Mike Moran

By Mike Moran

Why Your B2B Content Marketing Isn’t Ready for Personalization

Why Your B2B Content Marketing Isn’t Ready for Personalization 150 150 Mike Moran

I am blessed to have a number of B2B companies as clients–each one wants me to help them with their content marketing. And I am luckily able to help them all, except there is one thing they all seem to want but don’t know how to deliver–truly personalized B2B content recommendations.

They see Amazon do it. They see other B2C companies do it. But why is it so hard for B2B?

The main reason is that B2C companies don’t personalize content recommendations so much as they personalize product recommendations. They watch what you (and everyone else) buys and they can determine what you are interested in, and which products relate to those interests. Amazon knows that if you buy one book on Civil War History that you will likely buy another. But if your B2B company sells one of your products to a client, its likely they are done. They don’t need another one.

And that sale is excruciating. What happens after the sale isn’t your concern. You want to accelerate making that sale in the first place. That’s why you want to recommend content. But how do you do it?

You likely aren’t ready. (I’m sorry.)

There are three things you need to recommend content:

Information about the visitor to your site. You probably don’t have any. Sure, you might offer registration, but how many clients actually register? What incentive do they have? And how many registered clients even sign in each time they come to the site? Do you drop cookies so they automatically sign in when they come back? What information do you ask them for? Do you use any Visitor Identification technology to get information about those who don’t register? If you don’t have good answers to these questions, you aren’t ready.

Information about the content on your site. You probably have even less of this, if that’s possible. You probably have no taxonomies that have standardized tag values for topics, industries, and other critical metadata. Or if you do, it hasn’t been updated in decades. And you are hoping that author manually tag the content correctly–which you know isn’t working. You have no automation applied to any of these problems to standardize the findability of content on the site. And you have no automated process to match content to visitors–whatever you are doing is using manual rules in your CMS or Marketing Automation system. So, either it doesn’t work or it doesn’t scale. You don’t think that is how Amazon is doing it, do you?

Information about what is working. OK, this one is something you have right? For every piece of content, you have bounce rates and exit rates in your web analytics system, where you also know every link that is clicked on every page, and the cookie ID of the visitor who did it. Great work, honestly. But where do you use that data? Do you use it for content recommendation, or does it just lay dormant in your analytics system waiting to be displayed on a dashboard? Information that gains meaning when it hits the analyst’s eyeball isn’t helpful when you are trying to scale. You need information in a form for automated processes to act on.

If you have all of these problems (and maybe even more), you might be tempted to throw away your whole marketing stack and buy everything from one vendor, because, surely, they have integrated all of these pieces together and now it will just work. Well, I haven’t seen it. This isn’t strictly a technology problem. You might have all the technologies you need, but you don’t have the processes to acquire clean data and the automation to put those technologies to work at scale.

If it seems daunting, you can throw in the towel, but you can make this work. You just have to stop believing in magic technologies and start believing in well-engineered processes and experts to make them work. You can do B2B content recommendation at scale without breaking the bank. You just need to be willing to step back and solve these three problems that are getting in the way.

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