Sales intelligence (SI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of information to help salespeople keep up to date with clients, prospect data and drive business. In addition to providing metrics for win-loss and sales confidence [1], SI can present contextually relevant customer and product information.
The 2008 survey of 300 companies by the Aberdeen Group [2] show that the recent economic downturn has lengthened traditional sales cycles. As businesses have been forced to reduce spending, sales representatives have been challenged to meet quotas. Top performing companies have implemented sales intelligence programs to improve the quality and quantity of sales leads. SI contextualizes opportunities by providing relevant industry, corporate and personal information. Frequently SI's fact-based information is integrated or includes Customer Relationship Management (CRM).
Although some aspects of sales intelligence overlaps business intelligence (BI), SI is specifically designed for the use of salespeople and sales managers. Unlike customer relationship management (CRM) and traditional business intelligence (BI) applications, SI provides real-time analysis of current sales data and assists with suggesting and delivering actionable, relevant information.
Sales intelligence solutions are predominantly designed for companies in the manufacturing, distribution and wholesale sectors. These are highly competitive markets, where volumes are high, margins are low. (SI) solutions provide unique insight into customer buying patterns. By automatically analysing and evaluating these patterns, Sales Intelligence pro-actively identifies and delivers up-sell, cross-sell and switch-sell opportunities.
The sales Intelligence market is currently experiencing two major changes that raise radical moves in the sector : the distribution model and the data sources.
Sales intelligence providers have historically been industry-centric with custom designed solutions to centralize and consolidate various customer data across the enterprises. Solutions were either delivered as tailor-made system or as isolated applications. With the emergence of SaaS (software as a service) in the cloud CRM solutions, sales intelligence providers are forced to migrate their solutions in the cloud, with deep interconnections with CRM solutions. Standalone client/server applications are less considered and struggle to maintain their market shares with vertical solutions.
The second change is related to data sources : social networks' and social media data have proven to be more effective than traditional sources to offer 360° comprehension of customers. With the openness of Facebook, Google or Linkedin databases (through their open APIs), the new providers offer constantly updates profile information and contact relationships. A new form of sales intelligence has emerged, encompassing social leads, sales influencers, partnership tactics, etc.