Inserting intelligence into Sales Processes

Sales-IntelligenceSales organizations have always been under pressure to uncover new opportunities, hit sales targets, and maximize productivity. But in today’s new age of the customer—where customers are better informed than ever and excellent service often trumps a lower price—sales goals cannot be reached simply through hard work. Sales teams need information that enables them to understand customers better and anticipate their needs.

With more knowledgeable customers, time pressures, and global competition, sales organizations are seeking ways to generate these types of insights to improve their key processes, including lead management, opportunity management, forecasting, account knowledge, upsell/cross-sell recommendations, and automated alerts about high-value prospects.

To gain these much-needed insights, leading sales organizations are turning to a new generation of analytics tools that incorporate new data sources, visualization techniques, and algorithms to reinvent the selling process. These tools allow companies to tap into unstructured sources of information, such as customer interactions on the web, as well as rich stores of historical data to better understand customers and prospects. The resulting 360-degree view, teamed with predictive analytics, is helping salespeople and sales managers zero in on the most profitable opportunities to pursue—and avoid ones that are likely to flame out.

One of the most recent developments in B-to-B analytics is tapping into new data sources and combining that information with other data systems to gain a 360-degree customer view. Currently, many CRM systems that are used to identify sales opportunities are limited to information about leads, contacts, and accounts.  However, with customers increasingly accessing information on the web before even talking to a salesperson, companies can dramatically improve their lead funnel by combining a wide range of information about customer activities (recent service calls, ordering activities, etc.) with insights into what their customers are clicking on. This can include which pages they visited or documents they downloaded from the company’s web site, as well as social media activity on sites such as Twitter and LinkedIn.

Sales intelligence provides new levels of information richness, usability, and reach to sales professionals throughout the enterprise. All users, from sales executives to front-line sales representatives, get up-to-the-moment, complete, and in-context sales insight—insight that is personalized, relevant, and actionable. It helps firms take faster and more informed decisions that help the sales organization compete more effectively, lower sales costs, and achieve better results. In addition, to help organizations achieve maximum value from their CRM sales force automation implementations.

Using analytics tools, salespeople can gain that intelligence by asking questions such as:

  •  Which are the best products to offer a particular customer or prospect?
  •  What similar customers can I sell to?
  •  What is the potential revenue impact of a specific deal—and how can I add products to grow the deal?
  •  What is the estimated sales cycle for this deal based on what has happened in the past?

The percentage of sales reps who make quota and the win rate of forecasted sales opportunities are too low in many companies, while time spent chasing the wrong opportunities and non-selling activities is too high. Why? A recent study by CSO Insights found that adoption of sales automation remains surprisingly low and that even the most well-known sales solutions fail to deliver on their promise.

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