Increasing revenue and sales across over 100 price zones
The health&beauty retailer Kosmo used Competera’s platform to optimize pricing
Kosmo utilized Competera’s platform to hit four goals during a nine-week market test
- To maximize revenue without losing profit margin
- To gain control over the creation of pricing and promo strategies
- To cushion the effect of high promo pressure in the industry
- To stop copying pricing moves of competitors
Challenge
-
Significant promo pressure: over
60% of discounted items; -
Vendors call the shots in terms of promos;
-
Competitor-based pricing only;
-
Over 100 price zones with different price elasticity.
Solution
Regular demand-driven recommendations for price and promo decisions
Managers used demand-based price and promo recommendations
Managers used traditional manual pricing methods
The market
test featured two groups
The two groups (160 products) have similar seasonality, as well as profit and revenue patterns. What is more, these groups are unlikely to be in the same basket (therefore changes in the test category could not have a significant impact on the control category, and vice versa).
Before launching the project, the retailer provided the necessary data to Competera, which included but was not limited to historical data, competitive data, data regarding business goals and restrictions.
Results: Kosmo hit all the set goals
Kosmo has managed to maximize revenue, gain more flexibility in the creation of pricing and promo strategies, has softened the effect of significant promo pressure, and has become less dependant on competitors’ pricing moves.
+8.1%
Revenue
1%
Profit margin saving
Despite significant promo pressure
+15.9%
Sales items
+9.8%
Gross profit
Front
Challenge
-
Rule-based competitive pricing exclusively
The company used this pricing approach for some 2,000 KVI products (out of 10,000 items in the portfolio) across over 100 points of sale and different price zones.
-
Bulky and time-consuming pricing
The in-house ERP and Excel-based pricing systems had technical limitations to store and process pricing data.
-
Extremely competitive and fast-paced market with extremely high promo pressure
Pricing managers lacked time to process all the necessary data and consider all the pricing and non-pricing factors to set optimal prices with necessary speed.
Solution
Some 2-3 thousand of weekly price recommendations based on short-term algorithmic predictions of demand reaction on price changes within the product portfolio.
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The health&beauty retailer maximized revenue without losing their margins
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Competera Pricing Platform helps retailers to craft optimal offers
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