Marketing Expert's Corner
This article written in 2006
"Give them any color they want, as long as it's black"
-- Henry Ford
In the early stages of an industry, when the key focus is making a reliable product in volume and at low cost, vendors can profitably ignore customer differences. But soon enough, along will come your own personal Sloan who uses differentiation to zap your monolithic "sell to anyone" strategy. And those pesky customers will up and leave you.
Alfred P. Sloan developed a strategy that nearly destroyed Ford in the late 20's by creating segmented product lines. Individually, GM's products wouldn't have done much damage, but collectively they were able to under-price as well as outclass anything Ford could do. Instead of the stable and monolithic designs from Ford, customers were attracted to GM's segmented brands, snazzy nameplates, and annual styling changes. Of course, 50 years later both GM and Ford became decadent and moribund (check out Halberstam's The Reckoning), but this marketing lesson from the US auto industry is timeless.
Segmentation for fun and profit
The first problem with understanding segmentation is the word "segment." The word usually means more or less similar sections -- like a piece of fruit, with fairly discernable dividing lines and patterns. But in markets, segments are often hard to discern and measure, with boundaries that are irregular or even invisible unless you've done some serious research.
Really usable market segmentation is pretty hard, so businesses tend to go with a guess. This is incredibly wasteful, and not just in the marketing arena. The wrong sales reps are hired, the wrong products are built, and the company's viability may be called into question. All because the company didn't have the right definition for the target market and customer segment.
My favorite example of bad segmentation is Volkswagen, whose CEO wanted to re-brand his company and decided to build the Phaeton: a 12-cyllinder 5.4 liter sedan weighing nearly 3 tons and costing as much as $100,000 before taxes. Thanks to branding effects, his segment was full of contradictions, so customers didn't really exist. The car sold only a few hundred units per year. Auf Wiedersehen, Herr Generaldirektor.
If there's one marketing reason why the Republicans won in the 2000-4 elections, it's because they invested millions in defining, testing, and cultivating their segments. Ask Ken Mellman, or Frank Luntz, or even Howard Dean. Segmentation is not an idle "marketing exercise" -- it provides leverage so you can get to and influence the people who will really make a difference to your results.
What kind of impact can segmentation have? For individual offers, an order of magnitude improvement. For the overall business, you'll have to settle for just a 3x increase in marketing and sales effectiveness. Segmentation works because it helps you focus on the right things.
Before we get into the "how," let's do a reality check. It's just as defocusing to have too many market segments as to not have any at all. Unless you're a giant company, it's almost impossible to effectively execute more than 3 segments for the whole business. If you're starting out, seriously develop only one segment at a time, while exploring/experimenting with one other. All too often, developing a segment is a matter of trial and error, so you have to be able to cheaply experiment for a few months to see which specific segmentation works for you.
Segmentation for Fun
A segment is a group of potential customers who have similar tastes, preferences, characteristics and buying patterns. Segments are defined by customers and behaviors, not by competitors. A segment can be defined along lots of different lines (age, income, education, geography, profession, company size...). When you have a new business with only a few customers, or you don't even have your product yet, you can only use visionary segmentation. You use theory and external data to develop your segment definition. Nothing wrong with this, but you'll almost certainly need to adjust your initial segmentation after the first few months of sales. Reality trumps hypothesis every time.
In visionary segmentation, the first place to look is your competitors: figure out what segmentation they are using, and then ask around to find out how it's working out for them. You'll never find any real numbers on their segments' performance (even from public companies), but if you discover that a competitor has recently had a lot of sales reps leave, their segmentation probably isn't worth imitating.
One reality check to do about visionary segmentation: how many competitors are vying for customers in a segment? If there are no competitors, you're either way early or have defined a non-existent market. If there are more than 10 direct competitors, you've either made the segment too general, you're way late to market, or a huge war of attrition looms.
If your product category has a "standard" segmentation used by industry analysts (like Gartner or Wall Street), you can't ignore that... but this type of segmentation will be far too generic to provide business leverage. For example, "Telecom" isn't a segment: it's an industry that is economically as large and variegated as Costa Rica.
In envisioning your segments, there are two huge mistakes to avoid. One is overestimating the customer's interest in or willingness to adopt new technologies: all too often, the crummy product they have now isn't causing that much pain. The second is jumping to the conclusion that because the customer is willing to buy, they're willing to buy from you. The only way to avoid these mistakes is to survey prospective customers and really listen.
At the very least, you can quickly figure out what segments you aren't in: what kind of people don't have a need, can't afford to solve it, are too dispersed to be accessed profitably? You can lop off huge sectors of the economy so that you don't fall into the trap of trying to sell to everyone.
Segmentation for B2B markets typically goes along these lines:
Knee-jerk: company size (e.g., $250 M-$2 B), company location (e.g., US), vertical industry (e.g., automotive and defense/aerospace). Get these data from the Department of Commerce, Lexis-Nexis, Dunn and Bradstreet, and business magazines.
Buyer technology base: users of BEA WegLogic, or IT operations people using CISCO. You can get these data from vendors and their industry analysts.
Buyer functional: by business process (e.g., bid-to-cash cycle, product development cycle), or by organizational affiliation (e.g., CFOs). Data on this can be obtained from professional groups, industry associations, and the business press.
User required qualities / attributes: for example, industrial engineers needing gasses with parts-per-billion purity, or time-domain reflectometers needing an 80 dB signal/noise ratio. These data can be hard to find, but start with professional associations like IEEE or SAE.
User behaviors / psychographics: for example, open source java developers, WiFi road-warriors, fast-track executives. Getting good data on this is hard, but you can get valuable hints from industry analysts, newsgroups, blogs, and -- of course -- competitors.
Segmentation for B2C markets typically goes along these lines:
Knee-jerk: age, sex, family status, ethnicity, education, income, state/province, and other demographics. Get these data from the Census Bureau, Department of Commerce, and trade magazines for your industry.
Consumer type: first-time user of this kind of product, occasional user, intense user, loyal user. This data is really only available from surveys and market research firms.
Consumer cohort: college students, urban twentysomethings, soccer moms, AARP members. These are related to demographics, but are defined more by whom they associate with than by just "who they are." This data is mainly gotten from analyzing community membership (like, "people who play X-box games" or "Macintosh owners.")
Values and Lifestyles: who the consumer thinks they are, what they value, how they live, and what they aspire to. This is really hard data to get, but is still some of the most valuable for the deepest marketing.
Generally speaking, the more of these axes you can use in defining a target market, the more you understand the prospective customer. The biggest mistake you can make in segmentation is to make the segment too general, too large.
Segmentation for Profit
Looking for segments is a whole lot more valuable and rewarding if you already have a bunch of prospects and customers to work with. Inductive segmentation has you look at people who are really in your market, and lets you understand much better who will be your profitable segments. This is particularly important for open source and viral marketing strategies (three links there) because you have large communities of interest that you want to monetize.
Once you have some good data, you'll need to organize it in a multidimensional database (because you can't know in advance how you want to segment). You'll probably want to get a consultant or other sharpshooter to crunch the numbers, unless you have a large enough business to justify this specialization on permanent staff.
While you're at it, look for repeating patterns in the people who didn't buy your product or service. Don't have any data on that? Better provide a monetary incentive for your sales reps to put real info into the SFA system about the ones who got away. Doing an email survey of people who lose interest is one of the highest value things a marketer can do.
The whole point of the analysis is to find the clusters of members, prospects, and customers that have consistent patterns of preferences and behaviors. So, start from the behavior you're looking for, and develop the segment definition from that. Segmenting along behavioral lines may surprise you:
Industry and company size are often not very relevant to (or highly correlated with) decision behaviors.
Geography (particularly country) and job title (particularly rank) may provide much more effective bases for segmentation.
Company personality (are they leaders or laggards, risk takers or Luddites?) and internal infrastructure (do they build vs buy, have they standardized on Oracle or SQLserver?) may also provide highly correlated behaviors.
For open source and viral marketing strategies, the individual's degree of participation may be the most relevant precursor to purchasing. If someone is constantly posting to your blog or forwarding your viral offer, they are exhibiting pre-purchase loyalty that can dramatically increase your yield. Make sure to add measurement points into all your systems that support community interaction and participation.
Using inductive segmentation, you may discover a dozen or more clusters of users...and the danger here is in creating segments that are too small to profitably pursue. You need to find a way to group them (even in unnatural ways) so that you have a manageable number of segments to pursue (3-5, tops).
Segmentation -- visionary or inductive -- is most effective with large communities. If you are working consumer markets, viral campaigns, or open source projects, segmentation can be make-or-break for your business. So get some good data on your customers, segment them, listen to what they say, and create an offering just for them: don't let yourself be Sloaned.
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