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HD Data Nestle Profit Declines as It Misses Sales Forecast

Deere Offers Soft Outlook after Sales Miss

EBay Forecast Misses Estimates as Marketplace Growth Stalls

As a tough economic environment appears to return, such news is becoming common.

Forecasting sales is a tough challenge and companies have long relied on teams of analysts crunching numbers in Excel to estimate forecasts. According to Sirius Decisions research, 79% of sales organizations miss their forecast by more than 10%.

To understand this frequent failure, let us look at how sales forecasting is traditionally done in companies:

  • Top-down forecasting – This method relies on historic trend analysis to arrive at a forecast. However, it fails to consider the health of the current pipeline or the quality of deals in your sales funnel.
  • Bottom-up forecasting – This method relies on subjective and biased deal-level probabilities provided by sales reps and managers. It aggregates deals in the pipeline to arrive at a forecast. This method does not account for deals that are not in your pipeline.

InsideSales.com, through its HD Forecast product, adopts a hybrid approach, combining both top-down and bottom-up, but more importantly uses predictive analytics to provide an accurate and reliable sales forecast.

Deal-level forecast predictions

Using advanced machine-learning techniques, InsideSales.com can predict the likelihood of winning a deal in your CRM with a high degree of accuracy.

Rather than relying on biased, rep-provided deal probabilities, or even a handful of deal attributes, the algorithms make use of thousands of data points.

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The algorithms adapt to emerging patterns in data, learning the nuances and changing circumstances of individual companies. This is made possible by a unique underlying temporal platform with version history capabilities – providing high-definition data for these sophisticated algorithms.

For example, they can quickly recalibrate themselves in response to a new product launch or a geographic expansion. As a result, predictions are always precise, even for the most dynamic businesses.

For every deal, two scores (values of 0-100) are produced:

  • Win score – Likelihood of winning a deal
  • Commit score – Likelihood of winning a deal in the current quarter

While “win score” can be used to prioritize deals to work on, “commit score” provides an objective and unbiased likelihood of winning the deal in the current quarter, making it a valuable deal-level forecast prediction.

Aggregated forecast predictions

While deal-level predictions are useful, they do not address the overarching challenge of predicting a company’s sales forecast.

Using “commit score” for deals in your company’s pipeline, you can calculate how much of your sales pipeline can be won in a given quarter.

Let us call this “winnable pipeline.”

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Predictive Forecasting

However, this alone falls short of being accurate in predicting a company’s forecast as there could be “unknown pipeline” as well.

There are a few reasons for this:

  • At any given time, there could be deals that open and close in the same quarter. These could be true “bluebirds” or simply “late entrant” deals with a short sales cycle.
  • Sales reps could be sandbagging by not tracking deals accurately in CRMs so that they can maximize their commissions or simply because they want to avoid management attention.
  • There could be seasonality in a company’s sales cycle, which could contribute to temporary spikes.

HD Forecast applies predictive forecasting methods to its high-definition versioned data to uncover such factors among other nuances to account for the “unknown pipeline” that can be won in the remainder of the quarter.

The resulting predicted forecast, which combines the “known pipeline” forecast and “unknown pipeline” forecast, provides a highly accurate prediction of a company’s forecast – which can double the forecast accuracy of sales teams.

Download this ebook to learn how to become a predictive sales organization.

Becoming a Predictive Sales Organization

Free eBook:Becoming a Predictive Sales Organization

Discover how data science can help you improve your sales forecasts and increase revenue.

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