Welcome to another edition of the Car Dealership Guy Podcast Recap newsletter—the key lessons from top operators, founders, and execs shaping the future of auto retail.
Today’s guest is Art Dessein, Vice President of Sales at Impel.
We dig into why service operations offer faster AI wins than sales, the breakdown in online service scheduling that's costing dealers millions, and how consolidating tech vendors is essential for both customer experience and operational efficiency.
Service operations deliver faster AI wins than sales due to massive scale differences.
Dealerships face a fundamental resource allocation problem where they focus 90% of their energy on sales while service holds 60 times more customer records.
"The number of customer records in the DMS is 60 times greater than the number of internet leads they get. But the mind share allocated to service is like 10%."
This creates an enormous opportunity for AI-powered service retention, especially since 55% of customers in dealership databases haven't returned for service in over 12 months.
Online service scheduling is broken and costs dealers millions in lost revenue.
Current service scheduling systems create massive customer friction that drives business to competitors, with abandonment rates revealing the depth of this problem.
"Do you know what the abandonment rate, so the people that start out trying to schedule their car on their service scheduler, what percentage defect or abandon it before completing it on average? It's like 81%."
The complexity compounds the problem, with service scheduling requiring an average of 21 clicks and using confusing industry terminology that customers don't understand, like "LOF" instead of "oil change."
Dealership over-messaging drowns good communications with bad ones.
The proliferation of marketing tools has created a messaging crisis where valuable communications get lost in the noise.
"Every dealership knows innately that there's over messaging their customer. I don't think any dealership [would] be like, no, I don't think I'm sending enough messages."
The solution requires consolidating vendors and sending fewer, more personalized messages that customers can actually respond to, rather than one-way marketing blasts.
Voice AI faces technical limitations, but text conversion offers immediate value.
Current voice AI technology struggles with latency issues that customers immediately detect as artificial.
"Even if it's 0.3 seconds, the consumer picks it up that it's a bot, right? And then they're circumvented, it's not a great experience."
The more effective approach involves converting phone conversations to text messaging, which eliminates callback loops and creates ongoing dialogue opportunities.
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CDPs aren't necessary for smaller dealer groups using AI effectively.
Customer Data Platforms require significant investment that may not justify the cost for smaller operations.
"If you're a single point store, even if you have two, three, four, five stores, like is it worth it to invest in this CDP? Like, if you got to spend, let's say a million bucks, like that's just cash. How many cars do you have to sell to recoup that million dollars?"
Some dealer groups are bypassing CDPs entirely and using AI to synthesize data from existing CRM and DMS systems instead of making large capital investments.
AI should replace people in specific tasks to improve overall operations.
The industry conversation about AI replacing workers misses the broader opportunity for operational improvement.
"Of course it's gonna replace people, but there's also this fallacy, which they think like technology will come in and completely eradicate that position in which the person will be left out of a job. That's not really the case. A lot of dealership groups will repurpose that person as something that [they’re] much better suited for."
This replacement allows dealerships to redeploy human talent toward higher-value activities like personalized customer service and relationship building.
Fixed operations compete on convenience rather than price with independent shops.
Service departments lose customers primarily due to convenience issues, not pricing differences.
"You go to the average consumer and you ask them what the price of an oil change is, the Jiffy Lube versus the dealership, they would not be able to tell you. The reason they go somewhere else is out of convenience."
With 190,000 independent repair shops versus 36,000 franchise dealerships, convenience becomes the primary competitive differentiator.
Point solutions create tech stack complexity that harms customer experience.
The accumulation of single-purpose software tools creates operational inefficiency and customer confusion.
"There's this shift in a lot of dealership groups looking for a solution that can enable them to do just that...why do I need 29 different vendors to be messaging my customer? Can't one do it or can't two do it?"
This consolidation trend affects both dealer operations and customer experience as multiple tools often create conflicting communications.
Service departments hold more revenue potential than sales departments.
The focus on new vehicle sales overlooks the significant revenue opportunity in service retention.
"The money is not in the CRM, the money's in the DMS. And if you look at it, it's like, how are you going to get more people to service from you?"
With service customers representing 60 times the volume of sales leads and average repair orders of $460, service retention offers substantial revenue opportunities.
AI implementation requires strategic thinking beyond technology adoption.
Successful AI deployment depends on identifying specific operational problems rather than implementing technology for its own sake.
"There's a cohort that's looking for, ‘Hey, we need to do more with less,’ and there's some that are like, ‘Hey, we gotta sell more cars,’ or ‘We have to service more cars, but we can't take the additional expenditures that it might take to hire like we used to.’ It's pretty costly. "
Dealers should focus on operational efficiencies and customer experience improvements rather than simply adding AI tools to existing processes.
