Due to increasing the competitive pressure, the retailer's team first decided to test the most aggressive type of KVI pricing strategy.
The essence of the strategy: for both Hard KVIs and Soft KVIs, the Imprice platform began to automatically set the minimum price on the market, lower than the key competitors' prices (if this minimum price met restrictions of margin set by experts).
For other goods' roles, such as Foreground or Long tail, they launched ai-driven price optimization, based on demand sensing and chose the maximum of gross profit as an optimization criterion.
The Imprice platform managed prices of around 20,000 SKUs, which was 60% of the revenue and 65% of the gross profit of the pilot hypermarkets.
Step 4. Low season, "first minimum price" strategy for KVIs and demand sensing
For the pilot hypermarkets, FRUNZE pricing experts continued to manage promo prices and prices of a few categories, for example, cigarettes and ultrafresh products.
When evaluating the effectiveness of dynamic pricing, experts removed from the calculations sales data for the promos and "remained categories."
To keep within these daily limits of price tags, the retail chain used the Intelligent Queue, an analytical tool of Imprice that determines which prices have to be changed first and which price changes can wait.
On July 4, 2022, the Imprice system started to automatically calculate prices and send them to pilot hypermarkets.
Pricing experts of the grocery chain set upper limits on the quantity of price tags changing daily:
✓ Prices could be changed only on weekdays.
✓ On Tuesday, it was allowed to change <=700 price tags.
Tuesdays were days of suppliers' prices adjusting and cost prices changing.
✓ On other weekdays, it was allowed to change <=150 price tags only.
1 — Pilot and control stores selection
2 — Integration.
3 — Clustering.
4 — Low season, "first minimum price" strategy for KVIs and demand sensing.
5 — New pricing strategy for KVIs and price optimization for Long Tail and Foreground.
Schedule for Intelligent Queue, set by FRUNZE experts. Screenshot from Imprice
Buyers reacted quickly to the reduction of KVIs' prices: sales of the entire assortment rose sharply within the first 2 weeks. The number of cash receipts also increased.
Such a rapid reaction to prices is rare in grocery retail.
It usually takes several weeks to change the shopping behavior of a significant part of the consumers.
An example of the dynamics of a Hard KVI sales. In the second week of applying an aggressive competitive pricing strategy, sales of the item increased by 2 times, despite the low season. The growth in sales of KVI leads to an increase in sales of goods that are bought together with the KVI.
Pricing experts compared LFL of pilot with LFL of control stores. An aggressive competitive strategy boosted sales in pieces in pilot hypermarkets.
However, the increase in revenue was insignificant, and gross profit performance even slightly weakened.
Why it happened:
a) Significant decrease in the sales margin of KVIs.
b) Low season.
c) The first weeks of the pilot are the stage of the most active price exploration by AI algorithms.
If historical data does not contain enough price statistics for price optimization, then it requires an extended set of pricing experiments. Within a set price range, the algorithms change prices, measure the elasticity of demand, and calculate the optimal price — in this case, the price that ensures the maximum gross profit for the store.
Before the start of the pilot, FRUNZE rarely changed prices for most items of the assortment; therefore, the algorithms needed a significant amount of price experiments to collect statistics.
Commonly, business results slightly decrease within the price exploration period.