The process of researching and buying cars changes quickly with the invention of new technology and new ways for consumers to consume information. For dealers, keeping up with these new methods, behaviors, and technology can be the difference between having a competitive edge or being left behind.
As a Google Premier Partner, Leadbox was invited to attend Google Canada’s Think Auto event in Toronto. The Google ‘Think Auto’ events are designed to provide dealers and agency partners with information about consumer buying behavior and marketing best practices that are made possible with Google’s massive amount of data and analysis.
This Google Think Auto was no exception. Joining 1500 other like-minded marketers and dealers, we went in with eyes wide open and came out with brains jammed full!
Here’s a highlight reel of what we got out of it:
Not just Google’s data, but the data that resides in your website platform, CRM, DMS or POS systems. Dealers may not realize it but the wealth of information that’s sitting inside your dealer systems after many years of sales and consumer transactions is pure GOLD.
Your sales data not only has your customer’s contact information but information on verified buying behavior of your customers. You, not Google, know exactly what your customers have purchased, how long it takes for them to purchase, what their financing rate is much more.
Using this information you can segment your audience and create hyper-targeted and personalized messages to maximize impact on all type of sales and marketing initiatives including new car/used sales, return sales, parts, and service.
In fact, we talked about how useful audience segmentation and how to use it in our blog: Audience segmentation: The most available way to increase the effectiveness of your ads.
For some dealers, the word ‘data’ and ‘analytics’ can be unfamiliar and, as a result, impedes the adoption of using data to make decisions or guiding strategy.
An interesting point that Google makes is for dealers to “not fight” the data – especially for dealers that did not grow up with the availability with large amounts of data.
As Google points out, these dealers may be used to making decisions based on ‘gut feel’ or ‘experience’ and may feel threatened by analytics as some of these numbers may contradict their strategies or decisions.
The point that was made is to think of data slightly differently – to approach it as a tool rather than definitive answers. To reframe the use of data to help make better decisions, not take away decision-making abilities or to make definitive statements about the future.
Yes, the only thing that’s consistent is inconsistency. People’s buying behaviors change and only by adapting to these changes, can we be successful.
This means using Google’s data to better understand your buyers’ interests, likes and common attributes. The more you know about them the better you can create messaging and use appropriate channels to effectively reach them.
Using Google’s data, you can create audience groups that are more likely to respond to your marketing or offers. These audience groups perform much better than generic interest-based groups when performing outbound marketing.
In fact, you can be quite specific on the type of audience you’re looking for. For example, Google can provide you with defining attributes specifically for ‘In Market Toyota Shoppers in BC’ or ‘In Market Ford Shoppers in Ontario’.
Need help getting started with this? We’ve worked with Google to get a great collection In-Market shopper insights already that you should take a look at.
Check out our resource: Understanding the In-Market Audience for
Many of us data geeks and self-proclaimed ‘analytical artists’ speak of all the benefits and great strategies that can be done with the vast amounts of data that is theoretically available.
As Google points out, that may not always be the case in all scenarios. Many dealerships don’t have perfect data or the ability to track everything. However, the point that Google is trying to make here is that this shouldn’t be a reason to NOT start using data. The goal is to start small and to use your data – any data – to make decisions.
This allows you to progress your methods to get better data over time and have your predictions work better over time.
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