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Bringing Science to the Art of Sales
Seven principles for boosting business through analytics.
For the rest of the August 2012 issue of CRM magazine please click here
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In today's market, companies can ill afford a poorly performing sales organization. Taking a scientific approach by applying analytics across the sales process can augment a sales force's experience, judgment, and intuition and help create more effective, fact-based decision-making.

Analytics as part of the sales division is still in its infancy. The good news is that the last decade has ushered in widespread enterprise resource planning, CRM, and sales opportunity management systems—all improving the availability and quality of sales and sales-related data for analytics.

Accenture research highlights seven principles companies should consider when introducing sales analytics. Adhering to these will help ensure that new analytical insights result in meaningful gains.

Find your starting point. The first step is to decide how to apply analytics across the end-to-end sales process. Focus on introducing analytics into one or two functions.

Analytics are successful only if acted upon, and that means connecting data to decision-making. A good success story will help win over critics. Solid evidence will prove how making fact-based decisions will strengthen the business.

Don't turn sales reps into number crunchers. Most sales organizations have analyzed how salespeople divide their time among various job functions. The results are depressing—actual time spent with customers is extremely low.

Selling based on facts and insights is a critical skill and will become dramatically more important. Rather than asking your sales team to chase those facts and insights themselves, offer a good support function.

Support analytics. A company already engaging in analytics may have an analytics support group or analytics center of excellence with statisticians and data management experts. Alternatively, a company may have some form of sales operations or sales capability function. Housing the sales analytics support team within these areas can be a good place to start, provided there is a good base of talent on which to build.

No matter how far along an organization is in developing its sales analytics capabilities, it is important to understand the requirements of sales analytics. A sales analytics initiative should not place extra burdens on the sales force. Analytical insights must be processed and packaged before being handed over to the salesperson.

Embed analytics into strategies and processes. Analytics is not extraneous. Analytics enables a specific step that salespeople should take as part of the selling process. If the salesperson is expected to weave analytical insights into the conversation with a customer and use data to support this conversation, create materials he can take to the customer with minimal rework.

Foster an analytics culture. The sales subculture of many companies may consider analytics as somewhat alien. In that case, sales leadership should encourage the acceptance of analytics and foster a fact-based culture.

Ask for facts to back up analytical assertions. This will help the broader sales organization understand that leadership is serious. Sales leadership can also reward the use of analytics, communicate success stories, and ensure that salespeople understand their changing roles.

Don't let lack of data discourage you. Some sales leaders believe their companies have insufficient data to make a solid push into analytics. Sales analytics doesn't necessarily require mining terabytes of customer data. In some cases, the analytical process creates its own data. Some talent management analytics use a survey to collect detailed data on top sales performers along the dimensions of personality, behavior, and competencies. This helps more precisely identify factors that drive top performance.

Look beyond today. While finding the right starting point is critical, it is equally important to develop a future vision for sales analytics.

This vision could include a decision-making framework on how to incorporate analytical insights into the day-to-day business. It could include a type of analytics Accenture calls "market sensing," designed to monitor and provide insights on business volatility by processing large chunks of unstructured data and spotting patterns in that data.

The process for applying analytics to sales can be daunting. But adhering to these principles will help assure that new analytical insights result in meaningful performance gains, furthering the organization's push toward high performance.


Jan Van der Linden is a senior executive in Accenture's sales transformation practice, where he advises clients on customer strategy, analytics, technology, and sales performance issues. Naveen Jain is global lead for Accenture's sales transformation practice.

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