ABC analysis of products

Definition

ABC analysis of products is a method for classifying assortment by its contribution to key business metrics: revenue, margin or turnover. In practice, sellers split SKUs into three groups (A, B, C) to prioritise purchasing, stock levels and marketing.

How ABC analysis works: steps and formulas

ABC analysis is carried out via a simple five-step algorithm. Below is the exact sequence and the formulas used by sellers on Kaspi.kz.

1. Choose a metric. Revenue, margin or number of sales are commonly used. For most Kaspi.kz sellers it is recommended to start with revenue and then test by margin.
2. Gather data. The analysis period is 3, 6 or 12 months. The faster the turnover, the shorter the period. Export data by SKU: quantity sold, revenue, cost of goods sold, returns.
3. Calculate each SKU's share. For each SKU calculate total revenue and its share of overall assortment revenue: share_i = (revenue_i / total_revenue) * 100%.
4. Cumulative share and ranking. Sort SKUs by descending share and compute the cumulative share. Standard split: A — top items contributing roughly 70–80% of revenue; B — the next 15–25%; C — the remaining 5–10%. In count terms A is often ≈10–20% of SKUs, B ≈20–30%, C ≈50–70%.
5. Assign classes and test. Tag SKUs and check if the distribution makes sense: if 2 SKUs produce 80% of revenue, that's a normal Pareto distribution; if not, adjust the cutoffs.

Numeric example. A seller with 1,000 SKUs generated 120 million KZT in revenue over 6 months. The top 200 SKUs produced 90 million KZT — 75% of revenue. So those 200 SKUs are class A (20% of SKUs → 75% of revenue). The next 250 SKUs produced 24 million KZT (20%) — class B. The remaining 550 SKUs are class C (5% of revenue).

Why ABC analysis is useful for a seller on Kaspi.kz

ABC analysis converts assortment management from intuition into prioritised actions. Specifically for Kaspi.kz sellers it works like this:

• Purchase focus: allocate 60–70% of working capital to A-items. Example: with a monthly turnover of 10 million KZT, direct 6–7 million to replenishing A.
• Availability control: set higher stock levels and replenishment frequency for A-items. A stock-out on A-items causes a noticeable drop in rating and revenue on the platform.
• Marketing and traffic: concentrate ad budget and promotion on A and promising B items. Use clearance promos for C-items to free up warehouse space.
• Warehouse management for Kaspi FBS/FBO: for FBO keep more A-items in Kaspi's warehouse locations; for FBS configure express delivery and replenishment schedules to avoid stock-outs and speed up turnover. See guide on FBS for specifics.

Examples on Kaspi.kz: real seller scenarios

1) Seasonal demand. A sports accessories seller found that 30 SKUs generated 65% of revenue during the summer. They increased safety stock for those SKUs before the season and moved slow SKUs to clearance, improving cash flow.

2) New SKU launch. After launching a new line, the seller ran ABC analysis at 3 months and again at 6 months. Some SKUs initially in B migrated to A as repeat purchases grew; others returned to C. This helped to adjust reorder points and promo budgets.

3) High-return SKU. One electronics seller saw a SKU in A by gross revenue but, after accounting for returns and warranty costs, its net contribution fell to B. Reclassifying it led to reduced ad spend and renegotiated supplier terms.

Practical tips for implementing and maintaining ABC analysis

• Automate data exports from the Kaspi.kz seller cabinet and keep a clean SKU master with cost, barcode and supplier info.
• Run analysis on both revenue and net margin — compare results and prioritise according to business goals (growth vs profit).
• Use rolling periods (e.g., last 6 months) to smooth seasonality. Maintain a separate view excluding large one-off promotions.
• Set differentiated policies: higher safety stock and reorder frequency for A; forecast-driven orders for B; limits or dropshipping for C.
• Integrate ABC classes into pricing, promotions and Buy Box strategies — invest in content and ads for A and promising B SKUs.
• Document rules and review exceptions regularly with the procurement and operations teams.

Common mistakes and how to avoid them

• Using gross revenue only: ignore commissions, returns and cost and you may overrate low-margin SKUs. Use net revenue or margin for more accurate classification.
• Too short or too long period: a 1-month snapshot can be noisy; a 24-month period can hide recent trends. Choose period by category velocity.
• No follow-up actions: classification without operational rules won't change results. Define purchasing, stocking and marketing actions per class.
• Static thresholds: don’t fix class boundaries forever — retest and adjust based on distribution changes.

Short checklist for implementation on Kaspi.kz

• Export SKU sales, costs and returns for the chosen period.
• Choose metric(s): revenue and/or margin.
• Calculate SKU shares, sort and compute cumulative shares.
• Assign A/B/C classes and document policies for each.
• Automate periodic recalculation and monitor exceptions.

Conclusion

ABC analysis is a simple but powerful tool for Kaspi.kz sellers to focus investments, improve availability and boost profitability. Start with revenue, validate with margin, automate the process and tie classes to concrete purchasing and marketing rules — this turns insights into measurable business improvements.