What do Exatom and Zuko actually do?

Both are specialist form and checkout analytics tools. They watch how visitors interact with every field — where they hesitate, which inputs they re-edit, and where they abandon. Unlike Google Analytics, both reveal field-level behaviour rather than page-level totals. The real differences sit in how they track, how much setup they need, and what you can do next.

Zuko started life as Formisimo in 2014, founded in Manchester to reduce friction in online forms, and relaunched under the Zuko name in 2019. Its session-based pricing is geared towards SMBs and lower-traffic sites.

Exatom is a European platform built for the demanding end of the market: CRO specialists, product owners and ecommerce teams running high-traffic forms. It is the leading form analytics platform in automotive, insurance and energy, where a single point of form conversion can be worth a great deal. Both tools answer the same question — why visitors fail to complete a form — but they are built for different ends of the market.

How do the two tools track visitors, and does consent get in the way?

This is the clearest architectural difference. Exatom is cookieless, so its tag can run outside your cookie-consent banner and report on every visitor. Zuko sets a first-party client-ID cookie, which means it sits inside consent management. Visitors who decline cookies fall out of your data, and on many sites that gap is substantial.

Consent rates vary, but it is common for a meaningful share of visitors to refuse non-essential cookies. Every refusal is a session your form analytics never sees, which quietly biases your sample towards the people who happen to accept cookies.

Because Exatom is cookieless, the tag can be deployed outside the consent-management platform and report on close to 100% of traffic. To be fair to Zuko, this is not a privacy shortcoming on their side — Zuko stores no personally identifiable information and holds ISO 27001 certification. The issue is coverage, not compliance.

How much setup does each tool need?

The two tools start very differently. With Zuko you enter the URL of each form you want to track, and if the same form appears on several pages you merge those reports together by hand. Exatom finds every form on your site automatically and merges the same form across pages for you — no URLs, no manual stitching.

That gap matters more than it first appears. A single form template often lives on dozens of URLs — a quote form on every vehicle page, a renewal form per policy type. In Zuko, each of those is a manual definition and a manual merge; miss one and your numbers are quietly wrong.

Exatom detects every instance, recognises that they are the same form and reports on them as one, with zero configuration. It also lets you rename field labels, so a field reported in code as billing_pc appears to stakeholders as “Billing postcode”. The dashboard reads in business language, not HTML.

Which tool gives you more field-level detail?

Both report drop-off, time-in-field and field returns. Exatom adds error-focused metrics — error rate, error categories, the actual error messages shown, and autofill rates — plus hesitation time and, soon, rage clicks. Zuko leans on returns, interaction time and AI-generated summaries. If diagnosing why a field fails matters most, Exatom's error data is the deciding factor.

Knowing that a field underperforms is only half an insight. Knowing the exact validation error a visitor saw — a rejected phone format, a date pattern the field would not accept — is what turns a vague problem into a specific fix.

Autofill rates matter for the same reason. A field with a low autofill rate is often one the browser cannot recognise, which usually points to a missing or wrong autocomplete attribute. That single signal can explain a surprising amount of friction.

Can you fix forms inside the tool, or only measure them?

This is where the platforms genuinely part ways. Zuko reports the problem and stops; Exatom also acts on it. Three Exatom capabilities have no Zuko equivalent: performance alerts that flag any metric slipping on any form, AI nudging that guides visitors through trouble spots in real time, and autofixes that correct known issues automatically.

That distinction matters most when you cannot easily change the form itself. Many forms live inside legacy stacks, third-party checkouts or systems where a developer ticket takes weeks.

Performance alerts mean you do not have to watch dashboards. Exatom monitors every metric on every form and tells you the moment completion drops or an error rate spikes, so a broken deploy is caught in hours, not at the end of the month.

AI nudging works on the visitor's side. When someone hesitates or hits a recurring error, Exatom can surface the right guidance in the moment — without a developer rebuilding the form — which matters most on legacy stacks and third-party checkouts where change is slow.

Autofixes go a step further and correct common issues automatically, from missing autocomplete attributes to input formatting. Zuko offers none of this: its route to improvement is to rebuild the form in its separate form-builder product. Analytics tells you where the leak is; Exatom is what actually stops it.

So which should you choose?

Pick Zuko if you run a smaller site or a simple form and want a low-entry, session-priced analytics tool. Pick Exatom if you run high-traffic, high-stakes forms and want cookieless coverage of 100% of traffic, near-zero configuration, deeper error analytics, and optimisation built into the same platform. For automotive, insurance and energy, Exatom leads.

For high-traffic operations in automotive, insurance and energy, Exatom's edge is concrete: session-volume pricing punishes scale, while Exatom sees the visitors consent would otherwise hide and lets you act on what you find without a development cycle.

Zuko remains a sensible option for a smaller business with a single form and modest traffic, where a low entry point matters more than depth. But the moment forms become high-traffic, multi-step or revenue-critical, the gaps in coverage and the absence of built-in optimisation start to cost real money.