MKTG 476 776 - Lecture 11 PDF

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Lecture 11 (Ehrenberg) Brand Performance Measures (BPM) Size-Related  Market share  Penetration o % of customers who buy at least once in a week or year Loyalty-Related  Frequency o Average number of purchases per buyer  % of one-time buyers o # of single-unit customers (buy only one time per year)  % of “100% loyal” buyers  “Share of wallet”/SCR (share of category requirements) o Among the people who buy that brand, what is the market share? o What percentage of customer purchases are of your brand? o = Brand Purchases (#)/ Total Category Purchases by Brand Buyers (#) Others  Choice set sizes  Concentration o Greater concentration for bigger brands o Since alpha is scale parameter, expect big brands and small brands to have similar alpha  Mean is r/alpha  Mean for big brands > mean for small brands o Bigger brands will have higher r  Duplication of purchase Byron Sharp doesn’t believe in 80/20 – he says the law is “60/20”, which suggests the nature of heterogeneity is the same across all brands. Correlation What is the correlation between market share and each brand performance measure? Purchase % of “once % of “100% Penetration SCR Frequency only” buyers loyal” buyers Market Share +++ + -+ ++ O&J Brand Performance Metrics Brand Share Penetration E

33%

50%

Frequency

Once-only

100%

SCR

4.0

32%

38%

66%

A H F G D C B

15% 15% 13% 11% 7% 4% 3%

32% 29% 24% 26% 21% 11% 10%

2.9 3.1 3.5 2.5 2.0 2.0 1.8

47% 48% 58% 58% 71% 64% 60%

13% 17% 17% 19% 5% 27% 30%

42% 41% 47% 32% 27% 28% 40%

Commentary  Ehrenberg would say: “the way to grow your brand isn’t by getting your customers to buy more, but rather by growing the base” (growing the base)  Ehrenberg did not like exceptions to his laws; he would dismiss brands that are exceptions as not part of the market  Frequency varies positively, but not that strongly  Why is % of “once only buyers” negative? o Heavy category buyers are spinning their Poisson wheels with good lambda’s. Since their lambdas are so high, they roll their dice often; eventually, at some point, they end up buying the low market share brands  Rolling the same dice – just more often o By random chance, heavy purchasers are “stumbling into those brands” o Conditioning for penetration – among the buyers of the brand, how many are “once only”?

List of Laws  

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Double Jeopardy Law: brands with less market share have fewer buyers, who are also less loyal Law of Buyer Moderation: Regression to the mean of purchase behavior over time; heavier users become lighter, lighter users become heavier buyers, and non-buyers begin to buy the brand Duplication of Purchases Law: All brands, within a category, share their customer base with other brands in line with the size of those other brands o Of all the people that bought Brand X, what percent bought Brand Y, Z,…? o When you start looking across all the brands, it gets interesting o Columns are incredibly constant across – it doesn’t matter what the initial brand (Brand X) is

Double Jeopardy Definition  Buyers of small brands buy those brands less often than buyers of big brands buy big brands o Niche brands are much harder to find and sustain – this essentially rules out the existence of a niche brand o Big brands get higher frequency AND higher penetration

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Reference: Double Jeopardy Revisited (Ehrenberg) o First identified by William McPhee (about Sunday comics) Also seen in the data of Facebook & other social networks

Professor Fader’s Departures 

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Triple Jeopardy o Even according to Ehrenberg, for major market leaders, some behave like an even bigger brand than they already are  Even if we accept double jeopardy (which tells us big brands will be purchased more than the little brands), there will be even more than that  Positive residual for the biggest brand – observed purchase frequency will be even higher than it should be o Professor Fader wrote a paper with David Schmittlein o Reasons include social contagion, differential retail availability (access; small stores often only carry the big brands), “mental” availability o Detecting triple loyalty  Run D-M, get the “expected” penetration/frequency and compare to the “actual” (residual from model) o Reference: Excess Behavioral Loyalty for High-Share Brands Non-stationary: throw your die away, take another

Excel Implementation Orange Juice From Brand A’s perspective αA ∗α A +1 Γ ( α A +n ) S ∗α A +2 Γ ( α A) Γ (α A +n)Γ (S ) S+ 1 ∗…= P ( 100 % loyal )= = S +2 Γ ( S+n) Γ (α A )Γ (S+ n) Γ ( s) Remember: Γ ( S +n ) = ( S +n−1 ) ! 

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Depends on how many purchases you’ve made o In the first period, our expectation of their probability of buying brand A is equivalent to market share o In the second period, we condition on the first (conditional expectations) As well as which brand we’re considering When calculating P(100% loyal) based on Dirichlet, on the aggregate, it should be similar to the P(100% Loyal) found in the data o Note: Ehrenberg noted that P(100% loyal) doesn’t line up as well as the other metrics

Note: this is a static, stationary model! The changes are due to conditional expectations – as we see a customer over time, we reduce some of the uncertainty and zoom in on their true underlying propensity. Γ ( S +n−α A ) Γ ( S−α ) ( S−α A ) ∗( S+1−α A ) Γ ( s +n−α A ) Γ ( S ) Γ ( S+n ) S Penetration= 1− P ( 0) =1− = ∗…= S+ 1 Γ (s ) Γ ( S−α ) Γ (S+n)  Penetration lines up pretty well % Once Only=n  

Γ ( S −α A + n −1 ) Γ (S) α A ( S−α A ) ( S +1−α A) +…=n α A /¿ S+2 S S +1 Γ ( S−α A ) Γ (S+n)

“n” possible sequences (could purchase once at any of the n purchase opportunities) Solve for one sequence, and multiply by n

Donation Amount  Dirichlet Multinomial on donation amounts  There is still double jeopardy! But there is no triple jeopardy

Ehrenberg’s Slide Deck 

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Giant companies (CPG and media) would pay Ehrenberg a lot to find out what their alpha’s were (and the other metrics) o If there were deviations, he would say they were transient He has a big ego, but he was very productive

Overview  “In near steady-state markets (mostly)”  Emphasizes BPM o From Professor Fader’s perspective, if you get the alpha’s, everything else comes along for free – this is more important than the BPM  Attitudes change with behavior (in other words, they follow alpha) o You are endowed by alpha, and everything follows from there o Can answer attitudinal questions based on alpha o For example, with toothpaste, we consider perceptions such as: freshness, whitens your teeth, etc.  Biggest toothpaste brands have the most checkboxes on these features  People associated good features with the biggest brands  Ehrenberg makes the model seem incredibly complex & technical to make it inaccessible o Estimated parameters using Means and Zeros, as a choice process o From aggregate-level data, not customer-level

Aside Quorn Example – “meat substitute Quorn is broadening its market from vegetarians to appeal to the mass of healthy eaters in a quest to become a $1 billion global brand”  Instead of making it narrowly appealing, they tried to “check as many boxes as possible” to get the availability  Reference: “Simply Better” o Be broadly appealing & pretty good at everything, instead of excellent in one specific area o Everything else will follow from that Note: Professor Fader does not see the two as a causal link, but it’s interesting to think about Interesting Case Study  New US instant coffee o Break-even market share is 5% o This equates to 8 purchases per year per 100 households  We have two options for strategies o Niche: 1% buying 8 times = 8 purchases per 100 HH’s o Add-on: 8% buying 1 time = 8 purchases per 100 HH’s  Ehrenberg says you have no choice between the strategies (and he’s mostly right) o You will end up among the distribution of other companies in the market o For example, given a market share of 5%, you will be between Sanka and Highpoint  Sanka’s Market Share is 9%, % buying is 5%, purchases per buyer is ~3  High Point’s: 9%, 1%, ~2.6  It’s really hard to change or boost your alpha o E.g., you advertise to maintain your alpha where it is o Professor Fader thinks it’s really hard to tell for a young brand Strategic & incorrect assumptions  Differentiating our brand is a vital marketing task  Loyalty metrics reflect the strength, not size, of our brand  Customer retention is cheaper than acquisition  Price promotions boost penetration not loyalty  Who we compete with depends on the positioning of our brand image  Mass marketing is dead and no longer competitive  Buyers have a special reason to buy our brand  Our consumers are a distinctive type of person  20% of our customers make 80% of our purchases  Ehrenberg challenges all of these assumptions Approximate shortcuts  Double Jeopardy: Brand X’s purchase rate w0 approximately as: w x = 1−b x

w x relates to its penetration b x

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o Frequency∗( 1−Penetration )=k , where k is a constant o What does variation in k mean?  High “k” brand  niche brand  Low “k” brand  a lot of people buy, but not very often  change-ofpace brand  E.g., ginger ale o Can start to look, at the margin, for niche-ness vs. change-of-pace-ness o Can also do this at the category level  Examples of things in the grocery store that not a lot of people buy, but people who buy make many purchases  Cigarettes, organic foods, baby products, pet products  What do they have in common? High margins  Can equate the k in each category to different kinds of marketing characteristics Duplication of Purchase o b x/ y , how many buyers of Y also buy X, relates to b x , approximately as: b x/ y =D b X  Remarkably constant  Brand Y doesn’t matter; only Brand X does  Those who buy X in additional to Y is just a function of X’s penetration o Example in Instant Coffee Dataset  2.8 x Brand Y’s Penetration is basically equal to the percent of Folger’s buyers who are also Brand Y’s buyers

The Long Tail 

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Chris Anderson’s Hypothesis o Back in the old days, we were held hostage by brick-and-mortar stores o Brick-and-mortar stores carried the most popular brands o Now with technology, can supply more niche brands  there is a lot of value in the tail o People who buy the long-tail content are the weird, infrequent buyers Long tail is not real! o People who buy the long-tail content are the heavy category purchasers o Role of hits is greater than it ever was before o Music industry should run like this: give the hits away for free, and look at this array of other products by the same label  Get the heavy consumers to pay for the long-tail content  Spotify (Daniel Ek) is aware of this Reference: “The Long Tail” by Chris Anderson (Why the future of business is selling less of more), “Should you Invest in the Long Tail?” (Elberse), “Blockbusters” by Elberse...