behavioural research
Behavioural Research for Pet Insurance Quote Flows
Quote abandonment in pet insurance is rarely about price alone. Confusing field labels, unexpected questions about breed or pre-existing conditions, and unclear excess structures all drive drop-off before a customer ever sees a premium. OpenScouter captures the exact moments where confusion turns into abandonment.
Where Pet Insurance Quote Flows Break
Pet insurance quote journeys ask customers to make consequential decisions quickly: species, breed, age, vet cover limits, excess options, and optional add-ons like dental or complementary treatment. Each of those steps is a potential exit point. Most analytics tools tell you where customers leave. They do not tell you why.
FCA-regulated pet insurance providers operating under Consumer Duty (PS22/9) have a specific obligation to evidence that products and communications deliver good outcomes for retail customers. Demonstrating that your quote flow is genuinely comprehensible, not merely technically functional, is part of that evidential burden. Behavioural research gives you the data to support that case.
The problem is rarely a single broken element. It is a sequence of small friction points, a field label that assumes veterinary knowledge, a tooltip that appears too late, a premium summary that does not map to what the customer was expecting, that compound into abandonment. Identifying that sequence requires observing real users, not inferring from click data alone.
Our approach
Three Streams, One Session
Each participant completes your live quote flow while OpenScouter captures interaction signals (clicks, scrolls, rage clicks, hesitation patterns), a concurrent think-aloud voice recording, and locally processed facial expression data. The three streams are correlated by an AI pipeline so you see not just what broke, but what the participant was saying and feeling at that precise moment.
A Higher-Signal Panel
OpenScouter sessions use neurodivergent participants, people with ADHD, dyslexia, autism, and related cognitive differences. They surface usability issues that neurotypical users overlook or tolerate silently. For a quote flow that asks customers to process policy terminology under time pressure, this panel is not an accessibility exercise. It is a diagnostic instrument calibrated to find the issues most likely to affect a broad customer base.
Human-Confirmed Reports, Structured for Action
AI correlation surfaces candidate insights. A human researcher reviews every finding before the report is delivered. The output maps friction points to specific steps in your quote journey, from species and breed entry through cover selection to the final premium screen, with prioritised recommendations your product and design teams can act on without further interpretation.
The average US ecommerce checkout has 11.8 form fields, almost double the number needed to capture the required information
Baymard Institute's finding about ecommerce checkout forms containing roughly double the fields actually needed to complete a transaction is directly relevant to pet insurance quote flows, even though insurance is not ecommerce in the strict sense. Pet insurance quotes require genuinely complex data: species, breed, date of birth, postcode, vet history, and cover preferences. But the way that data is collected is a design choice, not a regulatory requirement. When form structure is driven by underwriting data models rather than customer comprehension, quote flows accumulate fields, conditional branches, and terminology that made sense to the product team but create confusion for the customer completing the journey. The Baymard finding is a useful reference point because it demonstrates that form bloat is a documented, measurable problem with direct consequences for completion rates. For FCA-regulated pet insurers with Consumer Duty obligations, the question is not only whether customers can technically complete the quote, but whether they genuinely understand what they are selecting. Behavioural research is the method that distinguishes between those two outcomes.
What you receive
- Session recordings with synchronised interaction, voice, and facial expression timelines
- Annotated friction map of your quote flow, step by step from first field to premium display
- Prioritised findings report with severity ratings and recommended design changes
- Specific observations on terminology comprehension, including breed classification, excess framing, and cover limit language
- A summary suitable for internal stakeholder review or inclusion in Consumer Duty outcome monitoring documentation
Frequently asked
- Which pet insurance providers is this relevant for?
- Any FCA-authorised insurer or appointed representative offering pet insurance products in the UK where the quote journey is a primary acquisition or renewal channel. Consumer Duty (PS22/9) applies to FCA-regulated firms in this sector, and behavioural evidence of comprehensible customer journeys is directly relevant to the outcomes monitoring obligation.
- How many participants do you use in a study?
- A typical OpenScouter engagement runs between five and twelve participants depending on the scope. For a single quote flow with one or two variants, a focused session set is sufficient to surface the primary friction patterns. We scope the panel size to the question, not to a fixed template.
- Why use neurodivergent testers for a mainstream insurance product?
- Neurodivergent testers find usability issues that neurotypical users never notice or never articulate. In a quote flow that uses insurance-specific terminology, asks customers to recall their pet's medical history, and presents multiple cover tiers simultaneously, cognitive load is high. Participants with ADHD or dyslexia will surface label ambiguity, information hierarchy problems, and confusing conditional logic faster and more reliably than a standard panel.
- How does this relate to form field count and quote flow length?
- Baymard Institute's research into form usability found that ecommerce checkout forms routinely contain far more fields than the transaction actually requires. Pet insurance quote flows face the same structural risk: underwriters need specific data, but the way that data is collected, how fields are sequenced, labelled, and grouped, determines whether customers complete the journey or abandon it. Behavioural research identifies which fields cause genuine confusion versus which are simply unfamiliar but navigable.
- How long does a study take from brief to report?
- From a confirmed study brief to delivery of a human-reviewed report, a standard engagement runs in days rather than months. We test against your live or staging quote flow, so there is no integration work required on your side before the study begins.
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