Product Experience | Service Design
Enhancing Product Discovery & Navigation for Better in-Store Shopping Experience
Service Design | Product Design | Journey Mapping
6 months
Team of 7 | Project Lead
Tata 1mg | Customer Journey Mapping for in-store interaction
Project Overview
Imagine entering a small size retail pharmacy store to quickly buy a pain relief medicine on your way to the office...
As you navigate through the aisles, you are overwhelmed by a disorganized display of products—stacked with no clear distinction between categories, making it difficult to locate what you need. The store, though stocked with a variety of essential products, lacks a seamless experience that can guide you effortlessly.
BUSINESS NEED
After establishing an online presence in the healthcare sector, TATA 1mg aimed to create an omnichannel experience by integrating the same level of ease of choosing products in the offline brick & mortar retail stores.
GOAL
Transform the store with an intuitive, visually engaging, and efficient product placement while optimizing backend operations to support this change
IMPACT IN 6 WEEKS
20%
increase in Average Order Value (AOV), improved Product Discovery & Sales
56%
revenue increase of Monetised Brand Partners from product shelf placements
36%
reduction in Stockouts due to localised demand-based Inventory Optimization
MY ROLE
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75% -Devised a hyperlocal visual merchandising strategy for 50+ retail stores, to categorize and determine the ideal product placement of the OTC products.
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50% -Collaborated with cross-functional teams of 7 from procurement, retail operations, store associates, marketing, and brand management teams, to conceptualize and pilot strategy in flagship store.
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50% -Designed Visual Merchandising Guidebook
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90% -Designed OTC products Dashboard for associates to track, update and maintain product placements, and optimize inventory with demands and sales pattern
Tata1mg Retail Store | OTC Area
BEFORE
AFTER
Before and After image of the Gandola with improved product grouping and placement
Internal Dashboard for Store Associates to Maintain OTC Product Display
OUR PROCESS
A Multi-Layered Approach to Visual Merchandising
PROBLEM FRAMING
Identfying all the current challenges
We started by visiting stores in the Delhi-NCR Region to identify how customers are browsing, how product categories are placed in relation to one another and how store associates stock shelves?
INSIGHTS FROM CUSTOMER RESEARCH
We took insights from the research team (survey with 50+walk-in customers) to understand customer needs and pain points.
I was overwhelmed by the amount of products, cluttered together, making it difficult to find what I needed
-Richa
If I can find some healthy snack options with my supplements, it'd be very convenient
-Shourya
I wanted to compare ayurvedic and non-ayurvedic supplements before buying, but I couldn't find it
-Anant
PROBLEM DISCOVERY
It is only the tip of Iceberg
OUR HYPOTHESIS
What this means to Business?
With our research and analysis, we hypothesised that we are loosing potential sales by displaying low-demand-slow moving-SKUs in high value golden zones. Also, the store inventory is not reflecting the local customer's demand and sale pattern, thereby leading to lower customer satisfaction and potential loss of customer loyalty.
PRODUCT CATEGORISATION
Mapping Category Affinity
With the data collected from stores, competitor's research, and customer survey— we tabulated all the possible category labels based on customer-association with different labels and groups to create a master product category for retail stores.
In order to create a consistent brand experience, we reimagined category labels in alignment with our online platform tagging to provide a more cohesive omnichannel experience to our customers across online & offline channels.
EXPERIMENTATION
IN ONE-STORE
Executing Strategy in our Flagship Store
BEFORE
NEW PRODUCT CATEGORY PLACEMENT
What is and What should be?
We analysed current product placement in the store and identified scattered placement of categories. This created a gap in the way customers navigated through store while browsing, and led to low footfall-grey areas.
AFTER
Reorganised category placement in the store, leading to an 'Exploration Zone' with new products, more space to discover and interact with different brands before moving to 'Everyday Essentials' which is mostly a fixed buy for customers.
PLANOGRAMS
With lack of any software support, we spent time manually creating Planograms to implement new product placement strategy.
We also had to create guideline for how monetised vs non-monetised brands are to be placed in the store, in compliance with brand ask and legal contract.
POST IMPLEMENTATION:
We saw an increase in Average Order Value (AOV) by 20%
Before vs After executing product display guidelines with store associates
IMPACT IN 6 WEEKS
20%
increase in Average Order Value (AOV), improved Product Discovery & Sales
56%
revenue increase of Monetised Brand Partners from product shelf placements
36%
reduction in Stockouts due to localised demand-based Inventory Optimization
HOW DO WE SCALE ?
Across 50+ stores in different cities with different sales & demand
PROBLEM AREAS
Biggest Challenge with Scaling
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Manual & Time-Consuming Processes – The absence of merchandising software forces associates to manually create and update planograms, making the process inefficient.
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Store-Specific Variations – Different store layouts, fixture types, and inventory levels require an adaptable approach, making scalability a challenge.
HOW MIGHT WE?
How might we enable store associates with the dynamic information to efficiently track, update, and maintain store displays—ensuring optimal product placement, inventory alignment, and brand compliance across diverse store locations?
SOLUTION
Internal Dashboard for Store Associates
A centralized store display dashboard will serve as a scalable, data-driven solution to enhance visual merchandising, by providing dynamic planograms, managing inventory levels with demand, and reducing manual efforts in execution.
Internal Dashboard for Store Associates to Maintain OTC Product Display
To-do Task List Feature
Adding a daily 'To-do' task list feature, to provide store associates to easily track, priortize, and update the display
USER TESTING
By early testing the concept with the store associates, we realised that while a central dashboard is great for tracking everything and provides a very comprehensive overview, with easy to send queries and reports to central team to bridge communication— a mobile version to complete task to maintain and update store display would make the process more easy.
SOLUTION
Mobile Support and Sync
A centralized store display dashboard will serve as a scalable, data-driven solution to enhance visual merchandising, by providing dynamic planograms, managing inventory levels with demand, and reducing manual efforts in execution.
Internal Dashboard for Store Associates to Maintain OTC Product Display
POSSIBLE IMPACT
By streamlining the information communication process in an easy, intuitive and simplified process, associates can maintain the store display with the data-backed solution.
There is a 'Ask question' feature that allows store associates to send queries to central team for updating category tags or queries about any brand/category that can be resolved in 1-2 days, allowing faster improvements.
CONTENT DESIGN: Using converstional tone that adds delight & engagement
REFLECTION
How I Would Approach This Situation Now?
AI-Powered Store Experimentation Mode
Enable associates to simulate and test different visual merchandising strategies within a virtual store environment. By using a drag-and-drop interface, users can rearrange brands and SKUs on digital shelves, instantly visualizing potential layout changes. This experimentation mode leverages AI to predict the impact of these changes on sales performance based on historical data and current trends.
Predictive Shelf Performance Analytics
Integrate AI algorithms that analyze past sales patterns to forecast product performance in various shelf positions. This enables smarter placement decisions by identifying which configurations are likely to drive higher conversions or reduce inventory stagnation.
Cross-Store Intelligence Sharing
Use machine learning to recommend successful merchandising strategies from similar stores (“sister store insights”). AI identifies high-performing layouts from comparable locations and suggests them as potential models to replicate or adapt.
Conversational AI for Planogram Optimization
Introduce a chatbot interface where store associates can simply input instructions or notify the system of new inventory arrivals. The AI then automatically generates the most optimized planogram, taking into account factors like current inventory, customer preferences, and shelf performance data.
Cognitive Merchandising with Mental Model Testing
Experiment with customer mental models by simulating different layout flows—e.g., grouping by use case or lifestyle versus traditional category-based shelving. AI tools can analyze customer response simulations to recommend configurations that better align with how shoppers think and behave.