By Ran Shaul
Everyone is talking about big data and social influence as the new Promised Land, but finding and proving the true value is a challenge. Marketing teams often can’t generate the expected sales that marketing automation, social media, loyalty, etc. programs/tools have promised.
Making “Social Marketing” Meaningful
Meaningful relationships with the power to turn prospects into customers and inactive customers into buyers are rooted in offline connections, not online interactions. Anyone can have 500+ Facebook friends these days and of course some people have the time to comment, like, repost, share, tweet, etc. every product they purchase or store they visit. That doesn’t mean anyone actually listens or is driven to act.
Socializing data—combining big data techniques with factual evidence of social influence—empowers marketers to map meaningful relationships between people in a database to influence purchase decisions and enhance brand loyalty rather than simply relying on Facebook friends and Twitter followers. Real-world relationships tend to involve more in-depth interactions, a heightened level of trust and intense similarities—be it current interests, hobbies, activities, salaries, education level, stage of life, etc. Combined, these factors make real-world relationships much more influential when it comes to people’s buying decisions than online social circles.
This is especially true based on specific topics/products – for instance, there may be one person who someone turns to for advice on a new car purchase and another upon whom they rely for direction on anything/everything child related. Add to that the ability to see—based on past transactional history and sales data—who tends to create a domino effect of purchasing activity, and marketers are suddenly able to better determine the right audience, channel and offer to reach and convert.
At the end of the day, people buy what their friends buy. Finding connections helps marketers better reach potential buyers who are much more likely to act because their friends have already done so.
Marketers need to tap a social graph that maps out powerful, real-word relationships based on concrete bonds (e.g., family, coworkers, college roommates, neighbors, teammates) to get more from their existing prospect and customer data.
Being able to pinpoint and target “purchase influencers” thanks to advances in big data and social graphing sounds great, but what are the real business stories? Industry innovators are already reaping the rewards of socializing data to drive sales. Let’s take a look at a few prime examples:
- The credit card industry is a good place to start. While marketers have relied on traditional prospecting models and direct marketing-based acquisition for years, they’ve seen the same meager response rate across the board. No one credit card company could really claim to be breaking through the noise and achieving stellar conversion. However, by employing new influence analytics to those same campaigns, credit card companies are now able to triple the conversion rate by targeting purchase influencers and their real-world connections.
- High-end consumer products are also able to push previous boundaries. We’ve found that the higher the price, the higher the influence a prospect/customer can have on their social circle. For instance, if one of your prospect’s influential friends purchases a high-end TV, they and the rest of their circle are five times more likely to purchase that same TV within an eight-week window as the buyer justifies their big, new purchase by actively advocating its finer points. In addition, while close friends may not rush out to buy the same, exact dress, we’ve seen that purchase influence is most notable for high-end designers/retailers when it comes to their collection. Buyers are more likely to shop at the same stores and buy from the same collection as their social circle.
- There’s also a negative side of influence – which, in some cases, can be more powerful than the positive influence. Telecom and utilities are the prime example here. We’ve found a chain reaction in social graphs – if an influencer cancels a contract or switches providers, their social circle is five to six times more likely to do the same either immediately or at the end of their contract.
Combining the power of big data with the value of the social graph, marketers are realizing a two to five times boost in ROI. It is the next logical step in an ongoing evolution, and it is already changing the game in acquisition, cross-sell and retention across a variety of industries.
Ran Shaul is founder and COO of Pursway.