I was asked by a reader if I had an opinion on Nearmap (NEA), specifically the Group Portfolio Lifetime Value (LTV) which NEA calculates as $365.5m at the end of FY2017, see bottom line in their financial presentation. When you consider the market cap is around $260m maybe there is a play here? Maybe so let’s dig deeper.
A bit of CFO housekeeping before we start. I find these rules kind of important when I am valuing a company.
How does NEA define LTV? From the FY2016 Financial results presentation. ACV is Annual contract value and is a proxy for revenue contracted:
Unfortunately this definition of LTV fails Rule 2. The company has ignored the costs of running the business and the cost of acquiring clients. Whichever way companies like to spin it, costs of running a business matter. To be fair to NEA the big daddy of Saas, Xero, calculates its LTV a similar way. So it is wise to remember the basic CFO rules when assessing an LTV number.
Below is my estimation of the LTV of the Australian operations. At the end of FY2017 the company had 7,227 clients paying an average revenue per year of $5,165. The gross margin was 80%. I estimate General and Admin (GA) expense for Au was around $13m or $1,800 per user. This is a combination of Au GA segment costs, pro-rata Corporate overheads and pro-rata capitalised development costs for the group.
I have assigned a portion of capitalised capture and development costs to the GA expense per user as after all taking photos and developing the product is a cost of doing business. I am sure the companies selling their services to capture and develop are booking NEA costs to revenue.
This is important as we know from the Bonus Rule that free cash does not equal profit or EBIT. The following table shows from FY2015 NEA capitalised development costs. This has improved profitability at the Income statement level. I guess if you added these costs in, EBIT would look terrible and I am not sure what that does to the STI and the LTI.
In FY2017 the company spend $14.9m in development costs and only booked around half of this to the P/L. However these are costs to running the business and represent real cash outflows.
NEA has managed to reduce churn from 13% to 10% in FY2017. From the company announcements NEA added net 400 new clients in Australia for FY2017. Factoring in churn then I estimate the company added gross 1,083 clients for FY2017.
NEA spent $7.8m in S&M in FY2016 to acquire these clients at a CAC of $7,180 per client. This is a huge step up from FY2016 where I estimate the CAC per user at $2,881.
So adding these all together my rough estimate for a LTV after all costs is around $117m for the Au operations and this is not discounted. Fair way away from NEA LTV calc of $365m.
NEA is in a US expansion phase so we should not discount the value that is being created there. NEA produces the following slide which shows US revenue tracking against a similar time frame in Australia.
Again with Rule 1 in mind revenue does not equal profit. What would be more valuable if we could measure how much money NEA is spending to generate this revenue. After all I could give away dollar coins for 70c all day long, my revenue would look great but I still lose money.
Luckily we have such a tool. Sales efficiency is a measure of the dollars spend in Sales & Marketing (S&M) and the uplift that this spend brings in committed revenue the following period. Sales efficiency and its versions are termed the “magic number” and is the most common way to benchmark SaaS companies.
For example in the table below NEA spent $7.8m in FY2016 on Sales & Marketing in Australia. Assuming a lag in the sales cycle this spend achieved an uplift of $5.6m in Annualised contract value in FY2017. In this case sales efficiency is 0.72.
As we can see from the chart below sales efficiency for the AU operations has been trending down.
FY2014-2015 was a great year for NEA. It spend $2.8m in S&M in FY2014 which then translated into a uplift of ACV of $6.1m in FY2015. Since then the company has had to work harder to retain and gain new clients. Every incremental dollar in S&M in FY2016 only brought about 72 cents in ACV for FY2017.
It will be interesting on the FY2017 S&M spend in Australia of $8.3m what the return will be for FY2018.
So what about Sales efficiency in the US operations? There is not a lot of data here but sales efficiency is heading in the right direction.
An observation I would make is it is starting from a low base. You would expect your sales efficiency to be at its highest early on in the product cycle as you convert your early adopters. For example NEA spent $5.8m in the US on S&M in FY2016 for a sales efficiency of 0.96. When the company spend the same amount of money on S&M in FY2015 in Australia it produced a sales efficiency of 1.6.
The following chart from Redpoint partners shows the average sales efficiency for 20 public traded Saas companies in the US. You can see the average falls below 1 after year 10. Also notice that Years 6-7 tends to be peak efficiency, and all the best Saas exceeded a value of 1 in this period.
NEA spent $8.6m in the US on S&M in FY2017 so they hope this brings a big increase in contract value for FY2018. NEA in its FY2017 presentation quoted a target of doubling ACV in FY2018. Doubling ACV would give a Sales efficiency of 0.81, lower than FY2017.
Sales efficiency should not be taken in isolation. If you have a low churn then you can afford to have a lower sales efficiency as you have the clients for a long time. Similarly if you have a low fixed cost base then you could have a low sales efficiency. But if you have a high churn and a high fixed cost base then you need to compensate with a high sales efficiency.
So in summary a lot of expectations seemed to be factored into the current share price based on what I can see. I have no clue as to whether this may or may not be fulfilled, so it is in my too hard pile.
A final point, I found NEA to have a really complicated set of accounts. It was hard to find the data points to establish a good handle of the unit economics. More often than not when the analysis requires a ton of work and engineering I have found these companies to be the least profitable to invest it.