Analytics isn't a feature.It's the premium tier you haven't priced yet.
Commercial software providers charge a median 25% price premium for analytics, in a survey of more than 500 of them. The build vs. buy question isn't only what it costs to ship. It's how much of that premium you keep, and when you start collecting it.
Your price card, with the tier that wasn't on it before. What it costs to get there is the whole build vs. buy question.
Every expansion conversation lands on the same slide
A customer asks for dashboards and the account manager wonders out loud whether that's an upsell. Then the board asks its quarterly question, and the honest answer is the one lever you already have.
A 25% premium, benchmarked.On static dashboards, in 2015.
The premium isn't a theory anybody has to be sold on. It was measured, and it was already going up.
Four numbers you already know.One you probably haven't run.
Only one field starts filled in, and it's the cited benchmark. Everything else is yours, and nothing here is stored or sent.
Run your premium math
Fill in the fields and this fills itself in. It's the number the build path never shows up as a line item, because nobody invoices for revenue that didn't happen.
Customers forgive free features.They don't forgive paid ones.
A premium tier raises the stakes on quality. Nobody escalates a rough free dashboard. They do escalate a feature they pay 25% extra for when it hands them a wrong number.
Churn runs backward
Churn on a premium tier isn't a usage problem, it's a downgrade. The customer stops paying the premium, your expansion story reverses, and the number your board is watching moves the wrong way.
The tier has to stay worth it
On the build path, the premium comes with a permanent engineering commitment to keep the thing worth paying for. That's not a launch cost, it's a subscription you pay to your own roadmap.
It lands in your COGS
A build and its upkeep sit in your cost of goods whether or not customers upgrade. The tier has to sell well enough to cover a cost you're paying either way.
That's what turns maintenance into a revenue problem. Anthropic published what happened to its own internal analytics agent: ~95% accuracy at launch, ~65% a month later, after the documentation stopped keeping up with a changing data model (Anthropic). A free feature survives that. A paid tier doesn't, and the customer who catches the wrong number stops paying for it, not just using it. The mechanism is page 2's whole subject.
Both paths, on the revenue questions
The rows that matter here are about when the tier becomes billable and where its cost lives.
Build the premium tier yourself if:
The tier is your core roadmap
Analytics is the product, and the premium tier is the thing you're building the company around rather than an adjacent line on the price card.
The analysis is proprietary
Your pricing power depends on analysis only your team can implement, because the method itself is the differentiator and not the interface around it.
You can afford the wait
Six to twelve months of uncollected premium is genuinely affordable, and the engineering is strategic rather than a means to a tier you want to sell.
If the goal is expansion revenue this fiscal year, the build path's real price is the premium that goes uncollected while it's underway.
Three structures that work
Whichever path you take to build it, these are the shapes the tier tends to take, with the tradeoffs stated honestly.
A premium tier
An Insights or Intelligence tier above your current top tier, anchored on dashboards plus plain-English questions. Clean story, clean upgrade path, and it repositions your existing top tier as the middle of the menu, which helps every renewal conversation whether they upgrade or not.
A per-unit add-on
Priced on the unit your customers already think in: per site, per location, per crew. Works on its own or as the pricing axis inside the premium tier. The risk is nickel-and-dime perception when your core is priced on the same unit, so keep the add-on's unit price simple.
A portfolio package
Custom-scoped and priced per relationship, for the customers running many locations who want rollups across all of them. Right for your five biggest logos, wrong as the only option, because it stalls mid-market deals in procurement.
What reliably fails: metering questions or seats, which teaches your customers to ration the asking until the tier looks unused at renewal, and a beta that stays free long enough to teach them the price is zero.
Your brand, your pricing.Your tier structure.
Querri is the white-label AI analytics layer you can package as your own premium tier. The instance is live with your data in about a week, so the launch date is set by your packaging decisions rather than your sprint capacity.
The margin math is the part people miss
Because you're selling this tier, where the cost sits matters as much as what it is. A homegrown build sits in your COGS whether or not customers upgrade, so the tier has to cover a cost you're paying either way. Consumption pricing moves that cost onto the usage that's generating the revenue, which is the difference between a tier that carries itself from the first customer and one that needs volume before it breaks even.
Insights for everyone, depth for the tier
Viewing and sharing are free, so you can put answers in front of every user and charge for analytical depth instead of paying per seat for the audience.
The launch date is yours
Two tickets, then the timeline belongs to packaging and pricing rather than to a sprint board. That's what makes a renewal-cycle launch plannable.
The security review is shorter
SOC 2 Type II, ISO 27001 and HIPAA readiness are already in place, which matters because enterprise-tier pricing invites an enterprise-tier review.
Your brand
Ships in your UI under your name. Your sales team demos it as yours, because it is.
Each of these is something a customer would pay to stop guessing about
The questions are the tier's feature list, and the reason the premium holds is that the answers are worth money to the person asking.
The short answers
How long does it take to go live?
Two gates. The instance is live with your data in about a week; a customer-facing tier typically lands two to four weeks in, after tuning, which needs no engineering time. From there the launch date is a packaging and pricing decision, not a sprint commitment.
What does it cost?
Less than the cost of one engineer, on consumption pricing. Viewing and sharing are free, which is what makes insights for everyone with depth in the premium tier a workable package.
What should we charge?
That's your call and your pricing power, but the survey benchmark is a median 25% premium for analytics, and that was set on static dashboards a decade ago.
Doesn't white-labeling mean we're reselling something generic?
The analytics run on your data, answer your customers' questions, and wear your brand. What you're not doing is spending a year rebuilding the plumbing under it. Your differentiation is the product the analytics live in and the data only you have.
One argument, four doors
Every page shows its numbers and its sources, including the honest cases where building is the right call.
The real cost of building in-house
$150K to $340K in year one, 6 to 12 months, and a maintenance tail that never ends. The math line by line, with a worksheet you can rerun.
Everyone is asking when you ship AI
Anthropic's own analytics agent went from 21% to 95%+ answer accuracy on the same model. The model was never the hard part.
Your export button is a demand signal
Analytics rated 43% of an application's perceived value a decade ago. Your customers want it more now, not less.
The premium is benchmarked.The tier is yours to package.
Start with one export, or challenge us with as many sources and connectors as you'd like. In 3 to 5 business days you get a branded 4 to 5 page report: what's clean, what's broken, and the questions your customers could already be asking your product. Free, and yours to keep.