Future of Marketing Content: Reflections on the Content2Conversion Conference

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I spent the early part of this week at Demand Gen Report‘s Content2Conversion conference. The event was superbly run, as usual, but I didn’t sense any over-arching pattern until I was literally on my out the door and stopped for one last chat with some colleagues.  Then I knitted together – at least to my own satisfaction – what had seemed to be disconnected observations.

The first strand was the number of systems that offer detailed information about content consumption. Vendors including Highspot, SnapApp, Ceros, Uberflip, and ion interactive all let marketers track customer behaviors within a piece of content – such as how much time is spent on each page or even regions within a page. On reflection, it struck me as amazing that we have this level of detail available, given that just a few years ago marketers couldn’t even tell whether a given piece of content had been looked at. The uses for this information are obvious, including helping marketers to understand which topics are most appealing and giving salespeople insight into the interests of individual prospects. But I wonder how many marketers or content creators are ready to take advantage of this information. Of course, it’s clear that they should. But I suspect most are already overwhelmed by the less precise information available through less advanced technologies. This leaves them with little appetite for still greater detail.

Naturally, my own preferred solution to this technology-created flood of data is still more technology. Some of this involves advanced analytics to extract the significant needles of information from the hayfields of detail, although I don’t recall seeing vendors who do that type of analysis at the show or hearing speakers discuss them. But the more interesting response is to automate content creation and selection directly, using the detailed information to create new content and to send the most appropriate content to each individual. Again, there weren’t many solutions at the show that promised to do this, apart from Captora – which extracts keywords from a company’s Web site and its competitors’ sites, constructs draft landing pages for the most important topics, and deploys them (after some manual polishing) with links to CRM or marketing automation data capture forms. Captora is focused on paid and organic search marketing, so it can’t pick which ads to display to which prospects. But I also chatted with people from Adaptive Campaigns (which did not exhibit), whose system uses rules to generate highly customized programmatic display ads. And, on the way to the airport, I caught up with Idio, another system that automatically analyzes content and picks the best match for each individual – although Idio doesn’t do any content creation or dynamic customization.

As you know from the Machine Intelligence in Marketing Landscape in my last post, I’ve also identified a several other systems that use automated methods to generate and select content. I’ll even predict that machine generated content will be a major trend in the near future – precisely because it’s the only practical way for marketers to take full advantage of the detailed information now available on content consumption.

This connects to another theme that I did actually hear articulated at the conference: the need to move beyond “quality” content to appropriate content. That’s an interesting evolution, since recent discussions have often focused on the challenge marketers face in just getting the volume of content they need for increasingly segmented programs. That requirement hasn’t ended, but I heard more discussion of how to create the right content mix and how to create content that is compelling enough to attract attention. To some extent, this argues against the notion of machine-generated content, which will probably never be better than mediocre and formulaic. But I can easily imagine a world where humans create a few great pieces of tentpole content and use a lot of simple, machine-created messages to feed people to it.  The machine-based messages won’t be brilliant but they’ll be effective because they’re highly tailored to their targets. This tailoring will be enabled by behavioral and intent data, which were also popular topics at the conference.

I also have one other observation, which was totally unexpected (the best type!).  It might be just my imagination, but I think I sensed a bit of overconfidence among marketers about their ability to buy new technology. This is certainly surprising, given that marketers until recently have been more frightened of technology than anything else. I’ll speculate that a new generation of marketers are more comfortable with technology in general and are now reaching positions where they have control over purchasing decisions. Mostly that’s great: the industry can’t advance if marketers are afraid to try new things. But some of these buyers may not realize that they are unfamiliar with the full scope of products available or that deploying complex technology is much harder than signing up for a new software-as-a-service application. Let me be clear that this concern is is based on one conversation I had and one comment that a friend overheard.  So I might be overreacting. Still, it’s something to guard against; overconfidence can lead to cavalier decisions that are just as harmful as indecision based on fear.

Republished with author's permission from original post.

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