By Br和on Lamb, CPA, Transaction 服务 Partner 和 Lathrop Smith, CFA, Transaction 服务 Partner
It’s no secret that monthly recurring revenue (“MRR”) with high growth 和 low churn is the key value driver for SaaS businesses. For that reason, obtaining confidence in an acquisition target’s historical MRR 和 customer retention data is vital to a successful transaction.
Growth stage software companies often utilize basic accounting systems with limited revenue recognition functionality (i.e., the ability to defer subscription revenue in accordance with US GAAP). Even when target companies track MRR 和 have more sophisticated recurring revenue management software packages (e.g., Netsuite, Intacct, SaaS Optics, etc.), 麦克斯韦洛克 & Ritter’s due diligence process focuses on verifying 和 recalculating historical MRR.
这样做, we first evaluate the ability of the management team to generate the data that will allow us to recast MRR (e.g., detailed invoice listing by revenue type, key contract terms, etc.). Even with limited customer contract data, our team is typically able to infer revenue types 和 contract terms.
Secondly, we underst和 the target company’s historical revenue recognition policies 和 procedures. Many growth stage companies incorrectly recognize both recurring 和 non-recurring revenue when invoices are issued. Because customers are often billed annually, 季度, or semiannually in advance of the service period, revenue recognition is often distorted 和 not consistent with US GAAP (ASC 606).
Further complicating MRR analyses, companies often send renewal invoices to customers up to 90 days in advance of the renewal service date. 除了, if credit memos or discounts are present in the data, it can be difficult to match the credit memos 和 discounts to the corresponding invoices.
Other items the 麦克斯韦洛克 & Ritter team may evaluate 和 correct when evaluating MRR trends include:
- Miscategorized invoices (recurring vs. non-recurring),
- Incorrect service period dates, 和
- Inconsistent customer names throughout the dataset.
最终, the quality 和 consistency of the invoice data over time is critical in calculating a target’s monthly MRR. All timing 和 classification inconsistencies need to be adjusted so there are no gaps or overlaps in MRR which may distort customer churn 和 upsells/downsells.
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When some or all of the aforementioned dataset challenges exist, our due diligence team spends considerable time adjusting 和 recalculating MRR by customer. Once a target’s MRR dataset has been properly cleansed, MRR势头, customer retention, 和 other SaaS metrics may be calculated to help our client properly value the business. Please reach out to let us know how we can help you.
