Ah, customer click histories. You’ve heard these are rich repositories of insight, and you’ve got just the right big data marketing tools to gather that information. Unfortunately, it isn’t quite that easy. Unless you know what you’re looking for within the data and how to get the data to spit out its hidden answers, click history data isn’t much good to you at all. Here’s how to get it to sing the songs of its people.
1. Ask and Ye Shall Receive
There’s often a disconnect between the marketer and the marketing data. Marketers tend to expect that their data will just stand up and start spewing forth its knowledge. While that would be nice, marketing data has to be carefully and repeatedly queried in order to coax out the hidden patterns and correlations and insight. Be wary when you find the answers you’re looking for lurking in the data, because it’s a tendency of all marketers to stop asking the data questions as soon as it gives them the answer they want. Keep querying. Ask many different questions in many different ways. Then you will get the hidden insights big data marketing tools are capable of delivering from customer click histories.
2. Relate Your Queries to Your KPIs
Just because you get answers from big data marketing tools doesn’t mean you get useful answers. The insight has to relate back to key performance indicators. For example, say your data queries reveal that the average customer goes through five touchpoints before they convert. Um, so what? Unless you can relate this information back to a KPI — such as what touchpoints have the highest dropout rates or the lowest conversion rates — it doesn’t do you much good. Always ask your big data marketing tools questions that actually have practical, meaningful answers.
3. Set Your Big Data Marketing Goals
Big data marketing is not an end. It’s a means to an end. This sounds self-evident, but more than a few marketers get these tools believing that having the tools is all it takes to get meaningful information from customer click histories and other metrics. Set a realistic, achievable, definable goal, and then use big data marketing tools to meet that specified goal. For example, you need to improve revenue by 1.5 percent by the end of the quarter. Or, you need to improve download rates of your new e-book by .75 percent. Only then can you determine if your big data marketing solution helped you meet your specified goals.
ReachForce helps marketers increase revenue contribution by solving some of their toughest data management problems. We understand the challenges of results-driven marketers and provide solutions to make initiatives like marketing automation, personalization and predictive marketing better. Whether you have an acute pain to solve today or prefer to grow your capabilities over time, ReachForce can unify, clean and enrich prospect and customer lifecycle data in your business, and do it at your own pace.