Coming from a chemistry background, I’d never have thought that the skills I was learning at university could be transferred to working as an analytics intern at FreeAgent, but this summer I proved myself wrong. After spending a lot of time taking courses in Python and SQL with the Code First: Girls charity through a year of lockdown, this internship was the perfect opportunity for me to develop everything I had learned even further. Over the course of the summer, I was tasked with working on a project designed to calculate the ‘lifetime value’ of FreeAgent’s customers. In doing so, I have found a new level of confidence in my own skills that I am sure will stay with me wherever I go next.

What is Lifetime Value, and why is it so useful?

FreeAgent is a subscription-based service which generates recurring revenue through subscription payments from different groups of customers. Estimating the expected present value of expected future payments, or lifetime value (LTV) of different customer segments can help FreeAgent make better-informed marketing decisions. My aim this summer was to create a reliable process for calculating LTV.

Process

Calculating an estimated LTV is a huge undertaking; one that can take a very long time depending on how thorough the results need to be. I only had three months to complete this project at FreeAgent, so prioritisation was key. I needed to understand the company’s customer segments and how they are tracked and reported. I also needed to know which of these metrics are considered to be the most important by the people who use the data. This ‘discovery’ stage proved to be as big a learning curve as any other part of the process.

Initially, a lot of my time was dedicated to modelling many different methods of predicting how long a customer might use FreeAgent for and then calculating estimated LTV. I was keen to use the programming language ‘R’ to do this but I had never used it before and had expected to need a significant amount of help to get up to speed with it. However, with my team giving me the freedom to work at my own pace while supporting me when I needed it, it turned out that I was able to work out nearly everything on my own! While this approach might have taken longer than if the team had simply shown me what to do, it made the overall process so much more rewarding. In the end, it also saved time as it left me better equipped to deal with any problems that arose. 

Using R for the modelling exercise gave me the ability to quickly test any theory I could think of and collect the results for easy comparison. This approach allowed me to really understand the advantages and disadvantages of the various methods I had available to me and to feel confident about the decisions I made.

Challenges

While developing our approach to calculating an estimated LTV using R had many advantages, it wasn’t a perfect solution. The required data had to be extracted by running different SQL queries by hand. While it’s possible to automate R scripts to run the queries, this isn’t a standard method used at FreeAgent and it could have introduced additional maintenance requirements.

As a result, a decision was made to combine the SQL and R logic using FreeAgent’s ETL tool, Matillion. Having never heard of the tool before, I found this to be one of the most unanticipated parts of my internship, but learning to use Matillion was a rewarding process. Rather than working with data in isolated chunks, I was able to gain a fuller understanding of the ways in which data is collected, transformed and maintained. It also forced me to take the time to truly understand every step of the maths I was using, rather than hiding behind the easy-to-use functions that R is so useful for. While it was unexpected, learning to use Matillion was one of the experiences that made my time with FreeAgent so worthwhile. 

Conclusion

I’m very grateful to have had the opportunity to work end-to-end on a project like this. From planning and developing the initial solution, to re-implementing the method in Matillion and then presenting my solutions to stakeholders, I have had a full, comprehensive experience of life in the analytics team at FreeAgent. The internship has taught me far more than simply technical skills and the advice and support I have received from the team has been invaluable. If you’re considering applying for an internship at FreeAgent, here is your sign to go for it!