Friday, October 29, 2010

Trade journal paper: Twitter – the post-millennial ‘SoapBox’

This is in the October issue of Grapegrower and winemaker. Written for a "non-new media" audience.

You can get the PDF of it at

Twitter – the post-millennial ‘SoapBox’

In the August issue we introduced you to Facebook and how you might use it to promote your winery, brands and cellar door. We argued that having a Facebook profile was like having a sign in the Piazza – it’s free and it keeps you in front of the customers. It’s true.

Now the bad news.

The adults seem to be moving towards a thing called Twitter – it’s where many people get their serious news and make their “grown up” connections. The upside for you is that you can get there early be comfortable there. What we see in the marketplace is that Twitter seems to be a 30-ish and older user – people looking for specific information from specific sources about specific topics.  Will it be the driving force that Facebook appears to be, we’re not sure, but it has changed the way a growing group in the marketplace disseminate and gather communication – that being the case it is something the winery needs to investigate as what is does represent is the shift in ‘how things are being done’.  Understanding Twitter, the whole idea and philosophy of it is key in recognising and understanding what could be described as ‘the new world’!

What is it?

Using lay-technical language it is a micro-blogging website that enables social networking. It enables users to ‘tweet’ through the service in much the same way as you would send an SMS.  It is limited in characters (140) like an SMS, so the type of communication is short and sharp – easy enough to understand why they are called ‘tweets’.  So we have SMS and we had blogging sites, what is so special about Twitter that has led to so many people joining in and it changing the way information is shared and the impact it has?

SMS are sent to phone numbers, typically one at a time although there are ways to send bulk using PC software or using the services of a direct mail agency.  Those who have your number can technically send you an SMS and you have no choice if it is sent to you than to receive it.

Your own personal news source

Enter Twitter.  The web-based service sees people joining Twitter, as a whole, and then choosing who they want to receive ‘tweets’ from – in Twitterspeak this is who they  are going to ‘follow’, rather than ‘subscribe to’.  It is like choosing who you are going to listen to, changeable whenever you want.
So, Mal Chia, Melissa Westbrook, Nicola Chandler and Laurie Oakes are on our list of
‘people we follow’, as well as a business called “Leading Learning”. We’ve decided that we want these people to be part of our ‘twitter stream’ for now at least.
You may then get your own list of ‘followers’ as well. Everything that you Tweet is visible on your profile page, but it is also ‘sent’ directly to those who are following you. 
From there, there are a range of ways a person can interact. You may simply reply to a person’s tweet – a sort of public conversation. If you like somebody’s message you might “Retweet” it to your own followers (RT). Or you might privately contact them with a direct message (DM).

Why people use it

Twitter is used in an Outward and an Inward manner. 

Inward communication: viewing your “Twitterstream”

In an Inward sense it is a way for the user to select a personalised “news stream”, to follow people and topics they find interesting, or might find interesting or are ‘attached’ to.  If you like wines from Winery XYZ then you might subscribe to their tweets so you get a bit of an inside track to their operations, a closer feel to their viticulture, winemaking and cellar door functions.  If it is of interest to you, not just marketing spin (drivel) then it means something because it is part of your self defined newsfeed.  A personalised, automated tracker, that keeps a vigilant eye on the little bits of information that are of interest to you.
If you are following 10 people, then those 10 people’s Tweets appear on your page.  Simple hey!  Pointless, maybe – depending on how you begin to see the opportunities it presents and certainly until you begin to see why and how people use it.

Outward Communication - A vehicle for self expression

Hence the Soapbox analogy.  Rather than dragging your Soapbox down to Hyde Park, climbing on it and talking for those who want to hear your view, you can now activate a Twitter account and communicate (or rant) to your heart’s content.  There are more than a few users who do – but there are more than a few users that see this as the opportunity to outwardly express information that others might be interested in. Have a look at some recent tweets:
  • “I like the simple #wine label design by @fullondesign for La Linea :)”
  • “Great to see our local wine hosts in Delicious magazine! Nice work @darenberg @chapelhillwine @coriole and @wirrawirra!”
  • “Busy day in Cellar Door today. People out and about enjoying a glass of wine and the glorious sunshine - even got sunburnt..”
The winemaker might express to followers what the juice they just pumped over looks like, some quick (short) remarks about the next release barrel tasting the winemaking team has just finished.  This is interesting, for those who have subscribed to you for this type of information. You have bonded with your followers and built your brand.

How you can use it

First: Sign in, get an account!

It’s easy. You can then upload a photo and customise your twitter page. Or get your young staff to!

Second: Follow some people!

Most news organisations and TV shows, plus many wineries and individuals have a twitter included: The Gruen transfer, Yes we Canberra, Kevin Rudd MP, Turnbull Malcolm and your local radio station. After the election, or if you get bored, you might “unfollow” them. It might be interesting – or not.

Third: Write some interesting stuff!

You only have 140 characters each time. And they don’t all need to be genius. Remember you’re just letting people know you’re around. If you’re doing a promotion trip in Singapore you might just say “”Warm here in Singapore, I’m doing tastings at Denise the Wine Shop all weekend”; if you just had a great wine with dinner – tell people.

Fourth: Engage and hang on!

Getting the account and writing some stuff can be just the beginning – it’s a case of “learning as you go”.

There are ways to upload photographs and link to websites. When people are writing about a particular “trending topic” they will “hashtag” it; for example election tweets were tagged with #ausvotes. This allows a user to filter all of their tweets so they can look at all of the election posts at the one time. If you want to watch the “stream of consciousness” of the twitterverse as they watch the Australian Broadcasting Commission’s “Q and A” then filter on #qanda.

Although you might start with the Twitter website, the internet world is full of tools that can make this work better for you. If you have an iPhone or some other web phone, you can send your tweets through a mobile app, you can get your tweets to update to Facebook. The opportunities are endless.

Back to your business: what it means for you

As a premium wine brand, one of your biggest challenges is to not be forgotten. Consumers are busy too, they generally don’t lapse in buying you because they don’t like you, they just don’t remember they like you.

Twitter is a low cost way to keep in touch with a whole heap of people. A random check shows that at time of writing, Elderton Wines had 900+ followers, Bird in Hand and D’Arenberg 1100+, Chain of Ponds 400+.

These are people who have already said “I’m interested in your winery”. Why not keep in touch with them?
You are doing your followers a favour by telling them of a latest release or event, linking to your recent log post or website entry or passing on (retweeting) an interesting tweet you got from your own inwards twitterstream.

In a world where companies pay thousands of dollars in advertising trying to make contact with interested customers, surely you can take a few minutes a day to engage with your people? And you might enjoy it.

Steve Goodman is a senior lecturer in marketing and program director for Higher Degrees by Research.

Cullen Habel is a lecturer in marketing.

Both are situated at the University of Adelaide Business School. Their research involves wine choice, virtual communities and market modelling in both domestic and international wine markets.

Tuesday, October 26, 2010

Love the ones you lead

I knew I liked Malthouse. From the hard, grumpy grey haired curmudgeon that took West Coast to a couple of premierships to now, I knew I liked him. Was it because he's got grey hair that - at least I thought - was well kept, like mine? Was it because he had that Russell Crowe shortness with the media - which I'm sure I'd have if I was forced to deal with it? Is it the fact that his Paul Keating nastiness and his Allan Border grumpiness seem to be more means to an end than personality traits - as I desperately convince myself they are with me?

These are all things that endear me to Malthouse - but I think it's something else. His victory speech:

"mumble, mumble, Eddie, mumble last year next year can give it away now... they are my boys and I love them dearly"

Now that is what I think impresses me about him. He loves the people he leads. Now that's one for me. Loving the people you lead is not optional, it's a job requirement. They are counting on you to be the best you can, to care about them and to - as much as you can - do what's in both of your interests. I see it in the best of the managers I have worked with. A notable example was a team led by a guy called Rod Davis who - not coincidentally - idolised Malthouse.

I have been criticised for the way I manage people - in the very few cases I'm asked to. Too soft, care too much about how they feel. Well alrighty then. Will I get taken for a ride? Strangely less than one might think - being loved by me is not neccesarily pleasant.

As Kerry Packer was reputed to say: "I believe you offer loyalty to everyone; which is not as big a strain as it sounds because very few people pick it up".

Monday, October 25, 2010

Lecturer's best guess: Why is TATTOO PARLOUR such a tough business?

One from my great honours student - thanks David. Lecturer "fish impersonations".

I'll come at this one from the idea of managing a servicescape - in particular the social and ambient factors. We've already spoken about the challenges of running a service business with the example of skydiving; you know, intangible, insepearable, variable and perishable. Many of that applies here, but we have the added issue of the physical environment.

And remember - a tattoo shop is likely to have a range of clientele. We have witnessed a whole new set of people putting tatts on; many women, many youngs guys. So, often different people are sharing that space.

So, Mary Jo Bitner about 20 years ago started talking about the servicescape - the environment in which you deliver your service. It has quite a few elements, and there has been a lot of work done since then, but importantly the servicescape involves Ambient Factors, Social Factors and Design Factors. Let's go through them:

Ambient factors: Music, lighting, fragrance. Have we seen where tatt shops are located? At least where I come from they're in busy streets that come alive after 11pm. I also think that the different groups of customers might tend to like different types of things.

Design factors: Colour - I see black is popular, spatial layout and functionality, and signs, symbols and artifacts.

Social factors: This includes the service staff and other customers. This is probably what makes life a little tricky for a retail tattoo artist. Very different people in the same store.

Let me talk about something I know; maybe I'll have a point. Many of my biggest issues in coffee shops come from the other customers, not from the service staff themselves. Many parents who take their kids to the football have trouble with other patrons swearing too much. Perhaps the variation in customers creates an issue for tattoo artists. I heard a great artist on the radio a year ago saying ALL TYPES of people are getting body art these days, there are no limits.

So, David, you set me a toughish little gig. I don't know too much about the tattoo business; and I hate talking about things I don't know. But I do know that managing the physical environment around service delivery is a challenge, and it makes sense that it would present its issues for a tattoo artist.

Thanks to Teagan (another hons student) who is doing her thesis about servicescape in winery cellar door. She helped me with the servicescape items.

Related Posts:

Why is RUNNING A SKYDIVE OPERATION such a tough business?
Why is the video store business such a tough business?
 Lecturer's best guess: Why is LAWNMOWER CONTRACTING such a tough business?

Wednesday, October 20, 2010

Lecturer's best guess: Why is LAWNMOWER CONTRACTING such a tough business?

Remember, this is where the lecturer gets put on the spot and needs to find some textbook answer to the question. I've been coming up with the businesses so far, but a couple of my peeps have started coming in with them now.

So, why is LAWNMOWER CONTRACTING such a tough business?

I'll stay away from the obvious - at least in Australia - that the environment has changed and nobody has lawns any more, but that could've been the way. Also the fact that lawnmowing is a service product, which we discussed with reference to skydiving. No I think I'll go with Harvard Professor Michael Porter's model, from around the late 80s. (Groan)

Look, universities still teach it. And it's a nice little rule of thumb. Lawnmowing contractors work hard, have trouble getting a fair price for their work, have lots of competition - all of that. I'm not saying it's a bad business, just that it's a tough business. Here's one explanation.

Porter's 5 Forces

So, above are the five things that are thought to contribute to how tough an industry is. We can apply them to the lawnmowing business:

Industry Rivalry: So, who jockeys? Jim's jockey against VIP against Mr Clip etc on a brand level, but then individual franchisees can freely compete against other franchise's guys. Fine most franchises have territory rules, but everyone is trying to find a way around that, and then there's the whole set of unaffiliated guys with mowers (and no overheads) who'll do it for ya! That brings:

Threat of new entrants: How much do you think it would cost to start up in the lawnmowing business? Given most guys already have a mower - NOTHING! We have a term for that - low barriers to entry. We could expect that if you had to spend $1m to get into an industry, there'd be less competitors than if you had to spend $100k. So is it that big a surprise there are lots of competitors in the lawnmowing business.

Bargaining power of suppliers: I don't know enough about the cost of commercial mowers/consumables to speak on this too much. But what other raw material goes into a lawnmowing business? How about labour. Fine if you're a one man show, but as soon as you need someone else to push mowers, you're in the business of buying labour. That is you're an employer. And in Australia, the bargaining power of employees is pretty high.

Threat of substitutes: I can cut my own lawn. I can let it die. I can put artificial turf in, or green concrete. I can landscape my garden. I can just let it go overgrown.Yep, all of these help make lawnmowing a tough gig.

Bargaining power of customers: Lots of suppliers, many of them need the money to put food on the table. a relatively undifferentiated product. Customers that don't necessarily need the product right now. They have plenty of power.

So that's one of the things a textbook would say about the lawnmowing business. A lecturer's best guess.

Related posts:
Why is RUNNING A SKYDIVE OPERATION such a tough business?
Why is the video store business such a tough business?

Monday, October 18, 2010

Lecturer's best guess: Why is RUNNING A SKYDIVE OPERATION such a tough business?

Remember the game? You ask me the question (ie fill the blank) and I rack my brain for the lecturer response you'd get from the text. We all have our ways of dealing with this, and mine is "well the textbook would say...."

So: Why is RUNNING A SKYDIVE OPERATION such a tough business?

My first point. It takes guts to run a skydive operation. A little because of the risk, insurance, capital costs, challenges with demanding "regulars", but I'll base my answer on the difficulties of running a service business. In a moment. That's Greg Smith below, runs a Dropzone at Langhorne Creek.
So there's one of the parts of the business. Tandem Skydives. Pay your $450 or so, drive out to Langhorne Creek, wait a while, fifteen minutes training. Wait a little more, get in a plane climb to height - exit, freefall, canopy ride, land. Unbelievable experience.

So why's it a tough business? It's a service product isn't it? At the end of a skydive, the client has nothing to show but (the most unbelievable) feeling inside. Marketing teaches stuff about this. It think it was Parasuraman and Berry, but by the time it's been written into endless copies of Kotler (and other) books, the original reference gets lost.

Challenges of marketing a service product

As mentioned above, it's hard to say what you've left with. Some skydivers say "If you haven't done it, no explanation is possible; if you have done it, no explanation is necessary". That's all good, but it makes the selling of the product a bit hard. So you try to pin down as much as you can - speed of the climb, size of the plane, safety record. As much as you can to "crystallise" the product.

Never more apparent than when you are strapped to another male in freefall. The provider of the service cannot be seperated from the delivery. You might not like people with blue eyes - if they're your tandem master that's a bit of bad luck. So the staffing is important. A good feeling at your DZ helps; getting a great relationship between your ground staff, other jumpers, your tandem masters and your customers is what's known as "value co-creation" - a good customer becaomes a big part of a good service.

Once a day has come and gone, you never get that time again. If you have the chance to run 12 loads in a day, you need the plane to be constantly in the air. Now that's not as easy as it sounds. There's a lot of stuff that needs to be managed, Tandem Rigs to be packed, Camera guys, and their gear, scheduling the plane, customers turning up on time, or wanting to be in the same plane together. And that's even before the two main variables - wind and cloud.

Related to much of the above, a service product is difficult to keep exactly the same - every time. Yes, for a skydive procedures are very rigid but still many things have the chance to vary. Different staff from week to week, of course the weather, there's only a certain number of tandem rigs to use and they need repacking after each jump. All of these things put pressure on "the business" in its efforts to keep the product consistent. And the classical approach to quality assurance is that consistency = quality.

So a skydive operation is a tough business, but not for the reasons you might think. It's not a "cowboy" territory; and the risks of skydiving can be managed. But as a pure service product, the challenges of intangibility, inseperability, perishability and variability are many. Just as well skydiving is so. Damn. Good.

Give me something to talk about. Add something for the blank below:
Why is                                   such a tough business?

Sunday, October 17, 2010

Lecturer's Best Guess: Why is THE VIDEO STORE BUSINESS such a tough business?

Lecturer's best guess:

Textbooks often argue this is about the product lifecycle. The model argues a number of things:

§Products have a limited life.
§Product sales pass through distinct stages.
§Profits rise and fall at different stages.
§Products require different marketing, financial, manufacturing, purchasing, and human resource strategies in each stage.
  and the pretty picture look like this:
I can remember the introduction of VHS videotapes back in the 1980s. Urgh. All the rage, we thought we were so cool. You could turn your own lounge room into a cinema. Leave aside that it was our first introduction to timeshifting as well.
Man, the power was with the video hire business then. In about 1982 my memory was of these conditions for membership:

  • Membership cost $80. My inflation calculator calculates that to be roughly equivalent to $180 today.
  • If you leave, you don't get your money back. But we'll let you have a video to keep.
  • New release nightly rental was $10. That's equivalent to about $22 today. 
Video hire stores sprung up everywhere. They were a license to print money. That was the growth phase. Then for a range of reasons - but mostly new technologies - the business went into maturity and decline, really in the mid 1990s.

Guess what happens in maturity? Shakeout. Market leaders begin to dominate, price competition, mergers takovers. Lower demand, consumer power increases. All sort of things. Watch "Larry the Liquidator" in "Other People's Money" as he speaks at an AGM for the "New England Wire and Cable" company that he was planning to corporate raid.

"I bet you the last company in [that business] made the best goddam buggy whip you ever saw. Now how'd you like to have shares in that company?"

Yep. I reckon owning a video shop would suck.

The product lifecyle is a nice concept. And we can all think of exceptions. In a related vein, the demise of cinemas was incorrectly predicted using similar thoughts, as was the demise of the laundromat. In both cases, sensible repositioning reinvigorated the product area - by satisfying new needs. Come to think of it, copper wire is far from dead too. So how good IS the product lifecycle model?

NOW you're thinkin like a marketing academic.

So, that's how we play the "Lecturer's Best Guess" game.

Care to play? Perhaps enter a one word comment below, or tweet it to @CullenOfAdelaid.

Why is _________ such a tough business?

Saturday, October 16, 2010

Introducing "Lecturer's best guess"

I'll be starting a new little activity soon. I'll be calling it "Lecturer's Best Guess". It's a game I've been playing for 15 years since I first started teaching marketing in Universities. Here's how the game goes:
  • I'm full up on most of the textbook marketing theories. I'm not saying they're right, but they're there, and they don't really change that much between undergrad, postgrad and MBA courses - at least as introductory "Marketing Management/Marketing Principles" courses.
  • "The world" presents a heap of real life questions - interesting things.
  • Somebody says "so what does your marketing textbook say about that?"
  • I scramble around and try to make some sense of it, through the eyes of the textbook
So why don't we play it here on this blog. I'll tweet out the question and you can have the pleasure of watching me scramble for an answer. It's a pleasure normally reserved for MBA students.

Friday, October 15, 2010

An old Academic Paper (2003): The Pareto Effect (80:20) in Consumption of Liquor: A Preliminary Discussion

Again, don't feel you have to persevere. But it's one of my earlier papers.

Keywords: Wine Marketing, Consumer Concentration, Pareto Share, Market Modelling

Cullen Habel, Cam Rungie, Professor Larry Lockshin, Tony Spawton

Wine Marketing Research Group
School of Marketing, University of South Australia
North Terrace, Adelaide SA 5000, Australia

PDF available at:


This paper considers two performance issues for several types of alcohol – category penetration and consumer concentration. Consumer concentration is addressed using the performance measure of “Pareto Share”, which is defined as the percentage of category sales to the top 20% of its consumers. The beverage categories of beer, wine and spirits are first compared for their observed 1-week time period. The categories are then modelled, using the Negative Binomial Distribution in order to extrapolate market behaviour to longer time periods of observation – in this case a month and a year. Findings of this study are that the Pareto effect varies considerably across alcohol types and that the apparent Pareto effect increases as the sample time increases. The implications for managers are discussed and areas of further research highlighted.


Categories have heavy and light users. In the first empirical study of this phenomenon, Twedt examined four categories of “Chicago Tribune” panel data in 1968, and asked the question “How important to marketing strategy is the ‘heavy user’?” He found the “heavy half” accounted for more than 80% of the category purchases for the two categories he considered.  A question of growing importance to alcohol beverage marketers must surely be “How important are our heavy users?” We may sagely nod at the mention of a “Rule of 80:20” where the top 20% of customers account for 80% of our sales volume but do we really know anything about it? Nagging questions include:

¨      Is there 80:20 rule for wine and other alcohol beverage types, or is it simply a “rule of thumb”?
¨      What percentage of a category’s consumption is due to the consumption of the heavy user? (How does consumption data present this?)

Other questions also come to mind once we begin analysing Pareto type distributions:

¨      Does the “rule” apply to each alcohol beverage category in the same manner?
¨      Does the time period of sampling matter? Is the Pareto Effect for a week’s sample of consumer behaviour the same as a month’s or a year’s sample?

A search of the literature shows a few articles that have quantitatively addressed this question of buyer concentration ((Twedt 1968),(Schmittlein, Cooper and Morrison 1993), (Anschuetz 1997), (Rungie, Laurent and Habel 2002)) and none at all within the context of wine. Stanford (2000) has shown that wine consumers consumer multiple alcohols but does not differentiate the heavy/ light consumption concentrations.

The nature of this paper is not to describe the characteristics of heavy users. Even in the nascent field of wine consumption behaviour significant research has been conducted into that issue. Examples include (Keown and Casey 1995), (Blaylock and Blisard 1993), (Goldsmith and d'Hauteville 1998). These articles have all considered heavy users but in the sense of how heavy usage correlates to demographic, geographic and, interestingly, psychographic variables. This valuable in itself, but it differs from our research.

Our objective is more general. Many practitioners only have anecdotal evidence as to how many heavy users their categories have. Spirits marketers may think that a large amount of their volume is consumed by a relative few of their customers but have they ever demonstrated this? Wine marketers may like to think that their product has a broad appeal, so heavier users may account for less of the total consumption of wine, but how do they know?

Firstly, we aim remove some of the “hearsay” around this light/heavy user argument. Using real consumption data and modern modelling techniques, we answer the “what” question more than the “why”. What is the Pareto Effect for Wine as compared to that of Beer or Spirits? We acknowledge the existing concept of the “Pareto Effect” and define “Pareto Share” as the percentage of sales volume that is made to the top 20% of a category’s customers.

Secondly we aim to demonstrate that considering the customer base over a longer time period gives a dramatically different picture of customer concentration. Schmittlein, Cooper and Morrison (1993) first showed how buyer concentration (what we are calling “Pareto Share”) increases as we consider longer time periods. We aim to demonstrate this finding within the context of alcoholic beverages and compare the nature of that relationship for three alcohol categories.

The Negative Binomial Distribution (NBD) has been shown to often represent the category repeat purchase rate (Ehrenberg 1959). Thus the NBD will be the major modelling tool we use to consider the “what ifs” of the category consumer profile.

The paper evolves as follows: i/ We consider the reported weekly consumption data for Wine, Beer and Spirits for a population of 4800 survey respondents, fit the NBD and assess the fit of the model to the observed data. ii/ We compare the Penetration and Pareto Share across product categories. iii/ The time period of observation is extrapolated within the model to simulate the change in perspective of a senior manager from one week to one month or one year. iv/ Theoretical and managerial implications are discussed.

Pareto Share

A corollary to the unevenness in concentration that comes about from the presence of heavy and light users is the commonly quoted “Pareto Effect”. Pareto was a late 19th century Italian engineer turned economist that first developed a mathematical description for inequity in a country’s income distribution. (Persky 1992) His original empirical generalisation was later applied to areas such as statistical quality control and later to the social phenomenon of unevenness in customer concentration. (Weiner 2000)

To a marketing manager, Pareto means “80% of our sales are made to our top 20% of customers” (Buchanan 2002); (Sanders 1987). In reality, the proportion of sales to the top 20% of customers often seems closer to 60% and varies considerably, based on the time period of observation (Schmittlein, Cooper and Morrison 1993) and the market share of the brand (Rungie, Laurent and Habel 2002).

This percentage of sales to the top 20% of customers, or “Pareto Share” as we define it, appears to be a valuable tool to address the nature of product categories. It allows us to understand to what degree the heavy users of that category account for its turnover. “Pareto Share” may offer insight to brand managers as to whether to pursue increases in penetration of their brand (as per (Ehrenberg and Goodhardt 1990)) or increases in loyalty (Zeithaml, Rust and Lemon 2001) or purchase frequency (Peppers, Rogers and et al. 1999) (Baldinger and Rubinson 1997).

Most importantly, looking at Pareto Shares gives us the opportunity to compare categories – those with similar Pareto Shares are dealing with customer bases that are very similar in their behavioural loyalty to the category. That is, categories that may appear to be entirely dissimilar may have their customer bases behaving in the same sort of manner. Some early findings (Allsop 2002) show that - for example – “purchase of desserts” and “trips to the supermarket” are identical in how much volume is accounted for by the top 20% of their customers. This non-intuitive finding demonstrates the benefit of stepping back from the complexities and nuances of “what you see on the shelf” and using the tool of Pareto Share to clinically assess what your customer base is doing. 


Data Set

Survey data of approximately 4800 respondents was analysed. This was based on a quota sampling of the Australian population for the Australian Bureau of Statistics Population Monitor in 1995. Face to face interviews were taken in the house of the respondent. Whilst descriptive statistics for respondents were collected, it is the consumption statistics that will be analysed here. Respondents were asked to recall their consumption of alcohol products on a daily basis for the week prior to the interview.

Data has been recoded into weekly consumption (ml) of three alcohol types: Full Strength Beer, Wine (Comprising Red, White and Sparkling), and Spirits. The original data collection included a number of other liquor types that are not included in this analysis, namely liqueurs, fortified wines, light beers, extra light beers.

Observed Figures and Fit of the Model

We fitted the Negative Binomial Distribution to each of the categories. The NBD has a shape that will vary according to the two parameter values that are used in it. The act of fitting the distribution is a matter of determining which parameters create the shape of the NBD that most closely fits the observed data. The histograms of observed and theoretical consumption for each category were plotted on the same set of axes in order to a/ give a general picture of the category consumption behaviour and b/ indicate the fit of the model.

The first thing we see is that the theoretical figures fit the observed data quite closely. We also see that approximately 400 people consumed only one glass of wine in the week and that 200 people had only two glasses.
 Aside from the poor fit of the model it is valuable to note that the numbers of light users of the category is less than that for wine and that the “tail” to the right hand side of the graph is fatter. We will later show that this higher number of heavier users gives a higher Pareto Share.

Spirits, again, exhibits the classic J-curve of the NBD under certain parameter conditions. Clearly the NBD is working quite hard to achieve a fit and describes the category consumption quite well.

It is important to consider the beer category, in particular, with care. It is plain to see that the fit is not as firm as the other two categories. This may be because we chose not to include light beer as part of the category or simply because of the limitations of the model in being able to fit all types of consumption/purchase behaviour.

Whilst looking at histograms of category consumption is valuable for considering the fit of the model and gaining a “picture” of the category, we need to look a little closer to gain insight as to the behaviour of the customer base.

The observed and theoretical Category Penetrations and Pareto Shares for the reported week are tabulated below.

26% of the sample consumed wine in the sampled week. This was significantly above beer (20%) and spirits (13%). This may infer that wine has a more universal appeal than beer or spirits in Australia.

The observed Pareto Share for wine was also below that of both beer and spirits. That is, the top 20% of wine consumers accounted for proportionally less of the total consumption than in the case of beer or spirits. Therefore the results indicate that as well as having a broader appeal across respondents, wine appears to be drawing its consumption less from heavy users than the other two forms of liquor.

In all three cases the NBD overestimated the Pareto Share of the category. This could well be due to the exclusion of the more marginal product types for each category (fortifieds for wine, light beer for beer, liqueurs for spirits). A predominance of light users of these marginal forms would explain this consistent overestimation.

Differing Perspectives

Another factor clouding the Pareto Effect is likely to be the perspective of the observer. A sales manager with a twenty-year history is unlikely to view his customer base from the same perspective as the sales representative who started a month ago. The sales manager is likely to recall customers who simply have not purchased recently. These “once a year” customers are more likely to enter the sales managers mental sampling time and change his perspective in two ways: i/ he will see higher penetration (the people who consume at all in the period), and ii/ the heavy users (the “once a week” buyers) become a smaller percentage of the total customer base.

This intuitive phenomenon can be modeled. The longer mental period that a sales manager observes can be replicated by extrapolating the parameters of the model. Thus while we have observed a week of market behaviour and captured it in the model, we can now look beyond the observed data. If the sales manager tends to consider a twelve-month period, we can do the same thing with the help of the model.

Extrapolation to longer time periods

Schmittlein, Cooper and Morrison (1993) demonstrated that the NBD could be extrapolated to estimate the market behaviour for longer time periods beyond the observed period. observation. We decided to assess the Category Penetration and Pareto share for our three categories based on a consumption period of one month, and one year.

Category penetration over longer time periods

Firstly the category penetrations (theoreticals only) for each of the time periods are tabulated below.
This straightforward result confirms our expectation that that sales manager will perceive a greater category penetration. It shows how the “once a year” customers will appear in the mental time frame (one year) of the sales manager and increase the overall penetration.

Whilst straightforward, the result is valuable in itself, in that it allows us to examine the penetration of wine on a long term basis. That is, in a year, close to 60% of people will drink some wine, compared to around 40% for beer and 30% for spirits.

Pareto Share Over Longer Time Periods

The Pareto Shares (theoreticals only) for the three categories, over the three time periods are plotted below.

In all three cases the Pareto Share increases as the time period of observation increases. That is, if we consider wine consumption for one year, the top 20% of consumers would account for 75% of the wine consumed. Interestingly, both Beer and Spirits’ Pareto Shares were about 80% for the one-year period which for these categories and that particular time period fits the terminology of “80:20 Rule”. The variability, however, across both categories and observation periods indicates this is more of a “Rule of Thumb” than a common occurrence.


What is Pareto and why does it vary?

It seems that the “Pareto Effect” is not a clear 80:20 relationship but that it varies among categories. Whilst it is not safe to make any general rule, the Pareto Share is more likely to be around 55% to 65% and most importantly – it varies with the time period of observation.

This variation in Pareto Effect can be described using a simple example. Consider a woman aged 23, her mother and her grandmother. The 23 year old woman consumes wine about twice a week as part of her busy social life, the mother maybe once a month at family get – togethers, and the grandmother maybe once a year at special occasions.

For a sampling time of a week, the 23-year-old gets into the sample but neither of the lighter users do. The sample is then full of consumers with a purchase frequency similar to hers. When we observe for a month, the mother is captured in the sample. By that time the daughter has consumed 8 times compared to the mother’s one. Thus the concentration, or Pareto Share of the one month sample is greater than the one week. Once the sampling period is extended to a year, the Daughter, Mother and Grandmother are all in the sample, with volumes of 104, 12 and 1 respectively. By including more light users the heavier users become a smaller percentage of the customer base and the Pareto share increases.

 Is wine different?

The higher penetration of wine in Australia as demonstrated in Tables 1 and 2 may be due to the multiplicity of functions that wine performs, such as a vehicle for learning, play, cultural assimilation, socialising (Groves, Charters and Reynolds 2000). The broadness of the appeal of wine across sexes (Keown and Casey 1995) is likely to be a contributing factor at least in Australia.

At the longer time periods of observation the category penetration rates all increase, and wine’s penetration increases its lead as we consider longer time periods. Wine consumption behaviour appears quite different to that of other forms of alcohol.

The lower observed Pareto Share for wine lends support to the notion that wine is the alcohol form that is consumed in moderation. The result may support the positioning of wine as an aid to health when consumed in moderation. (Spawton and Lockshin 2002)

The extrapolation to a longer time period shows an increase in Pareto Shares. The point of interest here is the variation in the rate of increase in Pareto Shares between categories. The Pareto Share increase for spirits is much greater in the transition from one month to one year than it is from one week to one month. (See figure 1) For wine the steps up are more even. The causes for this are worthy of further investigation, but the difference in the pattern is another indicator that wine is different to other forms of alcohol.

One less reason to panic

The increase of Pareto Share over longer time periods of observation is predictable, and theoretically well substantiated. Managers need to note this in their assessment of their customer concentrations. There is a case of a senior brand manager becoming alarmed when they considered their customer concentration, to find later that they had been considering 3 year data and comparing it to one year data. This paper has clearly demonstrated that this manager could have expected his concentration to appear different.

This brand manager’s alarm could have been soothed had they calculated the limit Pareto for their brand, and understood that concentration is dependent on the time period of observation.

A measure of the category’s health?

Pareto Share is a measure of how beholden a category (in this case three alcohol beverage categories) is to their heavier users. If the wine category is seen as competing with other categories for a share of the market’s consumption (Soft Drinks 2003) it may well be argued that other forms of choice modelling techniques may be used to describe the choice behaviour. One such model is the Dirichlet (Goodhardt, Ehrenberg and Chatfield 1984), which describes the multivariate purchase rate for brands competing within a category and involves a significant amount of the NBD theory contained in this paper. Under this particular model there are a number of parameters, but only one that relates directly to the strength of that brand. Each brand what is termed its “brand alpha” parameter, which in the model is the “weapon” it takes into battle with the other brands. Increases in a customer’s propensity to buy the brand in preference to others is directly represented as an increase in this “brand alpha”. It has been shown that an increase in the brand alpha is positively associated with an increase in Pareto Share of the brand. (Rungie, Laurent and Habel 2002)

As a result of its direct relationship to brand strength, Pareto share may well be the “signpost to the wine category’s health” that we are seeking.

Limitations and further research

We acknowledge the limitations of using face-to-face interviews, and relying upon respondent memory; this may have introduced a degree of collection bias. A cross sectional data set also has its limitations, as does the collection period of a single week which did not allow for observed/theoretical comparisons over differing time periods of observation.

Further research could include observations at other time periods with varying time periods of observation. As noted previously the exclusion of fortified wines, liqueurs and light beers may well have reduced the tightness of the fit of the NBD to our three categories.

This paper dealt with consumption behaviour – another interesting consumer characteristic is purchase behaviour. A similar analysis conducted on repeat purchase panel data is likely to yield interesting results.

At brand level there are Pareto patterns that vary with market share as demonstrated in FMCG. (Rungie, Laurent and Habel 2002) The variation of Pareto Share for wine brands could be modeled using similar techniques. Considering the crowding of the wine category this would constitute an analysis at the lower ends of the market share spectrum. We find no evidence of this having been done before.


We have demonstrated how customer concentration varies between three categories of alcoholic beverage and how that concentration varies with the time horizon. As such we consider this paper a valuable replication of Scmittlein Cooper and Morrison’s 1993 work in a different context. We have introduced the terminology of “Pareto Share” and defined it as the percentage of sales made to the top 20% of customers, and demonstrated how it may serve as a guide to a category (or brand’s) health. A deeper understanding of Pareto is likely to give the industry insight as to how to grow the category, and maybe give brand managers less cause to panic when they look at their panel data.
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Friday, October 1, 2010

2009 Conference Paper - Samboy, Facebook and the Bushfires: Extreme Conditions and the Persistence of Marketing Theory.

Don't persevere if you don't want to - it gets a biit rarefied.
Samboy, Facebook and the Bushfires: Extreme Conditions and the Persistence of Marketing Theory.
Presented at the Australia, New Zealand Marketing Academy Conference 2009
Conference Proceedings HERE
Reference: Habel, C. (2009). Samboy, Facebook and the Bushfires: Extreme Conditions and the Persistence of Marketing Theory. Australia / New Zealand Marketing Academy Conference, Melbourne, Monash University.

This descriptive paper chronicles the rapid growth of a “Bushfire Support” Facebook page, where a manufacturer brand’s web campaign was appropriated by the public as a fundraiser for the Victoria bushfires of February 2009. By harnessing the goodwill of the community, the Facebook group known as “Samboy is Back - JOIN NOW TO WIN $10,000 FOR RED CROSS BUSHFIRE APPEAL” grew to five times the size of its nearest competitor.
The Bass Model is shown to provide a reasonable representation of the growth of a bushfire fundraising group with 12 hour increments. Some patterns recur in marketing despite extreme conditions and the S-curve of the Bass Model appears to be one of them.

Facebook Groups, Pages and Entities
Facebook is one of many social networking websites where members create an online profile and build a social network of online “friends” who have also created their own profile. Created in February 2004, Facebook now boasts more than 50 million users worldwide, and continues to increase its functionality to photos, video, games and competitions (Crunchbase 2008).
Facebook provides individuals and companies with a number of avenues to raise awareness for their products. Any member may open a special interest group of their own and invite other members to join. Similarly, brand owners may create a page for their product at no charge, and members of the public may choose to join as a “fan” of the brand. Group creators are constrained only by boundaries of good taste, while the creators of a brand’s page must be officially representing the brand.
Table 1 gives some examples of these mechanisms and their followings as at February 12, 2009. An entity is where a brand is presented as if it were an actual person with a Facebook account. Another variant – causes – is similar to groups and has been left out of this example.
The Diffusion of Innovations
The concept of a social diffusion process is common fare in most consumer behaviour and market analysis courses. An innovation (be it a new consumer durable, new FMCG product category, even a new idea) is expected to follow a familiar pattern of acceptance from within a population.
Rogers (1962) had established the concept of a bell-shaped period uptake curve with his typology of adopter categories, drawing on the insights of Tarde (1903). The characterisations of innovators, early adopters, early/late majority and laggards have been challenged as difficult to measure (Goldsmith and Hofacker 1991), and varying between products  (Foxall 1993), however  the simple guideline has helped establish the idea of diffusion as a process of contagion.
Bass (1969) used the premise of “Innovators” and “Imitators” in the development of a quantitative application of the Rogers model. The resultant “Bass Model” has been used as a benchmark for the period to period growth pattern of consumer durables, mostly based on yearly penetration figures.
The Bass model’s p and q parameters act as coefficients of innovation and imitation respectively.

Samboy is Back! A competition and a Relaunch
Samboy was a popular brand of potato crisp in Australia from the 1960s with a strong following throughout the 1980s and 1990s. Substantial television advertising had established Samboy with the concept “The Flavour Really Hits You”, although the most recent ad appears to have been made in 1996 (Snack Brands Australia 2009). This strong advertising presence established Samboy as somewhat of an Australian icon similar to “Vegemite”. The brand came under US control in 2002 (Via Campbell Soup/Arnott’s) and back to Australian ownership under the consortium of “Snack Brands Australia” (The Real McCoy 2008).
Despite its apparent neglect as a brand, the brand appears to enjoy high recognition and a form of latent attitudinal loyalty (Dick and Basu 1994). During 2008, Samboy’s “Atomic Tomato” variant had developed a fan base of some 3000 members on Facebook. In order to harness this latent loyalty, the relaunch strategy for the Samboy brand in February 2009 involved a Facebook competition where individuals were encouraged to open Facebook groups with the theme “Samboy is Back” and grow their group to as large a size as possible by 11.59pm on February 15.
Alone, the brand’s Facebook page had accumulated over 20,000 fans in the six weeks from Christmas 2008 to early February 2009. A series of “wall posts” carried the following tone:

“OMFG I was seriously only ranting about how angry I was the other day that they didn't make tomato Samboy chips anymore.  I'M SO GOD DAMN HAPPY!!!”
(Source: Snack Brands Australia 2009)

Snack Brands Australia had specified the prize for the largest group to be $10,000, with each of the six states of Australia allocated a prize of $1,000. The SA group, alone, had accumulated more than 2500 members by February 7, while a Victorian “Beach Party” group had accrued about 10,000. There were already the makings of an excellent awareness campaign in place.
From Beach Party to Fundraiser
By late January, there had been a gentle turn toward the competition being used as a fundraising opportunity. By Feb 4 the competition leader was raising funds for humanitarian aid in Gaza, with 10,500 members.

And then there were the bushfires.

From February 7-14, a series of bushfires occurred throughout suburban and country Victoria that brought vast amounts of human suffering and property loss. Entire communities were razed, with death toll exceeding 200 people with thousands of other people rendered homeless. Such a disaster had engendered a spirit of giving and goodwill throughout a large proportion of Australian society.
What followed was the strong growth of a dedicated bushfire appeal group, and the redirection of the “Beach Party” funds to the bushfire appeal. At the time of the competition close, there were over 250 separate groups, with a median size of 55 members. Table 2 shows the three largest groups, accounting for 66% of all members.
Table 3 shows how with 110,000 members the bushfire group had grown to be a clear winner. Even the redirection of the Beach Party fundraiser did not generate the numbers to come close and the Gaza group had shown a strong following as well. The winner’s growth rate peaked in day 2, at 36 new members per minute.
The Bass Model Applied to the Samboy Facebook Group
The period to period changes in growth rate as shown in table 3 are consistent with the S-shaped penetration curve of the Bass model. The seven days of operation of the competition are first divided into twelve hour increments, which we refer to as “daypart”. For the given number of ultimate adopters (Nbar), the basic equation for the prediction of new members in exactly period (t) is given by:

Where N(t) is the number of members that had joined up to the beginning of time t. Parameters  p and q are estimated using a least squares method and the fitted curve is given below:
Firstly, we note the time scale. It is rare for this model to be applied over such short periods, however it works quite well. Even so, the group grew more quickly, and had a longer tail than the Bass benchmark would suggest.
Finally, we reflect on the parameter estimates compared to an archive of 20th century innovations – all estimated on yearly increments. Although the time scale is compressed to 12 hour increments, the parameter estimates of .07 and .48 for innovation (p) and imitation (q) are consistent with the 30 or more categories reported in Lilien and Rangaswamy (Lilien and Rangaswamy 2002). 

Discussion and Conclusion
The Samboy relaunch campaign had already been a success from a brand management perspective, well before the Victorian bushfires. Within six weeks the viral campaign had crystallised an undercurrent of goodwill for Snack Brands Australia and stood as an excellent example of engaging their customer base with user generated content.
The tragedy of the Victorian bushfires had overlaid a “cause related” feel to the campaign, and had generated a great deal of activity. It is debatable whether or not the influx of the 80,000 extra members served to benefit Snack Brands Australia. As it was, the company and many group members needed to tread very carefully in the emotion charged days of February 2009.
Technically, a growth pattern that is normally seen over years had been compressed into a period of days. Although viral marketing is often thought of as something very new, the uptake pattern continues to adhere to one of the foundation laws of marketing, the Bass Model. Whilst this time the parameters were estimated on retrospective data, Lilien and Rangaswamy (2002) also specify an estimation method that purports to estimate group size and parameters p and q from only three observations of group growth. This offers the chance to use the Bass model in an alternative application as a predictive, forecasting tool for virtual communities. Such an analysis is beyond the scope of this paper but is worthy of further research.
Both Samboy, the Bushfires Appeal and the Gaza Appeal managed to benefit, in their own way, from a growth of a virtual community. We believe a fertile area for future research lies in measuring the “SOVC” - sense of virtual community (Blanchard 2007) within a number of these groups and examining the relationship of this SOVC to brand goodwill for commercial groups, cause goodwill for fundraising groups and importantly, any interactions between the two.


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