B2B Beat: Predictive Marketing Technologies Are in Your Future
September 6, 2015
You can make the case that B2B sales and marketing have always been about trying to predict the future – primarily by identifying which prospects were most likely to make a purchase.
With its acquisition last week of Fliptop, a provider of predictive sales and marketing software, LinkedIn plans to help B2B sales teams and marketing departments get even better with their predictions. “As the worlds of online sales and marketing rapidly converge, we believe there are opportunities to leverage Fliptop’s technology to achieve our broader goal of creating the most effective B2B sales and marketing platform,” David Thacker, LinkedIn’s Vice President-Product, wrote in a blog post announcing the deal.
Thacker said that the Fliptop team and technology will be used “to help us accelerate our Sales Solutions product roadmap and make Sales Navigator even more effective.” But even though the focus of this acquisition is on sales, B2B marketers should take note: Predictive technology is in your future.
In the past, B2B marketers made predictions on who their prospects were by using demographics. Marketers acted on this demographic information by placing advertisements in magazines, on television, or in other media by making educated guesses on where their prospects’ eyeballs were aimed.
The same basic predictive principles moved to the digital world – but expanded beyond demographics to also include a prospect’s actions. In the case of search, for instance, a prospect using keywords such as “centrifugal pump” tended to predict an interest in that product and made pump manufacturers interested in paying to advertise on search engines for those particular keywords.
Email, too, has predictive qualities related to prospects’ actions – their open rates and click-through rates. Based on prospects’ interactions with email, a marketer can predict the relative sales readiness of prospects and chose to, for instance, place them in a nurture stream or hand them over to sales as marketing qualified leads.
As Russell Glass and I wrote in “The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits,” predictive technologies, such as those developed by Fliptop, have taken the ability to identify prospects to a new level. “Predictive lead modeling companies,” we wrote, “use big data to create algorithms that help their marketing clients with predictive lead scoring. Essentially, these companies analyze a marketer’s current client base – or a segment of its clients – to determine what characteristics make a good customer: then the marketers go seek out other candidates with the same attributes. The algorithms are complex and bring together both online and offline data, and go far beyond what marketers would pay attention to in the past, but the point is that this data can yield valuable insights.”
This predictive data helps identify prospects but, perhaps more importantly, can also home in on prospects who are ready to buy right now -- based on characteristics such as job title and actions such as what websites they visited, what whitepapers they downloaded, how they're using social media. You can imagine that this is invaluable data for a salesperson who needs to close one more deal to surpass her quota for the quarter.
The B2B Beat predicts this kind of predictive data is only going to become more valuable and more important in the years to come.
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