Two pressing needs in digital marketing analytics are estimating ROI and improving conversions through better web metrics. I’ll be talking to you about both in the weeks to come.

The first focuses on optimizing the flow of qualified traffic. The second looks at optimizing what you do with that traffic. Both lead to better online profits.

Let’s actually start with the second one: conversions. To improve your site’s “close rate,” you first have to acknowledge that it’s a lot like running a bricks-and-mortar store — even if what you’re trying to “sell” is the action of subscribing to an e-newsletter or downloading a whitepaper.

You, as a hypothetical shopkeeper, can improve close rates by enhancing your store displays, experimenting with new offers, plus a hundred other tweaks to the “content” of your store. In other words you’d optimize your store’s content the way a web content manager adjusts page content.

Both of you would be doing it for the same reason. You’re trying to improve interest levels in order to get higher conversion rates.

Measuring consumer interest on a web page

For years I’ve been working on a single metric that focuses on visitor interest levels. It scores web content (text, graphics, video and audio) on its ability to cause people to be interested during a key phase in the sales cycle, when consumers are not yet ready to buy. In doing so, I’ve tried to address a galling problem in web analytics: digital window shopping.

Today we have a lot of knowledge about what people do once they arrive at a site. Modern web analytics allows us to see exactly what pages someone viewed before they converted. That’s very nice, but this work is driven by a deeply flawed assumption: That everything a visitor needed to know to decide on the purchase was acquired right then, during that singular user session.

The problem with optimizing content around conversions is that usually it’s only a small minority of people who convert on their first visit. Instead they visit, look at a page or two, think about it, and then come back once, twice, or even more times — all before they take an action! To add even more complexity, they may use different computers each time, or even a smart-phone visit or two.

Say goodbye to tracking people over time via cookie files!

People need to become comfortable with your offer, and see how the benefits outweigh the costs. This takes time.

Image from Wikimedia.org courtesy of Creative Commons

My solution forgets about conversion for the moment. It assumes that before visitors go further into the purchase process, they first become interested. Years ago I was surprised to find that there is little devoted to this important part of the online sales process, so I set about creating a metric of my own.

This metric isn’t arrived at by surveying users, but by measuring their behavior. That means standard web analytics systems can come up with this score fairly easily, even the free Google Analytics.

(However, it only works for sites with tens of thousands of web visits every month, and extracting the most value from the metric requires a site where content managers can archive and later revisit past versions of the pages they manage.)

Paying attention to the nose prints

I first published something on this metric, called “content interest index,” on my blog.

Back then I struggled to describe what it measures. Now I talk about storefronts and display windows …

You, the shop keeper, can look out your storefront and watch prospective customers pass by. If you display merchandise in the window, you can count how many people look in briefly before continuing their walk past.

That’s basically what a page view does. It tallies up visitor attention. Which is a good first step; Attention is essential to any sale, and it’s the “be-all and end-all” of traditional advertising. But any bricks-and-mortar retailer will tell you that glancing in a window is one thing. Actually purchasing something is entirely different.

Once consumers come into a store and talk to a sales clerk, they’re two stages deeper into the sales cycle. They’re just one step away from a purchase. You might say that they’ve entered a “conversion funnel.” Most sales floor retailers study their in-store conversion funnels as closely as online marketers do. Like us, they try to keep them tuned up and humming along. In both worlds this is the manipulation of consumer “desire” (used in a marketing sense — see my blog post for an elaboration).

But what about that important stage between looking in the shop window (attention) and actually negotiating with a sales clerk (desire)? That crucial middle step is what my content interest index measures. It’s analogous to counting the nose prints on the store window, and comparing how many smudges you find on the glass immediately in front of each product displayed there.

It looks for those people who are so interested in a product or offer that they “leave a mark” — something we can measure and compare.

So what?

This is especially important online because we’ve seen that prospective customers visit our web sites with far more frequency that most people would (or could!) visit a bricks-and-mortar store. To say this another way, online consumers can visit with an interest that is strong, but shy of converting, many times before they finally convert.

“Nose prints,” both real and virtual, are behavioral proxies for interest. When reported properly, the virtual kind (expressed through content interest index) can serve as a coaching tool to those content managers responsible for the key web pages surrounding your site’s conversion funnels.

My next post will talk about how content interest index is generated by watching behaviors that include sending content to a printer, emailing it to a friend, and social media sharing.

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About Jeff Larche

Jeff Larche

Jeff Larche has a deep background in database marketing and direct response. His is a consultant specializing in CRM and interactive marketing with Accenture. His own blog, which is also the name of his original consulting business, is Digital Solid. When he's not working at his day job, he's provided digital strategy support for a worthy not-for-profit, Rock the Green: mixing education about our environment with a day of great live music on Milwaukee's beautiful lakefront!

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Comments on Social Media Explorer are open to anyone. However, I will remove any comment that is disrespectful and not in the spirit of intelligent discourse. You are welcome to leave links to content relevant to the conversation, but I reserve the right to remove it if I don't see the relevancy. Be nice, have fun. Fair?

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  • http://thoughtwrestling.com/blog Mark Dykeman

    First of all, I love the title.

    Secondly, your metaphor is an excellent way to capture your topic and make it easier to explain and teach.

    Finally, I'll be waiting for your next article with great interest!

  • http://www.digitalsolid.com Jeff Larche

    You're very kind, Mark. Thanks! I'm as eager to post the follow-up as you say your are to read it. This is a category of measuring web behavior that holds a ton of promise.

    Also: Congratulations on joining Jason's “twelve disciples” (as Jason would put it: “heh”)! I'm honored to be in such extraordinary company and am excited about adding my two cents to the online conversation.

    • http://thoughtwrestling.com/blog Mark Dykeman

      Twelve Disciples? Oh man, I thought we were auditioning for the Twelve Stooges!

      That tricky Jason… :)

  • http://randyschrum.com Randy Schrum

    Jeff nice article, very informative—> I look forward to how the content interest index is generated.

  • http://insightsandingenuity.com Heather Rast

    I'd like to learn more about how factors like traffic source, navigation paths, and bounce rates (to use commonly understood terms from GA) factor in to your metric evaluation, if at all. To use your analogy (metaphor? Gah.), traffic source may be like medium (the driving tactic), navigation paths may be like in-store merchandising, and bounce may cover brand positioning, relevancy, product selection, even service. Look forward to reading more, thanks.

  • http://www.digitalsolid.com Jeff Larche

    Heather, I'll address those questions in my next post. My hope is to get it out sooner rather than later. I've been thrilled by the feedback to far.

    If you'd like to read more about the approach in the meantime, click through the link within the above post to my first “published” mention. It includes a white paper and my attempts 3+ years ago to describe it (I've improved with time and practice in how I frame the thing).

    Also, on the same, blog I posted something from earlier today, comparing CII to Google Analytics' $ Index.

    Thanks for your interest (pardon the pun — you know what I mean). :-)

  • http://www.ivanwalsh.com Ivan Walsh

    Hi Jeff,

    Looking at deep links often reveals what customers are really after esp if it's connected with SEO activities.

    Also, I try to get them to ENGAGE in some way be it RSS, email or whatever… so I can re-connect with them later.

    And. keep the call to actions above the fold. Golden rule!

  • http://anthonypiwarun.com/ Anthony Piwarun

    Jeff it's great to see a local thought leader make a thought-provoking post like this on a mainstream blog. Far too many marketers focus on just the bottom line instead of the path visitors take to perform desired actions. I look forward to reading more like this in your column.

    • http://www.digitalsolid.com Jeff Larche

      Thanks, Anthony. I look forward to your thoughts on the follow-up post about CII.

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