Predicting Profits

Big Data that Helps Sales People Find the Best Potential Customer
November 27, 2012, 6:19 PM ET
Rachael King

    In the Wall Street Journal article titled "Big Data that Helps Sales People Find the Best Potential Customer,"  Rachael King discusses companies overspending of time and energy on customers who are not profitable or worth the effort. 
     In order to minimize time put on the wrong customers, companies are investing more and more in predictive analytics. King uses the example of Startup Lattice Engines, a company which has pioneered the industry since its start in 2006. The company utilizes external and internal corporate systems to research customers behavior. 
    Further, King proclaimed: "The salesPRISM big data analytics platform integrates external information sources such as Experian, LexisNexis, public records and social media and internal databases including customer purchase history, customer service calls and Web site visits. After the product combines information from these sources, it uses predictive analytics – mathematical algorithms —  to identify behavioral and purchase patterns."

    Ultimately, by identifying the most valuable customers, companies can take the data and execute the information to benefit their sales, as well as, updating their talking points to fit customer needs.


In my opinion, I do not see why a company would not focus on predictive analytics. Lattice Engines, such as the one talked about in the article, allow easy tracking of consumers purchase patterns. Through sorting and analyzing deep background knowledge, the consumers are open to data analyze. The information discovered here and used properly aligns companies money to the right places. 

By aligning to the correct customers, companies will be more likely to be profitable. Therefore, I think that utilizing these engines will give companies a competitive advantage. 

Topics: sales, predictive analytics, lattice engines
WSJ ARTICLE LINK