Yahoo Sees Crystal-Clear Sales Forecasts with C9 Analytics

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Yahoo counts on close to 1,000 salespeople, account managers, and sales leaders to sell advertising that accounts for nearly all the revenue of the Internet company, which has a network of Web sites on topics such as news, sports, and finance, as well as services such as Yahoo Mail. But when it came to forecasting advertising revenue, the company faltered.

"Forecasting was a weekly disaster here," remembers Patrick O'Leary, senior director of sales operations and effectiveness. Accuracy was questionable, with different salespeople sometimes using numbers pulled from the booking information at different times. "We had the same conversation each week, arguing about the numbers," O'Leary says.

After trying both a homegrown forecasting solution and an Excel version, in June 2012, the Yahoo sales operation team tested C9, which provides pipeline visibility and improved forecasting. Within three weeks, it had plans to roll it out across its North American operations.

C9's biggest asset wasn't providing more precise forecasts, but rather making it dramatically easier for salespeople to do their jobs. Before C9, if a forecast changed by $500,000 from one week to the next, it would take an "archaeological dig" to find out why, O'Leary says. With C9, a graph and list displays all the changes in the past week, making it easy to pinpoint the root cause of any revenue difference.

Implementing C9 led to a cultural shift as well. "People started talking about the size and shape of the pipeline in the forecast," O'Leary says, enabling them to step back and analyze the forecast instead of just creating it. Individual salespeople saved two hours a week, and managers saved at least four hours a week. That added up to five full-time-equivalent positions on the sales side and one on the management side.

C9 also has applications that help benchmark results against past performance. Using historical and predictive analysis, C9 will analyze the pipeline against historical data. Based on the activity in their pipeline, salespeople can see if they're likely to hit their quotas. By analyzing metrics such as time since last touch and changes in close dates, C9 will do a risk assessment of the deal. Sales reps know how big their pipeline needs to be in order to make their numbers, or can compare metrics against a previous quarter to analyze their performance.

Sales leaders also have greater visibility into their team's performance. Using a treelike function, they can drill down into each region, to individual salespeople. "We're coaching managers to use this information to call people out," O'Leary explains. "If someone says, 'We've got another 500K coming in next week, we can now say, 'You've been working on that deal 120 days when the average is thirty days. What conversation did you have that made you think that?'"

Two years later, Yahoo has expanded C9's use. Implementation into Asian markets started in the fourth quarter of 2013, and implementation into Yahoo's European sales force began in the first quarter of 2014.

While many technology tools make managers happy but sap the time of busy salespeople, C9 has been embraced by the sales team. One salesperson told O'Leary, "This is the best tool we've implemented here in five years."

"Salesforce.com can be a necessary evil to salespeople, but C9 makes their job better," O'Leary says.

The Payoff

Using C9 analytics for sales forecasts, Yahoo's sales organization was able to:

  • save 2 hours a week per rep;
  • save 4 hours a week for managers; and
  • gain 5 (people) hours of full-time-equivalent capacity on the selling side and 1 full-time-equivalent on the management side.

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