Product Improvement : Nearbuy

A case study on how can we improve ‘Nearbuy’-A hyper-local eCommerce company based out of India. As a business, it allows customers to discover, buy and save on merchants nearest to them.

The main agenda behind this case study was to recommend new features which can be included in Nearbuy app to increase customer engagement on a regular basis.

1. First and foremost, let’s have a look at the addressable market

Figure 1- About Nearbuy and addressable market

2. Understanding customer pain points and creating value propositions

Figure 2- Creating a USP to increase user engagement

3. Identifying the success drivers

Figure 3-Understanding the success drivers

4. Product Recommendation based on learning

Figure 4-Product Recommendation : Show Users Trust

5. Product Recommendation based on learning

Figure 5-Product Recommendation : Clean UI

6. Introducing new product feature-Best deal discovery

Figure 6- Feature 1 : Deals Discovery

7. Introducing new product feature-Credit Transfer

Figure 7- Feature 2: Credit Transfer

8. Introducing new product feature-Whatsapp communication

Figure 8- Feature 3: Omnichannel communication

9. Introducing new product feature- Personalized Milestones

Figure 9- Feature 4: Personalized Milestones

Tasks for further activities involve-

1. Performing the Cost-Benefit-Risk Analysis
2. Prioritizing the features and recommendations using standard frameworks such as-RICE, KANO and others

Thanks for reading!

P.S- This case study was performed with one of my colleagues at B-School. Credit where it’s due

Feel free to comment your reviews. More to follow!

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