LTV and MER modelling for eCommerce brands at $2M–$20M
ROAS is a lie. It tells you which ad got the click, not which customer became your most valuable. We build LTV cohort models and MER dashboards that show you where to invest to grow the right customers.
Why most eCommerce brands are flying blind
ROAS masks real performance
A channel with 4× ROAS but high-churn customers is worse than one with 2× ROAS and loyal repeat buyers. Without LTV, you're optimizing for the wrong thing.
Attribution is broken
Every channel claims the sale. Meta says it drove it, Google says it drove it, email says it drove it. The only truth is blended MER – total revenue ÷ total ad spend.
No cohort visibility
Aggregate numbers hide problems. A great month of new customers can be offset by high churn from last quarter's cohort – you won't see it until it's too late.
CAC payback guesswork
If you don't know your 90-day LTV by acquisition channel, you're setting ad budgets by instinct. You're almost certainly overpaying for bad customers and underspending on good ones.
LTV by acquisition channel: what the data shows
12-month customer LTV varies significantly by where the customer came from. This is why blended ROAS misses the point.
| Acquisition Channel | Avg 12-mo LTV | Repeat purchase rate | CAC payback | LTV:CAC ratio |
|---|---|---|---|---|
| Email / SMS | $285 | 52% | 1.2 months | 8.5× |
| Organic search (SEO) | $240 | 44% | 2.1 months | 6.2× |
| Direct / brand | $210 | 48% | 1.8 months | 5.8× |
| Paid search (Google) | $165 | 32% | 3.4 months | 3.2× |
| Paid social (Meta) | $125 | 24% | 5.2 months | 2.1× |
Benchmark averages across acceleroi eCommerce client cohort analysis. AOV range: $65–$150. Results vary by niche, price point, and replenishment cycle.
What we build for you
Customer LTV Cohort Model
Monthly cohort analysis showing 30/60/90/180/365-day LTV by acquisition source, product, and customer segment. See which channels bring your best customers, not just your cheapest ones.
MER (Media Efficiency Ratio) Dashboard
A single north-star metric: total revenue ÷ total ad spend. We build a live dashboard segmented by channel, campaign type, and product – updated daily, no data delays.
CAC Payback Period Analysis
How long does it take each channel to pay back its acquisition cost? We model payback curves by channel and product line so you know where to increase budget and where to pull back.
Repeat Purchase Rate & Repurchase Curves
Which products drive repeat buyers? Which have one-and-done customers? We map your repeat purchase curves and identify the products and triggers that maximize 2nd and 3rd order rate.
RFM Customer Segmentation
Recency-Frequency-Monetary segmentation of your full customer base. Know who your Champions, At-Risk, Lapsed, and High-Potential customers are – and what marketing to give each segment.
Predictive LTV Scoring
ML-based LTV prediction for new customers in their first 30 days. Identify high-LTV customers early so you can prioritize them in post-purchase flows and suppress low-LTV segments from retargeting.
Tech stack we work with
Shopify, Klaviyo, Meta Ads, Google Ads, TikTok Ads, Amazon, subscription platforms
BigQuery, Snowflake, Redshift – or direct Shopify + Klaviyo APIs for lighter setups
Looker Studio, Tableau, Metabase, or custom Next.js dashboards for real-time MER tracking
Triple Whale, Northbeam, Rockerbox, or custom UTM + server-side pixel setups for iOS-robust measurement
This is what the AI audit will tell you about your unit economics
Run the free 48-heuristic audit and get findings like these – specific to your brand, in under 3 minutes.
No cohort-level LTV tracking in place
You're measuring blended averages instead of acquisition-cohort LTV. Without cohort data, you can't tell which channels actually produce profitable customers.
CAC payback period is unknown
If you don't know how many months it takes to recoup acquisition cost, you're flying blind on ad spend. Most brands discover payback is 2–3x longer than assumed.
MER not tracked against targets
Marketing Efficiency Ratio gives you the single number that matters for profitability. Without MER targets, scaling decisions are guesswork.
Calculate your customer lifetime value
Enter your numbers to see LTV, acceptable acquisition cost, and maximum ad spend per customer.
What LTV modelling unlocks for our clients
Average impact across clients who implemented our LTV and MER modelling recommendations.
Weighted average across 15+ LTV modelling engagements · Impact measured 6 months post-implementation
30+ five-star reviews
Data warehouse pros
Not just averages
CRO Expert Team
What to expect working with us
Data audit & collection
We connect to your Shopify, Stripe, Recharge, and analytics data to extract transaction history, subscription data, and customer behavior. We identify data gaps and fix tracking issues before modelling.
LTV model development
We build your customer LTV model – segmented by acquisition channel, product category, and cohort. You'll know the true value of each customer segment and which channels produce the highest-value buyers.
MER dashboard & attribution
Marketing Efficiency Ratio dashboards go live in Looker Studio. You see blended ROAS across all channels with LTV-weighted attribution so every dollar of spend is evaluated against long-term value, not just first-purchase revenue.
Predictive analytics
Churn risk scoring, next-purchase prediction, and CLV-based segment targeting. Your marketing team allocates budget based on predicted customer value, not just historical ROAS – a fundamentally better way to grow.
FAQ
What data do we need to get started?
At minimum: Shopify orders export and your ad platform data (Meta, Google). Ideally Klaviyo for email attribution too. We can work with 12+ months of historical data for meaningful cohort analysis, but can start with 6.
Do we need a data warehouse already?
No. For smaller brands we can work directly with Shopify and Klaviyo APIs. For 7-figure+ brands we recommend BigQuery + Fivetran or Airbyte as a long-term foundation – we help set this up.
How is this different from Triple Whale or Northbeam?
Attribution tools show you which channel drove the last click. We model long-term LTV by cohort – answering a different question: which channels grow customers who come back? Both are valuable; they complement each other.
How long until we have a working dashboard?
MER dashboard: 1–2 weeks. LTV cohort model: 3–4 weeks. Full RFM segmentation + predictive scoring: 6–8 weeks. We prioritize the highest-impact deliverable first.
What data do you need access to?
Shopify order data, payment processor data (Stripe/Recharge), GA4, and ad platform spend data (Meta, Google). We handle all data extraction and transformation – you just grant API access and we build the pipelines.
How is this different from Shopify analytics?
Shopify analytics shows you basic metrics like AOV and repeat purchase rate. Our LTV modelling goes much deeper – cohort-level lifetime value projections, channel-attributed LTV, churn probability scoring, and MER calculations that account for long-term value rather than just first-order ROAS.
Related services
Ready to fix what the audit finds?
The 90-Day CRO Sprint includes LTV dashboards, MER tracking, and a Looker Studio build alongside 6–8 A/B tests. +15% conversion rate in 90 days – or we keep working free until you get it, and refund 50% on day 91.
Apply for a Strategy Call →