> ## Documentation Index > Fetch the complete documentation index at: https://docs.ocular.dev/llms.txt > Use this file to discover all available pages before exploring further. # Customers & retention > Triggers in Ocular for cohort analysis, CAC payback, LTV, and repeat purchase behaviour — to diagnose customer acquisition and retention performance. Ocular has dedicated retention screens built for cohort analysis — more powerful than Chart Builder for these questions because they track cohorts over time, show period-by-period drop-off, and support acquisition vs. retention splits. **The hierarchy** * ****Sales Performance → New vs. Repeat Customer Trend**** {/* TODO: relink to /use-your-data/sales-performance once that page is published. */} — quick snapshot of new/repeat mix * ****Purchase Retention Cohort**** {/* TODO: relink to /use-your-data/cohorts/purchase-retention once that page is published. */} — definitive tool for repeat purchase, CAC payback, LTV, split-by capabilities * ****User Activity Cohort**** {/* TODO: relink to /use-your-data/cohorts/user-activity once that page is published. */} — site/app return rates from GA4 events, *before* repurchase *** ## Are customers coming back to buy again? **Trigger:** You need to know if you're building repeat demand or relying on one-time buyers — for forecasting, LTV, and acquisition-vs-retention budget decisions. **Start with:** Sales Performance → New vs. Repeat Customer Trend. Shrinking new share with stable volume → acquisition slowing. Shrinking repeat share → first purchases aren't converting to second. **Then go deeper:** **Purchase Retention Cohort** {/* TODO: relink to /use-your-data/cohorts/purchase-retention once that page is published. */} — tells you *where* and *why*. **Configuration:** Measure = Customers · Granularity = Month · Value Representation = Percentage. | Pattern | Meaning | Action | | -------------------------------------- | ------------------------------------------------ | ---------------------------------------------------------------------------------- | | Steep M0→M1 drop (only 10–15% return) | Most first-time buyers never come back | Re-engagement at Day 30–60 — welcome-back offers, product education, replenishment | | Flattens after M2–M3 (stable at 5–8%) | Loyal core; churn happens early | Invest in post-purchase flows, not late-stage win-backs | | Recent cohorts retain worse than older | Retention degrading — channel quality or PMF | Split cohorts by channel or discount code to isolate | | One cohort dramatically better | Something worked — campaign, product, onboarding | Identify and replicate | **Headline metrics:** Repeat Purchase Rate, Customer LTV, CAC Payback in the summary panel. **Decision:** Invest more in acquisition (repeat is healthy) or shift budget to retention (first-time buyers aren't converting to second)? *** ## Which acquisition channels produce customers who actually stick? **Trigger:** Spending across Meta, Google, influencers, organic — and you need to know which bring high-LTV customers vs. one-time buyers. **Go to:** **Purchase Retention Cohort → Split By: Discount Code (Acquisition) or Sales Channel** {/* TODO: relink to /use-your-data/cohorts/purchase-retention once that page is published. */} **Configuration:** Measure = Customers · Granularity = Month · Split By in Breakout mode. **What to look for:** Big M0 + steep drop by M2 → channel delivers volume, not value. Smaller cohort + flatter curve (15–18% still active at M5) → most sustainable acquisition source. **Cross-check with profitability:** Switch Measure to **Accumulated CM1 per Customer** to see which channels produce *profitable* repeat buyers after COGS. A channel might retain well but at low margin if it's discount-dependent. **Decision:** Which channels scale (high retention, high LTV), and which to cut (attract deal-seekers who churn)? *** ## How long does it take to recover my customer acquisition cost? **Trigger:** Finance or leadership wants proof that acquisition spend is sustainable — month-by-month cumulative revenue vs. CAC, per cohort. **Go to:** **Purchase Retention Cohort → CAC Payback toggle** {/* TODO: relink to /use-your-data/cohorts/purchase-retention once that page is published. */} **Configuration:** Toggle CAC Payback on. Measure = Accumulated Sales per Customer (or Accumulated CM1 per Customer for profitability-adjusted). Cells turn green once accumulated revenue surpasses CAC. | Payback timing | Meaning | Action | | ------------------------ | --------------------------- | ---------------------------------------------------------------------- | | M1–M2 | Healthy — recovers quickly | Safe to scale | | M4–M6 | Acceptable, watch cash flow | Tighten CAC targets, improve first-90-day repeat rates | | Beyond M6 or never green | Unsustainable | Cut budget; check if discounting is inflating CAC without building LTV | **Split by channel** (Discount Code or Sales Channel) to find channels that pay back in M1 vs. never break even. **Decision:** Is CAC sustainable, and which channels to scale vs. cut by payback timing? *** ## Are users coming back to my site — even before they buy again? **Trigger:** You want to track engagement retention, not just purchase. Site return rates dropping is a leading indicator — purchase retention will follow. **Go to:** **User Activity Cohort** {/* TODO: relink to /use-your-data/cohorts/user-activity once that page is published. */} Tracks GA4 event-based retention. Unlike Purchase Retention Cohort (counts purchases only), this counts any event — session starts, add-to-cart, product views. **Configuration:** Start Event = `add_to_cart` (or `session_start` for broader engagement) · Return Event = `session_start` · Granularity = Week · Split By Entry UTM Source. **Cross-reference with Purchase Retention:** Strong site return + weak repeat purchase → problem isn't engagement, it's conversion. Users come back but don't buy. Check pricing, availability, checkout friction. **Decision:** Which channels/audiences need better post-visit engagement (email, retargeting, content), and is the drop-off at site-return or repurchase? *** ## Who are my highest-value customers, and what do they have in common? **Trigger:** Building segmentation, planning a loyalty programme, or trying to acquire more of your best customers. **Go to:** **Purchase Retention Cohort → Measure: Accumulated Sales per Customer or Customer LTV** {/* TODO: relink to /use-your-data/cohorts/purchase-retention once that page is published. */} **Configuration:** Measure = Accumulated Sales per Customer. Use Split By: Shipping City (Acquisition), Product Category (Acquisition), or Discount Code (Acquisition) to find what high-LTV cohorts share. **Quick snapshot:** **Sales Performance → City Performance Across Price Buckets** {/* TODO: relink to /use-your-data/sales-performance once that page is published. */} — shows where high-value orders concentrate geographically. **Decision:** Which customer profiles for lookalike audiences, and which first-purchase products/channels to prioritise for more high-LTV acquisitions? *** ## How does AOV differ between new and returning customers? **Trigger:** Are returning customers spending more (loyalty signal) or less (discount dependency) than first-time buyers — and does it vary by channel? **Go to:** **Purchase Retention Cohort → Measure: Net AOV or Gross AOV** {/* TODO: relink to /use-your-data/cohorts/purchase-retention once that page is published. */} **Configuration:** Measure = Net AOV · Granularity = Month. M0 = first-purchase AOV. Later months = repeat AOV. If AOV declines later, repeat buyers may be cherry-picking discounts or buying lower-value items. **Split By Sales Channel** to see if the pattern varies. Channels where new customers spend more than repeat → discount-heavy acquisition inflating first orders. **Quick snapshot:** **Sales Performance → Discount Affinity by Customer Type** {/* TODO: relink to /use-your-data/sales-performance once that page is published. */} — discount usage by new vs. repeat by category. **Decision:** Is retention generating more valuable repeat purchases, or are repeat buyers being conditioned to buy only on discount? ## Next Courier RTO, pincode failures, billing discrepancies. All categories and the quick reference table.