Acquisition, retention and lifetime value by first-purchase month · 16 Sep 2025 – 31 Aug 2026
Records analysed
Customers (resolved)
Orders
Net revenue
Cohorts12 monthly
Row grainOrder line item
Read this first. The business grew ~4.5× during the window, so 60% of all customers were acquired in the last three months and have had almost no time to repeat. Cohort rows are therefore triangular — compare cohorts down a column (same age), never across a row. The Sep-2025 cohort covers only 15 days (18 customers) and is excluded from all trend conclusions.
Headline KPIs
Ratio metrics are recomputed from their components (sum of numerator ÷ sum of denominator), never averaged from per-row or per-cohort ratios.
Growth & Acquisition
August 2026 is a complete month (31/31 days), so month-on-month comparisons are valid at the right edge.
Monthly revenue and orders
₹ lakh per month · first bar is a partial 15-day month · hover for orders and customers
Revenue split: new vs returning
Share of monthly revenue from customers acquired in an earlier month
New customer acquisition trend
First-time buyers per month — this is the cohort size for each row of the matrices below
Average order value
Revenue ÷ distinct orders. Falling AOV at scale signals mix shift to lower-ticket SKUs
Customer Retention Cohorts
Each row is a cohort defined by its first purchase month. Month 0 is the acquisition month (always 100%). A cell shows the share of that cohort that made at least one purchase in that later month. Blank cells are months that have not happened yet.
Retention matrix — % of cohort active
Read down a column to compare cohorts at the same age
0%~3%6%+Blank = future month · N = cohort size
Average retention curve
Weighted across all mature cohorts, with the customer base behind each point
Month-1 retention by cohort — the improvement signal
Share of each cohort that came back in the very next month
Revenue Cohorts & Lifetime Value
Three views of the same cohorts: total rupees generated, rupees per acquired customer, and cumulative LTV per customer as the cohort ages.
Total revenue (₹)
Revenue per customer (₹)
Cumulative LTV per customer (₹)
Revenue matrix
Rupees generated by each cohort in each month of its life
LTV accumulation curve
Cumulative revenue per acquired customer — flatness after M0 is the core finding
Revenue contribution by cohort over time
Each calendar month's revenue, coloured by when those customers were acquired
Repeat Purchase Behaviour
Retention above is measured at month granularity. This section looks at purchase frequency and timing directly.
Purchase frequency distribution
Customers by lifetime number of purchase occasions
Days to second purchase
Among the 2,034 customers who repeated at all
Repeat rate at equal maturity
% repeating within their first 3 months — a fair cohort-to-cohort comparison
Product & Category Drivers
Which products bring the revenue, and — more usefully — which entry products produce customers who come back.
Category revenue mix over time
Share of monthly revenue by product category
Repeat rate by first product purchased
Minimum 150 customers per product · top and bottom performers
Top 15 products by revenue
ASP = revenue ÷ units. Complete product list is 185 SKUs.
Key Findings
Recommendations
Ordered by expected revenue impact against effort. Each carries the number it is based on.