Social Selling 2.0: Big Data Just in Time

We’ve all seen the statistics—B2B sales and marketing professionals are at a greater disadvantage today than they’ve ever been at any other time in history. Their buyers make purchasing decisions before they even have a chance to call, they spend far too much time researching accounts, and traditional channels like email and phone get less attention than the Yellow Pages.

So it comes as no surprise that the concept of social selling has created quite a buzz as the potential savior of sales and marketing pros everywhere. But while social media should certainly play a key role in the modern B2B sales process, social alone won’t solve all the woes of today’s sellers.

Build trust

Smart sellers understand that social channels are ideal outlets for building credibility in their industries. They can share articles relevant to their solution, join special interest groups, and attract followers and connections through that process. In the old days, sellers would bring their Rolodex from company to company—now they bring their LinkedIn network.

Engage in relevant conversations

Social channels are also great for monitoring key trends, announcements, and conversations that a seller knows are relevant to the solutions he or she pitches. And LinkedIn groups are constantly connecting like-minded buyers around roles or business problems that sellers can tap into. Once established as a trusted member in a group, a seller can engage in highly relevant social conversations with top prospects, helping to influence their purchasing decisions.

Enter Big Data

But social selling also comes with its own set of challenges. LinkedIn, a favorite network of business professionals, now has over 200 million users—and hundreds of millions of Tweets cross the Web every day. These volumes make it extremely difficult to sift through all the noise to find relevant conversations. Additionally, social users often blend their personal and professional personas, making it even more difficult to determine their actual needs. Lastly, social selling usually relies on a “snapshot” in time, meaning only the most recent posts, tweets, or comments bubble to the top.

Despite all of its promise, social selling can actually feel a lot like hunting for a needle in a haystack. The reality is that social media is only one piece of a much larger puzzle. A company or a prospective buyer might give subtle hints that they are in the market for a solution, but when combined with other information such as public records, announcements, or trends, social data can offer a far more complete picture. A prospect that seemed vaguely interested at first glance might emerge as a really hot buyer with an immediate need.

Secondly, social needs to be tracked within the context of time. Seeing that a company posted several new job listings for a key role might be interesting, but knowing the hiring rate has tripled in the past month offers real insight. Or the fact that a company’s posts about a given topic have doubled in the past month might reveal a lot more than a single relevant nugget.

Social selling is part of the modern sales process, and successful sales organizations are much more likely to adopt tools and best practices that include social. But to mine the true value of social data, it must be combined with all the other information you can assemble about a prospective buyer, tracked over time to identify key trends and buying signals that paint a complete picture.  New Big Data tools can do just that.

Rob Bois is the director of product marketing at Lattice Engines where he is responsible for strategy and positioning for the company’s Big Data sales and marketing platform. Prior to Lattice, Rob held product marketing roles at Eloqua and IBM and also served as a research director for the CRM practice at AMR Research (now Gartner Research).

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