Content marketing isn't easy to do. There's no doubt that it's effective, but it's very hard to do it well. It's a little like publishing a book blindly. You have no clue if anyone will be interested enough to read it - and want another. Despite this, content marketing is still an important part of any marketing plan - so how can we overcome this problem?
One strategy is to write your content so that it is targeted to a specific type of individual. This isn't a new concept in marketing. Buyer personas are a core concept but most buyer personas are an educated guess. The buyer persona you're targeting may not be the type of person you're actually attracting with your content.
If your company does have a number of customers already and wants to really leverage the power of content marketing, then a more refined understanding of who is actually participating with the company is necessary. When you know your audience you can write to them. That's where data mining can come into play.
Data mining is a set of processes for analyzing a large dataset to find statistically significant information. Most data mining for content marketing purposes uses sophisticated engines to crawl through the net to find signals related to particular keywords or topics. From this analysis, predictions are made to learn more about what type of person reads what, and what readers of one topic might be interested in reading next.
But this can be turned around the other way. Instead of looking at the wider net, you can use data mining techniques on your own customer database to see which visitor behaviors correlate with particular pieces of content.
You might be asking isn't that what analytics is for? True, analytics can help but data mining takes it one step further. Analytics by its nature only looks at surface behavior, and for a small to medium-sized business this might be all that is necessary. A simple examination of which articles performed the best is a pretty good indicator of what your audience is interested in. However, if you have a large number of visitors there may be deeper patterns that cannot be so easily discerned. By leveraging these patterns via your content marketing it can become more effective.
Here are some of the questions data mining can answer when done right from a content marketing perspective:
Let's take an example from Sink Law, a large personal injury firm, and their blog. How do they know if they're getting a good ROI from their blog? They can compare their website analytics to the consultations they get, whether those consultations begin as calls, online chats, texts or email. The firm could compare the blog topic, length of topic to the magnitude of response, to help determine which types of content generate the best return on investment. Data mining techniques could pull all of this information together and look for patterns about which combinations of client statistics and content marketing engagements lead to a call. Perhaps a post on a recall of child safety seats resonates very strongly with young mothers compared to other articles on child safety. Done correctly, data mining will help reveal what works and why people took action, so it can be replicated in the future.
This is just the start of a much longer topic, but one that is clear. Content marketers are looking for any way they can get an edge to build up their audiences. Leveraging existing customer information to build up more refined buyer personas through data mining is a matter of when, not if.
Content marketing is challenging for many organizations. Oracle’s Content Marketing has solutions to simplify the process of creating, distributing and promoting your content. Visit our website for more information. If you are in the market for new content marketing solutions that works for you, read the Buyer’s Guide: Evaluating Content Marketing Solutions for an easy way to access your solution requirements and options.