Price, Segmentation, and Demand Estimation

1. Price, Segmentation, and Demand Estimation MIST 8990 UGA Evening MBA Program August 19, 2005 Presentation by: Patrick G. McKeown

2. How Revenue Management Optimizes ProfitFor Any Business Segment the Market Predict Customer Demand Optimize Price Recalibrate Dynamically Segmentation based on purchasing behavior, not just current or past classifications Forecasts of demand and capacity at product/price level Continually monitor performance and update market response Mathematically determine capacity availability and price that maximizes expected profit

3. Three Elements of RM • In looking at the previous slide, it is obvious that there are three key elements to revenue management: • Segmentation • Demand • Price • Let’s consider each of these, starting with price

4. Definition of Revenue Management Selling the • Right Product to the • Right Customer at the • Right Time for the • Right Price

5. Price Let’s consider the importance of price in revenue management McKinsey and Co. has said that: • A 5% Improvement In Sales Expense Increases Profits By 3 % • A 5% Improvement In Sales Volume Increases Profits By 20% • A 5% Improvement In Selling Price Increases Profits By 50% How does this work?

6. Profit Equation Profit = (Price – Variable Cost) x Units Sold – Sales Expense Where • Price is set by your company • Variable cost is cost of each unit to you including commissions • Units Sold = Sales Volume • Sales Expense includes all fixed costs associated with the sale of the product and includes advertising, front and back office expenses, Web site costs, and so on

7. Example Assume: • Initial Price: $135/unit • Initial Variable Cost: $75/unit • Initial Sales Expense (fixed): $50,000 • Initial Sales Volume: 1,000 units • This results in an initial profit of: • (135 – 75) x 1,000 - 50,000 = $10,000

8. How do we increase profits? Profits of $10,000 may be ok, but how do we increase them? • Cut sales expense? A popular option, but how low can you go and still be in business? • Increase sales volume? A good idea, but how do you do it without decreasing prices or increasing sales expense (advertising)? • Increase price? Unpopular with customers!! • Which is best? Let’s look at the 5% solution

9. Cutting Sales Expense by 5% • Cutting sales expense by 5% yields a new profit of (135 – 75) x 1000 – 47,500 = $12,500 • A 25% increase in profits! • Pretty impressive

10. Cutting Sales Expense Another 5% • Cutting sales expense by another 5% yields a new profit of $14,875 or another 19% increase in profits • Less than a 10% cut in sales expense has resulted in an almost 50% increase in profits Great! But how much can you cut sales expense without damaging the business? • Will profits keep going up?

11. Increasing Volume by 5% • Another solution is to increase volume by 5% (assuming this can be accomplished with no increase in sales expense or a cut in prices) • Increasing volume by 5% results in a profit of (135 – 75) x 1050 – 50,000 = $13,000 or a 30% increase • Even better than cutting costs!

12. Increasing Volume by Another 5% • A subsequent 5% increase in volume results in a new profit of $16,150 or an additional 24% • So, increasing volume by slightly more than 10% results in a greater than 60% increase in profits! • But, can volume be increased that easily?

13. Increasing Prices by 5% • Both decreasing sales expenses and increasing volume have resulted in significant increases in profit—will increasing prices do as well? • Increasing the price by 5% results in a profit of (141.75 – 75) x 1000 – 50,000 = $16,750 or a 67.50% increase in profits • The best yet!

14. Increasing Prices by Another 5% • What happens with another 5% price increase? • Profits now = $23,837 or an additional 42.3% increase in profits • A price increase of slightly more than 10% results in a total increase in profits of 138%

15. Comparing Strategies Effect on Profits

16. Comparing Long Term Effects on Profits

17. Setting Prices If price is such a clear determinant of revenue and profit, how do we set prices? • Microeconomic approach • As a fraction of costs • Based on what competitor does • Negotiations with customer • Other ways?

18. Revenue Management Approach • “Products” do not necessarily have an inherent value • Value depends on the customer demand at the time of the purchase • Products have different values to different groups of customers • Demand at a point in time for a given customer segment drives prices • The concepts and process of determining the highest revenue prices is subject of this course

19. Revenue Management Process Revisited Segment the Market Predict Customer Demand Optimize Price Recalibrate Dynamically Step 1: Segmentation based on purchasing behavior, not just current or past classifications Step 2: Forecasts of demand and capacity at product/price level Step 4: Continually monitor performance and update market response Step 3: Mathematically determine capacity availability and price that maximizes expected profit

20. Step 1: Segment Market • What is market segmentation? • Dividing a mass market up into many micro markets • Often defined in terms of demographics (sex, age, income, etc.) or psychographics (attitudes, lifestyle, etc.) • In revenue management, we define segmentation in terms of what customer is willing to pay and how they will respond at time of purchase!

21. Segment Customers Segmenting the Market • Segment the customer base according to price-response characteristics for each product • Define observable market segments, each with differentmarket response • Clustering techniques are used in defining micro-markets

22. Segmenting Customers • Price is based on demand for customer segments • Market segmentation is the key to enhancing revenues in revenue management • Many ways to segment customers but we want customer-centric segmentation** • Different customers value different attributes **Robert G. Cross and Ashutosh Dixit, “Customer-Centric Pricing: The Surprising Secret for Profitability “

23. Customer Centric Segmentation • Based on buying behavior • Uncovers large differential willingness to pay for subjective product attributes—customer centric pricing • Price differentials are greater than many businesses assume • Can be basis of substantial profits • Company that creates value captures benefit of value instead of brokers or other resellers

24. Segmentation Methods • Timing of purchase (advance vs JIT) • Sales channel (“click” vs “bricks”) • Volume of sale (order quantity = one vs many) • Delivery speed (discount for slow delivery) • Perishability of product—”time segmentation” • Others—age, geography, …

25. Segmentation Examples • Airfare • Business customers value JIT capability of purchase over cost of ticket • Leisure customers value low cost ticket over long advance purchase time or ability to change it • Consumer purchases • Web customers often value lower prices over immediate access to product • Store customers often value immediate access to product over lower costs

26. More Examples • Age • Discount for children (fly free under 2, eat free at Holiday Inn with parents, etc.) • Discount for Seniors (National Park Golden Age Pass, discounts at other tourist attractions, etc.) • Time of Day • Happy Hour • Early Bird Specials

27. And Yet More Examples • Geography • Discount for local citizens • Clubs • Buying Clubs (Sams’, etc.) • Dining Clubs (buy one, get one free with coupon)

28. Online Shopping Segments** • (5%) E-bivalent Newbies -- Newest to the Internet, somewhat older, likes online shopping the least, and spends the least amount online. • (17%) Time-Sensitive Materialists – Most interested in time and convenience, less likely to read reviews, compare prices or use coupons. • (23%) Clicks & Mortar -- Tend to shop online but prefer to buy offline, more likely to be female homemakers, have privacy and security concerns about buying online, and visit brick-and-mortar shopping malls most frequently. • (16%) Hooked, Online & Single –More likely to be young, single males with high incomes, have been on the Internet the longest, play games, download software, bank, invest and shop online the most often. • (20%) Hunter-Gatherers -- More likely to be married, typically age 30-49 with two children, most often goes to sites that provide analysis and comparisons of products and prices. • (19%) Brand Loyalists -- Most likely to go directly to the site address of a merchant they know, are the most satisfied with shopping online, and spend the most online. **http://www.harrisinteractive.com/news/allnewsbydate.asp?NewsID=116

29. Time Segmentation • Value of product changes over time • Buy early for security or later for flexibility • Demand may drop significantly for a perishable product • Perishability applies not only to agricultural products • Example: demand for concert tickets goes to zero after event occurs

30. Pricing Based on Segments • Once segments are created, use demand estimates for each segment to set price • Higher demand results in higher prices • Don’t want “leakage” from higher priced segments to lower priced segments • Leakage can result if segmentation is not perfect

31. Building Fences • Revenue will disappear unless customers are penalized for moving to a lower priced segment • Need to create “fences” to maintain segments by avoiding leakage • Examples of fences: • High cost to change a low price ticket • Requirement of a Saturday night stopover for low price ticket • Advance purchase requirements for lodging or rental cars

32. Step 2: Estimating Demand Once segments are created, the next step is to estimate or forecast demand for each segment A two step process • Build an off-line demand model for each segment using various forecasting techniques, e.g., regression, curve fitting, and cluster analysis • Build an online updating system for keeping the demand model current

33. Demand Time Demand for Perishable Product S1 S2 S3 S4

34. Demand for Event or Trip Tickets Demand Days 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1

35. Demand Models Common demand models • Linear: D = A – Bp where p = price • Example: D = 100 – .4p (demand goes down by 0.4 units for every one unit increase in price) • Curvelinear: D = Ap-e where e = price elasticity of demand • Example: D = 2 x 109 x p-4

36. Comparison of Demand Models

37. Linear Approximation to Curvelinear Demand Curve • Note that for a range of prices, the linear demand line is a good approximation to the curvelinear demand curve • Using the linear approximation makes it easier to use mathematical modeling to optimize prices for each segment • More on demand forecasting later.

38. Step 3: Optimizing Price • Usually carried out via mathematical programming • For airlines, rental car companies, hotels, etc, very large linear programming problems are solved on a regular basis to set prices

39. LP Formulation More on LP later!

40. Step 4: Dynamically Recalibrate Customer Demand Price and Availability Results In: Long-Term Profit Maximization

41. IT Requirements for Dynamic Updating • To dynamically update prices, heavy use of IT is required • Very large databases to track customer responses to price changes • Data warehouses to store historic information on customer behavior • Large application servers to run optimization problems on a regular basis

42. Summary • Revenue management can be a key contributor to increased revenue and profits • RM requires that data on customer behavior be acquired and converted into market segments • Data must also be used to develop customer response models and to build the optimization problems • A unique blend of IT and management science/operations research methodology