Personalization works better when you just ask.
Goals, routines, interests, and contact preferences are the four things customers will happily tell you — and the four things behavioral data models worst.
Inferred preferences are expensive guesses.
Two customers buy the same Reishi blend. One is chasing better sleep, the other is managing stress at work. Their orders are identical and their needs are not. Every email you send from that order is a coin flip — and the customer has no idea you were guessing.
- Clicks measure curiosity, not intent.
- Opt-out is the only preference signal most stores ever collect.
- A goal declared once stays useful for years; a click decays in weeks.
- Gift buyers and household shoppers distort behavioral inference completely.
What a preference survey should actually cover.
Example questions for a functional mushroom and adaptogen brand — split across goals, routine, content, and channel.
- 01
What are you working on for yourself right now?
Focus and mental claritySustained energySleep qualityStress and moodImmune resilienceRecovery and training - 02
When does your wellness routine actually happen?
Before 7amWith breakfastMid-morningAfternoonEvening wind-downIt's inconsistent - 03
Which of these would you like to hear more about?
New blends and launchesRecipes and ritualsResearch and sourcingRestock remindersMember eventsOffers only - 04
How often do you want to hear from us?
Weekly is fineA couple of times a monthMonthlyOnly when something is newOnly order updates - 05
Where do you prefer to hear from us?
EmailSMSBothNeither — just my order emails - 06
Anything we should know about your diet or sensitivities?
VeganCaffeine-sensitiveGluten-freePregnant or nursingNo restrictions
Illustrative example questions. Signals can draft equivalents for your own catalogue and audience.
A Signal profile, not a survey export.
Each answer becomes a named, reusable property on the customer — available to Shopify, Klaviyo, and Compass.
Primary Goal
The outcome the customer is actually pursuing, in their own words.
Preferred Routine
The time of day their ritual happens — and when a message will land.
Content Interests
Recipes, research, launches, or offers, so campaigns stop being one-size-fits-all.
Contact Frequency
A declared cadence you can honour instead of guessing at send volume.
Preferred Channel
Email, SMS, or both — captured rather than inferred from engagement decay.
Dietary Constraints
What never to recommend, so relevance improves and returns fall.
Send the message they asked for.
Declared preferences are the cheapest relevance you will ever buy.
In Shopify
- Keep declared preferences on the customer record where support can see them.
- Segment by Primary Goal to plan merchandising and bundles around real demand.
- Spot goals your catalogue does not yet serve well.
In Klaviyo
- Sync Content Interests and Contact Frequency as profile properties.
- Build a self-service preference centre that feeds real segmentation, not just an opt-down.
- Send the evening wind-down story only to customers whose routine is in the evening.
In Compass
- Blend declared preferences with observed behavior in one unified profile.
- Use preference data to inform AI-assisted recommendations and audiences.
- Optional — Signals delivers all of the above with Shopify and Klaviyo alone.
Ask your customers what they actually want.
Start with a preference survey template, then keep the profile current with Sparks.