Hey everyone - I just had a growth equity interview with a firm that focuses on SaaS and it went well up until the case study. I struggled going from raw data to waterfalls and MRR analysis in the given timeframe.
All the models I build in my banking job are for companies with large Corp dev teams and so we usually get pretty clean financials.
I’m going through some practice growth equity interviews and am struggling with best practices on how to go from thousands of rows of raw customer data —> MRR waterfalls etc.
One of the precedents on my banking drive has a TCV case study done with heavily nested formulas that I’m not used to using in the banking models I build.
Does anyone have recommendations on how to go about this and best practices? Anything would be helpful. Thank you
For enterprise software investing - In the MRR build, you need to show that you understand and can easily calculate the following using raw customer data -
- Beginning ARR, adds, churns, expansion/contraction, Ending ARR (and YoY growth)
- Key stats like Net Retention, Gross Churn, ACV (also known as ARPC), ARPNC, Customer Concentration
- If it is connected to the P&L, you need to also run LTV, CAC, LTV/CAC, Payback period, Rule of 40% figure
Basically, you need to lay out the MRR by customer and then calculate the above figures to summarize your analysis. I would say that having a strong opinion on the industry as well as the figures goes a long way. For instance, net retention over 100%, gross churn under 5%, ARR growth of 40%+, LTV/CAC of 3x, and low concentration, are often considered fairly strong metrics. Others feel free to share your insights if I missed anything or if you run this differently.
Definitely - thanks for the insight. For me to pull the data into another tab to run the analysis, the formulas I currently am using are heavily nested index match match offset formulas and are hard to follow after a while. This makes me think there’s probably a more simple way and am not sure if there are any best practices used in the industry
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