SaaS Sales & Marketing Spend Efficiency Data

What is a good rate of new revenue for every dollar of sales and marketing spend in SaaS? Below we compare the change in revenue at the time a SaaS company IPO’d to the sales and marketing spend in that same year. That simple formula is the “Sales Efficiency”. For example, if revenue for a SaaS company grew from $100mm to $150mm while S&M spend was $80mm, the Sales Efficiency would be calculated as ($150-$100)/$80mm resulting in $0.63 of new revenue for every $1 in S&M spend that year. Observations and data are below:


No scale. Of the last 156 SaaS IPOs we looked at, the median S&M efficiency was $0.67 cents and the average was $0.97. In other words, the typical SaaS company on median generated $0.67 of new revenue for every dollar of marketing spend. The year prior to the public filing, the median was also $0.71 and the average was $0.94. There was practically no movement which is striking consistency.

Lack of data. Over time, SaaS companies have stopped reporting 3 full years of financials. For instance, of the first 80 companies on the list, 73 provided 3 years of data so we could do the analysis. Of the next 76 companies, only 23 provided 3 years of data. The list is in order of IPO, and the lack of more recent data hurts the analysis.

More recent data. If we isolate the last 20 IPO’s, the median and average in the year of IPO are $0.67 and $0.75 respectively. Interestingly that means SaaS companies have not gotten better at improving Sales Efficiency over time. Again, the consistency is striking.

The return is good. If every dollar of S&M spend yields $0.67 of new revenue which is 90%+ ARR, so long as you’re retaining that ARR every year and growing it (Net dollar retention is over 100%), the S&M function is working well. Assuming 100% net dollar retention, your payback period is ~1.5 years, which is a great return on any investment where you keep a customer forever and grow them.

Thank you for the readership. Visit blossomstreetventures.com for more blogs and SaaS data.


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