STP + Marketing Research, with Finance & Operations cross-links
Prof. Karthikeyan Balakumar • All figures are illustrative synthetic data for classroom discussion.
The Setup
Anjali Menon is the 41-year-old CEO of VoltRide — ex-McKinsey partner, founded the company in Bengaluru in 2023. Three years in: 1,850 scooters/month, 3.1% market share, FY25 EBITDA −₹112 crore. Next funding round closes in six months. Her lead investor has asked her one question she can't answer on a slide: "Who, exactly, is VoltRide for — and why should anyone outside that group ever buy one?" She has convened you as an external advisory panel. By the end of three hours she wants ONE segment, ONE positioning statement, ONE twelve-month metric — each backed by one number from the data.
See the case document for the full setup. This tab is Exhibit A live.
Who is actually winning the Indian electric two-wheeler race — and does the leaderboard agree with the P&L?
Before you touch CB theory, read the scoreboard like a first-year MBA.
The Competitive Landscape
NPS by brand — and a Session 1 lesson about axes
Chart design is Consumer Behaviour. Toggle the Y-axis range and watch how the same five numbers tell two different stories.
Chat commit (30 seconds)
Ola sells 16,400 units/month and loses ₹1,584 crore. Bajaj Chetak sells 11,480 units/month and makes ₹421 crore. Same category, same regulation, same consumers. Type in chat — one sentence — what Bajaj's parent company is doing that Ola is not.
🔍 Reveal — the Black Box at work▸
The incumbents inherited 50+ years of absorbed infrastructure. Bajaj has 4,100 dealers. Ola has 782. TVS sells 3.4 units per dealer per month; Ola sells 21. Ola's per-dealer productivity looks heroic — until you realise Bajaj's dealer network was already paid for by 45 years of ICE scooter sales. Their EV unit only pays marginal EV-specific opex. Ola is financing showrooms, service bays, and brand trust from scratch, in real time, out of investor capital.
This is the Black Box model (Session 1): the visible output (market share, NPS, profit) is shaped by invisible internal structure (legacy infrastructure, brand equity, supplier trust).
You have a 2,000-respondent survey. Pick a segmentation scheme. Which one actually predicts who will buy?
Year-1 recap: demographic, behavioural, and psychographic segmentation — side by side, same data.
How predictive is each scheme?
✍️ Silent write (2 min)
Your marketing team is about to buy ₹40 lakh of media targeting "Young Urban Males, 25-34, Tier-1, Income ₹12-24 L". Mute yourself. In your notes app, write a 3-line memo to the CMO recommending what to do instead — using only the Behavioural table. When the timer ends, the professor will cold-call three of you.
🔍 Reveal — the STP lesson hiding in plain sight▸
Demographics describe people. Behaviour predicts what they will do. The demographic spread is 0.22 — within noise. The behavioural spread is 2.43 — more than 10× stronger. The top behavioural segment ("Petrol-to-EV Switcher") converts at over 50% high intent. The bottom ("Casual Commuter, Range-Anxious") converts at under 1%. Both are well-represented in every demographic bucket. The first-year MBA instinct — "target 25-34 urban males" — is a media plan that sprays budget across buyers who will never switch, and misses the petrol-scooter commuter with home charging who would switch tomorrow.
Session 1-2 link: this is what "STP from the consumer side" means. Maslow and MOA are hiding inside behavioural segments: the Petrol-to-EV Switcher has Motivation, Opportunity, AND Ability. The Range-Anxious Casual Commuter has only motivation.
Where does VoltRide sit in the buyer's mind — and is there any empty space worth owning?
Perceptual mapping is only as useful as the axes you pick. Pick well and you see a gap. Pick badly and everyone looks the same.
Full attribute profile
💬 Chat commit (90 seconds)
Find one pair of axes where VoltRide sits in genuinely empty space. Post the axis pair in chat — just "X vs Y" format. The professor will pick the three most interesting pairings and test them live on the map for the room. Bonus before you post: try Status Signal × Resale Confidence. What do you see?
🔍 Reveal — the Nano trap▸
"Cheap" is not a position. "Affordable" is. The Tata Nano was priced at the bottom of the car market and positioned as "the world's cheapest car" — every buyer heard the insult instead of the invitation. VoltRide cannot win a tech-innovation war (Ola/Ather own it) or a Brand-Trust × Service war (Bajaj/TVS own it by heritage). The empty quadrants are Resale Confidence × Value-for-Money and Range Confidence × Charging Convenience — which are also the axes the behavioural segment "Petrol-to-EV Switcher" actually cares about. The segmentation tab and the perceptual map just agreed with each other.
Buyers rank battery life as their #1 fear. The engineering data says the battery will outlast the scooter. Who is right?
Perceived Risk + Information Asymmetry — the CB concepts that keep ICE scooters in showrooms.
Range anxiety vs real usage
Discussion Prompt
Battery lasts ~12 years. Scooter lasts ~8. The battery will outlive the vehicle you bolted it into. Why does 71% of the panel still rank battery life as their #1 concern?
🔍 Reveal — the paradox you can make money on▸
The battery outlasts the scooter — and nobody believes it. LFP pack, 2,500 cycles, 180 cycles/year ≈ 12 years to 80% capacity. Chassis design life: 8 years. The math says the battery outlasts the scooter by 50%. The field says 2.1% fail in year 5. The fear says 71% are terrified.
The brand that closes this gap credibly wins. Not with a longer warranty — everyone copies that in 90 days. With a certified resale floor + battery health passport + public cycle-life dashboard. Information-asymmetry reduction as marketing strategy. This is where CB meets Operations: Operations built the data, Marketing has to make the buyer believe it.
Ola sells 9× more scooters than VoltRide and loses 14× more money. Bajaj makes ₹10,840 per unit. VoltRide loses ₹7,000. Is this a marketing problem, an operations problem, or a storytelling problem?
Where CB meets Finance: the resale shock, the TCO reality, and the dealer-network moat.
Per-unit P&L across the competitive set
Same five numbers, same sign, different felt-magnitude. Consumer Behaviour lives in the gap between those two stories.
Ola — bleeding cash, scaling the bleed
CAC ₹11,200. Contribution negative ₹9,500 per unit. Every scooter Ola sells deepens the hole. 782 dealers, each sells 21 units/month — looks heroic, until you realise each dealer was built with fresh capital in the last 24 months.
Bajaj / TVS — the boring winners
CAC ₹2,800-3,100 (brand pull, not ad spend). Contribution +₹7,300 to +₹10,840 per unit. Dealer reach 3,800-4,100 — built over 45-75 years on ICE scooter margins, already fully depreciated. Their EV unit is a marginal business riding a paid-off fixed-cost base. This is what "playing the game well" actually means.
The hidden tax on EV ownership
Every buyer ranks resale in the top 3 concerns — every marketing team treats it as a "talk to the dealer later" problem. Fast-evolving battery tech means the generation that lands 24 months after your purchase can erase ~33% of your residual. A buyer loses this money silently. The brand that promises (and underwrites) a resale floor turns the #3 hidden objection into a feature.
VoltRide's board meets tomorrow. You have 90 seconds. Give them one segment, one positioning statement, and one number you will defend.
Synthesis — Sessions 1 + 2, Year-1 recap, and everything you just argued in the last two tabs.
Try a scenario — or build your own
🚪 Final Breakout (15 min)
Groups of 5-7: pick ONE target segment + ONE positioning statement, build a 90-second board-room defence. Rules: (1) cite one number from each of Tabs 1-5, (2) name one competitor you are explicitly NOT fighting, (3) commit to one metric you will be measured on in 12 months.
🔍 Reveal — what these tabs have been quietly telling you▸
Every tab pointed at the same quadrant. Tab 1: money is in operational leverage, not volume. Tab 2: Petrol-to-EV Switcher and Gig Worker Commuter are the only segments that convert. Tab 3: Resale Confidence × Service Network is empty quadrant. Tab 4: 71% fear the battery, data says the battery outlasts the vehicle. Tab 5: resale shock is real, TCO breakeven is year 2, operational leverage beats new spend.
The position writes itself:"VoltRide — the petrol-to-EV scooter with a published resale floor and a battery you'll outgrow before it outgrows you." Lead with Resale Confidence, back it with a buy-back guarantee, target Petrol-to-EV Switchers in Tier-1/Tier-2 with home charging. Every tab was an argument for this.