Big data in retail industry

INTRODUCTION:

A lot of people are under the impression that great marketing is an art, but of late, big data has introduced a scientific element to marketing campaigns.
Smart marketers are now relying on data more than ever to inform, test, and devise their strategies.

And though data and analytics will never replace the creative minds behind the best marketing campaigns,
it can definitely provide the marketers with the tools to help perform better.

Consumers have 24 hour access to abundant product information which has revolutionized the retail sector.
With digital technology becoming ubiquitous, shoppers can make informed decisions using online data and content
to discover, compare, and buy products from anywhere and at any time.

For brands and retailers, information is also a game-changer. Retail data analytics has the ability to help companies
stay at par with the shopping trends by applying customer analytics to uncover, interpret, and act on meaningful data insights.

PROBLEM #1: Siloed, Static Customer Views
Many retailers still struggle with siloed data – transaction data lives apart from web logs
which in turn is separate from CRM data, etc.

PROBLEM #2: Time Consuming Vendor & Supply Chain Management

Supply chains are already driven by numbers and analytics,
but retailers have been slow to embrace the power of realtime analytics
and harnessing huge, unstructured data sets.

PROBLEM #3: Analysis Based on Historical Data

Looking back at shoppers’ past activity often isn’t a good indication of what they will do next.
Instead, real-time prediction based of current trends and behaviors from all sources of data is the key.
Prediction and Machine Learning in Real Time.

PROBLEM #4: Efficiency
Although the majority of retailers consider operational efficiencies to be of the utmost importance,
less than a third are able to figure out how to achieve them.
While “67% of retailers consider overall business operations efficiency to be of high or critical importance,
only 27% consider themselves able to manage this well,

1. Big Data in Retail Industry IÉSEG School of Management, Campus de Lille Sabir Akhtar Jatan Dewgun Victor Ernoult Lucas Bonnett

2. Our Agenda Introduction How can data analytics help the retail sector Success Stories

3. Introduction Business Business

4. The struggle of Retail sector with data    Weblogs , bulk data and transactional history Unstructured data set Historic data Efficiency                                                          

5. Big Data: A Game Changer Customer Conversion Customer Identification Optimizing Price Personalized In-Store Experience Forecasting Demand Predicting Trends BIG DATA CHANGING THE RETAIL LANSCAPE Customer Journey Analytics Store Layout

6. Some Data Tools

7. Add a Slide Title - 1

8. Real Life Examples ? RFID tags on clothes​  RFID reader in the object.​ ​ Each product brought in the fitting-room is detected and analyzed

9. How is that meaningful for companies ? Different applications :  Identify patterns to see what consumer like. Can influence future collections Compare articles tried, and those actually bought Which products are tried together. Identify if specific sizes of articles are often tried but never bought (size problems ?)

10. Real Life Example 2nd Largest department store retailer in the US behind Walmart, and listed in the US stock exchange (market ?) They basically data mine their way into women's belly. 

11. How ? They used statisticians to analyze consumers data :  Each client is assigned a guest ID number, tied to their credit card, name or email address as well as demographic information. This was link to every basket they purchased in the store. Group of ladies that had signed up for baby registery groups, and then analyze their consumption patterns. Then use their findings to further apply to each and every customer buying in the store

12. Results Ladies in the " focus group" were buying larger quantities of lotion around the beginning of their second trimester  In the first 20 weeks , pregnant women loaded up on supplement like calcium, magnesium and zinc. They were able to identify 25 products that allow them to assign each shopper a "pregnancy prediction" score. And estimates each stages of pregnancy. Helps the company design specific promotion offers depending  on  average consumer scores...