Making Revenue Predictable is Easier than You Think
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We’ve worked with dozens of B2B companies, and they all have struggled with the same question: how do I know if I’m going to hit my quarterly target for the next 4 quarters?

Using revenue engineering principles, we have been able to predict revenue within 5-10% before the beginning of the quarter in every case – often 9 months earlier.

It really isn’t rocket science. It requires using the data from a CRM like to create a predictable model of revenue based on marketing, opportunity, and pipeline characteristics. But there are some requirements:

1. The data in the CRM must be consistently entered and follow an identified sales process.
2. Attributes of a deal handoff from marketing or inside sales to sales must be known and tracked.
3. Sales opportunities must be tracked in a way that measures statistical characteristics of the pipeline, including deal size, deal length, and conversion rates.

Does that sound hard? It isn’t, if your CRM system is implemented and configured properly. In fact, making it easy for marketing and sales teams to use the system is the key to consistency. Here is some good news about a revenue-engineered approach:

1. The amount of data that sales reps need to enter is minimized in the system.
2. Any sales methodology can work, as long as it is used consistently.
3. Key characteristics that tell you whether there is risk in your pipeline are served up by the system – it doesn’t take an analyst churning out reports.

What we’ve found in architecting CRMs and processes for B2B companies is that the easier you make it on the people in the process, the more likely you are to get accurate, consistent, reliable data to predict and forecast revenue. As a byproduct, you also get a wealth of intelligence about how to grow your revenue faster.

Learn more about Revenue Engineering.

About author:
Dana has led high-growth marketing teams for almost 20 years. She has a proven ability to distill new thought leadership concepts for product companies in the B2B space, and create a lead generation infrastructure to measure sales and marketing effectiveness. Her work with the analyst community has led to superior ratings of technology companies, including leadership positioning on the Gartner Magic Quadrant.

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