I'm scalping my coffee subscriptions on CAC assumptions I cannot actually verify because Shopify shows me almost nothing useful

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Check out Metorik for this. You’ll be able to check out your actual LTV really easily, and even lifetime profit too. They have a great cohort report where you can see which products people buy in their first order and then how often they repurchase and their LTV over time so you can see which of your subscriptions or coffee beans people love the most.

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honest answer to your actual question: right now you don't know, and scaling meta spend on an unverified repeat assumption is the most common way subscription brands quietly go broke. so slow the scaling until you can see your payback. that's not a tooling gap, it's a "you're flying blind on the one number that decides everything" gap. you don't need a new analytics product to get this though. for a subscription business the data already lives in your subscription app (recharge/bold/whatever) plus a shopify order export. take everyone you acquired in a single month at least 3 months back, and just count how many of them placed a 2nd, 3rd, 4th order and the total revenue they've generated since. that's your cohort retention. a spreadsheet does it in an afternoon. you only graduate to a paid cohort tool once you're tired of rebuilding the sheet. the number that actually matters isn't "do most come back", it's contribution margin payback. at $38 cac, what's your margin per order after cogs, shipping and fees? if it's say $15, you need roughly 2.5 orders just to break even on acquisition. so the real question becomes "what % of a cohort survives to order 3", because that's basically your breakeven line. if fewer than half get there, a big chunk of your spend is underwater and scaling makes the hole bigger, not smaller. and watch your one-and-done rate specifically. heavy churn right after order 1 in subscriptions is usually a product, onboarding or wrong-audience problem (classic when a discount pulls in deal seekers who never intended to stay), and no cohort dashboard fixes that. nail first-to-second order retention before you pour more into acquisition.

Two separate problems are tangled together here. One is "can I even pull this data." The other, the one that actually matters, is "am I reading the right number once I do." On pulling the data: Did you try asking Shopify Sidekick to just generate the cohort report for you? It can build one in the ShopifyQL editor from a plain-language prompt, and if it hands you something clean, that is the fastest path. If Sidekick gets confusing or vague, build it manually. Shopify has a cohort view baked in now: Go to Analytics, then Reports. Either open the default "Customer cohort analysis" report, or click New exploration and switch the report method from Free form to Cohorts. Set the primary metric to "Amount spent per customer." The tooltip describes it as the average cumulative amount customers in that cohort have spent at your store since their first order. Each row is a cohort (the month they first bought), each column is months since first purchase. That is your 30, 60, 90 day view, no more guessing. Now the part that matters more than the clicks. "Amount spent per customer" is revenue, not profit. So if your CAC is $38 and you wait for a cohort to cross $38 in cumulative spend, that is your revenue payback point, not your real one. You have not recovered your $38 until the cohort crosses $38 in gross profit. Quick definitions so we are not talking past each other: CAC (customer acquisition cost): the real cost to acquire one new customer. Shopify will not hand you this, it does not record your ad spend at all, so take total ad spend from your backend finance or accounting report and divide it by the new customers you acquired in that same window. That is your real CAC, not Meta's reported cost per purchase. COD (cost of delivery): everything it costs to fulfill one order. For coffee that is landed product cost (beans, bags, packaging), pick and pack, the shipping label, and payment processing. Subscriptions reship, so COD hits every reorder, not just the first. Gross profit: net sales minus COD. Contribution profit: gross profit minus ad spend. So the honest version of your question is: at what month does cumulative gross profit per customer cross $38. That is your true CAC payback. Pull the cohort report on revenue to see the shape, then haircut each cohort by your gross margin to get the profit version. Example only, plug in your real number: if your gross margin on a coffee order is 60 percent, a cohort sitting at $63 in cumulative revenue is only about $38 in gross profit, so that is roughly where you actually break even, not the month they hit $38 in sales. For a subscription brand specifically, three things I would lock down: Split your spend by who it actually brought in: new customers versus returning customers. CAC is only about new customers, so dividing total spend by new customers inflates the number if any of that spend (and the orders it drove) actually came from returning customers. The cost to bring a returning customer back is a separate, usually cheaper line that deserves its own tracking. Note this is a different cut from prospecting versus retargeting, and the two should not be confused: prospecting is new-customer spend by design, but it is not the only spend that brings in new customers, and retargeting is not automatically returning-customer spend. Retargeting converts plenty of first-time buyers who just needed a nudge, and it also pulls back lapsed customers, so it sits across both. Attribute spend by the outcome (new vs returning customer), not by the ad type. Track the percentage of new customers who never place a second order, and treat that one number as a headline metric. You said some churn after one order and some stay a year, so a single average is blending two very different groups into one misleading figure. If most customers never come back for a second order, then a small loyal group is quietly carrying your payback math, while paid spend keeps buying one-time buyers who never earn back the $38. Read payback by cohort over time, not just the lifetime average. If newer cohorts cross the profit line later than older ones, your acquisition is getting more expensive in real terms even when the headline CAC looks flat. You are not necessarily spending into an invisible problem. You just cannot answer the question yet, because you are staring at revenue when the real question is profit and time. Build the cohort view, convert it to gross profit, find the month it crosses $38, and put that payback window next to how long your cash can float the gap between paying for a customer and earning it back. On a reship subscription model, that cash gap is usually the thing that bites before churn does. Suggested readings, a few prior comments from this subreddit: Can your unit economics support paid ads eCommerce financials, the metrics that actually matter Same ROAS, different profitability Cash conversion cycle and inventory float

which subscription app are you using? thomas lalas recently posted on linkedin something interesting about 30-60-90 day subscription economics that could be very useful here

The fact that you're asking this question puts you ahead of most people scaling subscription businesses on Meta. A lot of brands scale on the same assumption and don't question it until cash flow tells them something is wrong. At $38 CAC for a coffee subscription, the entire model lives or dies on retention, and you're right that scaling without knowing your actual cohort data is risky. You don't need Shopify's native analytics to figure this out though. Export your order data, sort customers by first purchase date, and track how many of them placed a second order within 30, 60, and 90 days. It's manual but it gives you the answer you need. If 70% of customers are still active after 90 days, your $38 CAC is probably sustainable. If 50% churn after one or two orders, you're losing money on acquisition and scaling just accelerates the problem. The practical move before increasing spend any further is to pause scaling, pull 3-4 months of customer data, and build a simple retention curve. Once you know your actual repeat rate and average lifetime, you can back into what your CAC ceiling actually is rather than guessing. That number should drive every budget decision from here. Scaling based on vibes works until it doesn't, and with subscriptions the gap between profitable and unprofitable can be surprisingly thin.

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