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After working at Microsoft, founding Spindle, and toiling in the salt mines of local and social search for many a year, I know a bit about people ‘discovering nearby’ via their phones. Unfortunately, I’ve come to realize it’s a exceedingly difficult space. Given the number of people that have…

great read from @patk

Ok, that was legit. Well put.

The emerging problems highlight another challenge: bridging the “Grand Canyon,” as Mr. Lazer calls it, between “social scientists who aren’t computationally talented and computer scientists who aren’t social-scientifically talented.” As universities are set up now, he says, “it would be very weird” for a computer scientist to teach courses to social-science doctoral students, or for a social scientist to teach research methods to information-science students. Both, he says, should be happening.

Recent Big-Data Struggles Are ‘Birthing Pains,’ Researchers Say - Research - The Chronicle of Higher Education (via infoneer-pulse)

The Agent-based modeling Sociology course I took while getting my CS graduate degree was awesome. Ended up publishing a paper based on the simulation we built that studied the effects of different social network topologies on the spread of fads.


Box’s Not So Magic Number


One of the key metrics we encourage our SaaS portfolio companies at Flybridge to be focused on is the magic number. Sure growth rate and lifetime value and customer acquisition costs and churn are all important but the magic number is magic for a good reason: it gives a great sense for how much sales and marketing spend are driving monthly recurring revenue growth. In other words, it summarizes a number of metrics in a single number. If you’re not familiar with the metric, made famous by Josh James, take a read here to get up to speed.

Our praise of the magic number often translates to religion at our SaaS portfolio companies. In one particular company, after implementing magic number reporting and discovering it to be 1.9, a sales manager cold emailed James to share his excitement. James responded “Hire more reps then” and introed the company to his CTO at Domo (who went on to become a customer).

While we get to apply this metric to our portfolio companies - most of our SaaS companies report it on a quarterly basis - it’s sometimes fun to apply the same lens to other companies. With Box filing their S1 earlier this week, we wondered what sort of numbers they have been seeing. The quick: not such magic ones. 

As we go through this, remember that James’ rule of thumb:

[I]f you are below 0.75 then step back and look at your business, if you are above 0.75 then start pouring on the gas for growth because your business is primed to leverage spend into growth. If you are anywhere above 1.5 call me immediately.

Revenue and Sales and Marketing

Finding the numbers to calculate the magic number by quarter for Box based on their S1 filing is pretty straight forward: just go to the Quarterly Results of Operations section, find the revenues and sales and marketing costs by quarter and use James’ magic number equation (QRev[X] - Qrev[X-1]) * 4 / ExpSM [X-1]. That leaves the following:


Now this is slightly imprecise in that it looks only at new revenue growth not new annual contract value growth in a given quarter, a more true way of calculating the magic number, but it’s the best we can do with the data reported. Given James’ rule of thumb, ever quarter since the quarter ending 7/31/12 has been one worthy of stepping back from, not one worth pouring gas on.


The issue with the calculations above is that they do not take into account what Box counts as Sales and Marketing expenses. Normally this line would contain just expenses associated with the various functions but, in Box’s case, there is more to the story. Box offers free trials of their product and the Sales and Marketing section of the S1 gives a hint of how Box accounts for the expenses associated with the free trials:

Sales and marketing expense also consists of datacenter and customer support costs related to providing our cloud-based services to our free users

Being true to James’ calculations, it’s not really fair to burden the magic number with the cost of datacenter and customer support expenses so, for the benefit of Box, let’s back these out. It’s impossible to be precise here since the company doesn’t break these items out individually but we can use a note in the filing to guessestimate:

Sales and marketing increased by $72.0 million, or 73%, during the year ended January 31, 2014 compared to the year ended January 31, 2013. The increase was primarily due to an increase of $45.5 million in employee and related costs, including higher commission expenses of $16.0 million, driven by headcount growth from 374 employees as of January 31, 2013 to 513 employees as of January 31, 2014, and higher sales, an increase of $12.6 million in datacenter and customer support costs to support free users, an increase of $6.4 million in allocated overhead costs, and an increase of $2.8 million in travel-related costs.

If you assume that all the expenses grew at the same rate from 2013 to 2014 (and this is a pretty big assumption but really the only one that can be used), you can roughly calculate what percent of sales and marketing expenses go towards each line item:


If you apply this same rule of thumb to the reported Sales and Marketing expenses and back out the 19% costs associated with free customers, you arrive at the following:


Better (because the sales and marketing expenses have been adjusted downwards) but still far from great. So how do these compare with some other enterprise SaaS public companies? The answer: not so well.



The magic number isn’t the end all be all for SaaS metrics but it’s a very useful one. It doesn’t take into account things that may benefit Box’s business such as longer than average lifetime values and increasing customer values over time, but it’s an important metric nonetheless. The magic number analysis in Box’s case suggests that the company is spending money faster yet growing slower than comparable public SaaS companies - essentially throwing cash at growing top line revenue with decelerating results. If one of the Flybridge portfolio companies demonstrated these magic numbers, especially on a downward decline, we’d be wondering if it made sense to keep pouring fuel on the fire. We’ll see if the public market will wonder this as well. 

Note: A big thanks to Bart Hacking, CFO of BetterCloud, for running the numbers and germinating this post.

This is what a great analysis of a SaaS business looks like (given limited time to prepare).