Lifecycle and Email
Segmentation and personalisation
Send on behaviour, which you already have, rather than on preferences nobody filled in. Scoped as its own piece because that is how it is usually bought.
What are you buying when you buy segmentation and personalisation?
Send on behaviour, which you already have, rather than on preferences nobody filled in. In practice that means behavioural segments built from purchase and browse history rather than from demographics, and then the harder half: recency, frequency and value segmentation applied to sending rules rather than to a report.
Why this work exists
This is where the gap between what a business believes about itself and what is on record turns into lost revenue.
It sits inside Lifecycle and Email, which is the broader discipline, and it is the part people most often ask for by name.
The nearest piece of work to it is deciding how often is too often for this audience. Where that is already handled, this moves faster than the estimate; where it is not, the two get done together or neither of them holds.
What good looks like
A finished version fits on two pages. Anything longer is a draft that stopped.
The gap between that and where most accounts start is why this is scoped as segmentation and personalisation rather than as a line inside something larger. Building the win-back that is worth sending is the usual second step once it is in place.
When this is the right work
The diagnostic signs:
- Everybody gets the same email
- Your preference centre has fifteen fields and a two per cent completion rate
- Personalisation means inserting a first name
If none of those is true, something else is probably the constraint, and the Lifecycle and Email overview maps the alternatives. The usual neighbours are getting the data into the platform so personalisation is not a guess and finding the transactional email nobody has looked at in two years.
What the work covers
In order, the work is:
- Behavioural segments built from purchase and browse history rather than from demographics, done before anything downstream is committed to.
- Recency, frequency and value segmentation applied to sending rules rather than to a report, with the evidence kept so the decision can be defended later.
- Content variation that is worth the complexity, tested rather than assumed. Usually quick; occasionally the thing that reopens the whole scope.
- A preference centre short enough that people complete it, which clients tend to want evidence for, so it is documented as it goes.
How it runs
It runs in three passes. The order is not interchangeable.
Bringing in whoever owns the system
Developers, agency partners or whoever actually controls the platform get involved before recommendations are written, not after they are rejected.
Proving it in one place first
Changes get made to a small, representative slice and measured there before being applied everywhere. It is slower for three weeks and faster for the rest of the year.
Clearing the contradictions
Where two systems disagree about the same fact, that gets settled before anything is built on top of either of them.
What each part runs into
The obstacles differ by part and by market:
- Behavioural segments built from purchase and browse history rather than from demographics – working in Bengaluru this means accounting for a procurement step nobody accounted for
- Recency, frequency and value segmentation applied to sending rules rather than to a report, and in Surat the constraint on it is a measurement baseline that was never taken
- Content variation that is worth the complexity, tested rather than assumed, harder in Sharjah because of a language mix the content has to match rather than assume
- A preference centre short enough that people complete it – in New York, complicated by the fact that an enquiry path that runs through a messaging app rather than a form
The version that does not work
Building segments nobody sends to. A model that exists only in a report is a modelling exercise, not a marketing one.
It is the reason this work sometimes looks like it does not work.
How it is measured
Revenue per recipient by segment, and unsubscribe rate by segment. It is reported with the existing metrics rather than replacing them, because a new number nobody recognises persuades nobody.
It is reported against the same definition every month, because a metric that is redefined is a metric nobody trusts.
What you end up with
Specifically: a segmentation model wired into the sending rules, with the variations that earned their place.
Written once, for the person who has to do something about it.
How it differs by sector
Read across three sectors, the differences are clear:
- Travel and hospitality, constrained by the fact that aggregators hold the demand, so direct booking depends on being the specific named property.
- SaaS and technology: Product-led companies where the buyer self-educates and the trial is the sales call. so this work has to account for that before anything else.
- Finance and fintech, where regulated claims, compliance review in the publishing path, and trust signals that have to be real. which moves this work earlier in the plan.
The industry pages carry the rest of that detail. Travel and hospitality and SaaS and technology are the two where this piece of work most often decides the outcome.
Common questions
How many segments do we need?
Few enough to maintain. Three segments used properly beat twenty that exist in a spreadsheet.
Is first-name personalisation worth it?
Marginally, and it is not personalisation. What was browsed and what was bought tells you far more than what somebody is called.
Can this be scoped on its own?
Yes, where the diagnosis says it is the constraint. More often it runs inside a Lifecycle and Email engagement, because the adjacent work is what makes the result hold. The scoping conversation settles which. The short version is here. App Store Optimization and Brand and Creative are the long ones.
How long does this take?
The diagnostic part is usually two to three weeks. What follows depends on what the diagnosis finds, and we scope the second phase after the first rather than quoting both upfront. Featured snippet or AI overview deals with the first ninety days, Core Web Vitals field data or Lighthouse lab score with everything after them.
How much of our time does this take?
A few hours in the first fortnight, mostly answering questions about history that cannot be reconstructed from the data. After that, a monthly review. How much should SEO cost? is the shortest useful page on this. How do we rank in the map pack? is the most complete.
Ask about segmentation and personalisation
Send the site and the symptom. The reply names the first thing we would look at and why.
See the gaps before you spend against them
Send what you have. We read it before the call, so the call is about decisions rather than discovery.