As a frontline manager, you’re responsible for the accuracy of your forecast
While there is no way to predict the future with 100% accuracy, there are steps that you can take to provide a more educated and accurate forecast to sales leadership. To learn more about how Gong can help you check the reality of your committed deals, let’s look at some best practices.
Forecasting best practices:
Determine the health of the pipeline expected to close this period
Are the deals your reps are forecasting real? A number of factors play into the overall health of a deal, which come together to provide you with a better sense of whether a deal is likely to close. You need to be a bloodhound.
Likewise, are there deals not forecasted that should be? Ask the right questions to confirm.
Bring data to your pipeline reviews
You’re already conducting pipeline reviews today—enhance these meetings by using data to drive your discussion. This should be a proactive conversation to help you mitigate risk for future deals.
How can you use Gong to help you forecast more accurately?
Let’s look at how Gong can help you implement these best practices in more detail. We also have a step-by-step recipe you can follow.
Look holistically at the health of the deals in your pipeline to identify risk
The first step towards preparing a more accurate forecast is determining the health of the deals forecasted to close. Deals that don’t have consistent back-and forth, with the right stakeholders, can invite risk into your forecast. And while some surprises are fun, surprises in your forecast are not.
It is also important to take into account other deal catalysts that could push a deal to close in a later period than forecasted. What does the procurement cycle look like? Is this a larger deal with multiple approvals? Are people sick or out on vacation? These factors all play into determining the overall velocity of a deal.
Learn more about determining pipeline health and how to leverage Gong for better deal visibility through our deal strategy best practices.
Use Deal Intelligence to drive your pipeline reviews, to help better inform your forecast
The root cause for inaccuracies in forecasting is the lack of insight into the interactions that reps are having with prospects. Pipeline reviews typically rely on a rep’s personal account of where each deal stands and are often focused on the immediate deals in the forecast.
While the majority of this time is often spent trying to understand whether the deals forecasted to close are real, it should also be an opportunity to identify deals that are not forecasted to close, but should be.
Data-driven pipeline reviews that look further out into the future will give you a more accurate picture of where all active deals actually stand. This can directly increase the accuracy of your forecast and allow you to be proactive in identifying problems across your pipeline, picking out at-risk deals before they stall.
By leveraging Deal Intelligence in Gong to drive your pipeline reviews, your visibility will become clearer, and your coaching will become more effective.
Dig into your lost deals to see what went wrong
While losing a deal is always a frustrating experience, it can provide valuable insights to help you refine your strategy in the future to identify and mitigate risk.
Conducting a lost deal analysis helps you uncover risk indicators now, so they don’t threaten to derail future deals. This type of analysis is most effective when you look at the entire deal history, from pre-planning all the way through negotiation.
Was there consistent back and forth communication throughout the deal cycle? Was your rep multithreaded with actual decision makers? How did they handle objections as they arose?
These are just a few of the data points that can help you identify when and why a deal may have been negatively impacted. Hindsight is 20/20, right? Dig into your historical deal data to help you take informed action on future deals.
Ready to put these best practices and more into action?
For step-by-step instructions to help you immediately impact your forecasting accuracy, follow our recipe: Recipe: Cross check your team's forecast.