Granular market data - industry sales figures broken down by location, customer type and product model - shows where demand sits and where it is going unserved. A national total can look healthy while hiding segments a brand is not supplying, branches holding stock in the wrong cities and sales territories drifting without anyone noticing. Stuart Torpy, Managing Director of Wirtgen Australia, explains how that level of detail guides which markets to enter, how to compete in them and how to serve customers at lower cost.
"By way of example. Let's say the market is 200 units." For a managing director, that sentence raises more questions than it answers. Which models? Which cities? Which customer types? Granular market data answers those questions, and the answers change what a business does next. Wirtgen Australia, part of the Wirtgen Group, sells specialised road construction equipment across Australia and New Zealand - a niche market where a handful of units can move a result. For Stuart Torpy, detail is not a nice-to-have layered on top of industry market share data. It is the part that makes the data usable.
A market total is not enough to act on
A single national figure tells you the size of the game, not how to play it. Stuart puts the standard bluntly: "Because we are a niche player, we should know the markets that we play in with so much detail and better than anybody else."
That standard is hard to meet with broad numbers. As Stuart says, "You can't just be, the market's 200 units and here you are. That doesn't give us enough, doesn't give anybody enough."
The detail that matters spans several dimensions at once - and small shifts in any of them can change the commercial picture:
- locations, because demand in Perth is not demand in Sydney
- customer types, because owner-operators and tier 1 contractors buy differently
- models and product classes, because "sometimes it's only one group to the left or one group to the right that can make a massive difference"
Without that resolution, a business is operating on assumptions dressed up as data.
Granular market data shows where you are not competing
The clearest payoff from granular market data is seeing gaps you did not know existed. "Having granularity of the market itself gives you the ability to say, oh, there's a whole segment over here that we're currently not supplying because we don't bring that model in here, but it's available globally," Stuart says.
That discovery starts a strategic conversation, not just a reporting line. When Wirtgen Australia spots a segment it is not serving, it can weigh up whether to pursue local compliance for a model that already exists elsewhere in the group's range. In Stuart's words: "Once we know what the market is, we can then say, do we want to play? And if so, how do we want to play? Once we are there playing, then you've got to know what the score is."
The sequence matters. Market entry, positioning and performance tracking all hang off the same underlying detail. A national total supports none of those decisions on its own.
Location detail cuts the cost of serving customers
Granularity also pays off in operating cost, not just strategy. Wirtgen Australia runs five branches across Australia and New Zealand, and stock has to sit somewhere before it sells. "We spend way too much money shipping machines around between them because we think customer X is in Perth but he's really in Sydney," Stuart says.
Location-level market data reduces that guesswork. "The more we know where the customer base is, the cheaper we can actually supply the products to the customers." Demand data by area shows where machines should wait for buyers, instead of machines chasing buyers after the fact. The same logic drives inventory placement decisions with market data across a multi-branch network: position stock where the market is, not where habit says it is.
Participant-reported data beats estimates and import statistics
Detail is only useful if the underlying numbers hold up. Stuart draws a sharp line between the market segments where Wirtgen Australia has participant-reported industry statistics and those where it relies on estimates. In the covered segments, "the level of data we get is not anecdotal, it's factual."
Territory-level views make performance assessment factual
For sales management, micro-level detail turns opinion into evidence. "We can see where every deal is. Not to the customer level, and that's fine too, but we get a really good picture of who's underperforming or overperforming," Stuart says. Head office may see one territory; a local MD sees individual salespeople's patches. "We need our level of detail at a very micro level to be able to make those assessments of performance."
The same territory-level view supports fair dealer benchmarking by territory - judging performance against the local market rather than a national average. It also simplifies reporting upwards. Stuart files quarterly lost-sales reports to head office for each product line, and the segment with industry statistics is the easy one: "For reporting upwards, I love compaction because I just pull all the data out of PowerStats and throw it straight into our system for uploading to HQ."
Import statistics measure movement, not sales
Where no industry statistics exist, businesses fall back on import data - and Stuart is direct about its limits. Import statistics count machines entering the country, including the ones still sitting in a distributor's yard. "Import statistics would say that we've sold the machines. Absolute fallacy," he says. He recalls being told his brand had lost significant ground in one product class: "We've sold two, and you're saying we've lost 50 in a month?"
Participant-reported retail statistics avoid that distortion because they record what was actually sold, reported by the participants themselves under accuracy and transparency provisions. Stuart's conclusion applies well beyond his industry: "Without that level of granularity, those decisions are like throwing darts at a board, blindfolded."
Key takeaways
- National totals hide the detail decisions depend on - break the market down by location, customer type and model before acting.
- Granular data surfaces segments you are not supplying, turning a reporting exercise into a market entry conversation.
- Location-level demand data cuts distribution cost by positioning stock where customers are, not where you assume they are.
- Micro-level territory views make sales performance assessment and head-office reporting factual rather than anecdotal.
- Import statistics measure what entered the country, not what sold - participant-reported retail data is the stronger reference point.
Frequently asked questions
What is granular market data?
Granular market data is industry sales data broken down to the level at which decisions are made - location, customer type, product model and time period - at the maximum possible resolution as allowed by the project's reporting model. Instead of one national total, it shows how demand is distributed across those dimensions, so a business can see which segments it serves, which it misses and how its position changes over time.
Why is a national market total not enough for planning?
A national total hides the variation inside it. A brand can hold a healthy national share while being absent from particular regions, customer types or product classes. Decisions about stock, sales coverage and product range are made at those lower levels, so the data needs to reach them too.
Are import statistics a reliable measure of market share?
Import statistics are one useful input, but they measure machines entering a country rather than machines sold to customers. Stock sitting unsold in a yard still counts as an import, so they can overstate or mistime sales significantly. Participant-reported retail statistics record actual sales and give a firmer basis for market share comparison.
How does granular market data reduce distribution costs?
It shows where the customer base is, area by area, so stock can be positioned near likely demand instead of being shipped between branches after a sale is found. For Wirtgen Australia, knowing where the customer base sits means less money spent moving machines between its five branches.
Know the market at the level you manage it
Deciding where to compete, where to hold stock and how each territory is performing takes market detail at the level those decisions are made - by location, customer type and model. That is what industry market share data delivers when it is collected from participants and reported at a granular level. To see how a data sharing programme could give your industry that resolution, contact PowerStats.
