Ezili
Making Retail Stores Smart
DESCRIPTION
Today many of us prefer to shop online than from a physical store. While online shopping has evolved to provide a seamless and personalized experience that spans from scouting for products to buying to returns and follow-ups, the experience in physical stores have remained more or less same and limited.
That being said, to be able to hold a product in your hand, feel the material and texture, to be able to see the freshness of fruits, to be able to try out clothes before buying is something that drives us to physical stores and can’t be experienced online.
We did a small research in and around the megastores in Hyderabad, India and brainstormed on various solutions which can improve and give a better shopping experience to the consumer as well as give unprecedented advantage to the retailers as well. After all they are going to invest in these solutions.
We also tried to enlist the kind of advantage each of these solutions are giving back to both sides i.e., the consumer and the stores.
MARKET & USER RESEARCH
In the beginning we identified consumers who visit stores and the retailers to be the two main stakeholders and decided to focus research on them.
Post this we studied consumer behavior in mega-stores in Hyderabad and Chennai. In this research we observed complete journey of the consumer from the desire to buy something to buying the product and even follow-ups and returns.
We then divided this consumer journey into various distinct phases such as motivation, planning, compare, purchase, etc. in order to understand the users journey.
Post this we studied the mechanisms and processes involved on the retailers side.
These involved resource management, to stocking to inventory management. This study was done through interviews where various person were interviewed such as the store manager, department manager and floor staff.
BRAINSTORMING & CONCEPTS
Based on this research we brainstormed ideas and through an iterative process narrowed down and detailed some of the ideas into concepts.
The concepts range from mobile applications to internet of things concepts such as smart price tags. Some of these concepts are presented below.
Ezili Shopping App
Many people make lists before shopping. We envision an app that serves essentially as a list making app, made for a particular retailer or a one stop app for all retailers.
The user can start making a list by writing common words. The app can recognize the items and can suggest:
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Brand to choose from and quantity
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Ongoing offers in the stores
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Depending on customer's preferences the app can suggest relevant items
Smart Price Tags
A centrally connected digital price tag displayed on shelves next to the stack of the products. Currently the tags are printed on paper and changed manually, sometimes the tags displayed are outdated or incorrect.
Value for Customers
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Access to accurate, updated prices
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Additional information about the product can possibly be pushed to the screen. (user reviews, ratings, etc.)
Value for Retailers
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Prices can be updated in real time, any number of times without requiring manpower
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Unlike printed tags that can only be updated once a day, smart tags can be updated multiple times a day to change prices based inventory and time of the day
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It can also be used as an advt. platform for the product, advt. space can be sold by the retailer to the manufacturer
Smart Signage
Centrally connected digital signage that can display ongoing offers, information about the product as well as advertisements (instead of or in addition to printed signage).
Value for Customers
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Access to accurate, updated prices
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Additional information about the product can possibly be pushed to the screen. (user reviews, ratings, etc.)
Value for Retailers
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Offers can be updated in real time, any number of times without requiring manpower
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As the signage will be a screen, it can also be used as an advertisement platform for the product, advertising space can be sold by the retailer to the manufacturer
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Smart signage can serve as a platform to push marketing material
Predictive Analysis
Currently the store has multiple data points such as inventory data that is updated everyday, data on purchases coming from POS counters, purchase history of customers, etc. Using this data collected over a period of time, we might be able to deduce patterns in customer behavior which can be used to predict customer behavior, sales, etc.
Value for Retailers
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Anticipate user behavior and sales
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Feedback on marketing initiatives and store operation
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Better stocking based on anticipated sales
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Help in choosing what to stock and what not to