There are a lot of stats that we’re doing our best to track. But there are also ones that we’re not. While this is a data project, we had to make a call as to what data we thought was worthwhile tracking while letting some others go.
So… here’s what you’ll see on the site when it launches.
We’re tracking every deal that comes on the show. That includes the company’s name, the amount being asked for the and the equity or loan terms on offer. We also try to track as much gross sales data as we can make sense of, profit if any when it’s given, and the location of the business if it’s mentioned. Obviously, we track any deals that are made, their terms, and which sharks the deals are made with.
We’ve invented our own categories to put companies into and have categorized every deal. Updates are also tracked, with a specific eye toward capturing new sales data, company acquisitions, or new licensing deals and which companies those deals are with. We don’t actually enter that data into our database right now but will use it to fill out the pages we intend to do for every company.
Lastly, we also track for each episode which sharks have appeared.
What we don’t attempt to capture is the size of the market the business is in, net sales, or margins. Nor do we try to capture each offer made by every shark.
The size of the market a company is in, as has been pointed out many, many times on the show, is not really important to the success of the company unless that market consists of a hundred people. Then you’d have problems. But even the sharks see that sometimes you make your own market so I don’t bother to track that. We also don’t track net sales or margins because we’ve noticed that an entrepreneur will claim to have 70% margins but then the net won’t align with it and they’ll then claim that on a ten dollar product, customer acquisition is $4.99. If it costs $3 to make (70%) and $4.99 to acquire a customer, aren’t the margins more like 30%?
It just becomes confusing and almost impossible to keep track of. We’d like to track this kind of thing, it’d be great to be able to compare deals across the board and see if certain margins are more likely to score a deal than others but, until we get a staff who can sit down and really try to make sense of what’s said in every episode, we’re just going to have to let that go.
Perhaps the most controversial of all our decisions on data to not track is that we’re not tracking offers made by sharks that aren’t accepted.
Some might compare this to baseball and tracking hits but not at-bats. But we don’t see it that way. To us, it’s more like tracking every swing a batter may take at a plate appearance. But it’s also more complicated than that. For instance, if we were to track the offers being made, what would we track? The first offer made? Every revision to that offer? Just the final offer? What if an offer is made but then rescinded? Should that count?
I just watched an episode in Season 3 where Lori and Robert teamed up to make an offer until Mark wanted in but to cut Robert out. Robert then teamed up with Kevin to make the same offer Mark and Lori were making. How does that get tracked? And, more importantly, how should that be tracked in such a way as to be useful? Perhaps, in terms of tracking it like plate appearances, it might be useful to note that a shark made an offer at all but… when we started tracking we couldn’t see the value so we haven’t.
To me, this doesn’t have much of an effect on the data. It’s extremely rare that a company gets an offer from more than one shark and a deal isn’t made. And, even if one isn’t made–usually because the sharks rescinded their offers–does it really matter that offers were made at all if a deal wasn’t reached?
Perhaps the only area where I can see that this might be useful would be in possibly being able to identify which kinds of companies spark a feeding frenzy of offers, counter offers, and a large number of sharks. But even this can usually be captured by the deal data itself. When a feeding frenzy occurs, the entrepreneur usually makes out like a bandit as the sharks bring their deals down to be more in line with the original offer and sometimes even sweeten the pot a little with more money. And that’s what’s really important.
So we’re actually capturing a fair amount of stuff. But we had to let some of it go.
As time goes on, it might be interesting to revisit some of these decisions and see whether it might not be worth it to go back and add to our data set.
What do you think? Are we missing anything obvious?