In her article, “How Content Recommendation Creates Better User Experience,” Kaylee Baxter explained very clearly how content recommendations greatly improves user experience. I couldn’t agree more. Providing users a personalized content experience is equivalent to a librarian that knows your taste, and every time you visit the library, she is waiting for you with a reading selection assembled especially for you.
The comparison of the web to a library isn’t far-fetched. Both offer a breadth of content that is beyond the comprehension of the humble human mind. Both are impossible to navigate without the assistance of a librarian or Google. And both represent the biggest leaps forward of mankind as far as collective knowledge.
Going back to content recommendations, in her article, Baxter focused on the native advertisement aspect of content recommendations: a network of websites that join forces and their respective content assets to offer users a cross-website content experience. Once the user finished reading a piece of content, she is recommended a few more pieces of content that would interest her.
This form of native advertising fits perfectly in the serendipitous nature of web browsing. We no longer have a clear action plan when we spend time online. We let the web itself direct us, especially the social web. We usually have no idea where we’ll be a few clicks down the line, and we are more than fine with this; we welcome it.
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So, if content recommendations work so well across a network of websites, why not apply the same methodology to the browsing flow on your own website? It’s the next logical step in providing your website visitors a personalized experience. As mentioned above, we are almost expecting to be told where to click next. We want recommendations for what to read or watch or listen to next, so the same expectations can be fulfilled internally. Your website visitors will appreciate it. And we have the data to prove this.
BrightInfo offers a personalization algorithm based on content recommendations. In the charts below you can see our analytics console: the company in question saw a 229% increase in conversion rate and 95% increase in engagement over a period of one month.
But we didn’t stop there. How could we know for sure that the increase in conversion and engagement wasn’t because of something else? How can we be certain that it is our personalized content recommendations widgets that are responsible for these beautiful numbers?
We decided to A/B test it, clearing out any doubt we, or our customers, might have. We ran half the traffic with our algorithm and the other half a-la-natural. The results drove home what we knew from the start: personalized content recommendations work.
On-site content recommendations come in the form of widgets, similar to native advertising widgets, only instead of recommending content from “around the web,” the content being recommended is from your own existing content assets, on your own website.
The great thing about internal content recommendations is that they can be personalized in a much more profound way. This can be done manually or by an algorithm, but the same principles apply to both: first you need to know your content, next you need to understand your website visitors. Then, you need to match them together. In our case, we leave it to the algorithm to do the heavy lifting.
The other major benefit of content recommendations is that you make use of 100% of the content you create. One of the biggest problems in content marketing is, quite simply, waste. According to a SiriusDecisions survey, 60-70% of content created by B2B companies never gets used. That’s more than half (apologies for stating the obvious). Let’s see how content recommendations help you put all of your content to work.
The reason that so much content never gets used is the way websites, and especially blogs, are built. After you finish writing a piece of content, it basks in the sun of the front page for a couple of weeks or so (depending on your editorial calendar) and then slides into the dreaded inner pages. There, most content suffers from severe vitamin D deficiency.
If you use content recommendations on your website, it doesn’t really matter on what page this piece of content or the other is. The content recommendation mechanism is proactive; it doesn’t wait for visitors to accidently find the content they need but matches them with the most relevant content. This is how the shelf life of your content is greatly extended.
On-site content recommendations work for the same reasons native advertising works: they leverage the power of relevancy to deepen engagement and increase conversion. What’s more, they significantly increase your content ROI. And, they help you to get to know your audience much better and understand their needs. As a result, in the future you will be able to create content that is more focused and relevant. Everybody wins.
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