Better Forecasts: Using Activity Data for Predictive Forecasting

BY Zack Cronin

Zack Cronin

How to create your most accurate forecasts ever... advice from the experts

BoostUp CEO Sharad Verma recently hosted an all-start panel of revenue operations experts: Channing Ferrer, VP of Sales Operations and Strategy at Hubspot,
Jake Gertjan Hofwegen, VP of Global Sales Operations & Strategy at Nutanix, and Brian McTeague, VP of Revenue Operations at FastSpring. The group covered how sales activity data is transforming forecasting, and how to create the most accurate forecast possible.

You can watch the roundtable in full, below

Which forecasting model is best for you?

As for the best forecasting model, the panelists agree that each organization is unique and that teams need to choose the model that best fits their business strategy.

For example, Brian says that if you have a very predictable and constant revenue stream, a run rate model is very effective. A more volatile business will rely much more on both seller input and sales activity metrics to produce an accurate forecast.

Regardless of the forecasting methods, you must drive your predictions with data to gain the most accurate picture of what the future holds. You should forecast as early and as often as possible within a given timeframe so you can see how you trend against your goals, and so you can make adjustments from the start.

Jake adds that he likes to run his forecasts each week, starting from the top-down, with each level of the organization having their forecast due each day.

"The more granular you can be, the better you can track the business and ensure it goes where you want it to go." - Channing Ferrer

This provides teams with the ability to reconcile leadership's forecast with that of the front-line managers and reps and gain an accurate understanding of expectations. Within this process, he likes to use deal based forecasts. Frequent, deal-based forecasts also facilitate internal deal-based sales discussions within your organization.

Channing likes to involve humans in his forecasts on two levels. First, he uses models that account for what sellers feel about their deals and reconciles that with what data shows and finds that that provides the most accurate forecast.

How do you confirm a forecast and guarantee its accuracy?

With all of the data and metrics available today, it can be difficult to decide which is the most accurate, and which to use to confirm the exactness of the sales forecast.

Jake likes to use run rate metrics, and even create competitions between the CRO and RevOps team to see who can get the closest to make forecasting more fun.

When it comes to confirming the accuracy of a forecast, Brian again believes each business should look at the metrics that correlate to success within their specific organization. He suggests KPIs like a weighted forecast, stage metrics, recency of deal, or activity against the deal.

Brian looks at each salesperson's commit forecast, as well as "de-risking" actions made on the deal, like an ROI calculator or a reference call.

Sharad adds that indicators derived from sales rep behavior are extremely useful. You can use activity metrics to determine the outcome of a deal, but you must have consistent and accurate input data, which can only be achieved through automated data collection. The key is that the automated data is attributed to the correct rep, contact, and deal, which many revenue intelligence platforms struggle with.

What should you automate?

In short, teams now must automate the collection of all sales activity data. As Channing explains, "I would rather have them on the phone with a customer than entering information into the CRM." He admits there are times when a rep does have to enter information.

"You don't want to make your Sales Rep a Salesforce Admin... Automate as much as you can." - Jake Gertjan Hofwegen

Like when they are starting the MEDDICC process and are asking for discovery information. But, all sales activities, what occurred within them, and the context in which they took place, must be automated for use in forecasting. This automation also ensures that the data is as accurate as possible, as human error is eliminated.

Sharad adds that you cannot just capture activity, that you must also associate the collected data correctly. If data is correlated accurately, only then can you open the door to true sales data intelligence. You can not only analyze the activities that took place but the lack of activity that should have happened.

How can organizations reduce the drag on front-line managers and enable them to be more productive?

Guided-Selling is quickly becoming the next must-have in sales organizations. Brian says that the key to guided selling is that it cannot be controlling. It must be helpful to reps, for example, if a salesperson has not sent a key email, it should be able to alert them that they missed a step.

"We can now get buying indicators based on questions like: Are we talking with the right titles? Are the right people responding to emails or committing to meetings? Is the prospect committing more time as the deal progresses? Are you getting engagement in your sales process? Are you getting responses back? " - Sharad Verma

Channing recommends that tools be built on the best practices of top-performing reps. Rather than telling reps what to do, show them how the best-sellers are the most successful. Show them the data, and allow them to replicate it.

Data is Key

Ultimately, it comes down to your data. Your forecasts, their triangulation, and the decisions that you make from them will all be incorrect unless you fully trust your data. Teams today have access to a marketplace that is larger than ever, and full of automation and intelligence platforms that stand to transform organizational performance. It's time for companies to fulfill the needs of their modern sales teams with revenue intelligence.

"We try to find those ah-ha! moments involving activity... Like when high activity correlates with high performance. We look at when being more engaged in certain parts of the sales cycle leads to a win." - Brian McTeauge

BoostUp's View

In the modern age of digitized, remote selling, sales teams are faced with a new issue. How do you optimize for sales performance over a geographically distributed and disconnected workforce?

The answer is sales activity data collection and analysis. Teams must capture a complete record of every sales activity, who was involved, what happened within it, and the result. This data can then be analyzed for forecasting, to improve a sales team’s revenue attainment, and to enhance performance.

BoostUp.ai is the only out-of-the-box and end-to-end platform that drives data accuracy and the analytics necessary to extract true performance.

Its integrated sales intelligence solution brings call, contact, email, calendar, chat, business intelligence, and forecasting data into a single platform for maximum results.

Rather than relying on data collected by other tools, or reps, BoostUp automatically collects all sales data with the context that it occurred in. It analyzes these activities with AI for deal insights based on the context and sentiment of all engagement. This enables it to spot a lack of engagement to create signals for managers to coach more effectively and improve forecasting.

You can chat with us at demo@boostup.ai.