PartsPulse

Ask most parts dealers how their inventory planning works. They will describe a person. Someone who has been there for 20 years. Knows every bin, every part group, every reorder rhythm. No system behind him. Just experience, instinct, and a binder full of rules that only he fully understands. It works. Until it doesn't. They all worry about that one guy retiring someday, but knowledge shouldn't retire when the person does. Most operations are missing a system that learns what that person knows, reads demand signals by part group, and keeps the inventory plan current whether or not that person walked in this morning. Availability sells. Having the part is the first thing, before price, relationship, or anything else. The cost of not having it isn't just a lost sale. It's a customer who found it somewhere else and may not come back. Knowledge shouldn't live in one person's head. It should live in the system.

Most parts dealers use what's called cost-plus pricing. Start with what the OEM charged you. Add a margin. That's your price. This approach is simple but completely disconnected from what your customer is actually willing to pay. Airlines figured this out decades ago. Hotels too. Prices move with demand, with behavior, and with what each type of buyer is willing to spend. Parts distribution is one of the industries still anchoring price to cost rather than to the market. The gap that creates is invisible until you know where to look. A repair shop buys differently from a fleet. A customer who pays full price on brakes will discount shop on bumpers. Every transaction a dealer records is a signal: who bought, what they paid, what they skipped, and how often they came back. PartsPulse reads those signals. Customers are grouped by how they actually buy (frequency, basket size, and price sensitivity) and then analyzed by part category within each group. This brings a clear picture of what each type of buyer is willing to pay and whether your current pricing is aligned to that or not. That is where the margin is. Understanding which customers respond to price differently than the rest, and on which parts. You've got points of margin already available to you, if you can find them. If this sounds like your business, let’s talk.

Most parts dealers use what's called cost-plus pricing. Start with what the OEM charged you. Add a margin. That's your price. This approach is simple but completely disconnected from what your customer is actually willing to pay. Airlines figured this out decades ago. Hotels too. Prices move with demand, with behavior, and with what each type of buyer is willing to spend. Parts distribution is one of the industries still anchoring price to cost rather than to the market. The gap that creates is invisible until you know where to look. A repair shop buys differently from a fleet. A customer who pays full price on brakes will discount shop on bumpers. Every transaction a dealer records is a signal: who bought, what they paid, what they skipped, and how often they came back. PartsPulse reads those signals. Customers are grouped by how they actually buy (frequency, basket size, and price sensitivity) and then analyzed by part category within each group. This brings a clear picture of what each type of buyer is willing to pay and whether your current pricing is aligned to that or not. That is where the margin is. Understanding which customers respond to price differently than the rest, and on which parts. You've got points of margin already available to you, if you can find them. If this sounds like your business, let’s talk.

Most parts leaders think their biggest problem is bad data. It's not. You have the data. Your inventory system has it. Your pricing tool has it. Your sales team has it. The problem is none of them can see what the other one knows. Your pricing function doesn't know a key dealer just cut reorders in half. Your inventory planners don't know a competitor dropped price on the same SKU last month. Your sales reps don't know which customers are one bad experience from walking. The data exists. The coordination doesn't. That's why we built PartsPulse around a single operating loop: Detect, Explain, Act. Detect patterns and gaps your current tools can't surface. Explain root causes with real intelligence, not another dashboard. Act on AI-recommended actions, or let the system act autonomously. It's not a better report. It's a fundamentally different way to run a parts business. The 15-minute parts business starts here. How many tools does your parts team use before making a single pricing or inventory decision?

The parts chain has three players. None of them see the full picture. OEMs have catalog data. Dealers have transaction data. Equipment owners generate demand signals every single day. Everyone is sitting on information. Nobody is sharing it. The OEM can't see what their dealers are actually being asked for. The dealer is doing mental math every time a customer walks in with a broken part. The equipment owner doesn't care about any of it; they just need their machine back on the road. Three players in the same chain, each solving the same problem alone, leading to margin leaking at every handoff. They’re not doing their job wrong. They are missing a system capable of connecting with each other. PartsPulse is the shared intelligence layer across your entire parts business. One platform that sees what your OEM data knows, what your inventory signals indicate, and what your customers are actually buying and puts that in front of the right person at the right moment. From siloed to synchronized. The 15-minute parts business starts here.

We're hiring at PartsPulse! We're looking for someone with strong supply chain consulting and project management experience. I would ultimately like to help this individual grow to be our Head of Professional Services. It's a great opportunity and we've got an exciting project for the right person to dig into! https://lnkd.in/eewq9UVS

Meet Jose Rivera, our new Head of Engineering. 👋 Jose comes to PartsPulse with deep roots in transportation and logistics data, having built high-velocity systems that process complex shipping data and navigate fast-moving regulatory environments. He's the kind of engineer who thinks in infrastructure and builds for scale. What brought him here? A familiar domain with a genuinely new problem to solve, and a team culture he connected with from the first conversation. His mission for the next year is to equip the engineering function with the right AI development tools, the right way. Not just adoption for adoption's sake, but with the process and guardrails to make it last. Outside of work, Jose has been playing guitar for years. We're glad to have you, Jose. Welcome to PartsPulse!

Most parts pricing structures were built for a business that no longer exists. The customer groups made sense when someone set them up. But buying behavior shifted. Market signals moved. And the people closest to that information, your sales team, aren't in the same room as the people setting prices. That gap is quiet. It doesn't show up as a crisis. It shows up as margin you can't quite account for. We put together a quick diagnostic for parts leaders who want to know where their pricing operation actually stands today. Nine questions. Three areas. Honest picture. What most teams find is that the data to make better pricing decisions exists somewhere in the business. It's just not reaching the people who need it. That's not a pricing problem. It's a systems problem.

Most parts businesses are already using AI. They just call it forecasting, pricing models, or customer segmentation. The shift now is that AI is moving from back-office math to a front-line decision partner. Large language models let teams ask plain-English questions instead of wrestling with SQL or Excel, then route those questions into real analysis across sales, inventory, and pricing data. Underneath, machine learning is constantly predicting events: who will buy, what they’ll buy, when they’ll buy, and what happens if you move price up or down. The next leap is orchestration. Systems powered by agentic AI can watch for rising excess inventory, connect it to changing customer preferences, and trigger targeted price changes to move stock while protecting margin. And AI-powered clustering can group customers by behavioral and spend attributes so you can align pricing and terms to true willingness to pay, instead of treating every buyer the same. For distributors and manufacturers, the opportunity isn’t just “adding AI.” It is redesigning core processes so prediction, explanation, and action are baked into how pricing, inventory, and commercial teams work every day.

If you're a leader in the parts business, these four numbers probably look very familiar. Not because they're from your specific organization. Because they quantify what most parts leaders are already feeling. ➡ Higher carrying costs than last year. ➡ Pricing decisions made without the full picture. ➡ AI running somewhere in the operation, but without a clear view to whether it's being used in the right way. ➡ Demand opportunity that's real but consistently being left on the table. The window to reinvent aftermarket in 2026 is wide open. But it takes a tech-driven approach coordinated across the full business to achieve it. Swipe through. Then let us know what you're seeing on your end.