Clear Old Stock and Recover +3% of Previously Lost Margin
Hit the stock level and get maximum possible profit margin with discount depth differentiated on SKU-level, optimal markdown sequentions, and analytical prognoses on goal achievement.
Retailers lose money with traditional markdown campaigns
- ‘Blanket’ discounts
- Diluted margin
- Uncertain probability of hitting stocks
- Discount differentiation at SKU-level
- Maximized margin
- Suggestions on sequential discounts and predictions on hitting stocks
What is under the hood of markdown optimization?
Competera’s RNN analyzes retailer’s historical sales data to recommend an optimal discount at an SKU-level so the targeted stock level is reached with a maximum margin rate.
Based on set parameters (max. promo depth, markdown’s time frames, expected stock level), the platform’s time-series based algorithm generates the prognoses on hitted the stock level and gained margin.
- Historical sales (min 2 years)
- Historical promo (min 2 years)
- Promo calendar
- Product description
- Product stock availability
- Suggesting sequential discount periods
- Calculating cross elasticities and sales cannibalization effect
- Differentiated approach instead of blanket discounts
- Preventing profit margin from drop
No more black boxes: every recommendation is explained
Figure out the reasoning behind the optimal price recommendations.Competera interpretability features allow to:
- get insights on what was behind the Price Optimization engine’s decisions;
- check out how the set limitations have impacted the search range;
- find out what the demand elasticity curves look like;
- understand how the new price point impacts own product sales and what halo effect it has on other products in the category.