No plans, no tiers, no subscription - DataScope runs on a single credit balance. Here is exactly how a project turns into a credit charge, and how to keep the number predictable.
There is no plan to pick
A lot of analytics tools start with a plan comparison: which tier, how many seats, which features are locked behind the next one up. DataScope doesn't work that way. There are no plans, tiers, or subscriptions - every account, including one created a minute ago, has access to every feature. The only thing you buy is credits, and the only thing credits buy is usage: running an analysis or requesting an expert review. A larger credit pack doesn't unlock anything new; it just lowers the price per credit.
That's a deliberate simplification, and it means the entire pricing question comes down to one thing: how many credits does a given analysis actually cost, and how do you keep that number under control.
The four numbers behind every charge
Every analysis is priced from a formula with four inputs: a base cost for the analysis type, a complexity multiplier based on your file, an urgency multiplier based on how fast you need it, and a hard cap set by the estimate you were shown before you started.
1. Base cost by analysis type. Descriptive analysis (summaries, trends, data profiling) has the lowest base cost. Diagnostic (root cause, correlation, segmentation) costs more. Predictive (forecasting, risk modeling) costs more again. Prescriptive (recommendations, optimization) has the highest base cost of the four. This reflects how much computation each type actually does - a trend summary is lighter work than a forecasting model.
2. Complexity multiplier. Your file's size and shape - rows, columns - determine whether it's treated as low, medium, or high complexity. A small, simple file is multiplied down from the base cost; a large or wide dataset is multiplied up. This is why the same analysis type can cost noticeably different amounts on two different uploads.
3. Urgency multiplier. You choose how fast you need the result: standard, priority, urgent, or rush. Standard carries no multiplier - you pay the base, adjusted only for complexity. Each step up adds a multiplier on top, with rush costing twice the standard-urgency price for the same analysis. This is the one input entirely in your control: if the timeline doesn't matter, standard urgency is the cheapest way to run any analysis.
4. The estimate is the cap. Before an analysis starts, the project screen reads your file and shows a credit estimate built from these three inputs. That estimate becomes the ceiling - you are never charged more than the number you were shown, even if the analysis ends up doing more work than expected. If it does less, you're only charged for what it actually used.
A couple of worked examples
Take a Descriptive analysis - the cheapest type - on a small file at standard urgency. Small file means the lowest complexity multiplier; standard urgency means no urgency multiplier at all. That combination lands at the floor of what any analysis can possibly cost on DataScope: the cheapest type, the smallest file, the default urgency.
Now take a Diagnostic analysis on a mid-sized file, requested at rush urgency because you need the answer today. Diagnostic's higher base cost, combined with a mid-range complexity multiplier and rush urgency's multiplier on top, adds up to several times the cost of the first example. The type and the urgency you pick both move the number - urgency more sharply than complexity, since rush doubles the price outright.
The practical takeaway: if you're not in a hurry, standard urgency is almost always worth choosing. The speed premium is real and it compounds with whichever analysis type you've already picked.
Buying credits: packs or a custom amount
Credits are sold in four packs, and the price per credit drops as the pack gets larger - the standard volume-discount shape. The smallest pack is priced at the base rate; each larger pack lowers the effective price per credit, down to about 14% below the base rate at the largest pack (58,000 credits for €2,500). Which pack makes sense depends entirely on how much you expect to run: an occasional Descriptive analysis on a small file doesn't need the same pack as a team running weekly Predictive projects on large datasets.
If none of the fixed packs match what you need, you can also type in a custom amount - anywhere from a small top-up to a substantial one - and pay exactly that amount. A custom amount buys as many credits as it covers at the rate of the largest pack it reaches, so you're never worse off buying a custom amount than buying the nearest pack down.
Credits don't expire on a clock
Once purchased, credits sit in your balance with no expiration date attached. You can buy a pack today and use it gradually over months without losing any of it to a "use it or lose it" deadline. The only event that puts a clock on unused credits is closing the account entirely - at that point you have a 30-day window to use or export what's left.
This matters for how you think about buying credits in the first place: there's no pressure to guess your usage for a billing period and buy accordingly. You can buy a pack sized to a specific project, run it, and buy again only when you're planning the next one.
What happens if you run out mid-project
If your balance drops below what an analysis needs, DataScope won't let you start it - but it also won't touch anything you've already paid for. Past analyses, uploaded data, and completed projects all stay fully accessible; the only thing that's blocked is starting something new. Buying another pack unblocks it immediately, at any time, with no waiting period.
Keeping the number predictable
Three habits keep credit spend easy to plan for:
- Run Descriptive first on unfamiliar data. It's the cheapest type, and the summary it produces often tells you whether you actually need a more expensive Diagnostic or Predictive run - or whether the first answer was enough.
- Default to standard urgency. Reserve priority, urgent, or rush for the cases where the deadline is real. The multiplier is the single biggest lever on price, bigger than complexity in most cases.
- Read the estimate before you confirm. It's shown on the project screen before anything is charged, broken down by type, complexity, and urgency, so you can see exactly which input is driving the number before you commit to it.
For the exact published pack prices and the custom-amount calculator, see the pricing page. If you're deciding which analysis type to run in the first place, our guide to choosing the right analysis type walks through what each one is actually for.