Your dealership undoubtedly sees a lot of customers each day. Let’s say that each customer who walks into your showroom wears a different color shirt. Over the course of time, you see a trend in that every single customer who purchased a vehicle wears a red shirt. You’d probably start getting excited when you see a customer come onto the lot wearing a red shirt. In fact, you might come to the conclusion that perhaps you should start marketing to people in red shirts, as those customers are clearly buying vehicles from you. But that would be a bad assumption to make. Why? Because I could visit a dealership five times and each time wear a different colored shirt. It just happened to be a red shirt I wore on the day that I purchased.
The same thing applies when Google Analytics reports attribution. I like to call this the “Amnesia Effect of Google Analytics.” Google Analytics doesn’t remember that the customer visited the dealership five times, or that the customer wore a different colored shirt. Only the fact that he or she was wearing a red shirt when they purchased a vehicle. So, Google Analytics attributes the sale to the red shirt.
This may sound illogical, because it is!
Attribution is a subject close to my heart, and an area of expertise, I’ve recently written quite a bit about over the last few months. The subject can be rather confusing, especially if you don’t understand the different types of attribution models and which ones are more accurate than others. In a previous blog I received a lot of positive feedback on an analogy I used in an attempt to simplify the differences between first, last and multi-touch attribution. I thought I’d expand on the analogy to provide a mini “Attribution 101.”
A scenario that happens every day at most dealerships is that multiple salespeople are involved with the same customer over a period of time. It’s a well-known fact that the majority of customers don’t buy the first time they visit the dealership.
Mr. and Mrs. Smith come to the dealership. They’re approached by salesperson #1 who greets them. They say they wish to look around by themselves. Salesperson #1 hands them his business card and says he’ll be waiting in case they have any questions or would like to see a specific vehicle. As they leave, he manages to get their names and phone number and enters them into the CRM.
A week passes and Mr. and Mrs. Smith return to the dealership. Salesperson #1 is off and they don’t remember his name, or ask for him. Salesperson #2 greets them and answers specific questions about a couple of models they have interest in. He test drives both models with them and conducts comprehensive walk arounds explaining the various features and benefits of each vehicle. Mr. and Mrs. Smith thank him for his time and let him know they want to do a little more research. Salesperson #2 gets their information and the customers leave.
A few days pass and Mr. and Mrs. Smith return. Salesperson #1 and #2 are not on shift. The Smiths are greeted by salesperson #3. They inform salesperson #3 that they are interested in a specific vehicle and would like to get information on pricing and payments. Salesperson #3 sits them at his desk and goes over all that information with them. After the information is presented, the Smiths again say they would like to think about it and they leave.
The next weekend, the Smiths return and salesperson # 4 greets them. They inform salesperson #4 that they previously visited and test drove a specific car, have already worked out figures and would like to purchase the vehicle. Salesperson #4 sits them down and proceeds to wrap up the deal and delivers the vehicle.
In this case, how does the sales manager work out who gets credited with the sale?
Assuming everybody involved entered the customer in the CRM and followed up, most dealerships would credit salesperson #1 (first) and salesperson #4 (last). Salesperson #2 and #3 get no part of the commission. However, when viewed from an effort and influence perspective, salesperson #2 and #3 actually did the most work and had the most influence.
This is an example of first and last touch attribution. In a multi-touch attribution situation, a dealer would have the ability to see that salesperson #2 and #3 actually did the most work and could credit them with the most influence leading to the sale.
You need a bigger picture with accurate attribution data to make effective marketing decisions. Otherwise you will find you are experiencing the amnesia effect of Google Analytics – wasting money marketing to people wearing red shirts when, in fact, the color of shirt had no influence on the sale. It just happened to be what the customer was wearing when they purchased the vehicle.
I hope this helps bring about a better understanding as to why a multi-touch attribution model is imperative in making informed decisions based on accurate data that will produce greater ROI from your marketing budget.
Author: Steve White
Steve White is CEO of Clarivoy (www.clarivoy.com), the auto industry’s leading provider of Multi-Touch Attribution. Steve founded the company in 2009 as a digital agency and immediately set the company apart from the competition by creating an industry-leading performance-based pricing model, only charging clients if he improved their keyword rankings, incremental traffic and leads. This model required an obsession with identity resolution, tracking, analytics, and attribution which eventually led to Clarivoy’s evolution. Today, the company is focused on one thing and one thing only – Multi-Touch Attribution – and continues to launch new and innovative marketing analytics solutions for the auto industry.
Considered a digital marketing pioneer, Steve has over 20 years of experience working with clients to ensure they get the best results from their traditional and digital marketing campaigns. In 2014 he was named Ernst & Young Entrepreneur of the Year in Central Ohio. Steve is a graduate of Indiana University’s Kelley School of Business. An avid cyclist, he resides in Columbus, Ohio with his wife and three children. He can be reached at: email@example.com.