Role: Senior Manager / Lead - Revenue Modelling & Behavioural Sciences

Function: Revenue Strategy & Growth Ops (Watcho / Vzy)

Reporting to: Head - Revenue Strategy & Growth Ops (Watcho / Vzy)

Job Persona: What This Person Really Looks Like

1. Commercially Assertive

- Optimizes for incremental revenue, and long-term contribution margin

- Comfortable saying "this growth is value-destructive"

2. Behavioural Understanding

Understands that Indian OTT users are:

- Hyper price-sensitive

- Heavily influenced by defaults, framing, and social proof

- Inconsistent between stated intent and actual behaviour

3. Systems Thinker

- Connects: UX changes -> behavioural response -> funnel movement -> revenue impact

- Understands second-order effects (e.g. discount addiction, trial abuse)

4. Decision-Oriented, Not Model-Oriented

- Uses models to decide, not to impress

- Comfortable making calls with noisy data

Ideal Background

1. Strategy / Consulting + Consumer Behaviour

- MBB / Big 4 / Boutique strategy

- Has worked on pricing, consumer choice, or growth strategy

- Exposure to behavioural economics frameworks is a big plus

2. Revenue / Growth Analytics at Consumer Internet

- OTT, gaming, fintech, or delivery apps

- Experience running experiments on pricing, paywalls, or nudges

- Has seen how small UX changes materially shift revenue

Experience: 6 - 8 years

Education: Engineering, Economics, Applied Math + MBA (top institutes)

Detailed Job Description

Own & optimize the economic and behavioural engine of a hybrid OTT aggregation business-maximizing LTV, improving yield, and shaping user behaviour through pricing, packaging, and product nudges. Key responsibilities:

1. Revenue & Behavioural Modelling (AVOD + SVOD + TVOD)

- Model revenue across monetization types and user intent states

2. Pricing, Framing & Pay-out Optimization

Design not just prices, but price presentation:

- Monthly vs daily equivalent / Most popular anchoring / Decoy bundles

Balance:

- Consumer psychology

- Partner MG obligations

- Long-term margin health

3. LTV / CAC Forecasting with Behavioural Adjustments

Adjust LTV models for:

- Discount conditioning

- Trial abuse behaviour

- Seasonal impulsive buying (IPL, festivals)

4. Three-Way Integrated Financial & Behavioural Models

Maintain integrated models that account for:

- Revenue

- Behavioural decay (engagement drop-off after promos)

- Long-term elasticity impact of discounts

5. Sensitivity & Scenario Analysis

Stress-test not only numbers, but behaviour shifts:

- What if CPM drops, but watch-time rises?

6. Content Deal Structuring with Behavioural ROI

Build Deal Scorecards that include:

- Content's ability to trigger habit

- Repeat-view probability

- Evaluate MGs not just on reach, but behavioural stickiness

7. Board-Level Storytelling

Translate:

- "Users churned" - why they churned

- "Conversion dropped" - which bias broke

- Recommend actions grounded in both math and psychology

Technical & Behavioural Skills

Must-Have

- Advanced Excel / Google Sheets

- PowerPoint (Exec storytelling)

Behavioural + Experimentation

- A/B testing frameworks understanding

- Familiarity with behavioural economics concepts (formal or applied)

Nice-to-Have

- BI tools (Looker, Tableau)

- SQL (cohort & funnel extraction)