22_MadeATon6.0_RETAIL AI

"Lets get the local retailers benefitted"

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Inspiration

Many Challenges are present in a Competitive Retail Environment such as Balancing Suppliers, Costs, and Customer Satisfaction.There exists a significant gap in the connection and communication between retailers and consumers, despite the advancements in technology. Many consumers remain uninformed about the products available in their local stores and supermarkets. Additionally, consumers typically possess limited knowledge about the products they intend to purchase, unless they physically visit the market. The limitation of sales executives to reach every individual consumer to showcase both new and existing products exacerbates this issue. Consequently, consumers might never have the opportunity to experience products that could genuinely meet their needs or preferences, ultimately resulting in a loss of business for local retailers.

What it does

  1. We will be connecting the local retailers with the customers via our app. The customer is supposed to scan the QR to establish the interaction initially.

  2. Personalized recommendations, Deals of the day and the best offers available will be sent to the customers from the shops where they established connections.

  3. The real time monitoring dashboards are provided to the retailers in order to enhance their inventory management.

  4. General coupons, gift vouchers and festive offers will be intimated to the customers via a popular social media like whatsapp.

How we built it

  1. The app for the customers was built using flutter and for the backend we have used the django

  2. For recommendations, we have trained Matrix Factorization model

  3. For the real time monitoring dashboards, we used Microsoft Power BI, a data analytics tool

  4. For sending the messages via popular social media handles like whatsapp, we have done Robotic Process Automation bots using UiPath Studio

Challenges we ran into

  1. We thought of recommending the products with the help of ratings, but after some time as it didn't we switched training the models to recommend using customer interactions .

  2. We faced challenge in integrating the API with front end and in integrating ML models with flutter API

  3. We couldn't get a large dataset which suits our problem description, because of which we created the dataset manually.

  4. When generating the bots, initially we didn't get proper output because the time for execution of whatsapp web was changing dynamically and after that we resolved it.

Accomplishments that we're proud of

  1. We built the product from scratch, though we faced much challenged but we are done with the product.

  2. We have used many tech stacks in order to built the application and while developing, we have learnt many things from our mistakes.

What we learned

1.Learnt Django to build the backend. 2.Flutter frontend integrating with API. 3.Learnt to built the Matrix Factorization model. 4.Learnt to build a Bot in RPA and creating dashboards in Power BI

What's next for RETAIL AI

Our future plan for RETAIL AI is to implement this concept in real time . We need to improvise the section layout prediction so that we can increase the profit of the store. Loyalty programs to be added with the help of loyalty coins.

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