How Trackstar mapped a fragmented TAM and scaled outbound across dozens of use cases

Where they started

Trackstar sells a universal API for supply chain systems. Jeremy Schneck and his co-founder Daniel built integrations to fragmented, legacy warehouse management systems and normalized them into one API. Customers pulled them into sales channels, carrier billing data, and ERPs. By the time they talked to Apero, they had more than 200 integrations and customers from startups through enterprises.

They had product-market fit. Founder-led sales had worked. The next step was hiring a sales team and going to market in a way that could scale. Demand was not the bottleneck. Buyer mapping was.

A universal API does not map to one vertical. Inventory forecasting tools, returns management platforms, supply chain visibility vendors, tech-forward ERPs, 3PLs, and lenders can all be buyers. Each use case has its own language, its own pain, and its own set of APIs on Trackstar's side. Every time the team discovered a new use case, it opened another pool of prospects. Manually finding and qualifying them did not scale.

Jeremy's first move was to hire a go-to-market engineer internally, someone who would learn Trackstar deeply enough to pattern-match prospects to use cases. In parallel he met with more than a dozen Clay agencies. Then he read a LinkedIn post from Michael Slawson on what to look for in that hire and realized he did not have the context to make the hire himself. He should work with someone who already did.

Finding the real targets

Someone prospecting for Trackstar needs to understand how an inventory management system differs from a returns management system, a 3PL, or a supply chain visibility tool, and which Trackstar APIs each one would buy. Generic list building would miss the fit or mis-message it.

Michael's pitch was to treat the engagement like an embedded hire. He was New York City based, wanted to be part of the team, and asked Jeremy to dump the same context he would have given a full-time GTM engineer. They spent hours on use cases: how each buyer type would connect to Trackstar, what problems they were solving, and which APIs applied.

That context became a detailed ICP list. For each company: what they do, the ways they could use Trackstar's API, and which products they should buy. Outbound could name the problem class without sounding like they had scraped something creepy off the website.

Sometimes a prospect's integrations page lists the WMS platforms they connect to. That is a clear signal. Often the site is generic, or the feature they need is not listed because it is still on the roadmap. Apero built AI agents scoped to individual use cases. They scrape websites, check integration libraries where they exist, and pattern-match against companies Trackstar already understands. A site that fits three use cases can trigger a fourth the model has confidence in, even when the fourth is not spelled out on the page.

Conference prospecting was Jeremy's least favorite work: manually opening a thousand exhibitor websites before a show. That flow now runs through the same engine. Attendee lists go in. A curated list comes out: who is a fit, and for which APIs.

What Apero actually installed

Outbound and LinkedIn run against a scored TAM mapped to Trackstar's use cases and product lines, not a single vertical slice. Messaging references the buyer's problem class and the systems they likely integrate with, without pretending the team read their stack from a hidden pixel.

LinkedIn is a constraint as much as a channel. Jeremy gets twenty-five connection requests and messages per day. Conference attendee lists often arrive two weeks before a show with five thousand to thirty thousand names. The job is to spend those twenty-five slots on the highest-confidence fits, with copy that matches why they need Trackstar. Response rates stayed strong because the list was prioritized, not because volume went up.

Trackstar has sales hires now. Founders are not manually prospecting. Jeremy described the old world as him scrolling conference websites; the new one is a fully automated pass that returns fits and API mappings.

CRM work is ongoing. Jeremy's read on the category: CRMs are an unsolved software category on their own. What makes it workable is automation on top. Apero is wiring call notes into tasks, using outbound to close and open follow-ups, and pushing context into the CRM so nobody spends three hours a day updating fields by hand. Jeremy called the CRM implementation "surgery." The goal is a system that stays current without manual hygiene.

Results

1. TAM scored against dozens of use cases and Trackstar API lines
2. Conference meeting schedules fully booked at every show Jeremy attends
3. Sales team prospecting from scored lists instead of founder manual research
4. CRM automation in progress: notes, tasks, and follow-ups flowing without manual entry

Jeremy's conference schedules are fully booked. He contrasted that with the twenty emails a day he gets from vendors who clearly know nothing about Trackstar. Trackstar's outbound prioritizes the attendees most likely to need the product, with messaging tied to how they would use it.

On pipeline, Jeremy credits the outbound work with hundreds of thousands in pipeline after Apero helped build and score the full TAM against dozens of use cases, then run cold outbound and conference outbound. He has also pointed more than fifteen companies to Apero when peers ask how Trackstar runs go-to-market at scale.

Founders proved the motion. Sales hires run it now. The research layer that used to be Jeremy clicking through exhibitor lists runs automatically and returns scored targets with API fit.

What he'd tell a peer

Jeremy's advice for a company with a broad, nuanced buyer map: do not assume you can hire your way out without knowing what "good" looks like. He started down the GTM engineer path and used Michael's post as the checklist for what that hire would need to do. Working with Apero was the faster route to the same outcome.

On agencies, his concern going in was whether an outside firm could learn Trackstar's nuance well enough to pattern-match use cases. Michael spent time researching parallel business models after the first meeting and showed up with context. That mattered.

He describes the engagement as a ten out of ten and says he would refer Apero without hesitation. "Whenever people go, how do you do go-to-market scalably? I'm like, I work with this awesome firm."