Enrich Klaviyo Profiles for Smarter Segmentation, Lifecycle and Personalisation

Most Klaviyo accounts know exactly what a customer did. Opened, clicked, bought twice, went quiet in April. Very few know enough about who that customer is to personalise a campaign properly, decide where lifecycle spend should go, or build a flow trigger that means something.

That's the gap Klaviyo data enrichment closes. Outra writes household, life stage, property and purchasing-power context onto your eligible Klaviyo profiles, so your segments describe real households instead of email behaviour. Connect over OAuth, choose the profiles you want to enrich, and start using the new context in your segments and flows. No data warehouse, no reverse-ETL project, no engineering ticket.

Three things enriched profiles let you do

• Segment better: affluent homeowners, young families, recent movers, upgrade potential - definitions your merchandising team would actually recognise.
• Personalise better: change product, offer, creative and content by household context, not just by last product viewed.
• Automate better: trigger flows when someone enters an enriched segment, or when their household situation changes.

Everything below is built around those three jobs. If you only take one thing from this page: start with the flow or segment you want to improve, not with the attribute list.

1. Build more useful lifecycle segments

Klaviyo segmentation usually bottoms out at behaviour: purchased twice, hasn't opened in 90 days, viewed a collection. Useful, but every brand in your category has exactly the same segments, because everyone has the same fields.

With household attributes in the profile, you can build segments like:

• High purchasing-power customers who have lapsed
• Families with pre-school or primary-age children
• Homeowners with a garden or driveway
• Recent movers, and households showing move intent
• Upgrade potential: strong purchasing power, entry-level order history

If you want the segment-building mechanics in depth, the Klaviyo segmentation guide goes deeper on structure and naming. This page is about what enrichment adds on top.

2. Personalise campaigns and journeys

Once the context is on the profile, it can drive more than a merge tag. Use it to tailor:

• Product recommendations (family sizes vs single-occupancy, garden vs flat)
• Creative and messaging (ownership and permanence vs flexibility)
• Offer strategy - who needs a discount to convert and who genuinely doesn't
• Content depth, from a first-time buyer explainer to a straight restock nudge
• Send priority: which households get the SMS as well as the email

The discount point is the one that pays for itself fastest. Blanket 15% across a lapsed segment is a margin decision disguised as a marketing decision.

3. Trigger more relevant automations

Klaviyo flow triggers get considerably more interesting when profile properties change for reasons other than shopping. You can trigger on:

• A profile entering an enriched segment
• A change in move stage - move intent, moving, just moved
• A new enriched attribute landing on the profile
• A customer crossing into high-value or high-potential
• A lapsed customer matching a high-priority household profile

Four worked examples

Win-back: stop sending one email to everyone

Problem: the 90-day win-back goes to everybody with the same offer, so you discount customers who'd have returned anyway and spend on households that were never worth reacquiring.

Segment logic: Lapsed 90 days AND Purchasing power = High AND Move stage is not Moving.

Campaign action: high purchasing power gets a premium, non-discount reason to return; young families get a practical bundle; the lower-priority tail gets one plain-text attempt rather than a five-email sequence.

Measure: revenue per recipient, reactivation rate and margin after discount - not open rate.

Welcome flow: branch on household, not guesswork

Problem: one welcome series has to talk to renters in flats and owners of four-bed semis at the same time, so it says nothing specific to either.

Segment logic: split on Occupancy status and Family stage at email two or three, once enrichment has landed.

Campaign action: owners get the long-term-value and installation story; renters get flexibility, size and no-commitment framing; households with young children get the family range first.

Measure: first-order rate and first-order AOV by branch.

Post-purchase cross-sell: recommend what the home can take

Problem: the post-purchase flow recommends the catalogue's best sellers regardless of whether the household can use them.

Segment logic: Purchased category X AND Garden or Driveway = yes, or Property type = flat, or Pet ownership = yes.

Campaign action: outdoor and bulk lines to houses with space; compact and storage-friendly lines to flats; pet range only where there's a pet.

Measure: 60-day repeat rate and units per order.

Move stage: a trigger you simply don't have today

Problem: moving home is the highest-spend event in a UK household's year, and your flows are blind to it.

Segment logic: flow triggered on Move stage changing to Just moved.

Campaign action: a genuinely timely new-home sequence - replenishment, home categories, delivery to the new address. See why recent movers convert for the underlying behaviour.

Measure: conversion rate versus your standard lifecycle baseline, and category mix.

What data can be added

Grouped, and deliberately short:

• Household: property type, occupancy status, bedrooms, garden / driveway
• Life stage: family stage, employment stage, move stage
• Purchasing power: household income band, purchasing-power band
• Lifestyle: car ownership, pet ownership, area type

You choose which fields matter. Four well-chosen properties that change a flow beat forty that sit unused in the profile - and a shorter field list keeps your segment library legible six months from now.

How setup works

1. Connect Klaviyo securely over OAuth - no API keys to pass around.
2. Choose the profiles or segments you want to enrich.
3. Select the fields relevant to the lifecycle or audience use case you're solving.
4. Review sample output and build your first enriched segment before you commit to anything wider.
5. New eligible profiles enrich on an ongoing schedule, so the segment stays live.

What to expect, honestly

• The household data is UK-based, so UK profiles are the ones that enrich.
• Match quality tracks what you hold: name and postal address beat email alone; work emails and stale records match poorly.
• Not every profile will match. Write segment logic that treats a missing attribute as "unknown", never as "no".
• Existing profiles enrich as a batch when you connect them; new ones are picked up on a schedule rather than the second someone subscribes - so put enriched branches slightly later in fast-firing flows.
• You can start with a single segment rather than the whole list, and widen once you've seen the output.

Enrichment first. Better activation next.

Enrichment improves the profiles and segments you use inside Klaviyo. When you want to push further, those same definitions can inform the audiences you build for paid activation - so your lifecycle segments and your prospecting audiences finally describe the same kind of household. Have a look at profile enrichment and household audiences and start with whichever has the clearer commercial problem. You don't need both on day one.

Privacy and data responsibility

Outra is built to support responsible use of customer and household data, using non-behavioural household intelligence rather than individual-level tracking. You remain responsible for ensuring your specific use of enriched data, targeting and marketing communications has an appropriate lawful basis and complies with applicable privacy and electronic-marketing rules. Our privacy notice sets out how we handle data, and we're happy to walk your DPO through it.

Where to start

Pick one flow that you already know underperforms - most brands should pick the win-back - enrich the segment behind it, add one household condition, and measure revenue per recipient against the version you're running today. That's a week of work, not a data project.