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DekiskaDTC FASHION

Cut flow count by half and grew lifecycle revenue by 34%.

Dekiska had 41 active flows and no idea which ones worked. We rebuilt lifecycle around six programs with owners, guardrails and a measurable hypothesis each.

Neutral-toned knitwear on a studio rack being packed into a kraft box
MODELDTC apparel
ACTIVE FLOWS AT START41
LIST SIZE310k
TEAM1 email marketer
THE QUESTION

Is our lifecycle underperforming because we send too little, or because we send too much of the wrong thing to the wrong people?

+34%LIFECYCLE REVENUE
19ACTIVE FLOWS-22
0.14%UNSUB RATE-58%
SERVICES
  • Lifecycle architecture
  • Growth operations
STACK
  • Shopify
  • Klaviyo
  • Postscript
  • Looker Studio

The problem

Forty-one flows had accumulated over three years, most built by different people responding to different quarterly priorities. Several sent to overlapping audiences on the same day. Nobody could say which flow drove which revenue because none of them had holdouts.

What the inventory showed

  • 9 flows had not been edited in over 18 months and still sent daily.
  • The top 3 flows produced 78% of lifecycle revenue; the remaining 38 produced the noise.
  • The most engaged 5% of the list received an average of 11 messages per week.
  • Unsubscribes concentrated in the 48 hours after a customer entered three flows at once.

What we built

  • Global frequency caps and a suppression hierarchy applied before any new build.
  • Six programs: welcome, post-purchase, replenishment, browse and cart recovery, winback, VIP.
  • A holdout group on every program so revenue claims are testable.
  • A single Looker Studio view the client reads instead of five platform dashboards.

The result

Sending less made more money. Lifecycle revenue grew 34% while total message volume fell by roughly a third, and unsubscribe rate dropped by more than half.

"We deleted more than we built and revenue went up. That was uncomfortable and completely correct."Ecommerce Director, Dekiska
HOW IT RAN, 3 MONTHS
  1. PHASE 1Inventory

    Every flow, campaign and automation catalogued with its audience, overlap, revenue and last edit date.

  2. PHASE 2Consolidate

    22 flows retired or merged. Global suppression and frequency caps introduced before anything new shipped.

  3. PHASE 3Rebuild

    Six programs rebuilt with explicit entry criteria, an owner, a hypothesis and a holdout group.

  4. PHASE 4Run

    Experiment cadence, one structural test per program, results reviewed against holdouts.

HOW WE MEASURED THIS

Lifecycle revenue compares the 60 days after rebuild against the 60 days before, on a holdout-adjusted basis in Klaviyo and Shopify. Unsubscribe rate is per-send average. Client-approved. Attribution is last-click and therefore directional.

Read our evidence standard

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