An operator gets a lead through Sirelo or Relocately, quotes it, wins it, sends a crew, gets paid. Nothing about that transaction is unfair. The platform found a customer who needed a mover; the operator did the job well; the invoice cleared. By the measure most operators use to judge a lead source, that’s a good month.
Something else happened in that same form submission, though, and it didn’t cost the platform anything extra to collect. It logged the route. It logged the price that won and the prices that lost. It logged how many other operators bid, what season it was, whether the customer took the cheapest quote or paid up for the one with better reviews. None of that data was the point of the transaction, from the operator’s side. It was the entire point, from the platform’s.
That’s the distinction worth sitting with before writing this off as a normal cost of doing business. A lead marketplace isn’t selling access to a customer and quietly logging some exhaust data on the side. The lead is the receipt for a transaction that already happened. The pattern built from a million of those receipts is a separate asset entirely. It gets more valuable every time any operator, including a competitor, completes a job through the platform. And no single operator can ever buy it back, no matter how many leads they purchase. This is a data-moat asymmetry, and it’s worth naming precisely instead of shrugging past it.
It also shows up in a smaller, more immediate way that an operator feels firsthand. A slow March could mean the corridor is quiet industry-wide, or it could mean something in that operator’s own funnel broke: a slower response time, a price that drifted out of range, a competitor who started undercutting on exactly that route. An operator working from their own numbers alone can’t tell those two situations apart. The marketplace can, instantly, because it’s watching every other operator’s March at the same time. That’s the difference between adjusting a quote and panicking over a dip that was never really a dip.
What one enquiry teaches, and what a million enquiries teach
A single lead teaches an operator almost nothing that generalizes. This customer wanted this corridor; this price won or lost; this crew did or didn’t get booked. At roughly 200,000 of those enquiries, which is what Sirelo says consumers requested through it in 2025, an entirely different kind of information starts to exist. Which corridors are searching heavier this quarter than last. Which price bands make a customer keep comparing versus book on the spot. Which regions convert fast in January and go quiet in July. Nothing on that list lived inside any single enquiry. It only becomes visible once enough of them get stacked on top of each other. The only party present at every one of those 200,000 enquiries is the platform that ran them.
Relocately’s model sharpens the same point. Its site shows a customer up to six competing quotes per enquiry, drawn from a roster of more than 600 partners. Every time that comparison page loads, the platform watches which of those six bids won, against what price gap, in front of what kind of customer, and stores the result. Across the 175,000 users the company says it has served, that adds up to a six-figure run of live pricing experiments the platform never had to design. The bids are the operators’ own. The result of each experiment stays with the platform.
The asymmetry compresses into one line: the operator supplies an outcome, one enquiry at a time. The platform is the only party positioned to read the pattern across all of them, because it’s the only party standing at every transaction in the category, not just its own.
The business model, not a side effect
If this pattern were incidental, an accident of running a website, marketplaces wouldn’t build product around it or describe it to their own shareholders as an asset. They do both, in writing, in the exact adjacent industry a moving marketplace most resembles.
Angi, the home-services marketplace IAC formed in 2017 by combining HomeAdvisor with Angie’s List, runs a business model close enough to a moving marketplace’s that the comparison barely needs stretching: a homeowner submits a request; several matched pros compete for it; the pros pay for each match either way. In its own SEC filings, Angi tells investors that a proprietary algorithm decides which pros a homeowner is matched with and where each one appears, weighing the service requested, the location and how many pros are available. The same filings say trust in its ratings and reviews contributes significantly to its ability to attract both homeowners and pros.
Thumbtack, a service marketplace one category over from moving, built a feature called Instant Match on the project requests, structured intake answers and pro preferences running through its platform. By the company’s own account, the share of requests receiving three or more competing quotes more than doubled in the markets where it fully rolled out. Thumbtack turned that aggregate pattern into a product change. The change didn’t make life easier for the pros on the platform. It put more of them in competition for each job. The platform could engineer that outcome because it held every side’s requests and preferences at once.
Neither Sirelo nor Relocately has published the internal version of what Angi and Thumbtack describe openly about their own systems. The evidence doesn’t show they run an identical mechanism, and this article doesn’t claim it. What their own published numbers do establish is the scale of raw material available to build one: over 200,000 consumers requesting quotes in a single year, up to six competing bids on every enquiry, more than 26,000 movers listed in a single directory. A marketplace that size has the ingredients this pattern requires. It operates in a category that behaves the way two close-adjacent marketplaces say their own categories behave. Whether it has built the same system or not doesn’t change what those ingredients can produce.
Moving marketplace data ownership: what no operator can buy back
A moat, in the strict sense, is an advantage a competitor cannot purchase their way past. It compounds: it gets stronger with every transaction that runs through it. And that strength doesn’t transfer to whoever’s paying for a single transaction at a time. That’s exactly the shape of the problem here, and it’s worth running the arithmetic rather than asserting it.
Picture an operator who runs UK-to-Australia relocations and buys leads from a marketplace for two straight years on that corridor. They quote 150 times and win 30 of those jobs, purely for illustration. At the end of two years, that operator knows 150 outcomes: which quotes lost, which won, roughly what price cleared each time. What they don’t know, and can’t learn by buying more leads on the same corridor, is how many other operators bid against them on each of those 150 enquiries, what the full spread of competing prices looked like, or whether their own win rate is ahead of or behind the category average that quarter. They also don’t know how many enquiries on that corridor never reached a quote at all, because the customer abandoned the form after the first few numbers. The marketplace has every one of those answers, for every operator working that corridor, not just this one. Buying leads faster just generates more of the exact data point the operator already has plenty of, and none of the one they’re missing.
This is the same mechanism that put Zillow in charge of its own category. Tech analyst Ben Thompson has described the mechanism plainly in his own writing on the company: Zillow built an audience through tools people found genuinely useful, and that audience became something the real estate agents on the other side of the platform had to answer to. No contract required it. Zillow controlled where buyers started looking. Zillow’s own SEC filings list the database underneath its Zestimate tool among the company’s competitive advantages: roughly 140 million U.S. homes, built through substantial investment and the aggregation of multiple sources of property, transaction and listing data. No individual agent, however many listings they run through the platform, ever gets handed that view.
Multi-homing doesn’t fix it either. An operator who buys leads from Sirelo and Relocately and every other comparison site in the category still only sees their own outcomes on each one: their wins, their losses, their prices. Running the same corridor through three marketplaces instead of one produces three separate keyholes, not a wider window. None of those platforms shares its internal aggregate with the operators generating it, and none of them has any reason to. The aggregate is the asset. Handing it out would give away the one thing that makes the platform worth more than any single operator’s own website.
Movaros builds the pattern under a brand an operator keeps.
Building on shared infrastructure means the search behavior and price sensitivity a business generates stay attached to its own name.
Getting the job doesn’t settle the data question
The honest objection deserves a straight answer: the operator got the job. The invoice cleared. The truck rolled. Isn’t that a fair trade, whoever keeps the data afterward?
For plenty of operators, yes, on its own terms. Marketplace leads keep a fleet booked through months that would otherwise sit idle, and nothing here argues that paying for a qualified lead is a bad deal by itself. But that concession answers a different question than the one this article asks. The transaction and the data transfer happen inside the same form submission. It’s tempting to treat them as one exchange that settles the moment the invoice clears. The transaction settles. The data transfer doesn’t. It compounds, every time, whether this particular operator wins or loses, whether they ever buy another lead from that platform again. For every year they were active, an operator who stopped buying leads tomorrow would still have contributed to a pattern the platform keeps using long after they’ve left the category.
This doesn’t make Sirelo or Relocately unusual, and it isn’t a case against either one specifically. Almost every marketplace with a search box works this way, because that structure is the reason a marketplace is worth building in the first place: once enough transactions aggregate, the pattern becomes more valuable than any individual fee charged to produce it. The mistake isn’t using a marketplace. It’s assuming the per-lead fee is a complete description of what changed hands.
Platforms treat that pattern as worth defending, not as a side effect. In September 2021, DoorDash sued New York City rather than comply with a new law requiring delivery platforms to share customer data (names, phone numbers, emails, delivery addresses) with the restaurants that actually cooked every meal. DoorDash argued the disclosure violated customer privacy and would let restaurants use its trade secrets to compete with it. Restaurants that wanted the data argued the opposite: the rule would let restaurants market directly to the customers they’d been feeding for years instead of leaving that relationship entirely inside a platform that never touched a single plate. A company doesn’t take a fight like that to court over information it considers incidental.
The far end of what this incentive can produce showed up in Amazon’s own private-label business. The Wall Street Journal reported in April 2020 that Amazon employees had used data from individual third-party sellers to help develop competing Amazon-branded products. Those sellers were themselves paying Amazon for the privilege of listing. The practice violated the company’s own policy and contradicted an executive’s 2019 testimony to Congress, and by 2022 the SEC was reportedly investigating Amazon’s disclosures about it. There is no evidence that a moving marketplace does anything resembling that. What the episode shows is how far a company will go to protect aggregate participant data once it crosses from a courtesy into a real asset. If the aggregate view weren’t worth defending, none of that risk would have been worth taking.
The same asymmetry shows up in reputation too: why your reviews belong to the platform follows the identical logic as the search data it collects.
The pattern that never shows up on the invoice
Buying more leads, quoting faster, or negotiating a better rate per lead doesn’t solve this. Every one of those moves operates inside the same structure: one transaction at a time, on someone else’s platform, feeding someone else’s pattern. The lead price is negotiable. The pattern was never built to be sold.
An operator gets their own version of that view only by owning the channel the enquiries arrive through in the first place. Then the search behavior, the price sensitivity, and the seasonal pattern belong to a system built around that operator’s own name, not a marketplace’s. Building demand under a brand an operator controls, rather than renting it by the lead, makes a case that runs deeper than cost. Over a long enough horizon it’s cheaper, but the real reason is structural, not financial: it’s the only setup where the pattern compounds for the business that did the work, instead of for whichever platform happened to be standing between that business and its next customer.
Concretely, that means a quote tool that logs what a visitor searched and where they dropped off belongs to the operator’s own site instead of a marketplace’s dashboard. It means a customer who abandoned a quote at a certain price point becomes a data point the operator can act on next month, not a number folded into someone else’s aggregate. The payoff doesn’t show up in the first week. It shows up in year three, when one operator has three years of their own demand pattern to plan around and the other has three years of invoices and nothing else. Every enquiry that ever came through their business went straight into somebody else’s database instead of their own.
An operator who never sees this clearly will keep mistaking the invoice for the whole transaction. The invoice was only ever the part the platform was willing to hand back.
Medieval merchant bankers traded on knowledge as much as on gold: exchange rates in several cities at once, carried by letters between their branches. A merchant trading in a single city knew only that city’s prices. The banking house knew all of them, and every merchant who used its network to move money was, without realizing it, feeding that same house a clearer picture of the whole market than any individual trader would ever assemble alone.
