Newcomers to Britain usually notice the pervasiveness of the nation’s class system. This is a country which even has two classes of stamps! The British supermarket chains have long been a battleground of the class struggle, with some offering mainly own-label, discounted products, and others offering mainly own-label, premium-priced products! I can recall an elderly neighbour once asking me which of the several nearby supermarkets I shopped at, and then saying, “I’m so pleased!” when I gave an answer which she thought demonstrated that we were in the same social class.
Now there is news that some of the chains are heading down-market, in order to take advantage of the recession. But how to do this without losing your current market-position image, nor those customers still able and willing to pay premium prices?
Archive for the ‘Market planning’ Category
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A data architecture for spimes
Thinking some more about spimes, those product entities that exist individually in space and time. I can see they could lead to major changes in the way in which marketing data is collected, collated, stored, analyzed, and used. Clearly, individual spimes and their wranglers will generate a lot of data as they interact with the world and report back (eg, via RFID and GPS), and that data could usefully form the basis for marketing knowledge and marketing action. But the web changes everything. Spime wranglers, being intelligent human beings and companies, could comment and reflect on their interactions; the social web allows them to meet each other, across space and across time, in the same way that a houseowner can “meet” the previous or future occupants of his house. Likewise, intelligent spimes could also reflect on their interactions, and even wrangle less-intelligent spimes.
What software architecture is appropriate for this mass of data? Clearly, we’d want to store all the data, regardless of its format, in databases. My question is pitched at a higher level of abstraction than that of the databases. We desire that multiple, independent agents (both people and devices) are able to access the data, to read it and contribute to it, and maybe to over-write it (assuming they have the appropriate authorizations). Moreover, we want to be able to combine and reason-across the data generated by one spime, say a particular motor vehicle, with that of other spimes — say, other vehicles of the same model, or other vehicles owned by the same person, or other vehicles purchased in the same year, etc. We’d also like to combine and reason-across the data generated by spimes in different product categories — all the durables purchased by the Smith family in their life, for instance, or all the products purchased in Main Street, Anytown, last week.
An obvious data architecture for multiple, independent reading- and writing-entities is a blackboard. A blackboard architecture is a shared memory space which enables agents sending and receiving messages to be decoupled from one another, both spatially and temporally. Exactly as a blackboard does, messages left on the blackboard are stored until they are erased, and so the long-dead can communicate to the living, who can in turn communicate to the not-yet-born. Tuple spaces and the associated Linda language are an example of a blackboard architecture (implemented in Java as Java Spaces). We could imagine that each spime has its own tuple space, partitioned into secure sub-spaces for different spime-wranglers, from manufacturers, through each spime owner or carer, to after-sales service providers and disposal agencies. Access to spaces will need to be controlled, so that only authorized agents may write, read and erase data in their allocated partition. Here we could use something called Law-Governed Linda, an enhancement of Linda designed to add security features, although this may be too rigid for products whose uses cannot be readily predicted in advance. An architecture allowing access to a tuple space following an appropriate dialogue between the relevant agents may be more flexible.
So far, so good for the data storage and access. But spimes and spime wranglers will generate enormous quantities of data, and analyzing all this data will require some effort. Better then, to plan for this effort and automate as much of the data collation, aggregation, processing and analysis. Here, I suggest we should use so-called Tuple Centres, which are intelligent Tuple Spaces, able to reason over the data they hold. Because we will want to combine and analyze data arising from different spimes, these tuple centres will need to communicate with one another, and agree (or not) to allow their data to be aggregated. A multi-agent system (MAS) with agents representing each spime-space (ie, the tuple space of each spime), and, for many spimes, each partition of each spime-space, seems the most effective architecture. This is because the interests of the relevant stakeholders (spime-wranglers, marketing departments, manufacturers and service providers, data protection agencies, the state, the law) will vary and a MAS is the most effective way to formally represent and accommodate these diverse interests in a software system.
There are many details still be worked for this architecture. But even at this level, it is clear that the traditional marketing data warehouse architecture is not sophisticated enough for what is needed for spimes. Hence, my statement above that spimes could lead to major changes in the way in which marketing data is collected, collated, stored and analyzed. Use of spime data I will leave for another post.
References:
TuCSon, developed at the University of Bologna, Italy, is a platform which enables fast implementation of tuple centre applications.
The resonance of spimes
In 2004, Bruce Sterling coined the term “spime” for an object which tracked its own history and its own interactions with the world (using, for example, technologies such as RFID and GPS). In Sterling’s words, spimes
“are precisely located in space and time. They have histories. They are recorded, tracked, inventoried, and always associated with a story.
Spimes have identities, they are protagonists of a documented process.”
Spime wranglers are people willing to invest time and effort in managing the meta-data and narratives of their spimes. The always-interesting Russell Davies has been exploring the consequences of this idea for designers of commercial products.
Several thoughts have occured to me:
As with all new technologies, the future is unevenly distributed, and there have been spime wranglers for some artefacts for a very long time — for instance, for early industrial manufacturing technologies (eg, the 1785 Boulton and Watt steam engine (a diagram of which is above), in use for 102 years, and then immediately shipped by an alert wrangler to a museum in Australia in 1888) and for Stradivarius violins. The service log books of motor vehicles, legally required in most western countries, are a pre-computer version of the metadata and narrative which a spime and its wranglers can generate.
Secondly, spime wranglers, like lead-users, become co-designers and co-marketers of the product, because they help to vest the product with meaning-in-the-world. Grant McCracken has written on the trend to greater democratization of meaning-creation in marketing. (Note: I’ll try to find a specific post of Grant’s on this topic.)
Finally, it strikes me that the best way to conceive of the narrative and metadata generated and collated by a spime and, working with it, by the spime’s wranglers is through Rupert Sheldrake’s powerful (and sadly neglected) idea of morphic fields. I hope to explore this idea, and its implications for quantitative marketing, in a future post.
Run-time marketing
Although mobile communications (mocoms) began primarily as a service for business users and rich individuals, for over a decade mocoms have attracted a mass consumer audience. Perhaps for this reason, it is often the case that mocoms marketing folk have cut their baby teeth in the fmcg sector — those consumer goods that move off the shelves so fast that only a short, unpronounceable acronym with all the vowels deleted to save time would keep up with them. But there are many differences between telecommunications and other consumer products and services, and, despite having pre-cut teeth, these imports don’t always cut the mustard.
We have long tried to identify these differences, and the key difference seems to be the time at which the product is created. If you sell chocolate bars, you make them in a factory, deliver them to a store, and sell them to consumer. The product is created before it leaves the factory door. If you sell draught beer, the product is partly created before it leaves the factory (that would be the “beer” part of “draught beer”), but also partly created at the time the service is purchased (the “draught” part). So a publican who waters down the beer he or she sells will alter the quality experienced by the end-user.
But telecoms services are not created beforehand, and they are not even created at the time of purchase; instead, they are created at the time of use. Provision of a network and its level of quality are created and re-created each and every customer call, and not even just once per call, but repeatedly throughout a call. As a cellular phone user moves around during a call, for instance, his or her call will be routed through different cells, and these may vary widely in quality of service — for example, due to the presence or absence of other, simultaneous users in each cell. This is quality of service generated on-the-fly, at runtime, to use some computer-speak. And, as with all marketing, perceptions matter far more than reality: if customers expect a network to be congested they may be more accepting of quality of service problems than if they’ve been led to think they will be the only users of it.
Lots of fmcg folks don’t see the difference with their prior world. Marketing can’t simply order the folks in the factory to ensure good quality product, and then sit back, gin and tonics in hand, to commission a few TV spots. Instead, Marketing has to ensure that customer expectations are set and re-set realistically to match the quality of service being generated by Engineering as the network operates. For new networks, add, “and as the network rolls out”. Marketing have to monitor customer expectations and perception of network quality and compare with actual network quality in real-time, and adjust campaign tactics as they do so. Marketing, too, has to be generated, on-the-fly. It’s a lot harder than selling candy.
The network is the consumer
Economists use the term network good to refer to a product or service where one user’s utility depends, at least partly, on the utility received by other users. A fax machine is an example, since being the sole owner of fax is of little value to anyone; only when others in your business network also own fax machines does owning one provide value to you. Thus, a rational consumer would determine his or her preferences for such a good only AFTER learning the preferences of others. This runs counter to the standard model of decisions in economic decision theory, where consumers come to a purchase decision with their preferences pre-installed; for network goods, the preferences of rational consumers are formed instead in the course of the decision process itself, not determined beforehand. Preferences are emergent phenomena, in the jargon of complex systems.
What I find interesting as a marketer is that ALL products and services have a network-good component. Even so-called commodities, such as natural resources or telecommunications bandwidth, can be subject to fashion and peer-group pressure in their demand. You can’t get fired for buying IBM, was the old saying. Sellers of so-called commodities such as coal or bauxite know that the buyers make their decisions, at least in part, on the basis of what other large buyers are deciding. Lest any mainstream economist reading this disparage such consumer behaviour, note that in an environment of great uncertainty or instability, it can be perfectly rational to follow the crowd when making purchase decisions, since a group may have access to information that any one buyer does not know. If you are buying coal from Australia for your steel plant in Japan, and you learn that your competitors are switching to buying coal from Brazil, then there could be good reasons for this; as they are your competitors, it may be difficult for you to discover what these good reasons are, and so imitation may be your most rational strategic response.
For any product and service with a network component, even the humblest, there are deep implications for marketing strategies and tactics. For example, advertising may not merely provide information to potential consumers about the product and its features. It can also assist potential consumers to infer the likely preferences of other consumers, and so to determine their own preferences. If an advertisement appeals to people like me, or people to whom I aspire to be like, then I can infer from this that those other people are likely to prefer the product being advertized, and thus I can determine my own preferences for it. Similarly, if the advertisement appeals to people I don’t aspire to be like, then I can infer from this that I won’t be subject to peer pressure or fashion trends, and can determine my preferences accordingly.
For several decades, the prevailing social paradigm to describe modern, western society has been that of The Information Society, and so, for example, advertising has been seen by many people primarily as a form of information transmission. But, in my opinion, we in the west are entering an era where a different prevailing paradigm is appropriate, perhaps best called The Joint-Action Society; advertising then is also assisting consumers to co-ordinate their preferences and their decisions. I’ll talk more about the Joint-Action Society in a future post.
Method marketing
Method acting (aka “The Method”) is an approach to acting in which the actor tries to recreate and inhabit the emotional and psychological world of the person he or she is portraying. The approach was originally created by the Russian theatre director Constantin Stanislavksi, and is premised on the actor not merely “acting”, but “being” the character. If done successfully, the method can lead to great authenticity in performance.
But not everyone accepts this approach. There is a wonderful story of method actor Montgomery Clift, pictured here, on the set of Alfred Hitchcock’s 1953 film, I Confess, being asked by the director to stand by a window so that the cameraman could take a quick external shot of him looking through the window. Clift asked what his character would be thinking as he looked out the window. Hitchcock replied, Who the hell cares!, or words to that effect. The two argued, with Clift thinking that motivation and character was all, while Hitchcock just wanted his picture finished. (Hitchcock also greatly preferred actors who left all the thinking to him, and so it is not surprising that he and Clift never worked together again.)
I believe the same authentic empathy is required for good marketing, and marketers have to fully inhabit the world of their target customers. If the target customers are the same social class or ethnic group as the marketers themselves, then such Method Marketing probably comes without awareness — marketers are selling to people like themselves. But often marketers are not themselves part of the target audience, and have to struggle to understand their customers and their environments profoundly. Global companies that do this well, such as Unilever, are often thought by others to have “gone native”, allowing local managers great autonomy. Local autonomy, of course, does not guarantee empathy with local customers, but it certainly is necessary.
A situation I have experienced several times is a company from a developed country launching a subsidiary in a developing market. The latest marketing technology is deployed, including customer database systems and marketing data warehouses, to support customer profiling, friends and family programs, affinity marketing, the whole shebang. All this advanced technology requires air-conditioned offices and needs people with advanced skills to deploy and operate. Even if these people are local (and many are), they too sit in the air-con offices in the downtown skyscrapers in the capital city. An environment less like that of the target customers is hard to imagine. Although local marketers, usually with relatives in the villages, the kampongs and the favelas, will quickly realize the authenticity challenges here, they often have a hard time persuading their western-world masters that a problem exists.
The strangest example I ever witnessed was a long-winded discussion in a start-up mobile phone company in a developing country in Asia about whether to bill calls by the second or by the minute. The intended target market were people living in rural towns and villages. No one in the room seemed to appreciate that most of the target customers did not wear watches.
The post-modern corporation
Anyone who has done any strategic planning or written a business case knows that planning requires one to forecast the future. If you want to assess the financial viability of some new product or company, you need to make an estimate of the likely revenues of the company, and this requires making a prognosis of the level and nature of demand for whatever it is the company plans to provide. “Taking a view on the future” is what the M&A people call this.
The problem is that the future is uncertain and different people may have different views of it. There are usually many possible views one could take, and stakeholders are not always able to agree on which is the most likely. Financial planners typically deal with this uncertainty by developing a small number of scenarios: often called a best case, an average case, and a worst case. These scenarios are very rarely ever the actual “best” or the actual “worst” that the planners could conceive. More typically, they are the best or worst “plausible” cases. Similarly, the middle case may not be average in any sense of the word, but simply a case the planners happen to favour that is somewhere between the best and worst. Often the average case is the best the planners think they can get away with, and they contrast this with an outlandish upside and a still-profitable downside. As with other human utterances (eg, speeches and published papers), effective business planners take into account the views of their likely audience(s) when preparing a business plan.
For telecommunications companies operating in a regulated environment, there is a further wrinkle: the fifth “P” of telecoms marketing, Permission. To gain regulatory approval or an operating licence for a new service, telcos in many countries need to make a business case to the regulatory agency. Here, the regulators may have their own views of the future. Quite often, governments and regulators, especially those in less developed countries, feel they are behind in technology and believe that their country has a vast, untapped market ready for the taking. Sometimes, governments have public policy or even party-political reasons for promoting a certain technology, and they want the benefits to be realized as quickly as possible. For these and other reasons, governments and regulators often have much more optimistic views of likely demand than do the companies on the ground.
Thus, we have the situation where a company may prepare different business plans for different stakeholders, each plan encoding a different view of the future: an optimistic plan for the regulator, a parsimonious plan for a distribution partner and yet another for internal use. Indeed, there may be different views of the future and thus different plans for different internal audiences also, for reasons I will explain in my next post. Living with uncertainty, the post-modern corporation treats its view of the future as completely malleable — something which can be constructed and re-constructed as often as occasion or audience demands.
In my next post, I’ll talk about the challenges of planning with multiple views of the future, and give some examples.
Reference: This post was inspired by Grant McCracken’s recent post on Assumption-Hunting.