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Sales analytics: Apply the Moneyball approach in 2014

Generating sales revenue is tough enough in today's global economy. Fortunately, sales analytics can provide a much-needed boost.

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“Sales force automation and CRM systems are creating vast amounts of valuable data. And organizations are finding new and innovative ways to mine this information to analyze markets, reward customers, and anticipate trends.”

Michael Lewis’ book Moneyball: The Art of Winning an Unfair Game illustrated how replacing traditional baseball statistics with newer measurements helped build a winning team. Similarly, data analytics is creating a new world for sales teams in which age-old metrics such as “revenue” are no longer enough. Sales force automation and CRM systems are creating vast amounts of valuable data. And organizations are finding new and innovative ways to mine this information to analyze markets, reward customers, and anticipate trends. Plan to make 2014 the year that you do the same.

Becoming a data-driven sales organization is not easy, however. You need to focus on operational excellence, flawless execution, and substantial infrastructure. Fortunately, there are steps you can take to ease the process of introducing sales analytics to your organization. Here are the top four considerations for building a data-driven sales force:

  1. Consider corporate objectives. These days, there’s no shortage of metrics being used to gauge sales performance. The trick, however, is ensuring that the metrics you choose align with your organization’s corporate goals. For example, a start-up software company might base success on the percentage of demonstrations resulting in sales. An established manufacturer, on the other hand, may look to volume of deals or lead-to-customer conversion rates for strategic direction. Whatever the case, make sure chosen metrics reflect corporate objectives.
  2. Check your odometer for pipeline velocity. Sales teams are terrific at reporting how many deals are currently in the works and the value of these qualified opportunities. Unfortunately, many fail to evaluate the time required to turn these qualified opportunities into closed deals. Savvy sales reps take the time to calculate pipeline velocity. By analyzing when revenue is expected to come in, which opportunities are moving seamlessly, and where bottlenecks exist, an organization can better predict both short-term and future sales.
  3. Establish benchmarks. Data can reveal how many new customers were acquired last month, where they reside, and how much they are likely to spend in the next 30 days. But without clear benchmarks, key information can be missed. Compare findings, such as customers acquired, with data extracted from market research or third-party reports. It can paint a more comprehensive picture of a sales organization’s performance.
  4. Become a master of your data. From CRM systems to sales force automation tools, there are countless sources of valuable data to be analyzed to improve sales performance. Invest in your data to be sure you are getting the best analysis possible. Find and remove inconsistencies and duplicates from mission-critical data across these disparate systems. The result is a holistic and carefully integrated view of sales force activity and customer behavior. With this single version of the truth, sales reps can move beyond revenue to a new generation of metrics for improved sales performance.

For more insight, read Perspectives, the Informatica blog, to see how sales analytics can ignite a more successful product launch.

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Citrix uses Informatica solutions to gain complete customer insight on all products