myAI Scouts
Sent to anyone across the organisation who wants to submit an idea to the experimentation or A/B testing backlog — product managers, UX designers, data analysts, customer success managers, and sales reps at a B2B SaaS or e-commerce company. Ideas typically come in via Slack messages, Jira tickets, or informal conversations and lack the evidence and hypothesis structure the experimentation team needs to prioritise and scope them. The experimentation team uses findings to write a properly structured test hypothesis in the format "If we [change X], then [metric Y] will change by [Z] because [reason]" without having to chase the submitter for more context.
The specific problem or friction they observed
Describe exactly what you saw or heard that triggered this idea — a specific user complaint in Zendesk, a drop in a Mixpanel funnel, a pattern in customer calls, a Hotjar recording. Where did you see it, how often, and in what context? This is the most important input for evaluating the idea.
The behavioural assumption the idea rests on
What do you think users will do differently if you make this change? Be specific: not 'they'll have a better experience' but 'they'll scroll past the banner rather than dismissing it' or 'they'll complete the checkout step they're currently dropping off at'
What evidence already exists
What data, research, or signal already supports this idea — a Amplitude chart showing the drop-off, a user interview quote, a Hotjar heatmap, a sales call pattern? What would you show someone to convince them this is worth testing?
What a meaningful result would look like
If this test runs and succeeds, what specifically would move and by roughly how much — conversion rate, activation rate, session length? What result would make you confident this was worth the engineering effort to build?
This scout will be copied to your account as a draft. You can customise it before activating.