[Retention & lifecycle]() / [Use cases]() / [Lifecycle diagnosis]() [How it works]() [What you get]() [Scope]() [Start a review]() [Retention & lifecycle]()[Proof & decisions]() # Explain why email and SMS revenue moved. When revenue, deliverability or a cohort’s repeat rate moves, a clear answer within days: what changed, how sure we are, and the one test to run. [Start with a retention review]() [How it works]() Repeat rate down 3 points · October first orders Cause Share of the drop Evidence More buyers came in on the 20% code 58% Code buyers repeat at 8%, others at 13% Fewer Care Kit buyers 27% Kit buyers repeat more often Slower delivery in two states 15% Late orders repeat less The diagnosis, ranked by how much of the drop each cause explains. ## Sound familiar? - Email revenue dropped, and three people have three theories. - This fall’s first-time buyers aren’t coming back the way last fall’s did. - Open rates moved, and nobody knows whether it’s deliverability or the audience. Without a cause, teams rewrite the subject line and miss the promotion that changed who they were acquiring. ## What changes. ShowTodayWith the engine First reaction Theories in Slack A diagnosis within days Causes Subject lines and send times Audience, timing, content, delivery and product, ranked Cohorts Compared by month Compared by source, first product, discount and delivery Next step A long list of ideas One test, with an owner ## How it works. 5 steps, 4 stages. - AI**1** - Rules and automation**3** - Your team**1** - Approval 1. 1 Spot 1. Rules and automation ### Spot the change Alerts fire when revenue, repeat rate or deliverability move beyond normal. - Klaviyo - Google Analytics 2. 2 Separate 1. Rules and automation ### Check sending health first Sender authentication, unsubscribe handling and complaint rates, before anything about content. - Klaviyo 2. Rules and automation ### Cut by cohort and channel Splits by acquisition source, first product, discount, delivery and returns. - Shopify - Hightouch 3. 3 Explain 1. AI ### Explain the difference Ranks likely causes, and keeps what the data shows apart from what it only suggests. 4. 4 Test 1. Your team Approval ### Choose the test Your team picks one change to test, with an owner and a date. Each test resets the baseline ## What you get. Real work, every week. Memo 014 Owner: head of lifecycle October’s first-order buyers repeat less. The welcome code is the likeliest reason. Seen Repeat rate 8% for code buyers, 13% for the rest Not shown That the code caused it Test Hold the code from half of new visitors for three weeks Check Repeat orders at 60 days The memo that goes to the owner: what the data shows, what it doesn’t, and the test. Sending health · October - Sender authentication - One-click unsubscribe - Spam complaints Rising on weekly sends - Inbox placement at Gmail Sending health, checked before any theory about content. ## How you’ll know it’s working. 1. Time from change to diagnosis Days to an answer, not a quarter of theories. 2. Diagnoses with a confirmed cause How often the answer held up once we tested it. 3. Revenue and repeat rate recovered Whether the fix moved the number that started the question. Baselines agreed before we build. ## Works with what you have. Email & SMS - Klaviyo - Attentive Commerce - Shopify Data - Hightouch Measurement - Google Analytics We configure first Klaviyo’s reports and Shopify’s order data hold most of the evidence. We connect them and check sending health first. We build when The cause sits across audience, product, discount and delivery data that no single report joins. ## What a first build includes. Built in your accounts, around your team. Scope, fee and baseline agreed before we start. 1. 1 Design 2. 2 Build 3. 3 Run it, or hand it over [Start with a review]() [Scope this build]() ### We build - Alerts on revenue, repeat rate and deliverability - Cohort cuts by source, product, discount and delivery - A ranked-cause memo for every alert - A follow-up test for each memo ### We start from - Klaviyo and SMS account access - Order, refund and discount data - The campaign and promotion calendar ### From your team Owner Head of lifecycle Involves - Lifecycle - Growth - Finance ## Questions teams ask. How often is too often to email? It depends on the audience, so we test it. A randomized experiment at a large North American retailer covered 603,153 customers. Alternate-day coupon emails cut unsubscribe probability by 59.2% against daily sends, and short-term revenue fell 5 to 8% (a 2026 working paper). We’d test frequency on your list before changing it. Do Gmail’s sender rules change this? They set a floor. Gmail’s bulk-sender rules expect authenticated mail and easy unsubscribe from large senders, and we check those before looking at content. A drop with a sending-health cause looks different from an audience drop, so we separate them first. Who owns it once it’s running? You do. It’s built in your accounts, documented, with training for the people who run it. Ownership usually sits with your head of lifecycle. We can keep running it with you, or step back. How do we start? Usually with a retention review: two to four weeks, a fixed fee credited to the build, and a plan that’s yours. If the job is already clear, we can scope the build directly. ## Part of your retention engine. One of 12 use cases, in 6 parts. [See the whole retention engine]() 1. [Second orders **3**]() 2. [Subscribers **3**]() 3. [Contact that fits **1**]() 4. [Owners & loyalty **2**]() 5. [Lifecycle production **1**]() 6. [Proof & decisions **2**]() In proof & decisions - [**Retention proof**Prove which messages and discounts earn their cost]() - **Lifecycle diagnosis**You’re here Works with - [**Search diagnosis**Know why your search traffic moved]() - [**Second orders**Turn first orders into second orders]() See it at work - [**Also in**Finance & business intelligence]() ## Find the reason behind the dip. Start with a retention review. [Start with a retention review]() [**Talk it through first**15 minutes]() We reply within one business day. --- Source: [https://www.thekeating.co/use-cases/lifecycle-diagnosis/]() [Contact Keating & Co](mailto:nelson@thekeating.co) · [Agent guidance](https://www.thekeating.co/llms.txt)