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New C9 Forecast Solution Bridges Man and Machine

C9_LogoC9 announced the addition of a new layer of intelligence to its flagship product, C9 Forecast.  The new solution is the first to poll the sales organization on specific deals they believe will close and then uses machine learning to project total revenue.  The composite forecast blends both the objectivity of data science with the experiential knowledge of the field to increase accuracy by two to three times over conventional forecasting approaches.

Historically, relying on rep-level input to build a forecast has been a two-edged sword,” said Justin Shriber, head of products at C9.  “Sales agents have firsthand knowledge of deals and where they are in the sales process.  That said, the experience they rely on to gauge their propensity to close can be subjective. In our latest release, we’ve delivered a product that blends the perspective of sales professionals with the unbiased insights that predictive analytics can deliver.  Essentially, we’re crowdsourcing input from the field and using machine learning to turn it into an extremely reliable number.”

The newest generation of C9 Forecast is based on a combination of features that allow organizations to quickly move from a deal-level perspective to an aggregate view of where the quarter will land.

  • Deal-level Polling—Reps have the ability to vote on the specific deals they expect will close by scanning the complete set of opportunities in the pipeline and flagging those that are most promising.
  • Opportunity Scoring—Machine learning assigns a “close” probability to each deal, taking into account polling data from reps as well as hundreds of other signals that point to a win vs. loss outcome.
  • Machine Forecasting—Predictive models generate an aggregated forecast number by combining opportunity scores with data related to seasonality and macro-economic trends.  For companies with short sales cycles, these models account for the deals currently in the pipeline as well as the deals that will ultimately close but have not yet surfaced.

In our business, delivering a top line forecast number isn’t enough,” said Bob Kruzner, Director of Sales Operations at ServiceMax.  “Our managers and executives need to know the specific deals that sit behind the forecast numbers.  By taking the forecast to the opportunity level, C9 will give us a very clear sense of the different opportunity values we track for our business and how solid the numbers are.  C9 is core to our pipeline management and forecasting process.  Sales managers are spending less time submitting their forecast, affording more time to focus on helping their reps close deals.   The forward-looking insights have enlightened sales management where coaching is needed or deals are at risk, ultimately allowing us to dial in on exactly where we’re going to end up.”

C9 Forecast overcomes major challenges associated with spreadsheet-driven forecast processes.  Especially for organizations with high numbers of transactions, tracking deal-level expectations on a rep-by-rep basis quickly becomes unwieldy.  And few organizations can invest the resources necessary to quickly and systematically analyze and aggregate the data.   That’s why many companies have decided not to capture rep-level and deal-level input.  The result is a less accurate forecast that is disconnected from the transactions that ultimately drive it.

Unfortunately, even though companies have the raw data to produce great forecasts, it’s locked away in notebooks and spreadsheets.  That’s a problem technology can solve,” said Rajit Joseph, head of product management at C9.  “Our latest forecasting service creates a scalable way to determine the specific deals that will drive the forecast.  That leads to major improvements in everything from the way companies allocate pre- and post-sales resources to how they manage discounts.  Ultimately, it creates greater revenue transparency, accelerates top line growth and improves margins.”

 

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