Last week I ventured out to what I thought was a digital marketing networking event. In the usual manner, I checked in, picked up my drink ticket and then went to put on a name badge. And that is where I was greeted with an unexpected degree of complexity.
Yes, there were actually 10 choices of name tag color. Further, each color represented at least 3 more choices which were not necessarily related such as engineering and graphic design (orange category). After picking light blue for consulting, I began to mix with the crowd. Now, I like to think I have a good memory, but I made at least 3 trips back to the sign in table to remind myself what each color meant. So red is marketing and yellow is sports… what if I want to talk to a sports marketer?
And this got me thinking about choice. There has been some good research nicely summarized in two TED lectures about this topic, one from Barry Schwartz and the other from Sheena Iyengar. Basically, too many choices make us unhappy and can even inspire no action at all (aka “analysis paralysis”). We become less satisfied with the choice we made because it’s easy to think we missed an opportunity and selected the less-than-ideal choice. Further, too many choices raises our expectations which leaves little opportunity to be pleasantly surprised.
How can we use this in digital marketing analytics? I can think of two ways but you are welcome to contribute more in the comments section below.
Group then cull products
Researchers found when a large volume of choices are available, such as magazines in a rack, grouping them into as little as 4 categories increased sales. This aligns with the way we memorize data by “chunking”. It makes us happy to know we have found the right category and can now focus on limited remaining choices. There is no research on the ideal number of choices, but if we take a page from memorization techniques, I would guess it is no more than 6. So, if you had 4 primary groups with 6 secondary choices this would be ok. But 10 groups of 3 to 5 options would not be ideal, as we see with the name tags.
So if you have a products or services to sell, consider how many choices your audience can dive into from the top? Are the areas clearly chunked? Here is an example of a navigation failure. The services menu starts off well by chunking the choices into 3 groups but then 9 subgroups causes too much confusion about which choice to select.
This is where I would run an experiment to regroup the categories, perhaps even merging or eliminating some altogether. To be clear, what I am suggesting is an A/B test which has a control group, not a wholesale change. The research says (all other things being equal) sales should increase as well as customer satisfaction. Measure satisfaction with a quick survey. Now that’s an interesting test!
People walk away when it is too difficult to make a choice. The solution to this is, Iyengar found, is to gradually ramp the complexity. For digital marketing analytics, I like to think of this in terms of ramping the relationship, also called engagement. As we strive to know more about our customers ask for small engagements first. Then build up to larger asks. This key concept has long been understood in negotiation.
Applying this to website engagement, consider what you want people to do first. For example, if I want customers to download a whitepaper, then putting a large, complex form in front of them would increase the complexity and cause them to walk away. Gradually asking for more information each time is a better choice. The same goes for introductory videos or tools.
What about the back end of the sales cycle? We’ve gradually engaged and nurtured a customer all the way through the sales cycle and now… nothing. Would this not be the richest time to ask for higher engagement perhaps in the form of a product review on the site or even a tweet or share? Some companies are afraid they won’t be able to control this information and bad reviews might circulate. However, if a person is unhappy with your product or service already, wouldn’t you rather immediately address the problem than discover it randomly and perhaps too late? Afterall, you are engaged now.
Customer bliss comes from the reduction of friction, and often that friction appears as choice. Too many choices lead to paralysis. Digital marketing analytics can solve for this by culling and testing products and product groupings. Analytics also reminds us to ramp engagement as we ramp customer relationships.
Although I was planning to spend several hours in pleasant conversation at this Portland networking event, I actually left after 20 minutes. I met a financial planner, two bank tellers and an engineer. Did the overwhelming choice of name tags contribute to my dissatisfaction? Sure, a bit. It was difficult to know who to engage and how to engage. Maybe next time I will just enjoy a Web Analytics Wednesday.