How Matador gives individual dealerships, dealer groups, and OEMs the right level of visibility into automotive AI performance.
Understanding how AI is performing at one dealership is fairly straightforward. A store can look at its leads, conversations, appointments, customer engagement, and team activity and get a good sense of what is working. The picture gets much more complicated when the person asking the question is responsible for five stores, fifteen stores, or an entire OEM network.
Opening each report individually and piecing the numbers together isn’t practical. Group leaders need to see which rooftops are getting strong results, which stores are losing momentum, how consistently the technology is being used, and where a process may need a closer look. The Matador Enterprise Dashboard gives multi-store dealer groups a way to see all of that from one place instead of building the story themselves from separate reports. OEMs have their own dedicated OEM Dashboard designed specifically for visibility across participating dealer networks.
Why single-store reporting stops working at scale
Every dealership using Matador already has its own reporting, which gives the store a clear view of its leads, conversations, appointments, AI activity, and employee activity. That works well when the people reviewing the numbers are managing one dealership and only need to understand what is happening inside that operation.
A dealer group or OEM is asking a different set of questions. They want to know how stores compare with one another, whether a dealership is improving or slipping, and where coaching or additional support could have the biggest impact. OEMs need similar visibility across much larger participating dealer networks. When those answers require someone to review every rooftop separately, reporting quickly turns into a time-consuming exercise.
That challenge only grows as dealer groups add more rooftops. A larger organization may be managing several brands, different systems, different teams, and stores that joined the group at different times. There are real advantages to operating at scale, but it is harder to use those advantages when the group does not have a simple way to see how the entire organization is performing. As AI in automotive becomes part of more dealership workflows, that group-level visibility becomes even more important.
The challenge of seeing what is happening across multiple rooftops
Most visibility problems start small. A manager might notice that response times feel inconsistent or that one process is not producing the same results it used to. They know something deserves attention, but the reporting does not always make it obvious whether the issue is lead volume, customer engagement, process execution, staffing, or something else entirely.
Now apply that same uncertainty across several rooftops. Dealer groups rarely have identical environments at every store. Multiple brands may share one automotive CRM, newly acquired dealerships may still be using different workflows, and teams may have developed their own processes over the years. Even stores inside the same group can operate very differently from one another.
That is why comparing raw numbers from separate stores only tells part of the story. The information needs to be measured consistently before executives can make a useful comparison. A common reporting structure gives the group that consistency without forcing every dealership to run the exact same playbook.
The data also needs to be complete. If customer conversations happen outside the dealership's connected systems, part of the customer journey disappears from the reporting. Keeping communication and activity connected gives the group a much more reliable view of what is actually happening inside each store, especially as dealership AI becomes more involved in customer communication and follow-up.
What should dealer groups actually measure?
The number of messages sent is not enough to tell you whether AI is working, and neither is the number of appointments booked. Group leaders need to see what happened between those two points. They need to understand how many opportunities came in, how many were eligible for AI engagement, how customers responded, and what those conversations ultimately produced.
Matador's Enterprise Dashboard brings together leads, AI performance, tasks, automations, users, reviews, and trends. Group leaders can start with the organization as a whole and then look at an individual dealership when something stands out or needs more context.
The AI reporting follows a similar structure across different Matador agents. AI Engage tracks total leads, eligible leads, and engaged leads. Call AI shows calls answered, calls resolved, and appointments booked. For dealerships using conversational AI across multiple parts of the customer journey, that consistency makes the reporting much easier to understand.
The supporting metrics matter too. Messages by channel, AI-influenced appointments, engagement rates, videos sent, and opt-outs can help explain why one store's results look different from another. An appointment total gives you the result, but the activity around it often tells you what produced that result.
Comparing stores without pretending they are identical
There is an obvious problem with ranking dealerships using raw totals. A store receiving 450 leads a month is naturally going to produce different numbers from a store receiving 25. That does not automatically make the larger store the stronger performer.
Conversion between stages gives the comparison more meaning. A lower-volume dealership may be doing an excellent job engaging the opportunities it receives and converting those conversations into appointments. A high-volume store may have much larger totals while still leaving more opportunities on the table.
When a number needs more explanation, leadership can move from the Enterprise Dashboard into the dealership itself. The group-level view gives executives the high-level picture first, while the individual dealership’s reporting and Scorecard provide more detail behind the result. If one rooftop's engagement rate drops, the question is not simply whether the store is underperforming. The more useful question is what changed.
Finding the stores that need a closer look
The Enterprise Dashboard is most useful when it helps leadership decide where to spend its time. If one store is constantly improving while another is slowly declining, that trend should be easy to spot. Looking at the movement behind the monthly total gives the group a chance to catch that change earlier.
Handoffs can tell a similar story. When Matador escalates a conversation to a dealership employee, the reporting can show how frequently that is happening and what customers are asking about when it happens. If pricing questions are constantly being handed off at one store, the group has something specific to investigate. The AI may need better dealership guidance, the information available to it may need updating, or the internal team may need a clearer process for those conversations.
Finding what your best stores are doing right
The same reporting that highlights problems should also show leadership where things are going exceptionally well. If one rooftop keeps producing stronger engagement or appointment results than similar stores in the group, there is probably something worth learning from it.
That could be the way a store approaches follow-up or how its dealership-specific rules have been configured. If a lease-end offer is consistently generating better results at one dealership than at another, the group can look at what is different instead of asking every store to figure it out independently.
That makes standardization much more practical. Groups can take the processes that are producing strong results and use them as a starting point elsewhere, while each store keeps the rules, messaging, pricing guidance, and other decisions that need to remain specific to its operation.
Instead of deciding what a best practice should be, the group can see what is already working inside its own dealerships and use those results to guide what gets expanded.
Looking beyond appointments to understand AI performance
Appointments matter, but they are only one part of the picture. A dealership can have decent appointment numbers while barely using some of the AI capabilities available to it, leaving messages unread, or failing to follow up consistently with customers.
From there, the group can look at activity, engagement, and appointments separately. Activity shows how much customer communication is taking place. Engagement shows whether customers are responding. Appointment reporting shows how those conversations are turning into scheduled opportunities, including appointments influenced by AI, booked directly by AI, or created by dealership employees.
That level of visibility becomes especially useful when AI for dealership lead management is handling more of the work between the initial lead and the appointment. Keeping each category separate gives leaders a more accurate picture of what drove the result and prevents routine system activity from making customer engagement look stronger than it really is.
Creating accountability without mixing AI and employee activity
One of the benefits of bringing multiple stores into the same reporting environment is that everyone is working from the same definitions. A regional manager does not have to ask Store A for one report, Store B for another, and then figure out whether both teams calculated their numbers the same way.
The Users view also gives groups visibility into employee activity across their dealerships. Leadership can look at messages sent, customers contacted, review activity, videos sent and viewed, and appointments created by dealership employees. AI activity remains separate, so a salesperson's numbers are not being padded by work Matador completed automatically.
That gives groups a clearer understanding of how the technology and the team are working together. They can see where AI is moving opportunities forward, where employees are stepping in, and which people or stores are getting particularly strong results. As AI in CRM workflows becomes more common, separating those contributions is important if groups want a reliable view of both employee and AI activity.
For an OEM, the same principle applies across participating dealers. Response-time expectations and other program standards are much easier to manage when every store is being evaluated against the same underlying measurements.
Helping leadership decide what to do next
A dashboard full of numbers is not useful if someone still has to spend an hour figuring out what matters. It is meant to help leaders start broad, find something that deserves attention, and then get closer to the reason behind it.
A group executive may begin by looking at reach, customer engagement, and overall results across the network. If one store stands out, they can look at its AI funnels, recent trends, and dealership-specific reporting to understand what changed. The group view answers where to look, while the store view helps answer why.
Different people inside the organization can use that visibility differently. Executives may care about performance across the entire group, while regional leaders, GMs, and performance managers need to focus on the dealerships they directly support.
Reporting groups can be structured around those responsibilities so people see the stores that matter to their role. For a large organization, that is much more useful than presenting everyone with one massive list of rooftops and expecting them to sort through it themselves.
What this means for OEM dealer networks
OEMs face the same challenge at a much larger scale. A participating dealer network can include hundreds or thousands of independently operated stores, all with their own teams and processes, while the OEM is still trying to understand whether program standards are being met consistently.
Matador’s OEM Dashboard is separate from the Enterprise Dashboard and is designed specifically for this network-level view. OEM teams can see which participating dealerships are performing well against response and engagement expectations and which stores may need more support. They can also see where certain dealerships are producing strong results and use those examples to help other participating dealerships.
That makes enablement much more targeted. Instead of spreading resources evenly across a network, OEM teams can see where they are most likely to make a difference. Stores that are already performing well can help reveal what is working, while dealerships that are falling behind can receive support based on what the reporting is actually showing.
For OEMs supporting conversational AI platforms across a dealer network, having one reporting framework also makes it easier to separate successful processes from isolated store results. The OEM does not have to wait for the next audit or periodic dealer review to understand what is happening across the program because the data is already there to help teams make decisions as performance changes.
Turning reporting into better coaching
Reporting has the most value when someone does something with it. Seeing that a dealership's engagement rate dropped is useful, but understanding why it dropped and what the store should change is where the work becomes meaningful.
At the individual dealership level, Matador's 30-Day Performance Scorecard helps pull those pieces together by summarizing dealership performance and identifying areas that deserve attention. Adoption and engagement data can then help explain what may be behind the result.
For dealer groups, a regional leader can use the Enterprise Dashboard to identify the store that needs attention, then use that dealership’s Scorecard and reporting to have a much more productive conversation. Instead of telling a GM that the store needs to improve its numbers, they can talk about the specific part of the process that is creating the problem. If another rooftop in the group is handling that same part of the customer journey particularly well, leadership also has a real example to work from.
The following month provides the next piece of the story. The group can see whether the change worked, whether the metric improved, and whether the same approach is worth applying somewhere else. Reporting becomes part of an ongoing improvement process rather than something that gets reviewed once and filed away.
The right reporting view for every level
Matador’s reporting is designed around the level of the organization looking at the data.
For an individual dealership, the Matador Scorecard provides a store-level view of performance and helps teams understand what is working and where there may be opportunities to improve.
For multi-store dealer groups, the Matador Enterprise Dashboard provides a centralized view across rooftops. Executives can compare results, review how different Matador AI agents are contributing, spot changes in performance, and move into an individual dealership whenever they need more detail.
For OEMs, the Matador OEM Dashboard is a separate reporting experience built for visibility across participating dealer networks. OEM teams can understand where program standards are being met, recognize strong-performing stores, and direct coaching or support toward the dealerships that need it.
Ready to see what Matador can do across your dealership, dealer group, or OEM network? Book an appointment with our team to explore the reporting experience built for your organization and see how Matador can help you measure performance, spot opportunities, and improve results.
