Improve Conversion by Using a Consumer Decision Tree
When confronted with too many options, customers will stop in their tracks.
Too much choice creates confusion which prevents conversion. A time tested way to solve this problem is to create a Consumer Decision Tree within your application or website.
The Consumer Decision Tree simplifies making multiple choices by creating a flow where users need to make only one decision at a time.
Consumer Decision Trees come from the physical world where supermarkets have to make decisions on how to organize store shelves. More on that down below.
Let’s start with BBQ Grills as an example since there are way too many models to choose from without some help.
Ebay sells BBQ Grills with an efficient, mobile compatible Consumer Decision Tree that narrows my selection quickly and easily.
In three taps, ebay helped me narrow my consideration set from 23,000+ grills to 101 grills that fit my selections. At each step, ebay surfaced the most important criteria for me to consider. Within each criteria, there are options for the user to choose from. Ebay also ordered these options smartly, likely the most popular or most profitable.
The ebay Consumer Decision Tree is:
Fuel Type
Brand
Color
BBQs Galore, which only sells BBQs, shows me a confounding 500+ individual grills and no way to narrow my choices after just one click.
The flow of a Consumer Decision Tree encourages the user to progress towards conversion because it simplifies the process by presenting most relevant selection criterion at the right time. It’s as if the application is reading the user’s mind.
The best Consumer Decision Trees do read minds: they are designed based on input from user testing during Product Discovery. User testing can uncover what customers think is most important, 2nd most important and so on. Quantitative data after launch inform further adjustments.
Even though Consumer Decision Trees are just a series of filters, the ordering of these filters and the one by one presentation of the filters is what keeps customers from stopping due to too much choice.
The Paradox of Choice theory describes how consumers react negatively once they encounter too many options.
And there are many ways to offer a Consumer Decision Tree. Here, the Lemonade insurance company presents their Consumer Decision Tree using a chatbot interface.
In creating great user experiences, the prioritization of information is referred to as Information Architecture. The Consumer Decision Tree concept is just one of many ways to organize information and experiences for users.
Origin of Consumer Decision Trees: Physical Supermarkets
All of us encounter Consumer Decision Trees multiple times per visit without even realizing it when we shop for groceries.
Consumer Product Good (CPG) companies, including brick and mortar stores, have a lot to teach the software industry about driving consumers towards conversion. Next time you visit the grocery store, think about how each section is organized and how that might influence your next user experience.
Or in the case of Trader Joe’s think about how they create new products and create delight in almost every visit.
Whether it’s coffee, ice cream or peanut butter, the shelves are carefully stocked to make it easy for customers to scan for the exact item they are looking for.
Here’s a look at how my local supermarket, Safeway, organizes their peanut butter section.
Here is a simplified version of the Safeway Peanut Butter Consumer Decision Tree:
Packaging - Bulk or Normal
Quality - Regular or Premium
Brand - Jif or Skippy (or others)
Type - Creamy or Crunchy
Now if I just remember that the peanut butter is across the store next to the bread…
Caveat: Value Still Matters
Though having a Consumer Decision Tree implemented in your application or website makes it easier for users, it does not guarantee conversion.
You still need to have great prices, fast shipping, high levels of trust and other valuable traits for users to convert on your site.
Amazon is an example of a site with very little consumer guidance that converts very well.
Summary: An Easy Way to Boost Conversion
Finding the best Consumer Decision Tree will remove friction from the process and increase conversion.
And it helps to make those hard choices in mobile-first design where there isn’t enough screen space to show everything.
The best Consumer Decision Trees are derived from customer needs. And they vary product to product and service to service.
Product Discovery is one of the best ways to create a Consumer Decision Tree for a given product or service.
I’ve facilitated Product Discovery sprints for Product teams to create Consumer Decision Trees. With one online retail client, we saw an immediate sales uptick of 5% in the section of the site where we installed a customer-tested Consumer Decision Tree.
I’ve also used Consumer Decision Trees to improve wizard flows for business and consumer facing applications.
Jim knows how to build successful teams and products from scratch.
He co-founded PowerReviews, a B2B2C product reviews SaaS platform, that had an exit in 2012 for $168 million at a 13x multiple. In the early days of the web, he product managed and architected one of the original ecommerce sites that had a $66 million IPO in 1999, online sporting goods retailer Fogdog.com.
For his Product teams, he’s created a curriculum and training program that pulls from his 20+ years of experience and the best minds in Product Management. In addition, he relies on his software engineering background and experience to bridge the gap between their Product and Engineering teams. He graduated from Stanford University with a degree in Computer Science.
Jim is based in San Francisco and works with clients from 2 to 20,000 employees in a variety of industries and business models. Previous clients include VSP Global, PagerDuty, Dictionary.com, and Hallmark. He’s also worked with startups in machine learning, API development, computer vision, payments and digital health.
