Retention & LTV Analytics Expert - Audit Our DTC Data & Design the Insight Layer

We’re a DTC retention agency with our own analytics stack. We’re strong on the engineering - syncing each client’s Klaviyo + subscription data into a warehouse and surfacing dashboards. Where we want an expert is the thinking layer: which questions are worth answering, how to present the data so it tells a story, and how to read it. We want a full audit of our data + a blueprint for the insight system we’ll build. Paid test project first, then $2,000–$3,000 for the full audit. --About us We run a retention marketing agency for DTC/ecommerce brands (email/SMS + subscription). We’ve built an internal analytics platform that pulls each client’s Klaviyo (campaigns, flows, and events like Placed Order / Ordered Product / Canceled Order), their subscription data (CheckoutChamp, plus Klaviyo-side events from Loop/Skio), and client-level context into one warehouse, then surfaces it in dashboards. Integrating and displaying data is the part we’re good at. --The gap we want you to fill Our dashboards currently show numbers. What we’re missing is the interpretation layer - the part that turns data into decisions: - Which questions are actually worth answering? - How do you present each one so the data tells a story, not just a stat? - How do you read it - what does “good” vs “bad” look like, what thresholds/benchmarks matter, what’s the “so what,” and what action should it drive? The idea is one clear question per page, a plain-English takeaway computed from the data, and thresholds tuned per brand instead of fixed numbers. We want to design our own version, and do it better. We are not hiring you to build the tool - we build it. We’re hiring your analytical brain to design the blueprint we build against. --What we’ll give you Full access to our data structure - the schema/tables for clients, Klaviyo (campaigns, flows, events), and subscriptions (CheckoutChamp), plus any cost/margin context we have. Anonymized or sample data where it helps you reason about what’s real and computable. Happy to sign an NDA. A walkthrough of what’s currently synced and what our dashboards show today. What we want back (the audit) --A prioritized blueprint, grounded in our data, that answers: 1. Given the data we have, what are the highest-value retention questions we should build pages/modules around? 2. For each one, a spec (template below). 3. What are we missing - data we should be capturing but aren’t - and what each gap would unlock. 4. How you’d prioritize and sequence it if this were yours to build. For each question/module we’d want roughly this: - The question it answers (one sentence) - The metric(s) and how to compute them from our data - How to present it (chart / table / layout — rough is fine) - How to read it - benchmarks, thresholds, what good vs bad looks like, per-brand vs fixed - The takeaway sentence the tool should auto-write (e.g. “72.8% of revenue comes from repeat customers - a retention-led period.”) - The action it should drive - Data status - do we already have what’s needed, or is it a gap? Depth on individual subjects beats a shallow KPI wall. Example subjects: time between orders, cohort LTV, repurchase rate & drop-off between orders, VIP/whale concentration, subscription churn (active vs passive) & dunning recovery, subject-line performance, true email/SMS revenue share. --Format: a clear written doc (Google Doc / Notion / slides - your call), skimmable, that we could hand to an engineer and build from. A couple of fully worked module examples are worth more than a long list. You’re a fit if you - Live in DTC/ecommerce retention: LTV, cohorts, repurchase rate, time between orders, CAC:LTV, subscription churn/dunning, RFM/segmentation - Are data-literate — comfortable reading a schema and reasoning about what’s computable from it - Have hands-on Klaviyo experience; bonus for subscription platforms (Recharge / Loop / Skio / CheckoutChamp) - Can explain the “so what,” not just recite metrics - Bonus: you’ve designed or run retention analytics / dashboards before --How this works 1. Paid test project first. A small, scoped mini-audit (~2 hours, $100–$150). We give you one subject (e.g. time between orders or cohort LTV) and you show us how you think and present it, using the template above. 2. If it’s a fit, the full audit. Fixed $2,000–$3,000, roughly 2 days of focused work. We know strong people use AI to move fast - we’re paying for quality of thinking, not hours logged. To apply - Share 1–2 examples of retention analysis or dashboards you’ve designed (redacted/anonymized is fine). - In 3–4 sentences: pick one retention subject, tell us the single question you’d make a page answer, and how you’d have the data explain the takeaway. - Start your reply with the word “COHORT” so we know you read this.