MLR

Cleaning Up MRR to Understand the Key Value Drivers

By Brandon Lamb, CPATransaction Services Partner and Lathrop Smith, CFATransaction Services Partner

It’s no secret that monthly recurring revenue (“MRR”) with high growth and low churn is the key value driver for SaaS businesses.  For that reason, obtaining confidence in an acquisition target’s historical MRR and 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 and have more sophisticated recurring revenue management software packages (e.g., Netsuite, Intacct, SaaS Optics, etc.), Maxwell Locke & Ritter’s due diligence process focuses on verifying and recalculating historical MRR.

To do so, 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 and contract terms.

Secondly, we understand the target company’s historical revenue recognition policies and procedures.  Many growth stage companies incorrectly recognize both recurring and non-recurring revenue when invoices are issued.  Because customers are often billed annually, quarterly, or semiannually in advance of the service period, revenue recognition is often distorted and 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.  In addition, if credit memos or discounts are present in the data, it can be difficult to match the credit memos and discounts to the corresponding invoices.

Other items the Maxwell Locke & Ritter team may evaluate and correct when evaluating MRR trends include:

  • Miscategorized invoices (recurring vs. non-recurring),
  • Incorrect service period dates, and
  • Inconsistent customer names throughout the dataset.

Ultimately, the quality and consistency of the invoice data over time is critical in calculating a target’s monthly MRR.  All timing and classification inconsistencies need to be adjusted so there are no gaps or overlaps in MRR which may distort customer churn and upsells/downsells.

ML&R Due Diligence Team here for you

When some or all of the aforementioned dataset challenges exist, our due diligence team spends considerable time adjusting and recalculating MRR by customer.  Once a target’s MRR dataset has been properly cleansed, MRR momentum, customer retention, and 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.

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