NEW:
Turn Customer Data into Revenue with AI-Powered Smart Campaigns
%20(2).webp)
Welcome to the seventh episode of Flyntlok Unlocked.
The idea here is to take you behind the scenes, unlocking Flyntlok product insights, with the very people building and implementing the tools you use every day. Thank you for joining us!
I’m your host Jenny Moebius, Flyntlok’s CMO, and today we’re diving into something a little different. Instead of focusing on one feature, we're going behind the road map to look at how features get built. AI is changing how quickly product teams can turn ideas into working software. But speed only matters if you're solving the right problems. That's where dealer feedback comes in.
Flyntlok Head of Product Danielle Karr takes us behind the road map to explain how focus groups, support signals, betas, and a new development structure turn real dealership feedback into practical product improvements.
"AI helps us build faster, our customers ensure we build the right things."
--
Host: Jenny Moebius, CMO, Flyntlok
Guest: Danielle Karr, VP of Product, Flyntlok
In Episode 7 of Flyntlok Unlocked, Flyntlok CMO Jenny Moebius sits down with VP of Product Danielle Karr for a different kind of product conversation. Rather than digging into a single feature, they pull back the curtain on how Flyntlok decides what to build, how AI is changing the development process, and why dealer feedback is becoming even more important as software gets faster to create.
The central idea is simple: AI can help product teams build faster. But speed only creates value when you’re solving the right problems.
At Flyntlok, that means combining AI-powered development with something decidedly human: ongoing conversations with the dealers who use the platform every day.
As always, the episode starts with the person behind the product.
Danielle’s four-year-old son, Nico, is firmly in his machines-and-trains era, and he is convinced that his mom spends her days repairing excavators, tractors, and snowblowers.
Danielle has made little effort to correct him.
That misconception became even more entertaining early in her time at Flyntlok when a dealer introduced her to a hi-rail truck, a vehicle capable of traveling on both roads and railroad tracks. For a kid obsessed with trains, trucks, and engines, it was essentially everything he loved rolled into one machine.
It’s a lighthearted story, but it also points to something that comes up repeatedly throughout the episode: working closely with equipment dealers has brought Danielle much closer to the real-world businesses, machines, workflows, and people Flyntlok’s technology supports.
Before joining Flyntlok, Danielle spent much of her 20-year technology career at FactSet, working at the intersection of product management, engineering, strategy, and large volumes of financial data.
At first glance, financial technology and an equipment dealer management system may seem worlds apart. Danielle sees a clear connection.
Both environments generate enormous amounts of data. In a dealership, that can include everything from part numbers, quantities, and inventory to transactions, service activity, customer information, and financial data.
The product opportunity is not simply to collect all of that information. It is to turn a huge volume of data into insight that helps people make better business decisions.
That problem felt familiar to Danielle. What was dramatically different was the moment in technology she was stepping into.
Danielle joined Flyntlok as advances in AI models were rapidly changing what software teams could accomplish.
Soon after arriving, she and several Flyntlok developers attended The Gauntlet, an intensive two-week AI training program hosted by Main Street Partners. The team spent its time learning how to incorporate the newest AI tools into both the development process and the products customers ultimately use.
But Danielle says one aspect of that training mattered just as much as learning the technology.
The team was constantly challenged to answer questions like:
That emphasis has become fundamental to the way Flyntlok thinks about AI.
AI provides an incredibly powerful new set of development tools. But those tools still need direction.
One of the most tangible examples of AI inside Flyntlok’s development process happens before a developer even starts solving a customer issue.
The Flyntlok team has built an internal tool that can take an incoming support ticket — whether it contains a bug, enhancement request, or question — and perform much of the preliminary investigation automatically.
The tool can examine Flyntlok’s code base, look into the relevant customer environment, analyze what may be happening, and return a comprehensive set of findings to the developer.
That work might otherwise require hours of manual investigation.
Instead, the developer begins with considerably more context and can focus on determining the right solution.
Multiply that time savings across a development organization, day after day, and AI can significantly increase the team’s ability to respond and move initiatives forward.
But Flyntlok is also applying those same capabilities directly to the product.
The goal is not for Flyntlok’s developers to be the only people benefiting from AI-powered efficiency. It is to deliver that same type of acceleration to dealerships through features that eliminate repetitive work and make existing workflows easier.
AI changes one of the fundamental constraints of software development.
Historically, teams spent enormous amounts of energy asking, Can we build this?
As execution becomes faster, Danielle says the harder question increasingly becomes:
Are we building the right thing?
AI can be sent off to accomplish an enormous number of tasks. Dealers, however, do not need an endless stream of new features simply because those features are possible to build.
They need technology that meaningfully improves their businesses.
That makes understanding what is actually happening inside dealerships more important than ever: how market conditions are changing, where workflows are breaking down, what customers are asking of dealers, and which improvements will have the greatest operational or financial impact.
As Jenny sums it up in the conversation: speed can create noise. Talking to dealers creates direction.
To create more ownership and depth around those dealer problems, Flyntlok has reorganized development around six current focus areas:
Small groups of developers are responsible for becoming deeply immersed in each area.
Their job is not simply to work through a list of requested features. They are expected to understand how dealers actually operate in that part of the business, where friction exists, and what needs to evolve for the product to become more valuable.
At the same time, Flyntlok is continuing to collect signals about what the next development focus areas should be.
The structure creates concentration without closing the door to emerging dealer needs.
Before joining Flyntlok, one of Danielle’s biggest questions was whether she would have meaningful access to customers.
For her, that was not a nice-to-have.
It was a requirement for building a strong product.
At FactSet, Danielle had worked with customers who used their software every day and were deeply invested in how it worked. Their willingness to give detailed feedback made the product team significantly more effective.
She wanted the same relationship at Flyntlok.
What she found exceeded her expectations.
Flyntlok dealers tend to care intensely about the technology running their businesses. They are constantly thinking about how to become more operationally efficient, generate more revenue, connect different parts of the dealership, and get more out of the tools they already use.
Danielle describes them as builders themselves: people who can see how better technology can create revenue opportunities and operational improvements across a dealership.
That makes the customer community unusually willing to sit down with Flyntlok, share candid feedback, help ideate, and unpack problems.
And while Flyntlok emphasizes internal industry training — drawing in part on founder and CEO Sean McLaughlin’s dealership experience — Danielle says there is no replacement for seeing how dealers actually work and asking them questions.
Of course, listening to customers does not mean building every individual request exactly as it was submitted.
Different dealers may ask for different — or even conflicting — things.
The product team therefore uses two techniques to get beyond the initial request and identify the broader problem worth solving.
The first is the Rule of Seven.
When Flyntlok is investigating a particular topic, the team aims to speak with at least seven customers. Looking at a challenge from multiple dealerships and perspectives helps the team triangulate what is truly happening and design something capable of benefiting a broader portion of the customer base.
The second is the Five Whys.
Instead of accepting the first explanation of a problem, Danielle and the team keep asking why.
The goal is to keep peeling back layers until the team understands the underlying operational problem — not merely the feature request sitting on top of it.
Flyntlok put this approach to work in July with its first major series of customer office hours across the six development focus areas.
The response was larger than the team expected:
142 registrations, representing 63 individual users across 32 Flyntlok customer organizations.
The Flyntlok team came prepared with survey questions, discussion topics, and early product concepts and demos.
Dealers came prepared with opinions.
And according to Danielle, the conversations frequently began to guide themselves. Dealers compared workflows, challenged assumptions, described how work moved between departments, and helped one another expose the deeper operational issues underneath individual requests.
That depth is difficult to capture in a written feature request.
A support ticket may contain a few sentences and a screenshot. A live conversation can reveal who performs the task, how often it happens, where the handoffs occur, and why what sounds like a tiny inconvenience may actually create substantial friction because employees repeat it dozens — or even hundreds — of times.
The office hours produced both new ideas the team had not previously considered and strong validation of concepts already on the road map.
One of the clearest examples came from conversations about Smart Receive, Flyntlok’s AI-powered receiving functionality.
Smart Receive was initially designed around invoices. A dealership can upload an invoice and use AI to extract and reconcile information such as quantities, prices, and fees instead of manually keying everything into the system.
During office hours, dealers highlighted an important distinction.
The invoice workflow is not necessarily the same as the packing slip workflow.
An invoice may go to someone responsible for billing and accounts payable. A packing slip often reaches another employee who is physically receiving parts and needs to make them available to customers or the service department as quickly as possible.
And the packing slip frequently arrives before the invoice.
That insight broadened the problem the product team was trying to solve.
Flyntlok began investigating how Smart Receive could support packing slips as a separate document type, using the same AI-driven approach to reduce manual data entry and accelerate receiving.
The benefit goes beyond saving time at the parts counter.
When parts can be received and made available faster, the impact travels downstream to service as well.
It is a perfect illustration of why understanding the full dealership workflow matters.
Another product idea emerged after the CRM office hours went slightly off script.
Dealers spent roughly 18 minutes discussing something broader: how to learn and get more value from everything Flyntlok can do.
The platform has substantial functionality, and customers want to make sure they are using it as effectively as possible. Several dealers expressed interest in receiving more guidance directly inside the application.
That conversation connects directly to an AI project Flyntlok is currently testing internally.
The company is developing an AI chat experience designed to answer questions about Flyntlok — for example, how to configure a feature or complete a particular task.
The important distinction is that Flyntlok does not intend for this to replace its human support team.
Instead, the idea is to give customers another way to quickly answer straightforward questions while keeping Flyntlok’s support team available whenever a customer wants or needs a person.
And the team is taking accuracy seriously.
Today, the experience is being used internally by Flyntlok support. Incoming questions can be put through the AI system, and support team members then validate whether the answer is correct.
Flyntlok is tracking those results and identifying where the AI needs additional context.
Danielle’s standard for releasing it externally is intentionally high: the team needs to be extremely confident in the accuracy of the answers before customers are asked to trust them.
Office hours are only one source of product feedback.
Danielle describes four primary channels Flyntlok uses to understand dealer needs:
1. Focus groups and office hours
The new office-hours program creates direct, group conversations around targeted areas of the product. Based on the initial response and the quality of the feedback, Flyntlok plans to continue these sessions every other month.
2. Support tickets
The product team looks across support activity for patterns. Repeated questions or friction can reveal opportunities for small improvements inside one of the existing product focus areas — or help identify an entirely new area the development team should prioritize next.
3. Beta programs
Beta programs are particularly important for AI-powered functionality. Flyntlok can release a new capability to a smaller group of interested customers, observe how it performs in real dealership workflows, and collect feedback before expanding access.
4. Direct customer conversations
Product and development teams also conduct one-on-one outreach with customers who use specific areas of Flyntlok heavily. Danielle, for example, is actively speaking with customers about questions related to the mobile and rentals road maps.
Together, these channels give Flyntlok both breadth and depth: patterns from across the customer base and detailed conversations that explain what is behind those patterns.
Collecting feedback is only useful if dealers can eventually see what happened because of it.
Flyntlok currently communicates product changes through release notes every two weeks, documenting what has changed across the platform.
When development work originated in a support request, the team also aims to update the corresponding ticket so the dealer who raised the issue knows when it has been addressed.
Flyntlok is also exploring ways to bring product updates directly into the application itself.
The idea is to make announcements more relevant to the individual user. A parts employee, for example, could be alerted to new Smart Receive functionality, while someone in service could see information about an update relevant to their work.
As Flyntlok’s development pace increases, helping customers discover and adopt the right capabilities becomes another important part of the product experience.
The episode closes with a rapid-fire round on AI.
Danielle points to one major misconception about AI-powered software development: the idea that AI can simply build autonomously, indefinitely, and still consistently produce high-quality software.
Today, the human in the loop remains critical.
Developers still need to validate architecture, quality, accuracy, and ultimately whether the software being created has a meaningful impact.
So what should AI accelerate?
Execution.
Many of the individual steps involved in creating software can now happen substantially faster.
What should not be rushed?
Research. Customer conversations. Strategy. Road-map decisions. Prioritization.
Those remain deeply human.
And when Jenny asks whether AI makes customer feedback more or less important, Danielle’s answer is unequivocal:
More important.
The easier it becomes to create software, the easier it also becomes to create more noise.
Customer feedback is what helps Flyntlok distinguish between what it could build and what dealers actually need.
Flyntlok’s next round of office hours is planned for September.
This time, the sessions will begin by showing customers what has happened since the July conversations.
Some ideas may already have become released functionality. Others may appear as early designs or prototypes that need another round of dealer feedback.
The team will also share more about what it believes should come next on the road map — and ask dealers to challenge and shape those priorities.
And once again, part of each session will simply be left open.
Because some of the most valuable conversations from the first round were the ones nobody planned.
AI is dramatically increasing what software teams can accomplish.
But at Flyntlok, the goal is not simply to produce more software.
It is to build technology that saves time, removes friction, improves dealership operations, and ultimately helps dealers run stronger, more profitable businesses.
AI can accelerate the work required to get there.
Dealers provide the direction.
That is the model Flyntlok is building around: use AI to move faster, keep humans firmly in the loop, and bring customers closer — not farther away — from the product development process.
