You’re probably familiar with the popular saying, “Don’t count your chickens before they hatch,” which is essentially a warning not to count on something good happening before it actually comes to fruition. As people grow and mature, they typically learn that following this advice can save you serious disappointment and regret in the long run.
Enter sales forecasting, or the process of predicting future sales revenue over a given period of time. The necessity to “count your deals before they close” is in complete opposition of this life hack, and can be a major source of anxiety for sale leaders everywhere. With less than ⅓ of businesses classifying their sales forecasts as effective, it’s easy to see why many sales teams regard forecasting as a guessing game that they’re bound to lose.
But what if you could replace gut feelings and educated guesses with scientifically tested probabilities and processes? What if instead of making hopeful predictions, you could make well-researched hypotheses? Here are three proven ways you can stop stressing and start more accurately counting your proverbial chickens.
1. Give Your Scoring Strategy a Tune-Up
To help prioritize prospects and gauge their likeliness to convert, companies score leads based on criteria that they have determined signifies purchase intent, such as content downloads, website visits and much more. This is one way to lead score, but another method enables businesses to actively seek out and identify high-value prospects based on profile similarities with previously won deals.
For example, after analyzing your recent data, perhaps you discover that the CTO was the decision maker in nearly 65% of wins. In that case, it would make sense to score leads where CTOs are the main point of contact higher than others, as well as give them a higher win likelihood once they enter your pipe. You can also follow the same methodology for lost or unqualified deals: if 80% of deals where the CMO was the decision maker were lost, then score leads with this point of contact lower. The same goes for similarities in industry, company size, location – the list goes on.
Taking this smart lead scoring approach not only helps you be more sure that the leads you qualify will eventually turn into paying customers, but it also gives you real, data-driven evidence as to which deals you should count on to actually close and include in your forecast. For more insight into this strategy, check out this eBook: How to Eliminate Sales Forecasting Fallacies with a Data-Driven Approach.
2. Pay Closer Attention to Stage Duration
As any sales leader who has fallen short of his or her forecast knows, it’s not just about whether a deal closes, but about when it closes. Timing matters when it comes to forecasting, and while deals can sometimes encounter unforeseen roadblocks, having an intimate understanding of your stage duration can greatly improve your accuracy.
Stage duration refers to the amount of time each of your deals spends in a given stage of your sales pipeline, such as qualified, quote or close. Conducting a stage duration analysis as shown in the report below allows sales leaders to see more than just the average time deals spend in each stage and the pipeline as a whole. It also calculates the win likelihood of a deal based on the amount of time spent in a particular stage compared to deals that have been won.
Digging further into this information enables you to identify the types of deals that take longer to close than others, or are more likely to get stuck in a particular pipeline stage. This kind of information is highly valuable when it comes to knowing what deals to bank on and nailing that forecast.
3. Measure across Conversion Points
More often than not, very few metrics other than revenue are actually factored into the sales forecast, with less than 35% of organizations taking critical measures like deal volume into consideration. What’s more, even when these factors are considered, they are often measured in an isolated fashion. What good does it do your business to know how many marketing leads are accepted by sales if you can’t measure the impact this ultimately has on your bottom line?
Think of it this way: sales revenue is the cumulative result of each of the key conversion points within your sales pipeline. To accurately predict this number, your forecasting needs to consistently measure performance across these key conversion points over time, such as leads accepted, opportunities qualified, etc. And with access to a greater quantity and quality of data than ever before, businesses now have the ability to do just that using a new set of sales metrics called process measures.
Process measures are used to understand how leads and opportunities flow through your sales process and pipeline, giving you a more clear and accurate picture of expected revenue over time. With the ability to measure performance across each of these conversion points and see exactly how it ultimately affects sales revenue, businesses can create a much more accurate sales forecast.
Winner, Winner, Chicken Dinner
Sales forecasting doesn’t have to be a stressful endeavor. Sales leaders that are willing to follow strategies like those outlined above and take a scientific approach to measuring performance over time will reap the benefits. For more information around how you can you can begin understanding and utilizing the science of sales, download our free eBook, From Art to Science: 5 Steps to Predictable Sales Growth.