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Amazon LTV
LTV (lifetime value) has a bigger impact on an Amazon seller's margins than almost anything else, including supplier or shipping cost negotiation, but Amazon hides repeat purchase data — this video shows how to find that data in Brand Analytics and back-calculate LTV and 'lifetime ACOS' (LACoS) so sellers can measure and manage it.
Taking a customer's average purchases from one to two per year has more margin impact than supplier negotiation, packaging optimization, or shipping cost negotiation combined.
Amazon does not display customer lifetime value or repeat purchase data in an obvious way; it must be found in Brand Analytics and back-calculated.
Customer Loyalty Analytics segments customers into Top tier, Promising, At risk, and Hibernating, each with different targeting tactics (brand-tailored promotions vs. sponsored display purchase retargeting).
Standard ACOS/TACOS metrics ignore lifetime value; Sophie Society uses LACoS (Lifetime ACOS) and Lifetime TACOS to reveal the 'true' economics of ad spend over a bounded window (e.g., one year, since a literal 80-90 year lifetime is useless for payback math).
Once LACoS is known, a brand can justify much higher headline ACOS (even 90-100%) because repeat purchases recoup the cost over time.
For consumables/semi-consumables brands, knowing LACoS should shift more budget toward acquiring new-to-brand customers, since those customers become repeat buyers with good long-term economics.
Repeat-purchaser sales percentage indicates whether a brand is consumable (20-50% typical), semi-consumable, or non-consumable (8% in the example, indicating non-consumable).
A custom spreadsheet tool (Sophie Society's) takes repeat customer counts/percentages, repeat units, and product price as inputs to output total customers, total units, average units per customer, and lifetime ACOS.
Demographics tool in Brand Analytics defines a 'customer avatar' usable for Ad Console audiences, DSP targeting, and listing copy.
Market Basket Analysis shows products frequently bought together with yours, useful for keyword reverse-engineering and PDP mimicry of complementary products.
Customer Loyalty Analytics — A Brand Analytics dashboard (Brand view and Segment view) that segments a brand's Amazon customers by purchase recency, frequency, and spend. Apply: Access via Seller Central hamburger menu → Brands → Brand Analytics, set a longer time range, and review the segment pie chart to see distribution across Top tier, Promising, At risk, and Hibernating customers.
Customer segments (Top tier, Promising, At risk, Hibernating) — Four customer buckets defined by recency/frequency/spend: Top tier (recent, high spend, frequent), Promising (recent, occasional, above-average spend), At risk (infrequent/not-recent), Hibernating (long time since purchase). Apply: Target Top tier and Promising customers with brand-tailored promotions for good ACOS; target At risk with a shorter look-back sponsored display/purchase retargeting window and Hibernating with a longer look-back window.
Average repeat purchase interval — A metric shown at the top-right of the Customer Loyalty Analytics dashboard indicating the typical time between repeat purchases. Apply: Use it as the starting hypothesis for the look-back window on first-purchase retargeting campaigns, then split-test other look-back periods.
New-to-brand customers metric — A metric (visible in both Brand Analytics and the ad console) tracking growth in customers new to the brand. Apply: Track its growth percentage over time as a leading indicator of acquisition, and cross-check against new-to-brand campaign ROAS/ACOS in Ad Console reports.
Repeat purchase rate — The rate at which customers make repeat purchases, tracked over time within Brand Analytics. Apply: Monitor it over time as a proxy for lifetime ACOS improvement; treat rising repeat purchase rate as a sign lifetime economics are improving.
Segment view (forecast/decline breakdown) — A drill-down view within Customer Loyalty Analytics showing last year's sales by segment versus predicted/forecasted sales for next year, plus growth/decline breakdown. Apply: Check whether Top tier customers are forecasted to grow or decline, and if declining, prioritize brand-tailored promotions or sponsored display purchase retargeting for that segment.
Consumer Behavior Analytics / Repeat Purchase Behavior — A Brand Analytics section showing repeat ordered product sales as a percentage of total sales, repeat customer count, and repeat ordered units percentage (without showing total customer count). Apply: Use the repeat-sales percentage to classify the brand as consumable (20-50%), semi-consumable, or non-consumable (e.g., 8%), which determines how much LTV analysis matters.
LTV calculation spreadsheet — A proprietary Sophie Society tool that takes repeat customers, repeat customer %, repeat ordered units, repeat ordered units %, and product price as inputs to output total customers, total units, average units per customer, and lifetime ACOS. Apply: Feed in Brand Analytics repeat-purchase figures and current ACOS to back-calculate lifetime ACOS and average purchases per customer; obtainable by commenting on the video's post or emailing Sophie Society.
LACoS (Lifetime ACOS) / Lifetime TACOS — Metrics that recalculate standard ACOS/TACOS over a bounded time window (e.g., one year) to account for a customer's likely repeat purchases, rather than just the first sale. Apply: Use LACoS instead of raw ACOS to judge whether ad spend is sustainable — a headline ACOS of 90-100% can be justified if LACoS, calculated from repeat purchase data, comes out much lower.
Sponsored display purchase retargeting — An Amazon ad placement that retargets past purchasers, with look-back window tunable by recency segment. Apply: Apply a shorter look-back window for At risk customers and a longer look-back window for Hibernating customers, using the average repeat purchase interval as a starting point.
Brand-tailored promotions — Amazon promotions/coupons targeted at specific customer segments identified in Customer Loyalty Analytics (referred to there as 'high spend customers' and 'promising customers'). Apply: Direct these promotions at Top tier and Promising segments to defend against forecasted decline and capture good ACOS from low-cost repeat sales.
Demographics tool / customer avatar — A Brand Analytics report used to define who the brand's 'customer avatar' is based on demographic data. Apply: Use the customer avatar to build Ad Console audience targeting, DSP targeting (especially for consumables brands), and to write listing copy that speaks directly to that avatar.
Market Basket Analysis — A Brand Analytics report showing which products are frequently purchased together with a given product. Apply: Use it to find complementary products to target, reverse-engineer their listing keywords to add to your own, and mimic aspects of their PDPs since they likely share your customer avatar.
Ad Console new-to-brand reporting — A report in Amazon's Ad Console showing ROAS/ACOS performance specifically for new-to-brand campaigns. Apply: Check this report to confirm new-to-brand campaigns run at lower ROAS/higher ACOS, then justify continued/increased spend there once LACoS shows those customers become profitable repeat buyers.
DSP (Demand-Side Platform) — Amazon's programmatic advertising platform, mentioned as an additional channel for using demographic/customer avatar data. Apply: Especially for consumables brands, feed customer avatar/demographic insights into DSP targeting.
Big competitors, including a billion-dollar skincare company cited as an example, are already doing this same LTV/LACoS math in boardrooms, which is why CPCs in consumables categories are often high — the competition already knows the lifetime math justifies the spend.
Simply measuring repeat purchase rate creates a psychological effect ('what gets measured gets managed') that makes sellers subconsciously start optimizing for it, even before any deliberate strategy change.
Segment-view forecasting can reveal that most of a brand's 'top tier' customers are actually predicted to decline over the coming year, which reframes retention targeting as urgent rather than optional.
The average repeat purchase interval metric can be used as a data-driven starting hypothesis for the look-back window on first-purchase retargeting campaigns, rather than guessing.
Reverse-engineering the listings of products frequently bought together with yours (via Market Basket Analysis) lets you borrow their keywords and page structure, on the logic that you likely share the same customer avatar.
«LTV or lifetime value has a bigger impact on margins for an Amazon seller than almost anything else you can do to affect margins.»
— 00:00
«It's not even close.»
— 00:22
«Amazon doesn't show us customer lifetime value.»
— 13:49
«We're dead by then.»
— 15:56
«There are big companies doing, you know, these calculations in rooms with like tons of executives, right?»
— 19:47
«I actually can spend 100% ACOS because I know my average repeat customer rate and I know that that will catch up over time and my lifetime ACOS is significantly less than my average ACOS.»
— 20:53
«It gives you a more realistic picture over what the true economics are of the brand... this is definitely completely critical for every consumables brand to do. They should all be doing this exercise.»
— 22:15
«That's just basically free additional purchases.»
— 23:26
«If you reverse engineer and check out those listings of products that were bought together with yours, you might want to try adding some of their keywords to your listing... it is a complementary product to yours.»
— 25:00
«For anybody that wants this little tool that actually back calculates your LACos and your average purchases per customer and your lifetime value, just comment on this post... and we will send it to you.»
— 26:02
Reception
Comments are generally positive and engaged, with viewers requesting the spreadsheet and praising the content, tempered by mild frustration over regional unavailability on Amazon.
A framework-dense practitioner walkthrough that names and demonstrates specific Amazon Brand Analytics tools and a proprietary LACoS methodology, aimed at seller-operators rather than a general audience.
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