“Roughly half of marketing and media executives in North America said they believe predictive analytics and modeling to be one of the most helpful technologies for getting more value out of data, August 2016 research found.”
That’s comforting to me because it means there are lots of other marketing technology nerds out there. More importantly, it means that predictive analytics deserves your attention. It’s a powerful strategy than can improve the timeliness and targeting of your marketing messages.
Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened in the past, and use that information in order to provide a best assessment of what will happen in the future. It’s all about maximizing how you’re using your customer/audience data to get the most out of it. It’s not a new idea per se, but the capabilities are improving, and so are the outcomes.
Ben Kay, senior consultant in analytics at IBM, states that “effective analysis of social data can uncover personality traits which, from a marketing perspective, can enable brands to tailor communications ‘to a segment of one.’”
Léonard Gaya, head of digital at French publisher Editialis, says that, thanks to the implementation of predictive intelligence tools, Editialis is able to anticipate engagement at an individual level and has increased click-through rates “dramatically.”
In case you aren’t convinced: predictive marketers are 2.9X more likely to report revenue growth at rates higher than the industry average, and 2.1X more likely to occupy a commanding leadership position in the product/service markets they serve.
This is clearly very cool—I’m sure you’re with me on that now. It’s especially important as most marketers are seeing that their prospects’ buying journeys are nonlinear. Decision makers don’t just go through the same standard set of steps when they’re looking to make an investment. They have a lot of options for gathering information, from social media channels to company websites to webinars to industry events to peer recommendations… I could go on. But the point is that it’s becoming impossible to know when to communicate with prospects and what to say, in order to truly optimize the chance that the message will resonate with them and elicit an action. Oftentimes, there is a whole bunch of educated guessing going on.
Here are a few ways to use predictive analytics for marketing success:
- Improve customer intelligence: Condense customer data from across your organization—marketing, sales, finance, tech support—to get an all-around picture of your customers.
- Profile your best customers: Focus on the complete picture of your best customers in terms of spend, loyalty, openness to new solutions—whatever the traits are that you consider ideal. What did their buying journeys look like? How did they come to a decision to buy? What were the challenges they wanted to overcome with your solution/service? Predictive analytics can determine which attributes combine and correlate to turn a prospect into a customer. Then you can use that profile to your advantage—predicting what your prospects want and what step they’re likely to take next.
- Develop more impactful marketing campaigns: Once you understand the common qualities of your ideal (future) customers, it’s time to operationalize that information in the form of marketing communications. Use it to create personalized and timely messages with maximum likelihood of getting those prospects closer to making a purchase.
Think about how you use your data today—are you mining insights, profiling your ideal customers, and using that to automate targeted marketing messages? If not, you may have an opportunity to use data more to your advantage. Reach out if you have any questions!