Case Studies

Our client was retail chain with +1000 stores.

We achieved the stock reduction by:

• deploying the proprietary Big Data ETL for
  – acquiring the 5 years of all client stores’ related data
  – smart data audit and cleaning
  – creating data that client did not have previously (days since last sales, etc.)
• developing cutting edge analytics for
  – forecasting future sales
  – identifying problematic items
• creating smart algorithms based on previously developed analytics for
  – stores’ replenishment
  – inventory audits
  – assortment changes
• implementing algorithms with employees in order to
  – reduce shipments to stores and necessary
  – returning “dead” items
  – replacing slow sellers in store assortment with fast turnover and higher margin items
• implementing smart algorithm for maintaining the optimal replenishment and assortment as well as monitoring all items in stores

If you want to improve your cash flow by reducing inventory levels ask us about our experience and results in stock reduction projects.

Our client was grocery chain with +160 stores.

We achieved the margin increase by:

• deploying the proprietary Big Data ETL for
  – acquiring the 2 years of all client stores’ related data
  – smart data audit and cleaning
  – creating data that client did not have previously (product lifecycle, sensitivity of sales, etc.)
• developing cutting edge analytics for identifying the low and high yield items in terms of margin
• creating smart algorithms for recommending the item changes in all stores by performing optimization of over 700 million different scenarios
• developing and implementing the “Assortment Optimization Tool” for
  – evaluating assortment changes in terms of expected benefit
  – approving the assortment changes
  – automating the assortment changes in the ERP

If you want to improve your EBITDA with the existing product portfolio ask us about our experience and results in the assortment optimization projects.

Our client was retail chain with +200 stores.

We achieved the margin increase by:

• deploying the proprietary Big Data ETL for
  – acquiring the 2 years of all clients’ stores’ related data
  – smart data audit and cleaning
  – creating data that client did not have previously (sensitivity to promotion, impacted items, etc.)
• developing cutting edge analytics for identifying and measuring
  – product groups’ response to sales promotions
  – effects on total product group’s sales
  – bundling potential of promoted items
• creating smart algorithms based on previously developed analytics for
  – eliminates items that reduce overall product group margin
  – promotes items that increase overall margin and conversion
  – bundles positive items with the high margin non-promoted items
• developing and implementing the “Sales Promotion Development Tool” for
  – suggesting the optimal sales promotion to category managers
  – approving and modifying items selection
  – creating optimal purchase order for promoted items
  – automating the assortment changes in the ERP

If you want to improve your sales promotions’ profitability ask us about our experience and results in the sales promotions’ projects.

Our client was drogerie chain with +200 stores.

We achieved the conversion rate increase by:

• deploying the proprietary Big Data ETL for
  – acquiring the 3 years of all client’s sales and loyalty data
  – smart data audit and cleaning
  – creating data that client did not have previously (customer segments, etc.)
• developing cutting edge machine learning analytics for
  – creating customer segments
  – identifying segments probability of purchase
• creating smart algorithms based on previously developed analytics for
  – classifying customers
  – identifying customers’ propensity to buy individual product
• developing and implementing the “Sales Promotion Targeting Tool” for
  – suggesting the list of customers (loyalty numbers) and related product
  – modifying list based on the expected revenue and campaign costs
  – automating the offers sending in the marketing APP

If you want to make your customers more profitable ask us about our experience and results in the loyalty program projects.

Our client was fashion retailer with +60 stores.

We achieved the full price sales and margin increase by:

• deploying the proprietary Big Data ETL for
  – acquiring the 4 years of all client’s sales and procurement data
  – smart data audit and cleaning
  – creating data that client did not have previously (% of sorted, etc.)
• developing cutting edge machine learning analytics for
  – forecasting future items’ sales
  – identifying items with excess quantities
  – measuring sensitivity to discounts
• creating smart algorithms based on previously developed analytics for
  – identifying items to be transferred to another store
  – identifying items to be discounted
  – identifying items not to be discounted
• developing and implementing the “Merchandising Tool” for
  – suggesting activities to employees (transfer item, give a discount, etc.)
  – evaluating suggestions
  – accepting or rejecting suggestions
  – automating the decisions’’ implementation in the ERP

If you want to sell your products with more profit ask us about our experience and results in the managing merchandise in stores projects.

Our client was sports fashion retailer with +80 stores.

We achieved the conversion rate increase by:

• deploying the proprietary Big Data ETL for
  – acquiring the 3 years of all client’s sales and procurement data
  – smart data audit and cleaning
  – creating data that client did not have previously (lost sales, etc.)
• developing cutting edge machine learning analytics for
  – forecasting future items’ sales during the season
  – forecasting future sales for items not currently in stores
  – measuring lost sales
• creating smart algorithms based on previously developed analytics for
  – creating an ideal order for all items
  – evaluating an ideal order in terms of profitability
  – correcting an ideal order for the profitability, sell through and innovation factors
• developing and implementing the “Ordering Tool” for
  – suggesting number of items and quantities for all stores
  – evaluating suggestions in terms of profitability and stock levels
  – modifying suggestion
  – creating orders for all suppliers
  – automating the order transfer in the ERP

If you want to improve your ordering and buying process ask us about our experience and results in the procurement projects.

Our client was distributor with +400 delivery vehicles.

We achieved the number of deliveries increase by:

• deploying the proprietary Big Data ETL for
  – acquiring the 2 years of all client’s delivery data
  – GPS data for past 2 years for all vehicles
  – IofT vehicles sensor data
  – smart data audit and cleaning
  – creating data that client did not have previously (route alternatives, etc.)
• developing cutting edge analytics for
  – identifying delivery and other purpose driving
  – identifying active delivery v. stop time
  – identifying loading v. unloading time
• creating smart algorithms based on previously developed analytics for
  – identifying “ideal” v. suggested route
  – identifying “given: v. driven route
  – identifying driver v. route related anomalies
• developing and implementing the corrective measures
  – automated corrections for existing routing software
  – monitoring algorithm (and penalty system) for not following given routes
  – monitoring algorithm (and penalty system) for delivery times
  – adjustment of the salesman routes that are coming before delivery routes

If you want to improve your distribution processes ask us about our experience and results in the procurement projects.