Credits Explained: How Pluriel Pricing Actually Works

Most research software charges a monthly subscription regardless of how often you use it. You pay in January whether you run one study or ten. Pluriel works differently. Credits are the only currency in the platform — you buy them when you need them, spend them when you run a study, and keep the remainder with no expiry date. There is no pressure to use credits before a billing cycle resets, no feature locked behind a higher tier, and no per-seat charge as your team grows. You buy research capacity, and you use it on your schedule.

One credit corresponds to one research panel of up to 500 AI respondents. That is the standard unit — a full synthetic study with cross-tabulation, AI synthesis, raw data export, and a shareable results link. If you want a larger panel, you spend more credits: 300 respondents costs 0.5 credits, 1,000 costs 2 credits, 2,500 costs 4 credits, and 5,000 — our highest panel size — costs 7 credits. The additional cost of going bigger reflects the real compute required to generate, survey, and analyse a larger synthetic population, not an artificial pricing ladder. There is also an optional validation add-on: for 0.5 credits, Pluriel will compare your synthetic panel's findings against a real research PDF you upload, surfacing where the two align and where they diverge.

The analytical case for a larger panel is straightforward. At 300 respondents, you are working with a margin of error of ±5.7 percentage points — solid for directional screening, where the goal is to separate a strong idea from a weak one. At 500 respondents, that narrows to ±4.4 points, which is the standard threshold for reliable top-line findings. At 1,000 respondents, you reach ±3.1 points — and more importantly, you have enough respondents within demographic subgroups to make cross-segment comparisons credible. At 2,500 respondents, multi-variable cross-tabs become reliable. At 5,000, you are at ±1.4 points — the precision level that makes findings defensible in a boardroom or investor presentation. The credit cost scales with these analytical thresholds, not arbitrarily.

Credits are sold in four bundles. Single gives you 1 credit for $59 — the right entry point for a one-off study or for testing the platform before committing to more. Starter gives you 5 credits for $274, which works out to $54.80 per credit and saves $21 over single pricing. Growth gives you 12 credits for $599 — $49.92 per credit, our most popular bundle for teams that run research regularly across multiple client engagements. Scale gives you 30 credits for $1,349 — $44.97 per credit — for agencies and research-heavy teams who want to lock in the best rate. The per-credit price decreases with volume, but there is no expiry pressure — unused credits from a Scale bundle are available for use six months later just as they were the day you purchased.

Choosing the right bundle is a function of how many studies you run in a year and at what panel size. A solo founder running two or three concept tests per year at 500 respondents each will spend 2–3 credits annually — Single or Starter is the right fit. A brand team running monthly research across three product categories at 1,000 respondents each will need 24 credits in twelve months — Growth purchased twice, or a Scale bundle with credits to spare. An agency managing research for five to eight clients, running multiple studies per client per quarter, will likely need 30–60 credits annually, making Scale the cost-efficient default. The calculator on this page is designed to help you work through exactly this arithmetic for your specific research cadence.

One feature worth understanding: because credits do not expire and panel sizes are flexible, you can mix and match freely within a single credit balance. If you start a quarter with 12 credits from a Growth bundle, you might spend 0.5 on a quick 300-respondent concept screen, then 2 on a 1,000-respondent segmentation study, then 1 on a standard validation study, then 4 on a 2,500-respondent pricing study for a client. Each study is a separate run. The credits are consumed as you go, and the balance is always visible in your dashboard. You never lose credits between runs, between clients, or between months. The platform is designed to give you full flexibility over how and when you spend the research capacity you have purchased.

The practical upside of this model is that research decisions are no longer governed by subscription economics. Teams do not rush to run studies before the end of a billing month. They do not underuse credits they have already paid for. They do not over-invest in a large subscription tier because they might need it. They buy what they need, when they need it, and the platform gets out of the way. For growing businesses that want to run research seriously but do not yet know their annual volume, that flexibility is not just a pricing feature — it is what makes committing to a research practice feel reasonable.