Markdown
optimization for
apparel & footwear
Maximize gross profit and profit margins, hit the stock level,
and build a rewarding customer experience with Competera’s
Markdown Optimization.
Reach your goals with Competera
Create an optimal value offering balancing the sales volume, profit margins rate, and discount depth.
Hit the stock level and get rid of old inventory before the new season begins
Get maximum possible profit margin with stock level target and deadlines secured
Schedule optimal markdown sequentions based on data-driven analytical prognoses
Keep your prices competitive by following only your true competitors
Make sure your margin is not diluted by following unnecessary competitors. Competera’s algorithm reveals the true impact every player has on sales by analyzing retailer`s and competitive historical data.
- Suggestions on sequential discounts and predictions on hitting stocks
- Discount differentiation at SKU-level
- Maximized margin
Save time and reduce efforts by automating pricing process
Automation makes repricing at least 50% faster while reducing the risk of human mistakes. As any changes in data occur, repricing of a product group or separate SKU can be done either in real-time or it can be processed in batches.
- Suggestions on sequential discounts and predictions on hitting stocks
- Discount differentiation at SKU-level
- Maximized margin
Find optimal price optimization strategies with What-If simulation tool
With Competera, automotive retailers can test various pricing and promo scenarios based on data-driven analysis.
Set the constraints and parameters of the repricing campaign you would like to test and get the estimated impact it will have on key business metrics.
- Suggestions on sequential discounts and predictions on hitting stocks
- Discount differentiation at SKU-level
- Maximized margin
Want to know more? Click here to find out
Find how Competera’s demand-based Price Optimization helps retailers.
How markdown optimization works
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 hitting the stock level and gaining margin.
Data input
- Historical sales (min 2 years)
- Historical promo (min 2 years)
- Promo calendar
- Product description
- Product stock availability
Execution
- Suggesting sequential discount periods
- Calculating cross elasticities and sales cannibalization effect
- Differentiated approach instead of blanket discounts
- Preventing profit margin from drop
Competera case studies: proven by numbers
Read how Competera helps different types of retailers
Enterprise-grade Software
Once you choose Competera, we will provide you with a personal solution and pricing experts from the Competera team. They will guide you step-by-step through your journey to optimal pricing.
Data Audit
Full Integration
Pilot Project
Scaling
Feedback Audit
