Big data torpedoes sales forecasts, can cloud tools fix the problem?

By Jeff Vance, CIO |  Big Data

Consider this: The average sales representative has anywhere from 20 to 50 open sales opportunities at any given time. For a small organization with a sales team of 10, they have to keep track of a manageable 200-500 opportunities. For a large organization with a 100- or even 1,000-member sales team, the opportunities start spiraling out of control. A 1,000-member team with a modest number of opportunities, say 25 each, will generate data on 25,000 leads.

But it's not just each lead that is the problem. If the CRM system doesn't archive records but simply overwrites them when changes are made to a lead, valuable information will be lost. For instance, e-signature company EchoSign (which was recently acquired by Adobe) discovered an interesting pattern in lead-nurturing emails.

When you sign up for a free EchoSign account, you will receive three nurturing emails. The first will thank you for signing up, while the next two will offer usage tips. Of course, within each email users are given links to premium, paid services.

As with most email campaigns, the first email generates the most clickthroughs. Click rates drop with each subsequent email -- but only to a point. "I decided to test another series of emails a month out after users hadn't heard from us in a while," Loretta Jones, EchoSign's head of marketing says. The results surprised her. The first email sent a month later generated better results than all but the initial welcome email.

If in her recordkeeping, Jones simply updated each record, overwriting the results from the first series of emails, this pattern would have never emerged. However, patterns like this require storing lots and lots of data. Basically, you trade a lack of visibility for Big Data woes.

Sales Visibility Triggers an Avalanche of Data

If every single prospect or customer event is recorded, data starts to grow exponentially. In some sales cycles, records can be updated dozens of times before the sale is closed or abandoned. Each time a prospect attends a webinar, downloads a white paper, stops by a booth at a trade show, the record must be updated. The time lags between subsequent events are important, too. Over the sales lifecycle, there could be hundreds of versions of each record.

Remember that a 1,000-member sales team will easily have records on 25,000 prospects or more? If changes are tracked inefficiently, as they so commonly are, the already unwieldy 25,000-record database will balloon to hundreds of thousands or even millions of records.

Is the possibility of finding obscure sales patterns enough to justify the storage, management and maintenance of such an enormous amount of data? Burleigh of Cloud9 believes it is. "Deals and even the sales reps themselves tend to follow patterns," Burleigh says.


Originally published on CIO |  Click here to read the original story.
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