Past data, future use: Maximizing predictive analytics in marketing

Maximizing predictive analytics in marketing

While surfing the web one day, you check out the website of a bridal retailer and click on a few wedding dresses that interest you. Over the next week you’re subject to wedding-related ads every time you come online, pitching everything from bridesmaid dresses to venues to honeymoon destinations.

That’s the result of predictive analysis, and when used by savvy marketers it’s increasingly linked to sales growth. A December study by Forrester Research found top-performing B2B marketers in the U.S. are more likely to use such methodology, with users nearly three times more likely to exceed average revenue growth in their industries. And 89 percent planned to use some form of predictive marketing this year.

“Predictive insights help marketers nurture the right leads, convert sales faster and engage customers with more relevant content and information,” the study reports. “In fact, predictive marketers effectively manage a wider array of engagement activities across the customer life cycle, while retrospective marketers tend to focus mostly on increasing awareness and acquisition.”

How does predictive analysis work? The process isn’t new if you think of it as simply using data to predict consumer behavior. But through use of multiple tools on the market and/or the expertise of skilled data analysts, your company can use increasingly complex algorithms to aggregate data from a number of different sources. They might include everything from consumer interactions on your website and email campaigns to social media sites and information-subscription sources like Bloomberg, Thompson Reuters, Esri or Westlaw. And when used with statistical probability models, such sources often make surprisingly accurate assumptions about future consumer behavior.

In one forward-thinking instance, Amazon has secured a patent for information-gathering technology that allows it to anticipate what customers might buy in the near future, then strategically ship items to certain warehouses in anticipation of orders. But not every predictive analytics tool seems quite so mystical.

Those using call-tracking tools like CallView 360 and RoundTrip already have access to a plethora of data that can inform on further PPC strategy, effectively predicting the future success of their campaigns. By gathering metrics such as phone conversations per day, average call duration, conversions, most effective keywords and caller demographics, the system allows users to target marketing budgets where they can produce the most profits.

In general, here are other ways marketers are effectively using predictive analytics:

  • Better identifying leads: Some companies have achieved double-digit sales increases by leveraging the digital footprints buyers leave en route, according to It points to cases of 85 percent accuracy in predicting who will buy, when they’ll buy and what they’ll buy.
  • Creating better buyer personas: Identifying traits and past patterns allows for better identification of exactly who your audience is, even offering the opportunity to deduce customer lifetime value.
  • Better sales-funnel management: The right customers are targeted with the right messages as data predicts more of their characteristics, so leads can be more smoothly nurtured toward a sale.
  • Using knowledge to improve products: Compiling past customer feedback and combining that with other customer data can help companies resolve more pain points and invent better solutions.

In short, if you’re not at least experimenting with predictive analytics, you’re probably at a competitive disadvantage.

“The biggest benefits will come when marketers move beyond early-stage experimentation and start to use predictive analytics to find new market opportunities, streamline deal conversion, grow lifetime account value and turn loyal customers into advocates,” reports the Forrester study. “Now is the time to test the analytics waters and figure out your company’s appetite for applying customer data to marketing strategy and execution.”