How will you make your number this year? (Part 1)
A new data-driven approach to finding the highest propensity-to-buy customers
Recently I was talking to a CEO that was brought in by investors to scale-up a technology company in a hot new emerging category. He told me two issues were keeping him up at night:
“I know sales cycles are happening at this very moment that we want to be in, but aren’t.”
“My pipeline is filled with small deals. My reps are spending time on the wrong deals!”
For most B2B tech companies, this is the sobering reality. The satisfaction of making last year’s numbers has quickly given way to the challenge of making next year’s revenue goals. It comes down to this:
- How do I determine which companies are ready to buy, NOW?
- How many opportunities are out there? Do I have the right coverage model? Are we in EVERY potential sales opportunity that we can win?
- How do I engage these prospects? Am I wasting my marketing and sales $ on the wrong accounts?
Customers ARE buying this year. Unfortunately, your sales team IS calling on the wrong accounts and your competition IS in sales cycles you don’t even know about.
The problem is that the old way of sales targeting and segmenting is outdated. You don’t have the right data to intercept demand or find the highest propensity-to-buy accounts. Most tech executives have only a good hunch about where the revenue will come from this year, and struggle to generate the right kind of pipeline and target accounts for their sales and marketing teams to pursue.
We have developed a new data-driven model to help executives determine the accounts with the highest propensity-to-buy. Finding these sales opportunities requires an objective, third-party perspective, a different kind of data, and a more sophisticated way of segmenting the market. The result is the ability to break into existing sales cycles and find the buyers that are ready to buy, now – and the accounts you can win!
Why don’t companies have this data? It’s hard, takes time and requires expertise they may not have. Plus an independent, objective analysis may not be possible using an internal team with a naturally biased viewpoint.
Tomorrow, we’re going to talk about one of our clients using this powerful data-driven approach to sales targeting, and the results they’ve seen. In the meantime, what’s your approach? Is it working? Why or why not?