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13 Cards in this Set
- Front
- Back
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What is repeat buying? |
When a consumer buys an item more than once in a given time period. The average purchase frequency can be considered a measure of repeat-buying for a specific time period "The incidence of repeat-purchases from one time-period to another" Less than 100% repeat buying is the norm. period-by-period repeat buying is fairly low but much the same for the various brands |
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What near stationary markets? |
When many established brand and categories show little change in the medium term even though: Over several years there may be a trend (e.g. Holdens gains over Ford) Over a few weeks promotions may change sales alot. This stationarity occurs because customers are habitual and any customer defections are typically matched by aqusitions |
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Draw and explain the layout of the Dirichlet Model |
In stationary markets, the NBD predicts single brand data and the Dirichlet model predicts data on all brands in a category |
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Explain the Negative Binomial Distribution (NBD) and its two distributions |
In the NBD, each brand has the same distribution of customers. Most buyers buy infrequently
Gamma = weight of purchases (i.e. how often or how much). Lots of light buyers, few heavy buyers The proportion of people who are going to buy at least once, twice ect. Almost always fits
Poisson = The timing of these buyers (regularity in which people buy) timing is irregular but still predictable |
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Explain Zero-Order and First-Order effects |
Zero-Order - there is no order in the allocation of purchases across the brands; the chance to purchase a brand is determined by how many time the brand has been purchased in the past. Shuffling within a repertoire. Past purchases has no effect on future, but the combination of them does.
First-Order - there is some order in the allocation of purchases across brands; there is a higher probability to purchase again the last brand that was bought. What I buy today, I will probably buy tomorrow. |
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Explain the Gamma Distribution |
There are lots of non buyers and light buyers, but few heavy buyers. |
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Do light buyers matter? |
Light buyers still manage to account for a lot of your sales - simply because there are so many of them. Many of your customers are light because buyers buy from other brands, and because light buyers are the norm for the category too |
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What is the heavy half rule? |
The top (heavy) 20% of customers generate about 50% of your sales The other 50% of your sales comes from the of 80% who are light buyers.
This concentration is slight less for larger brands. They have more heavy buyers, but they account for a smaller % of their sales. Growth comes from light buyers. |
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Do Non-customers matter? |
Yes. Just because someone did not buy your brand this period doesn't mean they won't nest period |
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How many buyer should we have in a month, quarter or year? |
If you know how many you had in a period, the NBD can be used to predict the amount for any other period.
Or NBD can predict penetration for any period based on the brands market share and the category buying rate |
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How many buyers will have just bought once? How many will be repeat buyers? |
NBD can be used to predict the number of buyers (penetration) and how many will buy more than once. |
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What will be the ratio of heavy to light buyers? |
This is simple to calculate from the predicted distribution of buying rates. Note: it varies over time. one long time periods you will have more light buyers. |
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Most repeat purchase markets can be described as stationary in the medium term. What does this mean and how do we know this is the case? What are the implications for managers? |
At the category and brand level, market share doesn't change much. We know this because it is an empirical generalisation. Marketing activity does little to influence performance over this period
Stationary market occur because customers are habitual and any customer defections are typically matched by acquisitions. |
