Featured case study · E-commerce · Behavioral analysis
Pricing, Discounts, and Brand Power on Myntra
A behavioral analysis of pricing, discounting, category dynamics, and brand concentration on a leading e-commerce platform. Product ratings served as a directional proxy for engagement and demand across consumer segments.
01 · Myntra
Product analytics · E-commerce
180
product rows in the live table
- Project
- Pricing, Discounts, and Brand Power on Myntra
- Role
- UX Researcher
- Tools
- Excel · Pivot Tables · Data Analysis · Segmentation · Insight Synthesis
- Data source
- Myntra Products Dataset (Kaggle)
02 — Research question
How do pricing, discount strategies, and brand positioning influence user engagement, demand patterns, and consumer segment behavior on Myntra?
03 — Objectives
Five goals shaped the study.
- 01
Pricing and engagement analysis
Understand how price tiers translate into differences in customer engagement signals.
- 02
Discount effectiveness
Identify where discount depth begins to lose marginal impact on demand.
- 03
Consumer behavior and segmentation
Separate shopping behavior across budget, mid, and premium customers.
- 04
Brand dynamics and market concentration
Quantify how engagement is distributed across brands and uncover visibility advantages.
- 05
Predictive insights and strategic recommendations
Translate behavioral patterns into commercial direction and testable hypotheses.
04 — Methodology
A five-step analytical workflow.
05 — Key findings
Six insights, each with a strategic implication.
Tap a card to reveal the implication.
06 — Research visuals
Evidence visualized.
Ten analytical outputs supported the findings. Each is summarised here with the interpretation it earned — the chart is the artifact, the reading is the research.
01
0
product rows analysed
02
0%
of the catalogue is budget priced
03
0%
of engagement comes from budget products
The catalogue wasn’t distributed the way engagement was.
Fig. 01 · Distribution
Catalogue share vs engagement share by price tier
Catalogue share
- Budget50%
- Mid30%
- Premium20%
Engagement share
- Budget82.8%
- Mid12.7%
- Premium4.5%
Budget products are 50% of the rows but carry 82.8% of all 4,49,972 ratings — an engagement gap of 33 points.
Open live datasetFig. 03 · Price-tier performance
Share of total ratings by price tier
- Budget82.8%
- Mid12.7%
- Premium4.5%
Computed live from 180 product rows. Budget averages 4,141 ratings per product at ₹632.
Fig. 02 · Discounts
Bigger discounts didn't automatically mean better engagement.
- 0–20%1,998
- 20–40%3,827
- 40–60%6,378
- 60–80%3,770
- 80%+2,189
Mean ratings per budget product in each markdown band. Engagement peaks in the 40–60% band for budget products, then falls away at the deepest cuts.
Discount alone didn’t explain the pattern.
Fig. 04 · Category health
How categories behave, not just how they sell
- Apparel43.7%
- Beauty & personal care20.6%
- Accessories16.7%
- Makeup9.6%
- Wellness9.4%
Share of total ratings by category.
Apparel
- Products
- 78
- Catalogue share
- 43.3%
- Engagement share
- 43.7%
- Avg price
- ₹1,777
- Avg discount
- 50%
Responds more sharply to promotional triggers than to price alone.
Fig. 06 · Brand concentration
A small group of brands captured a large share of attention.
61.4%
of total ratings sit with the top 10 brands. The remaining 38.6% spreads across 18 other labels.
- Roadster9.6%
- Anouk8%
- W7.1%
- Vero Moda6.9%
- Biba5.8%
- Mast & Harbour5.4%
- Levis5.1%
- Van Heusen5.1%
Top 8 brands by share of total ratings.
Values shown come from the Myntra products dataset analysis. Engagement is a directional index built on product ratings, not a platform metric.
Fig. 01 · Bar chart
Catalogue share vs engagement share by price tier
Budget products capture more engagement than their catalogue share would predict. Premium underperforms on engagement density.
— Budget engagement outpaces catalogue by ~18 points.
Fig. 02 · Grouped bar
Discount tier performance across price segments
Engagement peaks in the 40–60% discount band for budget, but flattens or reverses at deeper cuts.
— Deeper discounts do not equal better outcomes.
Fig. 03 · Line chart
Engagement trend by discount depth across price tiers
A clear inverted-U curve confirms that discount effectiveness has an optimal range, not a linear relationship.
— Plateau then decline after ~60% discount.
Fig. 04 · Stacked bar
Engagement by product category and discount tier
Beauty and wellness lean toward low-discount engagement — habitual demand. Apparel and accessories respond more to promotions.
— Category behavior is not uniform.
Fig. 05 · Scatter plot
Price vs ratings across price tiers
Ratings distribute widely across the price range. Price alone does not explain engagement — segment behavior does.
— Low correlation between price and rating quality.
Fig. 06 · Treemap
Brand concentration and share of engagement
A small cluster of brands dominates the visible engagement area, while the long tail remains narrow.
— Concentration risk is structural, not incidental.
Fig. 07 · Donut
Share of top brands vs the long tail
The top 10 brands account for the majority of engagement, leaving limited surface for mid-tier and emerging brands.
Fig. 08 · Heatmap
Segment responsiveness by price tier and discount level
Budget shoppers respond most strongly in the 40–60% band. Premium responsiveness remains muted across all discount depths.
— The sweet spot sits in the middle, not the extremes.
Fig. 09 · Horizontal bar
Top 20 brands by engagement
Engagement drops sharply after the top cohort, illustrating the visibility and trust advantage of dominant brands.
Fig. 10 · Radar
Category behavior profile: habit, impulse, and confidence
Beauty indexes high on habit and brand pull. Apparel and accessories skew toward impulse and price sensitivity.
— Category archetypes inform promotional mechanics.
Fig. 08 — Segment responsiveness heatmap
Budget shoppers respond most strongly in the 40–60% band. Premium responsiveness remains muted across all discount depths.
07 — Strategic recommendations
Six decisions this evidence supports.
- 01
Strengthen value-led merchandising
Elevate budget-tier discovery in high-engagement segments where customer demand is already concentrated.
- 02
Avoid overusing extreme discounting
Cap promotional depth where marginal return turns negative and protect perceived value.
- 03
Improve trust and comparison support for mid-tier
Invest in decision confidence — reviews, comparisons, and credibility cues over heavier promotions.
- 04
Tailor promotional mechanics by category
Differentiate between habitual categories (beauty, wellness) and impulse-led categories (fashion, accessories).
- 05
Reduce brand concentration risk
Engineer discoverability for emerging and mid-tier brands to diversify the engagement base.
- 06
Reposition beauty as a strategic pillar
Align platform narrative and surfaces with where engagement already lives — not only where heritage positioning sits.
08 — Outcomes and reflection
From data to direction.
This study sits at the intersection of behavioral evidence and commercial strategy. The Myntra dataset was not a research commission — it was a self-directed exercise in applying UX research skills to real product and platform questions.
The findings connect observable patterns — engagement concentration, discount-curve inflection, category archetypes — to decisions a product, merchandising, or strategy team could act on. That translation is the work. Research positioned upstream shapes the question rather than confirming the answer.
6
Behavioral patterns identified
Core insights
6
Strategic recommendations
Decision inputs
10
Charts produced
Visual outputs
3
Segments analyzed
Budget · Mid · Premium