What Is TrustScore and How Is It Calculated?

Most business owners assume their Trustpilot score is just an average of their star ratings — add up the stars, divide by the number of reviews, done. It isn't. TrustScore is Trustpilot's own proprietary rating algorithm, and it's built specifically to produce a different, more dynamic number than a flat average would. That distinction matters practically: if you're managing a Trustpilot profile and trying to move the score, treating it like a simple average will lead you to the wrong strategy.

TrustScore is not a simple average

Trustpilot itself has been explicit on this point: the TrustScore displayed on a business profile is calculated using a proprietary algorithm, not a plain mean of every star rating a business has ever received. That's a deliberate design choice, not an oversight. A pure average treats a five-star review from three years ago identically to one posted yesterday, and it treats a business with 40 reviews identically to one with 4,000 as long as the average comes out the same. Trustpilot's stated goal with TrustScore is to produce a number that reflects a more current, more contextual picture of how a business is actually performing — which requires factoring in more than the raw average.

The factors TrustScore is known to weigh

Trustpilot does not publish the exact formula, the precise weighting given to each input, or the specific mathematical model behind TrustScore — and it's worth being upfront that anyone claiming to know the exact percentage breakdown is guessing, not quoting a disclosed source. What Trustpilot has publicly described are the general categories of signal the algorithm is known to factor in:

• Rating distribution. How your reviews are spread across the 1-to-5-star scale, not just the average of those numbers. A profile with a mix that leans heavily toward genuine 4- and 5-star reviews reads differently to the algorithm than one with the same average built from a bimodal split of mostly 1-star and mostly 5-star reviews with little in between.
• Review recency. More recent reviews are understood to carry more weight in the calculation than older ones. A business's TrustScore is meant to reflect how it's performing now, not how it performed at some point in its history — which means a strong historical average built years ago won't hold up a current score if new reviews have slowed or turned negative.
• Review volume and frequency. How many reviews a business has, and how steadily they continue to come in over time, is also known to factor into the calculation. A business collecting a small, steady stream of reviews every week is generally in a different position than one that collected a batch of reviews once and then went quiet for a year.

Trustpilot frames these as the categories of input the algorithm draws on — it does not disclose the exact math connecting them to the final number shown on a profile. Treat any claim of an exact weighting formula with skepticism; it isn't something Trustpilot has made public.

Why this matters more than it sounds like it should

A one-time review push is a weaker strategy than it looks

Because recency and ongoing volume are both known factors, a single concentrated push of reviews — asking every current customer for a review in the same week to hit a number — tends to move TrustScore temporarily and then lose momentum once the push stops and new reviews slow back down. The algorithm isn't reading a static, one-time snapshot; it's continuing to weigh how current and how steady your review activity is. A business that generates a smaller number of reviews consistently, month after month, is generally in a more durable position than one that spikes once and goes quiet.

A strong historical average can mask a declining trend

If a business built a great reputation years ago but review requests quietly stopped — no post-purchase email, no follow-up ask, nobody responsible for it — the lifetime average can still look strong on paper while the TrustScore softens, because the score is meant to be sensitive to what's happened recently, not just what happened historically. This is a common, unglamorous reason a TrustScore drifts down without any single bad review being the obvious cause.

Distribution matters, not just the headline number

A profile that's mostly genuine 4- and 5-star reviews with an occasional honest 3-star reads differently to the algorithm — and to a human reading the page — than one with a polarized split of mostly 5-star and mostly 1-star reviews clustered at the extremes, even if the two averages land close together. This is part of why addressing the root causes behind negative reviews matters as much as generating positive ones; shifting the shape of the distribution, not only the count of 5-star reviews, is part of what moves the score.

What this means for a practical review strategy

Given that recency, distribution, and ongoing volume are all known factors, the practical implication is straightforward: build review generation into a standing part of the business, not a one-off project you run when the score looks bad. A steady, repeatable process — asking at the right moment in the customer journey, making it easy to leave a review, following up once rather than nagging — tends to produce a more stable TrustScore over time than sporadic bursts of activity.

It's also worth being clear about what doesn't move TrustScore in a legitimate or sustainable way: buying reviews, incentivizing only positive reviews while filtering out negative ones (a practice known as review gating), or any tactic designed to manufacture ratings rather than earn them. Beyond violating most review platforms' terms of service, that kind of activity produces exactly the pattern TrustScore is structurally resistant to — an unnatural spike that doesn't hold up once recency and volume start pulling the score back down, and it risks the account itself. The more effective path is a genuine, ongoing process for asking real customers for real feedback, paired with a real plan for handling the negative reviews that inevitably come with a healthy volume of honest ones.

For a step-by-step approach to actually improving a weak score, see how to recover from a bad Trustpilot score. And if you're deciding where to focus review generation effort between platforms, the differences between Trustpilot and Google reviews are worth understanding before you commit resources to one over the other.