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# Pricing

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pricing optimization theory

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### Pricing

1. 1. pricing<br />
2. 2. 3 Cs<br />
3. 3. Economic Value Pricing<br />Definition<br />Economic Value to the Customer (EVC) is based on the insight that a customer will buy a product only if its value to them outweighs the value of the closest alternative, <br />or when the utility of a product depends on its value to the customer minus its price.<br />Therefore, to sell a product, a firm needs to price at or below its competitor’s price plus the value advantage its product has to the customer over the rival product.<br />
4. 4. Pricing below EVC<br />Uncertainty effect – people don’t believe the benefits you claim<br />Newness effect – people don’t understand the benefits<br />Temporary Discount effect –discounting from list drives sales, vs lower price<br />Expenditure effect – large single purchase<br />Its just not right – Price gouging<br />Strategic – winner takes all market<br />
5. 5. EVC for Advertising<br />Is EVC a good model for advertising?<br />Is there an EVC for advertising?<br />
6. 6. EVC as a Pricing Diagnostic<br />Is a product priced correctly<br />Overpriced<br />Value message misaligned to differentiation value<br />
7. 7. Price Elasticity<br />Price Elasticities. The price elasticity of a product measures the responsive­ ness of sales to a change in price. Price elasticity is defined as the percent change in quantity sold given a 1% change in price.<br />This helps analysts figure out whether revenues will be the same, higher or lower after a change in price. If elasticity=1, revenues will be the same from a price change. If elasticity is >1, revenues will be higher with a price decrease. If elasticity<1, revenues will be higher with a price increase.<br />Estimating a constant price elasticity. One problem with the formula ΔQd/Qd for the price elasticity is that it can take two different values for whether<br />ΔPd /Pd P or Q are the original or final values. This shouldn’t matter if you are comparing<br />price elasticities across segments and are always consistent about what values you use (for example the value that is used in the denominator, should be the one used to calculate the numerator).<br />
8. 8. Pricing Analysis<br />Ways of improving historical pricing analysis.<br />(1) CRUCIAL. Calculate different price elasticities for each type of customer, each region, each product.<br />(2) Use more data than just aggregate sales and prices • DHL employed software that included the reactions of customers who<br />called and got a quote but didn’t ship - that is, a failed sale. By in­ cluding data from this group of customers, they improved their ‘quote to book ratio’ from 17 percent to 25 percent.<br />(3) Use panel data econometrics where you include controls for places and times in your regression analysis. The problem is that this can get very expensive both in terms of personnel and costs of acquiring data.<br />
9. 9. Pricing along the demand curve<br />In the last lecture, we thought hard about how to measure the demand curve. But it is important to also think about why it slopes downwards. The answer is variation in how much our customers value our product.<br />The most crucial insight of this class is that we shouldn’t think about where we should price along our demand curve. Instead we should think, how many different prices to different customers can I charge along my demand curve?<br />
10. 10. Segmentation Models<br />Product attribute based<br />Customer based<br />
11. 11. Customer Based Segmentation<br />National (big brannd) vs local<br />International vs home market<br />Are there ther opportunities?<br />
12. 12. Product attribute based segmentation<br />Must be able to structure price to meet key attribute<br />Creating different products based on the atribute<br />Remnant vs premium<br />Optional extras – can be burdensome over time<br />
13. 13. Price Erosion Threats<br />Falling demand<br />Low differentiation<br />Increasing supply and substitutes<br />
14. 14. Pricing power<br />Market has limited capacity<br />Increasing demand<br />Strong differentiation <br />In April, 2009, in the UK, Amazon offered 100 popular MP3s at just 29p (0.50c) per download. Apple’s iTunes store responded by raising prices on the most pop­ ular MP3s to 99p, or \$1.50. Apple could do this because of switching costs and superiority of iTunes experience.<br />
15. 15. Out Pricing<br />Using 3 Ps<br />Product<br />Promotion<br />Place<br />Lowering price may be a trap<br />less revenues<br />Indicate low quality<br />Fragile market – disloyal customers<br />