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C9 Sharpens Forecast with New Features
User polls combined with machine learning capabilities give sales reps a better view into the future of their deals.
Posted Apr 30, 2015
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C9, a provider of predictive sales and marketing tools, has introduced additions to its C9 Forecast to help companies make more accurate sales forecasts—and save time in doing so.

The solution aims to equip businesses with sharper forecasting tools, potentially saving them hundreds of hours of work. In aggregating data from various sources and placing it in one system, it eliminates the tendency to leave valuable information stranded in spreadsheets. The program's "Pivot Forecast" function can be customized for various users within an organization; aside from salespeople, product managers can use it, for instance, to gauge the success of their products in different markets or regions. A major benefit of the solution, the company says, is to keep all parts of an organization updated and collaborating toward a better understanding of their influence on the bottom line.

The new features allow feedback from sales reps and Forecast's machine learning to work together. "There will always be a human element at play in sales forecasting that technology can't replace," Justin Shriber, vice president of products at C9, says. "But we're not setting out to replace that. Think about it like GPS. C9 wants to be the GPS of sales forecasting. The technology doesn't replace the driver, but helps him get where he's going. We want to help salespeople do their jobs better and make better predictions about deals."

"One of the things we often mess up is either thinking that machines can do anything or that they can't do much," says Denis Pombriant, president of the Beagle Research Group. "Take a look at The Second Machine Age—it discusses how we need to get better at mixing the raw horsepower of machines with the intuitive and interpersonal skills of people. I think C9 has, for a while now, been doing this with great results."

With the new version of Forecast, reps can vote on which deals or opportunities in the pipeline are the most promising or likely to lead to closes. Based on that data, the solution assigns scores to each deal to determine which ones are most likely to be fruitful down the line and how much revenue they'll generate. The Machine Forecasting feature takes the scores generated in these processes and places them alongside other factors that might influence outcomes, including economic trends and seasonality, to give businesses a better idea of what to expect.

"Most companies make top-line forecasts, which don't really provide a specific view of individual deals," Shriber says. Forecast, in contrast, brings forecasting down to the opportunity level, he adds.

Bob Kruzner, director of sales operations at ServiceMax, a Forecast client, said in a statement that his team has gotten a greater understanding of the specifics of each deal behind the forecast numbers, which has allowed him to save time on submitting forecasts and given management a clearer picture of where its sales reps need assistance.

 Among C9's other notable clients are Yahoo, Thomson Reuters, and LinkedIn.

The next step for such products, suggests Pombriant, is to combine marketing automation forecast tools with sales capabilities. "The two sides need to be fused in an end-to-end process that is still being born," he says.

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