Help me shape mSpoke’s Audience Preference Modules

We’ve come a long way in a few years.  Our solutions are helping some of the best known web properties  (call me I’ll give you names) drive up conversion rates - click throughs, registrations, you name it - for content-rich media sites. But I know we can do more at mSpoke. We can leverage the knowledge that we use to predict which content readers want next to create more value for more parts of our customers’ companies. I know we can do that - I’m just not sure how to go about it.

That’s where you come in.

I’m going to lay out for you what I think we can do, and offer up some examples of what the user interface screens might look like. I’m even going to link you to a very short survey about it all. But I’m not trying to sell you anything - yet. Instead, I’m hoping you’ll tell me what I’ve missed, how YOU imagine leveraging the knowledge I’ll describe to create value across your organization, and how your staff really wants to interact with all this on those user interface screens.

To understand the kind of information we’re working with you have to know the basics about how mSpoke works. It’s best understood as a three-step process:

Step 1: Analyze your content to really understand what each individual article is about
We extract detailed knowledge about the topics, themes and entities contained in each content morsel

Step 2: Observe readers interacting with the content
We use the info from Step 1 to build profiles of each individual reader’s interests, based on their interaction (what is read and what is passed up)

Step 3: Combine the content analysis from Step 1 and the profiles developed in Step 2 to recommend additional/future content matched to each individual user’s interests.
Recommended content might be articles, or ads, or white papers, etc.

But beyond improving the recommendations  we have so much rich, detailed data on what each reader actually reads, we can group those readers into valuable segments in many different dimensions. Interest in a topic? Sure. Interest in a particular vendor? You bet. Interest in one specific white paper, or webinar, etc.? Undeniably.  We believe our customers can use knowledge like this to more effectively avoid list fatigue, increase the effectiveness of their sales team by better understanding how their audience relates to an advertiser’s goals, and carve out an increasing number of more lucrative, narrowly defined audience segments.

Impressive, but how …?

No, I’m not about to give away our trade secrets. The important thing is we’ve built a system that can process both implicit & explicit attention streams to develop a set of user intentions.

For example, maybe your users have explicitly indicated an interest in a new packaging system from a registration form. This is a valuable intention we could use to make recommendations. However, as we recommend packaging systems to them maybe we discover they tend to click on information targeted at small & medium size businesses. That’s implicit attention. Then we use this to recommend other SMB information and maybe discover they also are interested in accounting systems. We develop a profile of their interests and we never stop evolving that profile as they interact with your content over time. (For example, maybe they stop clicking on packaging systems after they make a purchase.) This information is extremely valuable for us to make actionable recommendations to drive your conversion metrics, but how can we effectively share that information with our customers so you can do even more?

How Can You Help?

We’ve talked to some of our current customers & prospects about this and developed some initial ideas. You can take a look at those ideas - we uploaded some screen concepts to a SlideShare presentation.Please comment on them either on SlideShare or, better yet, in the comments section of this blog in order to facilitate discussion among the broadest possible group.

We really need you to participate in this discussion so we can build the right tools. When you take the survey, don’t forget it, too, is a work in progress - it aims to let you tell us what’s most important to focus on, but also let us know what else we should be asking!

Here is the link to the survey.

As a way of saying thank you, we’ll also select one of the participants at random and email them a $100 Gift Certificate from Amazon.