May 16, 2016, 4:24 PM

Measuring conversions that (seemingly) never happened

How can you quantify digital success when the customer buys offline? Start by changing everything you know about "conversions.”

Lead Photo

Here’s the scenario: Mr. Dreamhubby (maybe I’m idealizing just a bit) wants to buy an expensive luxury car for his wife. While perusing the Wall Street Journal site, he encounters an ad: the car model he’s been dreaming of is on sale! Excited, he clicks over to the richly-designed brand website, finds the model he knows she’ll just love, plays with the color schemes and accessory packages until he gets it just right. The next day, he closes the deal at the local dealership, and drives away to surprise me...uh, his wife.

A great story, and a great business success, right? Depends on who you ask. Because by traditional online conversion metrics, it’s an utter failure. Did the hubby actually buy on www.luxurycar.com? No. This means there was no conversion, nor any ROI for the ad. Moreover, the measurements registered after analyzing the interaction are counted as negative and added to the “non-conversion” bucket.  

Paradigm Shift: Conversion Cycles, Not Conversion Rates

For luxury brands, whose sales are often offline or in-store, tracking web site conversions can be as difficult as choosing a present that your spouse actually likes (when luxury cars are not an option, of course). 

The path from initial brand exposure to cash register can so be long and convoluted, and the customer journey so difficult to track, that showing any ROI for costly web site projects or marketing campaigns is next to impossible. In the luxury goods world, the brand web site is often more of a transit point for purchase via other venues. 

And guess what? It’s not just luxury brands. Most retail websites actually function as a transit point or an extension of the brick-and-mortar store. It’s no secret that website interaction plays a significant role in brand perception. Millions of design articles emphasize the importance of customer experience to brand loyalty and satisfaction. The problem is that visitor perception simply cannot be measured by the traditional “conversion rate” metric.

The issue here is fundamental: how do we define the concept of “conversion?” I believe we need to start thinking of conversion as a process and not as an action. We need to stop talking about conversion rates, and start talking about conversion cycles

A “conversion cycle” can be defined as the continuum from product or brand exposure to purchase. This process can involve multiple iterations and may also include transitions between different devices or between the offline and online worlds. Conversion is, after all, the result of an intertwined decision-making process, and the site visit is only a small part of this process. Think of it as an iceberg—what you see above the water is the result of everything hiding beneath the surface. 

Once we’ve accepted this paradigm shift, the next challenge is identifying where the customer is in the conversion cycle. When we know this, we can effectively push him or her forward in the funnel. Luckily, there’s technology out there to facilitate this.

Where is the Visitor in the Conversion Cycle?

Today, using predictive modeling and advanced customer experience technology, we can quantify level of customer involvement and identify intent on each page. This enables us to bring KPIs in line with the conversion cycle model, and effectively determine where each customer is in the conversion cycle. 

In order to gauge and respond to customers’ digital body language the same way we read and respond to nonverbal interactions in the offline world, we’ve identified patterns of behaviors that repeat themselves constantly throughout visitor sessions, and across different industries and devices. 

We’ve translated these patterns into four sets of advanced metrics that website stakeholders can leverage to quantify where the visitor is in the conversion cycle. In the near future, we believe that site stakeholders will be able to use this knowledge to react in real-time to each individual’s needs at each unique stage in the conversion cycle.

Inactivity (Time between Actions)

Inactivity is when a visitor’s mouse remains static after having navigated to a page or page element. The longer the time between actions, the more engaged prospects can be considered to be. Of course, if the visitor is inactive above a certain time threshold, we can assume that he or she got up to do something else, or clicked to another browser tab, and stop the inactivity clock.

From a psychological perspective, inactivity shows us how much a prospect is willing to devote cognitive resources to a product. Given that people don’t like to devote more cognitive resources than absolutely necessary—this is an important indicator of what on the site is of interest. 

Mode Shift (Disorientation, Exploration, Focus)

Traditionally, we look at simple engagement time as an indicator of conversion likelihood. But all engagement is not equal—and engagement on luxury brand sites all the more so. Where prospects are engaged in the conversion cycle is equally important.

Mode Shift is measured by number of visits, and the delta in time on a product page versus time on a category page. Here’s a sample breakdown of modes, based on our work with a major international luxury brand website: 

From observation of visitor sessions, we learned that on first visits, the website’s visitors are not focused. They land on a category page, they switch between pages rapidly – they’re disoriented, and not sure what they want. On second visits, they tend to explore two or three products. In third visits, we often see, they focus on one product—reading product reviews, tech specs, and more. 

Depth of Engagement 

The traditional engagement metric, time on page, is one-dimensional. Actual engagement has depth. A click on an element is a more powerful indicator of actual engagement than a hover. The speed of scrolling—including acceleration and deceleration - on a page is as important as the length of scroll. As the graphic below shows, Depth of Engagement allows us to understand whether a visitor is just skimming or actually reading, and thus more effectively gauge involvement.

Uncertainty

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