A few weeks ago I decided to do some simple analysis of our deal flow at Import.io. In order to do this I pulled our data out of salesforce.com and did some simple manipulation in Excel. I wanted to see the % chances of deals being won versus lost and how long it took.

But, as I started to look into the data something else emerged. It started to become obvious that the % chances of customers buying our web scraping solution dropped dramatically if they took too long to make a decision.

The first chart that I put together was this one.

It shows that, if there is an open opportunity (meaning that we are actively engaged with someone that might buy), there is a 63% chance of them buying within the first week. This almost halves in week 2 to 36% and then falls off a cliff to 7% in weeks 2-4 and 4% greater than 4 weeks.

I spoke to our sales team about this and they were astounded. They knew that customers were buying our product quickly (they have a need, we meet it, they buy) but they had no idea that essentially if they were spending a lot of their time chasing customers that had been outstanding for more than 2 weeks, then they were likely wasting their time.

I then decided to take a look at our overall sales funnel – and I didn’t like what I saw. Our sales team were feeling really good with the traditional metrics, # of opportunities, value of funnel etc, but as you can see from the below, over half of our funnel was made up of opportunities that were more than 2 weeks old – which meant that our chances of winning those customers was about 5% – whereas the sales team were forecasting them with the same percentage close as other opportunities.

As a result of this analysis we changed our process to support customers faster. We implemented chat on our web site so that customers could get instant answers, we gave customers full function product for free for a short period of time and we ensured that our sales team spent the majority of their time working with customers that we’d been engaged with for less than 2 weeks. It has been extremely successful for us, increasing our astounding growth rates – we’re currently running at ~400% annual growth – as customer’s need for data increases and our product provides them a great vehicle to do so, replacing or being an alternative to web scraping engineering projects.

Of course, this does not take into account the large percentage of our customers that buy self-serve on the web site; this analysis was just done on the customers that the sales team was talking to.

We will be looking for a ‘data wrangler’ soon to join the team. We have so much data to work with but need people to help us do so.