mind that this analysis allows you to understand the differences between specific groups.
Therefore, you can understand, among other things, which one deserves more attention for the potential financial return to the business.
For each point of improvement found, set an action!
You’re most strategic operation with Cohort!
Cohort Analysis is not new to the sales world.
However, as it requires a more detailed structure at the beginning of its follow-up, it often ends up being undervalued by the commercial management.
This decision can cost you over time!
In a scenario in which data is considered the “new oil” for organizations, the deeper the interpretation of information, the greater the potential for it to bring with it important signs for growth.