How B2B Websites Are Making Personalized Content Recommendations With AI
When Netflix debuted its global recommendation engine in 2016, it estimated that 80% of subscriber viewing choices were based on personalized recommendations.
What if I told you that B2B marketers need to be more like Netflix?
You see, those recommendations equate to cold, hard cash for Netflix. They save the company an estimated $1 billion dollars annually by keeping subscribers engaged with its content instead of losing them to another entertainment source.
Let’s compare this to your average B2B website.
When a person visits your website, how much content are they consuming based on a personalized recommendation? If your website is like most B2B sites today, it might have some macro-level personalization, tailoring the calls-to-action by industry or geography. But it’s not providing the micro-personalization everyone now expects online.
That means your web visitors are probably experiencing some serious friction before they find the content that’s actually helpful to them at their stage of the journey. Perhaps the blog post they select doesn’t link to other related content after they’ve read it—a dead-end. Or, they might be required to fill out forms for gated content that doesn’t contain the information they’re searching for.
In the end, many people will leave your site without getting the information they need. If it was a poor experience, they might not return. How much money did you just lose on those sales?
Conversely, how much revenue could you make if your site was more like Netflix, offering up micro-personalized content recommendations that actually help each visitor get relevant information and lead them towards a sale?
Artificial intelligence paired with a new class of data is spurring this kind of transformation in B2B websites right now.
And it’s doing so in two big ways.
1. AI Can Read and Understand Your Content
Let’s imagine you’ve been operating a B2B website for ten years. Perhaps you started blogging regularly at some point, and you’ve also developed a slew of videos and even some really helpful downloadable assets, like eBooks and whitepapers.
Excellent news! You have a ton of helpful content for leads. But there’s some bad news, too. While humans can know what an individual content asset is about, it’s extremely difficult to consistently tag lots of content and determine which is the most appropriate one to serve up next. And it’s impossible for humans to make micro-personalized, predictive recommendations on which content pieces to serve at scale.
AI can help. It can generate content metadata for you at scale, so you don’t have to tag content manually. And it can be trained on the attributes of the content—the type of asset, the topics, the expected reading or watching length, etc.—and then make thousands of recommendations automatically.
That’s because AI can use natural language processing (NLP) to read and understand text, regardless of language. So if you use a machine learning algorithm to review and sort through your content, it’ll discern what the content is actually about and create some interesting new data points about that content that may never have been revealed without AI intervention.
That’s where the second part comes in.
2. AI Can Make Recommendations for Website Leads
People want personalized experiences. But how do you achieve that when your website sees thousands or even millions of visitors per month, all at different stages of the customer journey, and with different wants and needs? The complexity around this task, if you were to attempt to do it manually, is completely unmanageable. It’s not a problem that a whole army of marketers could solve.
But personalized experiences are important. Predicting what the next best webpage, PDF, blog post, or other marketing asset to serve up should be mission-critical to delivering that micro-personalized experience.
Recommendations are just better business. If you’re not making recommendations to individual website visitors, you’re not making the most of your investment in content marketing, website development, and marketing technology.
Using artificial intelligence, your B2B website can become a Netflix-style recommendation machine. Thanks to the back-end work AI can do with tagging and sorting your content appropriately, you can use your website to track each visitor’s content consumption history and make micro-personalized recommendations about the content they should see next.
Put simply, AI does this by crunching massive amounts of data and making highly accurate predictions based on that (e.g. This individual spent 2 minutes and 27 seconds consuming this blog post, therefore they will most likely see value in this whitepaper). So even though a million people might be visiting your website, each one of them can get the recommendations that make sense for their individual journey.
These recommendations reduce friction, creating a better experience for prospects and customers alike. They lead to more pipeline and revenue for your organization. And they save your business money by efficiently scaling what no human could possibly do.
PathFactory is one tool that can help you build these personalized recommendations. PathFactory uses AI on your B2B website to create a truly personalized experience—which is what buyers demand. Use it to understand your content, tag, and sort it. Then, leverage that organized treasure trove of information to hyper-personalize recommendations for each B2B buyer that visits your site.
Interested in seeing it in action?
Click below to see a demo of PathFactory.