The tools available to marketers are endless - from data analytics to creative software, the sky's the limit when it comes to creating new programs that simplify and optimize a marketer's job. But marketing is more than reacting to consumer actions and creating engaging advertising materials. There's a whole set of data that drives the future of marketing.
Until recently, most marketing tactics were based on past purchasing decisions. Sales teams focused on current customers and typically relied on a profile utilizing a few signals, or features, about the business, the buyer or an activity such as an acquisition. If a prospect did not fit the profile, they were not pursued. Businesses did not have the resources - such as marketing automation tools - to discover potential customers that didn't display an active interest and consequently missed out on potential leads and revenue.
All of that is changing. With today's data and machine learning, predictive marketing analytics can now reveal a detailed pattern of traits that identify prospects likely to have the greatest revenue potential and conversion probability. Imagine you work for a computer software firm with an increased revenue target for the upcoming quarter. You can continue marketing to current customers to get them to buy more software. Or, you can use predictive marketing software to identify prospects that should be interested in buying computer software in the near future but aren't yet in your pipeline. Targeting these potential customers is more likely to yield higher revenue than a strategy that just focuses on extracting additional sales from your current customers.
Predictive marketing entered the mainstream within the past few years, but new research shows that in 2016 89% of B2B marketers intend to put predictive marketing on their roadmap, use data to optimize their marketing efforts and create more and better customer leads. They plan to use data to analyze customer profiles and behavior and then identify selling opportunities from a combination of signals such as company demographics and social activity. Data analytics is serious business; it's a way to predict a prospect's behavior before they even think about buying from your company.
And, predictive marketing goes far beyond the 4-5 basic signals obtained from a customer relationship management (CRM) database that marketers typically rely on. Predictive marketing evaluates potential buyers using tens of thousands of signals captured by external data crawlers. "Some of the most valuable signals are not direct buying signals like engagement but indirect ones like growth, use of certain technology or job postings for particular jobs," says J.J. Kardwell, President and co-Founder of EverString, a predictive marketing software company. "Predictive marketing's value is in finding those prospects that are not yet in your pipeline but should be--the ones that are most worth your marketing and selling dollars. It's about knowing when and how to get in front of prospects so that your product is the next logical step."
A company like EverString can pull in roughly 20,000 additional, external signals on every prospect, looking at everything from a company's social activity to the technology they use on their website.
Data reveals a lot about a prospect's purchasing behaviors. The more a marketer understands their potential buyer persona, the better they can tailor marketing efforts to directly speak to a new prospect. With a more personalized campaign, businesses experience a significant boost in their conversions and revenue. "There is a common misperception among some marketers--with a more accurate profile of their ideal prospects through predictive marketing, that there is no need for proactive outreach. That's not true," says Kardwell. "It's still essential for most companies to pursue an outbound strategy. Now, though, you have a lot more informed and customized ways to do it."
Marketing analytics have evolved from using a few signals to evaluating tens of thousands of signals in order to identify and communicate with the ideal customer. It's no longer enough to find prospects once they've reached the purchasing stage. The fun begins when marketers use predictive analytics to educate potential customers on how to think about what they need next. Then, it becomes truly predictive.