5 Ways to Keep It Real with Real-Time Marketing
Posted on November 8, 2016 by Peter Moloney
Instant delivery of marketing messages to customers triggered upon customer behaviors in real-time such as page views, clicks, social interactions, location, etc., is at the bleeding edge of today’s marketing tech. Watching all activity generates a lot of data that might indicate customer preferences and readiness to buy something. But as many marketers have found out, it doesn’t always work out that way. In the end, it’s results that matter; offers that get customers to buy more, without giving anything away to people who are going to buy anyway.
- Behavior vs. Needs
One problem is a tendency to confuse behavioral events with facts about customer needs, intent, or preferences. Just because someone views a page of golf clubs on an e-commerce site, does that mean they want to buy golf clubs? Maybe. It could also mean they are doing research for someone else, checking out the cost of a friend’s clubs, holiday browsing, just curious about what this retailer offers, or any number of other things.
If you monitor third party data, like home sales, does that mean the new home owner will welcome emails or ads for new refrigerators? It might. But if you get it wrong, you risk annoying your customers with unwanted solicitations, or worse, making them feel stalked. Who hasn’t been dogged by an email or ad with recommendations or offers just after visiting a related website?
- The Prospects Beyond Reach
The other problem is that you have to wait for customers to behave a certain way before you communicate a relevant message based on that triggered event. What do you do with good customers who have not engaged for a while, or who have opted out of your behavior monitoring schemes, or for whom good data is just not readily available? And how do you know if they are a loyal customer or at risk just from what they look at?
- Look into the Past to See the Future
Real-time behavior monitoring can provide valuable insights when it comes to making a relevant offer at the right time, but it is at best supplemental to the kind of analytics that matters most. While most behaviors are at best loosely correlated with buying intent, actual buying behavior is directly correlated.
Can you detect the “actual” buying patterns that are present across the entire customer base, how this compares to the past purchases of a given customer, and what that suggests about the loyalty and next purchases of that customer? Despite where they surf, what links they click, or what they say in the moment, people vote with their wallets. Predicting when people will buy and what they will buy from a deep historical analysis of purchasing patterns yields predictions that are more reliable and durable — meaning they are effective for longer periods.
- Play it Safe with Purchasing Patterns
So, any marketing communication that attempts to deliver highly relevant or individualized messages to customers should start with an analysis of past purchasing behavior before factoring in other behaviors. Also, purchasing data is usually the most reliably available and unambiguous data available for every customer. And using it to target customers and individualize messages is not controversial. It’s been used for that purpose by companies for, who knows, 100 years?
- Think Big, But Stay Grounded
Since nothing guarantees success, the best approach is to use both the big picture of purchasing behavior and in-the-moment behaviors to target and individualize offers to customers. But while you cannot always count on existing customers identifying themselves and leaving traces of their behaviors that you can collect, integrate, interpret, and use in real-time, you can always use the purchase transaction history you already own. As it turns out, it’s more effective anyway.
Peter Moloney is CEO of Loyalty Builders, whose Marketing Lift Service offers a simple, cloud-based predictive analytics service enabling marketers to get revenue lift from more relevant communications to their customers.