An Advertising Age blog post inaccurately entitled “The Death of Customer Segmentation” (those pesky subs) argues that traditional market segmentations should be combined with “self-segmentation” techniques such as user recommendations, networking groups, opt-in alerts and consumer generated content/feedback.
The author, Michael Fassnacht, finds traditional segmentation problematic because:
- It is too static in a fast-paced society
- People can belong to different segments at different points
- Consumers want more control over their marketing activity
He believes that incorporating these self-selection elements will empower the consumer to pick the most relevant messages for themselves.
I can’t quite articulate my problems with this article but they broadly fall into three areas
1. Segmentation is not a science
Segmentation is an art. It is about interpretation. It is about tendencies. It delivers a framework; not a silver bullet of success.
Segmentation analysis is created through factor and cluster analysis. . There is no correct answer – the final solution is decided by weighing up the coherence of each cluster against the ability to manage the result (ie a twenty cluster solution will produce more coherence than a four cluster solution, but twenty targets are harder to manage than four).
Clusters are only indicative; they aren’t precise or mutually exclusive. To illustrate this, I will use my favourite segmentation example: Phones 4u.
Take “Flashing Blades”:
All these descriptions will be tendencies. Flashing Blades are more likely to be these demographics, and more likely to follow this lifestyle. Otherwise, it would be a segment of about six people, not 1.68m. So within this group there will be some women, some pensioners, some teetotallers and some pacifists.
So, those identified as “Flashing Blades” aren’t pure “Flashing Blades”. They are just closer to this target than the others. Being part of different segments isn’t an issue.
However, a lack of dynamism could be a more valid criticism. In a few situations. Some behaviour patterns change, but it is unlikely that the core of a personality will. So while I have recently changed some of my leisure habits (one reason why my link updates are on temporary hiatus) I am still fundamentally the same person and will likely approach most markets in the same way.
And a segmentation is only likely to focus in one market, despite the complex interactions between them. In that respect, a successful segmentation may be self-defeating; I may be identified as a potential but through adept targeting I become a consumer/user/fan. Does that then invalidate the model or does it mean I can move into a new segment?
In theory I can, but a segmentation model is based on interplay of variables among one group of respondents at one point in time. A template of a few “golden questions” can approximate assigning people into segments, but over time segments are the same in name only – different biases and different tendencies will become primary determinants in cluster behaviour and so the segmentation becomes gradually less insightful and the golden questions less relevant.
While a segmentation is far from perfect, introducing consumer input isn’t the answer.
2. Self-segmentation will be ignored by the majority of consumers
Fundamentally, most people just aren’t that into picking out relevant messages, despite the author’s assertion. We are going back to perspective biases.
Of Facebook’s 200m members, how many fully customise their experience and give certain activities or adverts a thumbs up? Not many, I would guess.
I don’t think I would be incorrect to posit that most see advertising as a necessary evil – we put up with it in exchange for free content. If we had the option to turn off advertising, we would, even if we view some adverts as entertaining or informative.
If this were to happen, opt-in mechanisms would then become useful – people can’t only rely on word of mouth for product information. But I can’t see this happening very soon and more importantly, does the consumer even know what they want?
3. Self-selecting tools are only of limited value
Unless you are an Amazon-esque retailer with massive size and scope, opt-in elements are going to be fairly limited. I can’t see how any meaningful segmentations can occur outside of one person choosing to positively rate one item and another person not rating it.
Even in cases where it may be appropriate, there is still going to be a disconnect between what the consumer wants and what the advertiser wants. For instance, a low income urban male may choose to find out more information about Burberry products. But Burberry want to target Kate Moss, not the Blackout Crew.
Perspective biases can also become an issue – something may improve our lives, but we cannot conceive of it and so no activity around it is registered. The consumer doesn’t always know best.
This is why observation may be the missing element. If traditional segmentation does need to be enhanced, surely behaviouaral targeting tools (I’m thinking more Audience Science than phorm) would be better suited?
Rather than as a supplement to a traditional segmentation, they could be used as a sense-check. Does real-life behaviour match our abstract targets? Again, this is only going to be relevant for certain sectors, but I see it as being far more powerful than opt-in models.
Ultimately, segmentation models are frameworks. They are not a science and they are far from perfect, but they can be useful in the short-term. In the longer term, they become more difficult to maintain (particularly in fast-evolving industries) but perhaps a degree of behavioural targeting can be used as an indicator for the continuing relevance of the segmentation. It certainly shouldn’t be reliant on consumer opinion.
This post has been incoherent even by my lofty standards, so any thoughts on segmentation would be most welcome…
Image credit: http://www.flickr.com/photos/rogerss1/