The 5 Big Data Insights For Effective Social Selling

Christian Lowe Blog Post - 02/06/2015 Big Data, Data Mining and Predictive Analytics are no longer just buzz words or ephemeral trends. The wealth of data that is collected by companies is no longer just available to the "nerds" in the back office developing complex codes/algorithms to generate predictive models for the marketing teams. The cost to house vast amounts of data have dramatically come down dramatically as technological innovations have enabled even the layperson to access clean/actionable analytical insights into underlying trends contained within the sea of data. With this exciting age of increased access to deep insight into customer behavior and overal econometric trends, it is extremely important that marketers acknowledge and take advantage of the insight that can be gained. A similar trend that has developped almost contemporaneously has been the importance of Social Networking and its impact on how companies can reach customers as well as to gain insight into customer and their networks' preferences. The blending of analytics with social networking provides marketers with the ability to accurately gauge in real-time what are consumer preferences, what are emerging trends in buying behaviors and to predict the net lift a successful digital marketing campaign can have. A prime example of the impact of using analytics with social networking is when Starbucks decided to discontinue is popular holiday Pumpkin latte. This decision proved to be a very poor strategy as customers voiced their outrage. Traditionally, prior to social media and analytics, Starbucks may not have observed the impact of a horrible straegic decision for at least a month when monthly sales figures were released. Fortunately, Starbucks, armed with a strong analytics and social team was able to find out almost real-time through monitoring social networking sites (i.e. Twitter, Instagram, and Faceboook) that the decision to discontinue the Pumpkin latte was overwhelming unpopular and thus was able to reverse course almost immediately, thus saving potentially millions of lost revenue. A good article that highlights some of the key insights into using Big Data with Social Networking is below: http://www.business2community.com/social-selling/5-insights-increase-revenue-big-data-social-selling-infographic-01026894 The 5 Big Data Insights For Effective Social Selling While there is no limit to the breadth and granularity of information that can be gleaned from Big Data marketing analytics, marketers should at a minimum be looking to gain the following insights from data listening: 1.Who is buying: Buyers come in many shapes and sizes but generally can be boiled down to comprehensible “buyer personas” that marketing and sales teams can watch for, understand and serve. 2.Buyer sentiment: Find out what the various buyer personas are saying about your brand and products (and those of your competitors!) 3.What your buyers want: Find out what needs and products are trending and what buyers are asking for and complaining about online. 4.What information sources they use: Analyze data to see which sources of information various buyer personas turn to, and which information is most influential upon their purchase decisions. 5.The ‘Buyer’s Journey’: Perhaps more important than any of the other insights that marketers can deliver to sales is identification of the unique steps a buyer takes from inception to purchase. Knowing how buyers gather information, establish options and make decisions is the critical context that makes social selling programs tick. Utilizing the five insights gathered from Big Data and Social Listening, marketing departments can now arm sales with the information, attitudes and interests of each buyer persona and provide highly relevant content that is in line with these insights. The CMO should engage the VP of Sales to develop programs by which sales reps learn how, where and when to connect with buyers and prospects on LinkedIn, Twitter and other social media marketing channels. The ability for sales reps to reach buyers in a personalized way with the right content, in the right context, at the right moment is the secret sauce of sales. By listening to data, analyzing buyer behavior for key insights and arming sales teams with highly relevant information marketers today are in a unique position to reinvigorate the value that sales teams offer in the Big Data era.