Forecasting beyond the pipeline

January 21st, 2008 by Roy Russo

After reading one of Will Prices’ blog posts that touched on the impact of forecasting, it started me thinking about how most companies look at sales forecasting (btw, Will’s blog is a great read in general). Today, most companies use their CRM to forecast their future revenue stream. This is a perfectly acceptable practice and is frankly one of the primary reasons for using a CRM. Actually, when you look closely at CRMs, will see that they are designed more towards providing insight to management than actually helping the sales force close deals (but that is for another blog).

While many of these companies using a CRM are able to produce short term forecasting based off of the immediate sales pipeline, they often have little or no way to forecast beyond it. The main reason for this is that they usually don’t have the data needed and when they do, no way to analyze that data for predictability. I’m going to assume I just lost some people with this last sentence, so let me provide a simplified example.

Let’s say you are a B2B company that sells software primarily online. Most of your sales originate from people that visit your web site (which you know based off the lead source within your CRM). Your average sales cycle is 60 days (i.e. period from lead creation to opportunity closed-won… again, courtesy your trusty CRM). Your close rate is 50%, because are not doing a good job of qualifying leads (shame on you). Finally, your average deal size is $25K. So, in this example, if have 10 new leads created today, can estimate that will have $125K in revenue from them in 2 months time (obviously am over-simplifying this).

Since I know that most of my leads come from my web site, if I see that my web site traffic doubled since last month, I should also be able to safely assume that my revenue will increase as well. The problem is how much?

Now, let’s assume you have the capability to determine that 90% of your sales came from leads that visited your web site at least 4 times within 6 weeks of becoming a lead within your CRM. Given this indicator of sales, you can start predicting sales from web traffic. For example, if know that have 25 companies who have visited your web site more than 4 times within the last 6 weeks, then forecast a revenue of $562.5K in 3.5 months.

There are a number of data points correlating web traffic patterns to sales patterns that can be used to help forecast future sales. The key is to be able to derive these correlations based on historic sales information; otherwise all you are left with is a SWAG. Having a tool that automatically ties web traffic patterns to consequential sales opportunities also helps.

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