Form & Checkout Optimization

A funnel chart cannot show where field-level checkout friction occurs.

A step-level funnel report tells you that people leave during checkout. Field focus, error, and abandonment events show where. We read those events alongside session recordings, payment behavior, and scoped accessibility checks, then turn supported findings into hypotheses for test design. A known abandonment problem is the starting point. This diagnostic fits when the team needs field-level evidence to decide what to test.

You get a field-by-field friction map for the form or checkout, followed by an experiment plan for the highest-opportunity changes.

A checkout form with individual fields highlighted by abandonment rate and error frequency

Some of the 500+ brands we've worked with

See all references
  • Mini
  • GAP
  • Domino’s
  • TransferGo
  • Adore Mobilya
  • Jollytur

How the work runs

Find the field behind the funnel drop

Field events tell us where people hesitate, while recordings help explain what happened around that moment. AI can audit the tracking and rank the signals. Human reviewers confirm the evidence, including accessibility findings, and decide which hypotheses are ready for test design.

How we hold ourselves to it

  • Measure abandonment by field
  • Tie each finding to a field, error state, or step transition
  • Every proposed fix enters test design
  • Payment and trust questions need their own evidence

  1. Instrument field-level events

    Confirm or add tracking for field focus, field error, field abandonment, and time-to-complete per field. Step entry and exit remain useful, but they cannot identify the field where the problem occurs.

    Field-level event coverage for focus, error, abandonment and time-to-complete, with the gaps that were closed listed.

    AI assist
    Audits existing event tracking against a field-level checklist and flags gaps.
    Human gate
    The CRO strategist and analytics owner confirm the instrumentation is complete before evidence-gathering starts.
    Owners
    CRO strategist + analytics owner

  2. Map abandonment to specific fields and steps

    Read the field-level events against session recordings to see exactly where people hesitate, error out, or leave, separating a genuinely confusing field from one that's just slow to load.

    Field- and step-level abandonment map read against session recordings.

    AI assist
    Ranks fields by abandonment rate and error frequency, with recording links attached.
    Human gate
    The research owner confirms the ranking against a sample of the underlying recordings.
    Owners
    Research owner + session analyst

  3. Check payment and trust friction specifically

    Compare offered payment methods with observed attempts. Around common hesitation points, review available security cues, pricing, and the displayed total.

    Payment-method and trust-cue findings comparing offered methods with observed attempts.

    AI assist
    Compares offered payment methods against available audience payment-preference data and flags mismatches.
    Human gate
    The client owner confirms payment-method changes are operationally feasible before they're proposed as fixes.
    Owners
    Client owner + CRO strategist

  4. Check accessibility and input mechanics

    Review labels, error announcements, mobile keyboard types, autofill compatibility, and focus order against relevant WCAG success criteria and input-type conventions.

    Accessibility and input-mechanics findings against WCAG success criteria and input-type conventions.

    AI assist
    Runs an accessibility and input-mechanics check against the field-level markup.
    Human gate
    An accessibility-literate reviewer confirms flagged issues before they're added to the friction map.
    Owners
    Accessibility reviewer + engineering

  5. Build the field-level friction map

    Assemble findings about abandonment, errors, payment, and accessibility into one map ordered by estimated opportunity, so the highest-friction field is clearly prioritized.

    Friction map ordered by estimated opportunity across abandonment, error, payment and accessibility findings.

    AI assist
    Drafts the ranked friction map from the approved findings.
    Human gate
    The CRO strategist signs off on the ranking before it becomes a test plan.
    Owners
    CRO strategist + research owner

  6. Turn the top findings into an experiment plan

    Convert the highest-ranked friction points into falsifiable hypotheses ready for test design. The map informs the next test, and no fix ships from the diagnostic alone.

    Falsifiable hypotheses for the top-ranked friction points, ready for test design.

    AI assist
    Drafts hypothesis candidates from the top-ranked friction map entries.
    Human gate
    The CRO strategist and client owner approve which hypotheses move to test design next.
    Owners
    CRO strategist + client owner

What lands with your team

What supports each field-level finding

These records connect the tracking setup to what people did, what reviewers confirmed and which ideas are ready for an experiment.

  • Field-level event audit

    What's tracked at the field level today, what's missing, and what got added to close the gap.

    Accepted when

    Every field states what is tracked today, what was missing and what was added, so a later ranking is not built on absent data.

    Cadence: At the start

  • Abandonment and error ranking

    Every field ranked by abandonment rate and error frequency, with linked session recordings for the top entries.

    Accepted when

    Each field carries an abandonment rate and error frequency, and the top entries link to the session recordings behind them.

    Cadence: During diagnostic

  • Payment and accessibility findings

    Observed payment-method mismatches and field-level accessibility issues reviewed against relevant WCAG criteria.

    Accepted when

    Payment mismatches cite the observed attempt data and accessibility issues cite the WCAG criterion they fail.

    Cadence: Per diagnostic pass

  • Field-level friction map and experiment plan

    The ranked map plus falsifiable hypotheses for the top opportunities, ready for test design.

    Accepted when

    The map is ordered by estimated opportunity and each top entry has been converted into a hypothesis a test can disprove.

    Cadence: At diagnostic end

Before the work starts

When this work is the right next step

A checkout can pass design review and still lose users at a single field. A form may look clean in the design file while an offered payment method is missing or an error appears only after someone moves on. A step-level chart cannot expose either issue. Field events show the point of hesitation when the tracking exists.

A good fit when

  • The form has enough completions and abandonments to expose field-level patterns, but the funnel report still stops at the checkout step.
  • Focus, error, and abandonment events are missing for key fields, so nobody can distinguish a confusing input from one that simply loads slowly.
  • Design and engineering can change the checkout, yet they need a ranked friction map to decide which field deserves a test first.
  • Step-level drop-off with no field-level explanation.
  • An error appears after the user moves on or tries to submit.
  • Mobile opens the wrong keyboard for the input type.
  • A friction recommendation ships without field-level data.

Better handled as other work when

  • Form volume is too low for each field to produce a reliable read, so a step-level diagnostic is the highest confidence the data can support.
  • One diagnosed defect already explains the loss, so a clear fix ticket for the submit button or error state should precede broader optimization.
  • Nobody can change the checkout in this release window, so field-level evidence cannot reach test design.

People who own a single channel

Paid Search, Paid Social, CRO, and Programmatic each run under a named owner at Zeo. The consultants below are matched to the channel this page is about, so you can see who you'd actually work with.

Content we've produced on this topic

Videoby İlker EmirWays to Increase Conversion Rate | Ilker Emir, ZeoArticleby Zafer YıldızConversion Structure & Conversion Creation in Google Analytics 4

Tools we use

Tools behind this work

  • Contentsquare

    measures interaction one field at a time, not the page as a whole

  • Baymard Institute

    the external benchmark for a checkout field's likely mistake

Move past the step-level drop

Find the fields that need a closer look

The current form and its tracking show us what can already be measured. We'll identify the missing field-level evidence, rank the supported friction points and prepare the strongest ones for test design.
Review checkout friction

The questions we hear most

The diagnostic reads the current checkout and sends any supported fix through test design, so a redesign is not required up front.