Portfolio Project powered by Gareth Cox-Thorpe

Optimizing SaaS Customer Retention: Ideal Profile Analysis

Colleagues Reading Statistical Reports

A well-functioning data team is there to remove opinion from important decisions, they accurately direct the business on how best to approach problems and recommend ways to improve company performance.

In the dynamic landscape of Software as a Service (SaaS) enterprises, understanding customer retention and churn rates is crucial for company growth. These types of metrics effect many different departmental decisions. Sales can use the insights to optimise their sales processes, product development could use them to prioritise their workstack and the marketing department could use the insights to test a new marketing funnel.

The following task will give you the opportunity to showcase your analytical skills in a real-world situation for a member of a data team. You will have to ensure the data is clean and usable before building the required metrics and analysing the results so that you can make informed and accurate recommendations of how the business should move forward.

As the Head of Marketing, I want to understand the retention rates of our ideal customer profiles based on customer country and size. This will help optimize our outbound email marketing and target customers more accurately, increasing the likelihood of renewals when their subscription ends.

Your task is to use the provided dataset (in “Supporting Material” section below) to calculate customer retention and churn rates for a SaaS company. Identify the ideal customer profile based on customer country and size that yields the highest retention rates and, therefore, the highest likelihood of renewing.

Recommended Sequence of Actions

1.Begin by understanding the stakeholder’s request and why completing this task is necessary. This understanding will enhance your delivery of the final insights. Then, determine the best tools and approach to take for this task.

    2. Ensure you have accurate and clean data. Validate that each field’s format is correct and that there are no discrepancies within the dataset. If you don’t trust the raw data, others won’t trust your insights.

    3. Research retention and churn rate metrics, then create these metrics using the provided data.

    4. Represent your findings graphically.

    5. Test your results.

    6. Recommend next steps to the Head of Marketing regarding which customer segments to target and why.

    Bonus Points

    • Show the top 5 ideal customer profiles with the highest churn rate.
    • Show how the USA has performed in terms of retention over the last 2 years.
    • Show which customer tier has generated the highest total amount in the last 6 months upon renewal.

        The above task should be challenging, but you should have fun with it. You have the freedom to express yourself through the insights you generate. Decide whether you want to tackle it alone, work with your mentor, or collaborate with a team of mentees. You should be proud of the final result, so make sure to post about it on LinkedIn and include the hashtag ‘WomenGoTechDataTask’. Have fun and good luck!

          Dataset for the Task:

          Click here to download the dataset.

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