Analytics

ANALYSIS

Chance Favors the Prepared Mind: The Science of Sales Intel

In the Aberdeen benchmark report “Sales Intelligence: Preparing for Smarter Selling” (February, 2010), the research among 528 end-user sales organizations revealed that the most frequently used delivery models for sales intelligence were limited to remarkably traditional, if not predictable, applications: email, search engines, CRM/SFA tools and spreadsheets.

Paid access to secure information sources, a natural fit for sales intelligence product marketing, logged in at only 30 percent of all users, in fifth place in terms of end-user popularity.

However, the Best-in-Class survey respondents (companies with the highest team quota attainment and reduction of sales cycle) placed far more emphasis than Industry Average and Laggard firms on an automated integration with the CRM/SFA deployment, and also on the less-used third-party technology.

Push and Pull

These differentials, in fact, were supported by the trends identified in the research paper, which explores the extent to which organizations would “push” or “pull” their sales intelligence on behalf of their sellers.

While the aggregate survey data initially seemed to imply that “push” approaches were not particularly popular, closer analysis of the data from this research revealed trends that differentiated the Best-in-Class from other companies.

While most companies shied away from the apparent efficiencies to be gained by “push” methodologies, the top-performing organizations far out-paced them in their use of automated sales intelligence deliverables.

Business Context

Aberdeen’s 2011 Sales Intelligence research will determine to what extent the top-performing sales organizations have led the way in using smarter, more automated and user-friendly ways to filter only the most relevant data to their teams, while erecting effective barriers to keep the flood of unnecessary, irrelevant and time-consuming chatter away from quota-carrying staff.

If we accept and hope to reconcile both the traditional maxims that “time is of the essence,” as well as “knowledge is power,” then Louis Pasteur was correct in asserting that “chance favors the prepared mind.” With the right strategy and technology supporting sales intelligence deployments, sales teams can hope to hit their 2011 more effectively by collecting and using exactly — and only — the data they need to succeed.

From the end user’s perspective, the key benefits of sales intelligence are the opportunity to reduce the amount of time sales representatives spend searching for relevant, accomplishing improvements in:

  • Corporate top-line revenue growth
  • Team attainment of sales quota
  • Customer retention
  • Up-sell or cross-sell efficiency

This upcoming research will show that in order to improve sales productivity through third-party information augmentation and processing, companies must blend a combination of strategic actions and technologies to:

  • Automate the flow of externally sourced intelligence that is relevant to sales.
  • Improve the quality and quantity of leads in the sales pipeline in order to maximize sales rep selling time.
  • Identify high-value prospects through trigger events such as new product announcements, office openings or executive appointments, prompting more focused and successful quota attainment.
  • Improve sales reps’ knowledge of their territory, industry and accounts so they can hold more educated and consultative conversations with their prospects and customers.
  • Track prospect engagement (email click-throughs, website visits, etc.) to more accurately identify potential buying sign activity among prospective customers.
  • Unify customer information gathered through multiple and disparate “customer touch points” to better up- and cross-sell into existing accounts.

Peter Ostrow is research director of sales effectiveness at the Aberdeen Group. Readers interested in taking Aberdeen's survey for this upcoming research will gain access to the research results upon publishing of the final benchmark report after June 1, 2010.

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