How much data does your dealership collect per day? Think about every email opened, every appointment scheduled, every tire purchased, etc. There are thousands of transactions daily. It’s too much data for a single person to comprehend, let alone analyze.
But artificial intelligence (AI), fed by algorithms and machine learning, not only analyzes your data but also learns from it. In dealerships, there are many uses for AI, but one of the most exciting areas is in marketing.
Knowing how and where to allocate marketing spend and knowing the best way to reach every customer is a big challenge for dealers. Despite marketing vendors continuously enhancing their attribution and ROI reports, dealers still have the question, “What works and what doesn’t work?” AI can not only help you answer this question but also can help you to improve ROI by strengthening relationships with current customers and creating new sales and service opportunities.
When it comes to marketing strategies, many dealerships still use a one-size-fits-all mentality, sending the same messages through the same media channel to entire groups of customers without accounting for each customer’s unique purchase patterns and preferences. Unfortunately, this approach results in irrelevant messages that cause customers to ignore your marketing communications or even worse, unsubscribe.
Today’s auto consumer expects more. They demand personalized, relevant messages at each stage of the buying process.
One of the greatest advantages of AI is its ability to predict human behavior and improve interactions with customers. In sales, AI can accurately predict when a potential prospect is in the market for a new vehicle and what vehicle they are likely to buy, based on the analysis of data in your DMS and of third-party data.
When incorporated into an equity mining tool, AI can help identify customers who have equity in a vehicle and are potential trade-in candidates. Even if a service customer bought their vehicle at another dealer, AI can determine their likely equity without the need for credit checks. As we know, just having equity in a vehicle isn’t highly predictive of who’s ready to purchase. AI also helps to engage with customers who are motivated to buy a vehicle using personalized messaging and by facilitating dialogue with customers via chat and SMS.
Many people mistakenly think the purpose of AI is to eliminate human involvement. AI can actually improve the efficiency of a retailer’s staff. In-depth knowledge of customers’ preferences based on AI helps salespeople identify the best time to reach out and have relevant conversations with current and potential customers.
AI makes it possible to answer questions that were previously impossible to know. For example, “Based on this customer’s transaction history and vehicle data, what service is a customer likely to need and when are they likely to need the service?”
If it’s highly unlikely that a customer will come in for service in the next few months, why spend a lot of money marketing to them today? However, if it’s highly likely that a customer will visit a repair shop for service in the new few months for a specific service, you might want to spend a little more to reach that customer.
Part of the issue in analyzing past transactions is that service opcodes in dealerships aren’t standardized. An opcode for a brake job in one dealership may be entirely different than an opcode for a brake job in another dealership, even when both dealerships are part of the same auto group.
But machine learning can identify the multiple ways that “brake job” is written on an RO. With this ability, all the data from brake jobs on your ROs can be collected and standardized, along with the vehicle’s entire service history, and fed into algorithms that are created for a purpose, such as “identifying someone still in need of a declined repair,” or “likely to need tires?” Or, “After getting a brake job done, what is the next service that customers with this model are most likely to get?” You might also want to know how long the average customer waits before getting a specific service performed, or what prompted them to return—whether it was an email, paid search ad, phone call, Facebook ad or text.
AI can also help you to analyze customers’ past behavior to identify tendencies related to media channel usage, engagement with marketing messages, and promotional sensitivity.
This data can then get used to determine which media channels are best used to reach a particular customer, what time of day or night that message should get sent, which offer is most likely to be redeemed, and what content is most likely to motivate them.
The benefits of this highly targeted AI-driven marketing include increased engagement and response rates combined with reduced opt-outs.
Although AI won’t ever predict human behavior with 100 percent certainty, it can significantly increase the effectiveness of your dealership’s marketing strategy, improve the efficiency of your staff, and provide you with an edge over your competition.
About the Author
Doug Van Sach leads the strategy and analytics department at Affinitiv, which uses data science and customer insights to create acquisition, retention and loyalty strategies for leading automotive companies. Doug has extensive experience designing and managing retention and digital marketing programs for automotive and non-automotive retailers, including OEMs, dealer groups, national aftermarket retailers, and specialty sporting goods retailers. Doug also has experience developing process improvement and performance management programs for Fortune 500 companies while at Ernst & Young Management Consulting. Doug earned his BS from Miami University in Ohio and his MBA from Indiana University’s Kelley School of Business.
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