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Case study · Health & Wellness

NutriBlend: fixing the churn window instead of buying more subscribers

A UK supplements brand watching acquisition cost climb past lifetime value. The churn was not random — it clustered in months two and three, for a reason the data made obvious once anyone looked.

Supplement capsules and powder arranged for product photography

NutriBlend’s core subscription range — where the replenishment interval and the actual consumption rate had drifted apart.

Results snapshot

What changed in two quarters

Longer subscriber life meant acquisition budget could be raised rather than cut.

+29%

Subscriber lifetime value

Measured on 12-month cohorts

-34%

Month-three churn

The window where cancellations clustered

+18%

Revenue per email

Across the lifecycle programme

11 wks

To payback

On the engagement fee

Lifetime value here is net of refunds and payment failures, not gross subscription value at signup.

About the client

A subscription-led supplements brand

NutriBlend sells powders, capsules and gummies on a subscription model, direct to consumers in the United Kingdom.

NutriBlend built its business on subscription from the start. The acquisition side worked well: the creative was strong, the offer converted, and new subscribers came in at a cost the founders were happy with in year one.

By the time we were introduced, that had stopped being true. Media costs had risen, the offer had been discounted to compensate, and the lifetime value assumption underpinning the whole model had never been re-tested against what subscribers actually did.

Flat lay of supplement products and packaging
The challenge

Acquisition cost had overtaken lifetime value

The brief was to lower cost per acquisition. The actual problem was at the other end of the funnel.

Customer unpacking a repeat online order at home

Cancellations were not spread evenly across the subscriber base. They clustered sharply in months two and three — and the shape of that curve pointed at the delivery schedule rather than at the product.

Every subscription shipped on a fixed 30-day cycle regardless of what was in it. For the powders, a tub lasted closer to 40 days. Subscribers were accumulating unopened product, noticing around the third delivery, and cancelling.

Our analysis

The interval, not the product

Consumption data existed. Nobody had compared it to the shipping schedule.

We rebuilt the cohort view by product and by month, then laid the cancellation curve over the delivery calendar. The overlap was almost exact: for every SKU where the pack size outlasted the cycle, churn spiked one delivery after the surplus became visible in a customer’s cupboard.

The second finding was cheaper still to fix. The win-back programme fired at 90 days, long after the customer had mentally moved on. The real decision window was the fortnight before the third delivery, and nothing was reaching them in it.

Team reviewing subscription cohort charts in a meeting

Lowering acquisition cost would have bought more subscribers into the same leaking bucket.

Strategy

Make the schedule match the customer

Three commitments, in the order they had to happen.

Ship on real consumption intervals

Reach people inside the decision window

Report on value that survives

None of this required a new subscriptions platform. It required the schedule to reflect how the products are actually used.

What we did

The work, service by service

Four service lines, one team, one shared plan.

Phone showing unread email notifications

RETENTION

Onboarding stretched from seven days to cover the first three deliveries, with pre-delivery prompts landing inside the window where subscribers actually decide.

Online checkout screen showing payment details and cart

CONVERSION

The account area offered one obvious action: cancel. Adding skip, delay and swap as equally visible options converted a large share of would-be cancellations into pauses.

Photographer setting up studio lighting for product photography

CREATIVE

Usage guidance, dosing explanations and routine content replaced discount-led emails, which had been training subscribers to wait for offers.

Marketing team reviewing strategy at a whiteboard

MARKETING

Once subscriber life extended, the affordable acquisition cost rose. Budget went up rather than down — on the segments whose cohorts actually justified it.

Implementation

How it was sequenced

Fourteen weeks, ordered so the retention fixes landed before any acquisition spend increased.

WEEKS 1-2

Separate the signals

Failed payments split out from genuine cancellations, and lifetime value rebuilt net of refunds. The churn number turned out to be smaller and more fixable than reported.

WEEKS 3-6

Fix the schedule

Cycle lengths set per SKU and existing subscribers migrated with a clear explanation rather than a silent change.

WEEKS 7-10

Rebuild the lifecycle

Onboarding, pre-delivery prompts and the new cancellation flow launched together, since each depends on the others to work.

WEEKS 11-14

Re-open acquisition

With cohorts holding, target acquisition cost was raised and budget increased on the segments the data supported.

Migrating existing subscribers to a new cycle was the risky step. Explaining it plainly, rather than changing it quietly, is why it did not trigger cancellations.

Results

The KPI breakdown

Twelve-month cohorts, compared against the equivalent cohorts a year earlier.

Metric

Before

After

Change

Subscriber lifetime value

£118

£152

+29%

Month-three churn

19.2%

12.7%

-34%

Revenue per email sent

£0.44

£0.52

+18%

Average subscription length

4.1 mo

5.6 mo

+37%

Skip rate (in place of cancel)

2%

14%

+12pt

Failed-payment recovery

31%

68%

+37pt

Signup discount depth

25%

15%

-10pt

Skip rate rising is a good outcome here: a paused subscriber is worth far more than a cancelled one.

Supporting evidence

Before and after, side by side

The operating changes behind the numbers above.

BEFORE

•  One 30-day cycle applied to every product regardless of pack size

•  Onboarding stopping at day seven

•  Cancel as the only visible option in the account area

•  Win-back firing at day 90, long after the decision

•  Failed payments counted as churn, inflating the problem

AFTER

•  Cycle length set per SKU against real consumption rates

•  Onboarding covering the first three deliveries

•  Skip, delay and swap offered alongside cancel

•  Prompts landing in the fortnight before delivery three

•  Payment failures separated out and actively recovered

Supplement gummies photographed on a bright background

The cheapest single change was separating failed payments from cancellations. It cost nothing and immediately made the rest of the numbers honest.

We were about to cut acquisition spend. It turned out we could afford to raise it — we just had to stop shipping people a tub they had not finished.

Founder
NutriBlend

Services used

The service lines behind this engagement

Four of our nine service lines worked on this account, under a single plan and a single owner.

Lifecycle, onboarding, pre-delivery prompts and win-back — the service that owned the change that mattered most here.

Account area and cancellation flow, where a pause became easier to choose than a cancel.

Usage and routine content that gave the lifecycle programme a reason to be opened.

Acquisition budget reset against cohort value once subscriber life extended.

Classification

Platform, industry and market

Every case study on this site is classified on four axes so you can find the one that matches your situation.

Platforms & marketplaces

Where the store and the listings actually live.

PLATFORM

Industry

The category practice whose economics apply here.

Market

The geography this engagement was run for.

This engagement is filed as Email & Retention + WooCommerce + Health & Wellness + UK. It appears on each of those four pages.

Is your churn a product problem or a schedule problem?

For most subscription brands it is the second, and it is far cheaper to fix. Tell us what you sell and how often you ship it, and we will show you where your cancellations actually cluster.