Lecture 10: Pricing and Price Management

Price (Basic Definition)

• Amount a customer pays for product/service

Price Definition (Strategic Marketing)

• Represents customers perceived value exchange (What customer thinks the offering is worth to them)

• Reflects intangible and tangible product attributes (Brand and Performance)

Price as a part of the marketing mix + Strategic Value

• It’s one of the 4 P’s → The only one that generates revenue

  • Key for capturing value and being profitable

• How we price our products → Competitiveness and Brand positioning (Luxury vs. Value)

• Determines purchasing decisions and brand perception (Low = Poor Quality)

Price as a strategic signal: Starbucks

• Coffee is cheap and widely available -> Starbucks charges a premium

  • Why? The great experience (Atmosphere, Store design, Personalization) → Perceived Emotional and Experiential Benefits

  • High Price signals Quality -> No discounts maintains trust (Staying Premium)

Pricing and Promotion

• Discounts/Promotions boost short term sales -> Risk value erosion 

  • (Reduces pricing power) -> People wait for deals (Don’t treat you as premium)

  • Framing is key: Celebration vs. Clearance Discount

• Lesson: Pricing tactics align with how our brand is perceived

What is WTP

• Maximum price a customer is willing to pay for product/service (Upper boundary of market)

WTP isn’t a fixed number .. What is it influenced by? (4)

• Perceived benefits (Functional, Emotional etc.)

• Urgency (Bottle at airport)

• Customer Segments (Some are willing to pay a premium)

• Both Emotional + Rational Considerations: Identity, Prestige + Performance and Durability

What is Perceived Value

• Customers subjective assessment: Is a product worth its price (Bundle of all benefits vs. Price)

• Higher the Bundle, the higher the WTP

What is a Reference Price and how frequent promotions effect it

• Mental Benchmark for if a price is fair

• Shaped over time by Competitors, Past purchases, Marketing

• Frequent Promotions → Drive Price Downward (Anchoring)

What is prospect theory, How important is the reference point

• Losses hurt more, than wins give joy (We seek risks to avoid losses)

• Perceived value is based on framing and context:

  • Anchor a higher reference point → A discount on it feels like a win for the customer

Reference Point for prospect theory

• Changes around here are perceived the strongest

• Changes at higher magnitudes (Sums) are less strong (10$ off a Rolex)

Apple as an Example: 1) Why high WTP? 2) Why high prices 3) Anchoring 4) Prospect Theory/Loss Aversion

• iPhones are similar quality to competitors, yet consumers show high WTP due to Brand Prestige, Design and Ecosystem

• Key Strategy: Prices remain high (Few Discounts) and Anchoring prices with new iPhone releases

  • High Pricing -> Seen as premium and innovative

• Prospect Theory: Cannot miss out on new model (Need to Upgrade)

Price as a signal: High Price =

• Higher Quality

• Exclusivity

• Higher Value

• More Trustworthiness (In market with information asymmetry → Where we can’t gauge quality)

Framing Effects (Anchoring and Decoy Pricing)

• Anchoring: Initial price sets expectations

• Decoy Pricing: Bad offering -> Steers customers to profitable choice

Framing Effects (Bundles and Context)

• Bundles: Perception of savings

• Context: Environment, Comparison Set (Options) -> Shape price perception

Switching Costs

• Discourage Brand Changes:

  • Fees (Financial)

  • Procedural (Time consuming steps)

  • Learning (Need to learn a new interface)

  • Emotional (Loyalty to brand)

What is Elasticity

• It’s the ratio of (Percentage change in Demand to Percentage Change in Price)

How do we calculate Elasticity

1. Find % Change in Quantity Demanded: (New Qty - Old Qty) : Old Qty * 100

2. Find % Change in Price: (New Price - Old Price) : Old Price * 100

3. Divide the two

What is an Elastic Market

• When \varepsilon>-1 : The market responds to small changes in price, with larger changes in demand

  • If we increase prices, we lose revenue (Opposite Direction of Price and Revenue)

What is an Inelastic Market

• When \varepsilon<-1 : The market responds to changes in price, with smaller changes in demand

  • If we increase prices, we gain revenue (Same Direction)

What if $\varepsilon=1$

• Revenue is Maximized

• Unitary

Signs of an Elastic Market/Demand

• Non Essential Luxuries

• Many Substitutes and Low switching costs

• Limited Pricing Power: Consumers react strongly to price changes

• Never Absolute (Strong brands can become inelastic such as apple through emotional attachment)

Signs of an Inelastic Market/Demand

• Critical Needs

• Limited Substitutes

• High switching costs

• Strong Pricing Power: Weak reaction to price changes

Key things to know around elasticity

• 
  

  Commodities = Elastic, Differentiated Brands = Inelastic

• Subscriptions reduce elasticity over time (Payments become habitual)

• DISCOUNTING WORKS BEST IN ELASTIC MARKETS

What is Cross Price Elasticity

• Measures how demand for Product Y reacts → To changes in Pricing of Product X

  • Calculate: Percentage of Change in Quantity Y : Percentage of Change in Price X

What we can read out of the Coefficient Sign

• Positive: The goods are substitutes (Customers will switch: Uber and Lyft)

• Negative: The goods are compliments (If customers buy less of X, then also less of Y: Coffee and Cream)

• 0/Near 0: The goods are unrelated (Tomatoes and Shoes → 0 impact on each other)

Key Strategic Implications for Positive and Negative Coefficients

• Reveals Competitive Threats: If positive Coefficient-> Competitor

• Dependency Risks:  If compliment becomes more expensive (Negative Coefficient), demand for your own product may drop

Quick Recap: What is a conjoint analysis and how can we use it 3x

• How do customers make trade-offs between value and price 

  • We get Part Worth utilities (Utility of Features) -> Derive their WTP for attributes 

  • We can base prices on the value the customer perceives

  • We can Identify Optimal Product Bundles

What is A/B Testing, how do we use it to get optimal prices

• Customers randomly get different prices -> We compare performance metrics and decide on optimal prices

• We get their actual behavior

• Netflix uses this

Survey Technique PSM (Van Westendorps Price Sensitivity Model)

• Ask 4 Questions.. When is the price:

  • Too Cheap (Doubt Quality), A Bargain, Feeling Expensive, Too high to consider

Gabor Granger Technique

Measure purchase intent at each Price Point

Direct WTP Method

• How much would you pay

Limitations of Surveys

• No Financial Consequences, Hypothetical Bias (Say one thing, do another), Framing Effects of questions

Observation and Transaction Data: What is it and Advantages

• Analyze real world data -> Uncovers true pricing dynamics 

• Advantages: Shows: (Real Preferences/Behavioral patterns), Price Response over time

• Is more reliable but requires clean transaction Data

AI and Predictive Analytics → Applications and Ethical Concerns

• Use Machine Learning

• Applications: Dynamic Pricing to market conditions, Personalize Offerings, Forecast Price Sensitivity

• Ethical Concerns: Backlash due to feeling of Price Discrimination, Algorithmic Bias (Reinforces Inequalities), Lack of Transparency

What is Cost Based Pricing and What markets is it good in + Cons

• Price = Production Cost + Desired Profit Margin

• Simple but ignores WTP and leads to overpriced/underpriced products

• Good in B2B or commodity Environments (Raw Materials)

Competition Based Pricing

• Set price based on direct competitors

• Avoids Undercutting and Reacts to changes quickly but causes price wars and less profitability

  • Ignores WTP

• Good in Transparent Markets (Airline Fare Pricing)

Value Based Pricing

• Price based on value perceived by customer

• Customer Centric and supports premium positioning but requires deep Market understanding

• Works well for differentiated and innovative brands (Tesla)

What is Skimming Pricing, and what is the downside

• High Initial Price -> Maximize Early Profits (Early Adopters)

• Good for Innovative/Prestige Products that are exclusive

• Problem: Limited Volume

Penetration Pricing

• Low Prices to quickly gain market share and rapid adoption → Create switching costs

• Good for Accessible and Mass Market products

• Problem: Low profit margins and hard to rise prices later

Freemium Model

• Basic Version is free -> Advanced Features cost (Spotify)

• Attracts large user base -> Converted to customers

• Good for fast growth but infrastructure costs for free users is high + Low conversion rates

Pay What you Want

• Customers decide how much they pay (Donation/Trust Driven Models)

• Strengthens emotional connections and Brand is perceived positively

• But: Risk of low payments

Subscription Pricing

• Ongoing access to product for recurring fee

• Predictable Revenue that helps raise CLV

• Tiered Pricing (Maximizes Revenue, Remaining Accessible to as many as possible)

• Needs strong retention (Keep Customer Engaged) -> Reduce Churn

Bundling

• Combine services/products into one package 

• Increases transaction size and perceived value

• 3 Types:

  • No Bundling (Individual Items),

  • Pure Bundling (Only as a package) → Microsoft 365

  • Mixed (Both -> Optimal for revenue) → McDonalds Value Deal

Add On Pricing

• Sell basic product with add on upgrades (Tesla)

• Customization and Maximizes margin on high WTP customers

Trials

• Lower barrier to entry -> Customer gets to experience

• This reduces risk -> Mostly in subscription markets

• Conversion is Key → Frictionless upgrade path

What is Dynamic Pricing + Goal + Weak Demand Example

• Prices are adjusted in real time based on Data about changing Market Conditions (Weather, Demand)

• Goal: Revenue Maximization

• Weak Demand → Decrease pricing to stimulate demand

Time-Based and Consumer-Based pricing (Dynamic Pricing Types)

• Time-Based: Price varies by time, date and season -> Uber/Airlines

• Consumer-Based: Price based on user profile (Browsing History) -> Amazon Offers

Channel and Auction-Based Pricing

• Channel-Based: Price differs across distribution channels -> Store/Online

• Auction-Based: Price based on what customer is willing to pay -> eBay, Ticket Resale

How Dynamic Pricing Works

1. Data Inputs (Demand, Inventory) get analyzed by Algorithms and Pricing Tools

2. Output: Prices are then adjusted by the minute -> Maximizing Goals: (Inventory Use, Revenue Maximization)

Dynamic Pricing Examples: Uber, Amazon

• Uber Surge Pricing → Higher prices during peak demand (Also increases drivers coming online)

• Amazon → Prices shift depending on competitor prices

Role of AI and Machine Learning in Pricing

• Advanced Algorithms analyze huge amounts of Data -> Set Optimal Prices

4 Benefits AI/ML provides

• Predictive Pricing: Estimate price a customer is willing to accept

• Personalization: Pricing based on customer attributes

• Self Learning -> Improvement over time

• Instant Dynamic Adjustments (Real-Time)

Benefits of Dynamic Pricing

• Better Segmentation

• Real Time Reaction to Market

• Price and WTP get matched → Higher Profits

Downsides of Dynamic Pricing

• Feels Unfair → Backlash

• Ethical Concerns

4 Ethical Concerns around dynamic pricing

• Price Discrimination -> Different customers get different prices (Feel Manipulated → Leads to outrage)

• Reinforces Biases -> Prices can disadvantage certain groups (Be Fair)

• Needs Transparency → Algorithm Opacity (We don’t understand how it works ourselves)

• Don’t Exploit moments of stress

Strategic Benefits of Discounts

• Improves Profitability: Align prices with real time WTP

• Personalization: Personalized incentives through AI driven discounts

Strategic Risks of Discounts

• Overuse -> Price Integrity (Discount becomes anchor)

  • Hurts Premium Brand positioning

• Feeling of unfairness amongst Customers (Algorithmic Bias)

Psychological Effects of Promotions: Reference Points, Anchoring, Price Framing and Scarcity

• Reference Prices (Internal Benchmarks to compare)

• Anchoring: Set high price -> High discount looks attractive

• Price Framing: (100->59 is more attractive than: Save 41) -> Avoid loss > Gain

• Scarcity Messages (Don’t Miss Out): FOMO

Risk of using Psychological Effects

• Unethical: Huge backlash if seen as misleading

What is cross promotional strategy

Synergy via Loyalty Programs -> Must be consistent with Brand (Premium Brand shouldn’t do many deals)

Partner Discounts, Seasonal Events, Tier Discounts

• Partner Discounts: Increase reach and perceived value between two complimentary brands (Spotify and Hulu)

• Seasonal Events: Context makes sense -> Pricing aligned with significant moments (Black Friday)

• Tiered Discounts: 2f1 Deals -> Motivate customers to spend more

Case Study: Amazons Algorithmic Pricing

• Dynamic/Algorithmic pricing to optimize prices

• Use: Browsing History, Competitor Pricing, Stock Levels, Demand Signals

• A/B testing to maximize conversion vs. retention trade-off

Case Study: Uber and Surge Pricing

• Surge Pricing -> Higher Prices balance Supply and Demand

  • Incentivizes drives to work -> More available supply and lower wait times

• Controversial -> Feels unfair during emergencies and crises (Needs to be communicated well)

Case Study: IKEA and true Value Based Pricing

• IKEA first gets customer WTP and Functional Requirements through Ethnographic Research

• They then Reverse Engineer products to fit both Categories

• Use Local Market Pricing: Products should be affordable for local consumers

Case Study: Spotify Freemium and Tiered Pricing

• Freemium Tier -> Grow in Scale and get customers into the ecosystem -> Increase Switching Costs

• Tiered Pricing -> Different Plans (Student Plans etc.)

• Regional Pricing -> Capture WTP

• A/B Testing -> When to promote premium (App nudges for premium after multiple ads)

• Goal: Increase CLV -> Convert high usage free users to paying premium users

Case Study: Duolingo and Upselling

• Essential features are free -> Upsell to Duolingo Plus (Offline Access, Premium Features

• A/B testing used to optimize (Subscription Length, Feature limitations etc.)

• Personalized upgrade prompts: Streaks, Misses lessons etc.