Walk into almost any dealership group today and you’ll find no shortage of software. A DMS. A CRM. A website platform. Digital retailing tools. Call tracking. Service schedulers. Chat. Email. Reporting dashboards. And now, a fast-growing stack of AI tools promising to fix whatever the last tool didn’t. So if every dealership already has all this technology, why does it still feel like nobody has the full picture of the customer?
That question sat at the center of a recent V20 Voices conversation with Mike Morgan of Launch Labs, Jim Kosobucki of Morgan Auto Group, and Jeremy Nowling of Rohrman Auto Group. It wasn’t a conversation about which platform to buy next. As Morgan put it early on: “This isn’t a product pitch. This is a dealer to dealer conversation.” And the conversation that followed made a case that dealership leaders can’t really afford to ignore: the technology was never the hard part. The hard part is what happens, or doesn’t happen, to the data underneath it.
Here’s the operational reality most groups are working with. Sales activity lives in the CRM. Ownership and service history sit in the DMS. Website behavior belongs to the website vendor. Phone activity sits with call tracking. Marketing engagement lives inside whatever email or agency platform sent the last campaign. Each piece is useful in isolation. None of them, on its own, tells you who your customer actually is.
That fragmentation has a real management cost. Without a unified view, it’s hard to know who’s actively shopping, who’s quietly slipping away, who’s due for their next vehicle, or which of your marketing dollars are actually earning their keep. Kosobucki described where this is heading for dealers who get it right: “We’re capturing every web activity, every call activity, CRM activity, DMS activity, all of that information can be rolled up into a customer profile.” In other words: data isn’t just something you report on at the end of the month anymore. It’s becoming the operating layer the rest of the dealership runs on.
Every GM has seen the symptoms without necessarily naming the disease: bounced emails, dead phone numbers, duplicate customer records, service and sales histories that don’t line up. Nowling shared a number from Rohrman’s own experience that’s worth sitting with: “The biggest eye opener for us was finding out that 48% of our data that we had in our DMS was incorrect.” Not 5%. Not 15%. Nearly half.
When that much of the foundation is unreliable, everything built on top of it inherits the problem, campaigns underperform, service retention efforts miss real opportunities, and any AI tool layered in is working from bad inputs. Cleaning up the data isn’t glamorous work. It’s also the work that determines whether anything else you invest in actually pays off.
Most dealerships still default to a familiar playbook: pull a list from the DMS, send one message to the whole list, and hope enough of it lands. Nowling was candid about how that’s historically played out: “Traditionally in automotive, what we tend to do is we do an email blast to everybody in our DMS, and everybody gets that same message.” The problem is that a recent buyer, a long-time service customer, someone who abandoned the scheduler mid-booking, and someone casually browsing SUVs are not the same person having the same experience so why send them the same message?
Better data makes it possible to build tighter, more relevant audiences instead of one giant list. Kosobucki summed up the shift in approach: “The old spray and pray method is going away. We’re shooting with a laser gun now.” Less waste and better timing. Messages that actually match where the customer is in their journey.
Here’s a question worth asking at your next vendor review: if you own the customer relationship, do you also own the data about that relationship? Often, the honest answer is no, the audiences, the targeting rules, the attribution models live inside a vendor’s platform, not the dealership’s. Nowling laid out exactly what that risk looks like in practice: “If we cancel that vendor, the vendor takes all of the data, everything that we put into it, and now we have to start all over.”
That’s not just an inconvenience, it’s leverage you’re giving away. A sound data strategy flips the relationship: vendors plug into the dealership’s structure, rather than the dealership being trapped inside the vendor’s.
Practically, that means changing the questions you ask vendors from “what does your platform do,” to:
It’s tempting to think a customer data platform is itself the solution. It isn’t. Morgan was direct about this distinction: “There’s a big difference between buying technology and making it work inside a dealership group.”
The real work, data extraction, cleansing, appending, identity resolution, consent management, internal alignment, happens after the platform is purchased, not because of it. Kosobucki described how the value revealed itself gradually, as Morgan Auto Group built the structure out: “As you’re building it, your eyes start opening up.”
That’s the leadership lesson buried in this conversation: a data strategy isn’t a one-time install. It’s a capability you build, and it keeps paying dividends as more signals get connected.
Think about how few website visitors ever fill out a lead form. The rest, the people browsing inventory, comparing models, starting and abandoning tools, coming back later on a different device, represent real intent that most dealerships simply can’t see or act on.
That’s the case for identity resolution. As Morgan explained it: “As a dealership, you can only act on customers or interested shoppers that you can actually identify.”
Solve that, and you’re not just generating more leads, you are improving the experience for people who were never going to raise their hand in the first place. A service customer gets service messaging. An SUV shopper gets SUV messaging. Someone with a specific ownership history gets communication that actually reflects it. That’s better for the customer and a better use of the dealership’s marketing budget.
AI is the loudest conversation in automotive retail right now, chat, BDC, marketing, scheduling, follow-up, reporting, etc. But the panel was blunt about its limits. Morgan put it in a line worth remembering: “AI is only as good as the data that feeds it.” Feed it a customer profile that’s duplicated, outdated, or just wrong, and AI won’t quietly fix the mistake, it will scale it. Wrong message, wrong customer, wrong audience, faster.
Kosobucki offered a glimpse of what’s possible once the foundation is solid, website chat that actually knows the customer’s history: “Having that same capability on a website chat, that knows all this context about you, that’s going to be a game changer.” That’s the direction this is heading: AI with context, chat with memory, marketing with real identity behind it.
None of this matters as an abstract technology conversation. It matters because it shows up in revenue. Kosobucki shared one concrete result from Morgan Auto Group’s work: “We sold over 100 cars just from those data ups.” Those are deals that wouldn’t exist as traditional leads, they came from connecting signals across web, phone, and CRM activity that would otherwise have gone unnoticed.
Nowling pointed to a similar win on the service side: “We are now able to measure the revenue that we pick up off of abandoned audiences.” A customer starts booking service and doesn’t finish. That used to just be a dropped session. Now it’s a recoverable audience, with real, measurable revenue attached to following up.
Maybe the clearest leadership takeaway from the whole conversation was that this can’t be managed by committee, and it can’t be fully outsourced to a vendor. Kosobucki was direct about what’s required: “You have to have somebody in the store or in the group that kind of knows data. They have to know automotive data.”
That last part is the catch. A generic data analyst might understand structure and pipelines, but automotive data has its own dialect, the difference between a sold customer, a service customer, an equity opportunity, an orphan owner, a lease maturity, a declined service recommendation. Whoever owns this needs both data fluency and dealership fluency. In a large group, that might be a dedicated hire. In a smaller store, it might be a marketing director or operations lead who’s simply given clear ownership of the problem.
If all of this sounds directionally right but overwhelming, the first move isn’t buying another platform. It’s a plain audit of where things stand today:
From there, tie the strategy to a business outcome that matters to your group specifically, reduced ad waste, service retention, lease maturity capture, AI readiness, rather than chasing the newest buzzword. Nowling’s closing advice to dealers still on the fence: “Don’t wait much longer, because if not, the industry is going to continue to pass you by.”
The dealerships that come out ahead in the next phase of retail won’t be the ones with the most software installed. They’ll be the ones that own their data, clean it, understand what it’s telling them, and make every vendor fit into that structure, instead of the other way around. A CDP alone won’t do it. AI alone won’t do it. The newest marketing vendor alone won’t do it either.
What actually moves the needle is leadership: the decision to treat data as a core operating advantage instead of a technical side project nobody quite owns. Better data leads to better decisions. Better decisions lead to better operations. And better operations are what actually build a better dealership.
Listen to the podcast here: https://www.v20marketplace.com/podcasts/the-dealer-data-playbook/
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