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Case study for retail and supermarket chain store: Dynamic repricing, Weekly recommendation, Sales Prediction, Association rules and upsell.
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Below are the technology we used in this case and criteria that you need check when you apply the case to your own business use.
Marketing Division of Retail, SupermarketMarketing/consulting company
TARGET USER
Machine Learning, Predictive Analysis, Time Series Analysis
MAIN TECHNOLOGY
POS/Receipt Data, or, Data from Loyalty program, club card or membership card
INPUT DATA TYPE
Datawiz.io Case Study
Dynamic Repricing
DISCOVER POTIENTIAL PROFIT RANGE OF PRODUCT.
Weekly RecommendationFAST REACTION TOWARDS MARKET NEEDS AND CHANGES
Sales PredictionOVER COME THE SUPPLY DEMAND PROBLEM
Association Rules and Upsell
MANUPLATE THE KEY DRIVEN PRODUCT AND SATTELITE PRODUCT
Business Cases
Datawiz.io Case Study
Dynamic Repricing
DISCOVER POTIENTIAL PROFIT RANGE OF PRODUCT.
There is a price-demand dilemma, which is growing price does not alway
lead to more profit, because of the decline in demand.
Finding out the optimized point of each product on the price-demand curve
can help you maximize your profit.
Problem: Grow price & maximize profit
Case Study: Dynamic Repricing
The purpose of this case is to
find out when you could grow
price for which product and
how much you can grow. P
rice
Demand0 D1D2
P1P2
Recommended Price
Current Price
System gives prediction on
how to grow price for each
SKUs.
Our solution
Case Study: Dynamic Repricing
System runs calculation for all receipts and gets the average value of baskets. What we need
to do is to find out products inside lower value baskets that are not price sensitive for the
customer.
System can operate over thousand of SKU on a frequent basis
and has ability of growing price by the mean time keeping the
demand level.
Advantage
Case Study: Dynamic Repricing
Weekly RecommendationFAST REACTION TOWARDS MARKET
NEEDS AND CHANGES
It is complicated to research each
products in the store and launch
effective marketing compagin. Not to
mention to launch recommendation
in all SKUs weekly!
Problem of weekly marketing compagin
Case Study: Weekly Recommendation
TONS OF SKUs
POS DATA
TOO MUCH WORK
LIMITED TIME
Our solution
Our system can answer you the questions by only one click!
“What to do next week?”
“What to promote in each day of next week? ”
Our recommendation engine is based
on machine learning algorithm,
association rules and our product tree
algorithm. System can automatically
build dynamic recommendation models
according to different purchase behavoir.
Case Study: Weekly Recommendation
Promote the right product to right customer
BENEFITS
Case Study: Weekly Recommendation
Sales PredictionOVER COME THE SUPPLY DEMAND
PROBLEM
Guesswork and experience are the only tools that help you to calculate
how much products you should order from suppliers. And it often causes
either stortage or over supplement.
Customer couldn't buy the product they want and store loses
chance to sell. Over supply increases warehouse and employee
cost.
Problem: Out of storage and over supplement
Case Study: Sales Prediction
We built prediction modles based on different factors that influence
the sales, which include weather, fuel price, currency rate and
geographic elements.
Solution: Prediction model for future sales
The accuracy of prediction is
higher than 97%. You can do
prediction per month, per week
and even per day.
Prediction model is built for each
product and category that make sure
the high accuracy.
Case Study: Sales Prediction
Association Rules and UpsellMANUPLATE THE KEY DRIVEN
PRODUCT AND SATTELITE PRODUCT
Find key driven product;
Use key driven product to bring in more customers;
Increase sales of hight margin satellite products.
Purpose of applying association rules
Case Study: Association Rules and Upsell
It helps you to find out which
product to promote and the product
that drive most of the profit.
Satellite / accessory products can bring you more profit! We help you
find out them and promote at right time.
Our Solution:
Case Study: Association Rules and Upsell
We run clusterization for all baskets and filter out
the key driven products for each basket type.
Satellite products with high profit can be marked
according to request from store.
Except for applying association rules, we invented
product tree to extend the effect of algorithm.
On the product tree, you can see clearly which
SKU can trigger profitable sales.
Promote the product that drive most of the profit.
BENEFITS
Case Study: Association Rules and Upsell
YOUR CONCERN IS OUR RESPONSIBILITY
Datawiz Inc.www.datawiz.io
Gaidatara 1-D suite 302Chernivtsi, Ukraine+38 050 337 73 [email protected]
