Why talk of "segmentation" frightens me.

When I wish to provoke thought I often state that "there is no such thing as segments - only successful or unsuccessful products" or that "I do not believe in segmentation".

The first statement is, at best, a simplification about how I think about customers and users in relation to products, but it is a simplification that is closer to what I believe than just stating that any market can, or should, be thought of in terms of segments.  One could say that I am rounding off to the nearest significant decimal.

The second statement is largely true.  I think segmentation is counterproductive because it tends to act as a handy excuse for not succeeding in appealing to the user.  But more importantly, I think segmentation is counterproductive because the partitioning of the customer base is often not sufficiently knowledge-based.  Ask for hard numbers and more often than not, you will get the results from a poll or a focus group.  (This is so wrong I cringe at the lack of scientific validity whenever I see the results from polling).  And even when segmenting is informed by at least some data,  people don't always understand what to do with that knowledge.

By observation, not by decree.

Now, I have already admitted that "there are no segments" is not something I truthfully believe in.  But this statement is a useful stand-in for what I really believe.   Because what I really believe may be a bit trickier to understand on an intuitive level.  What I really believe is that segments can only be derived from recent observation.  There are two reasons for this.

The first reason is that merely guessing what segments there are is...well, just guessing.  Of course, there are many forms of guessing.  Some of them are cleverly disguised as science.  You can ask people what segment they are in.  You can ask questions that you think will determine what segment they are in (which might work, rarely does) or you can do what a lot of people do:  recycle random factoids from books or from the web.

Litmus test: If you have names for the segments even before you have data supporting their existence or describing their size or importance (not always the same), you are not being scientific.

(A quick comparison.  Automated news aggregation sites, like Google News, are all about automatic segmenting of news reporting.  Or "clustering" as it is called in search or machine learning nomenclature.  I forget which.  The software is not really pre-configured to know anything about any topic.  It works by ingesting a fair share of the world's newspapers and looks at significant similarities between articles to determine when new themes appear, breaking stories etc. and then clusters these articles together.  It knows nothing about, for instance, ice skating -- but if a significant event were to occur in the ice skating world, it would most likely be able to tell that "something" happened and that these articles belong together.   Even though the system had no way of knowing or anticipating anything about ice skating. These clusters come and go.  Some are short-lived, some are more persistent -- perhaps even permanent.  I see this as the same phenomenon.  Only:  I doubt that most segmentation in market research is done as dilligently)

The second reason is that segmentation changes.  While a given partitioning criterion may remain somewhat stable over shorter periods of time,  there may arise new partition criteria that are suddenly more important.  For instance, Internet access used to be rare and relevant to a small number of people.  In the west today, not having Internet access is more rare than having it used to be.  This happened relatively slowly over a decade or so, yet the advertising business and the content industry failed to catch on early enough and as a result, were late in upping their game.  There was no segment for "Internet users".  Then there was one but it was small. Then it got big.  Then it disappeared because everyone was an Internet user and those who were not...well, marketers usually don't care about cave-dwelling hippies off the grid, now do they.

To sum it up: if segmentation is to be useful it must be based on scientifically sound analysis of reality and one has to understand that it is a dynamic phenomenon and that the rate of change is usually accelerating.   Also it is important to understand that both quantitative and qualitative changes in partitioning occur. (Segmentation is, when we get down to it, a mathematical concept that has been sufficiently dumbed down to be taught in business schools.  But don't tell anyone I said that).

Which brings me to why I willfully mislead people by saying "there are no segments":  if saying so leads to people focusing on the product they want to build rather than flimsy data and naĆ­ve analysis of same,  that outcome preferable.

Besides: build a sufficiently brilliant product and it will cause observable change in segmentation.

Product first.

The last statement in the previous section also sums up why I don't think paying too much attention to segments is important.  It limits you in how you think about products and it does so in big and important ways.  Segmentation can be a tool for tweaking existing products, to eke out small incremental gains,  but it isn't a tool that is usable to innovate.  It isn't like they ran the numbers and figured out in the 1920s that "our market research says there should be a market for watches worn on our wrists".  Also there's this old chestnut:
"If I’d asked people what they wanted, they would have asked for a better horse"
(attributed to Henry Ford)
If you pre-constrain a product to fit within a given mold you may miss big opportunities.  You may constrain your creative forces to focus their energy on filling a spec rather than going back and asking fundamental questions. (This is probably why I have yet to find a garlic press that actually works:  they are all just bad copies of each other and the fundamental problem has yet to be solved).

The reason Apple revolutionized mobile phones is because they asked fundamental questions.  Not because they accepted the mold into which the incumbents hammered their products.

In retrospect most people will giggle when you show them the almost perverse degree of segmentation some mobile handset manufacturers wasted their energy on.  But just 5 years ago, the same people would probably think quietly to themselves "wow, they've really covered all the bases here" and be impressed at the diligence with which manufacturers managed to fill every niche and tweak every last bit out of their product.

There are more people thinking about products in more radical ways and with the means to actually act on their ideas at relatively low cost than before.  It would be naive to think that this has no impact on how we model and predict.  The consumer is exposed to more new ideas every year than ever before.

So when I say I don't believe in segmentation, it is because it evokes thoughts of slow, ill informed models that become irrelevant so quickly that they have limited predictive power.  But more importantly, I think they are not a good tool for ensuring nimble strategy.

The when quantitative factors go all hockey-stick it leads to qualitative changes.

(I would have liked to say something about segment size vs segment importance as well, but this blog entry is already too long and rambling so I'll save it for some other time).

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