Predicting the future is difficult, and this is no more apparent than when it comes to predicting sales revenue. According to Miller Heiman Group, 80% of sales organizations miss the mark on their forecasting by 25% or more.
But does the accuracy have to be this poor? An over-reliance on intuition and qualitative input from overly optimistic salespeople from dreaded forecasting calls, compiled into magical spreadsheets to crunch the numbers. No wonder.
The truth is that this method of “voodoo” forecasting — a method of using a smattering of chicken bones and entrails to predict the outcomes of your collection of sales opportunities — is simply missing the critical data and science to provide any accuracy. Not to mention, it tends to waste precious sales managers and sellers’ time.
Voodoo forecasting should be put to rest. It’s time to focus on the wealth of real measures and data that, if consolidated, could guide a more scientific approach and intelligence tools that could help guide better forecasts and more predictable revenue and better focus and performance.
The voodoo that you shouldn’t do
While optimism is essential in the sales process, revenue intelligence data helps determine exactly which deals are more likely to close or not and identify where adjustments are needed. This form of sales intelligence combines content engagement, buyer intent and sales activity data to provide a robust view of your sales opportunities and account health.
Without revenue intelligence, revenue teams are closer to leveraging chicken bones than data. Organizations must turn their focus from voodoo to revenue intelligence to ensure they’re seeing a significant boost in their forecasting accuracy.
With revenue intelligence, you no longer have to rely on voodoo estimates or the numbers you gathered from those dreaded – and inaccurate – forecasting meetings. Revenue intelligence emphasizes engagement and intent from the moment a prospect visits the corporate website to sales meetings and information provided by sales representatives during the exploration process. This all provides a comprehensive view that will help your buyer in the decision-making process and, in turn, accelerate the status to “closed deal.”
The four pillars of revenue intelligence
To obtain the clearest form of revenue intelligence, you’ll need to refer to the four pillars that assist in providing the crucial information that’s pivotal in improving your forecasting.
- Sales activity – A list of meetings that have been conducted and who attended, communications that were delivered to the buying group (emails, phone calls), notes on what has been communicated and response to those communications, data on the progression of the deal as it relates to the sales stages, and information based on the cadence of buyer group interactions.
- Content engagement – The content shared during buyer group meetings, the content shared at each stage of the sales lifecycle, how the buyer responded to the content, the content shared by essential members of the buyer group, buyer group members you haven’t reached, and the amount of time and specific content stakeholders interacted with.
- Value engagement – The key objectives and challenges the buyer group would like to address, proposed use cases and solutions, “do nothing” cost along with legacy solutions and pain points, prediction of outcomes from proposed solutions, estimated investment and ROI, and the buyer group’s performance on previous projects.
- Buyer intent – The indication as to whether or not the buyer group is really interested in finding a solution in your market segment, how they are interacting with your website and community content, and how they are interacting with trusted third parties and competitors.
As you work with these four pillars, one keyword to keep in mind is visualization. Transparency and visualization go hand-in-hand, and are imperative when collecting revenue intelligence.
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Visualization, you say?
To best understand and communicate, you can tell a story with data. Visualizing the four pillars of revenue intelligence will paint a clear picture of the data, rather than just providing a set of numbers.
Evaluating your team’s ability to understand the opportunities at hand and close the best deals starts with visually examining a timeline of the deal itself. That way, you can see engagement, activity and intent in an all-in-one, time-based view. The revenue intelligence-provided timeline of the deal provides essential information and insights on the possibility of closing a deal in a detailed, pinpointed manner.
Another vital step in the visualization process is the buying committee reach. By not reaching key members of the organization, you could be setting up your deal for failure. Using the data pillars, you can generate a visualization of which members of the organization you’ve had direct contact with, the content and value of the engagement, and which members are showing intent to move forward with the sales process.
The machines take care of the rest. Artificial intelligence (AI) and machine learning (ML) eliminate subjectivity and rely on facts to provide a realistic visual of where you’re at in the sales process. AI/ML assists in building sales, behavioral and profile data unique to the buyer. In turn, this will create a heightened awareness of who the buyer is and whether they’re interested in moving forward in the sales process.
AI and ML also process the data and uncover correlations and patterns, such as the activity and engagement that led to a deal lost or won.
Overall, revenue intelligence can drive better sales effectiveness, predictability and performance by capturing a comprehensive and holistic view of each entire sales opportunity. As the world continues to move to digital selling, revenue intelligence may very well be the game-changing addition to your sales tech stack.
You no longer need to rely on the ancient — and often unreliable — practice of voodoo forecasting. It’s time to focus on the facts and put your faith in revenue intelligence.
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