A step-by-step guide to building segment profiles

 example, segmentation  Comments Off on A step-by-step guide to building segment profiles
Jan 102018
 

Please note: This article explains how to build segment profiles using Excel – but a free segmentation tree and segment profiling Excel template is available for free download on this site along with simple video instructions on how to use.

The role of segment profiles

Segment profiles are rich and deep descriptions of a firm’s target markets. We try to include as much valid and valuable information as we can, in order to “paint a clear picture” of the typical consumer in the segment.

Once a segment profile has been developed, the firm then uses this information to help construct their marketing mix activities around the segment’s unique needs, preferences and requirements. In other words, segment profiles are the basis for forming and implementing an organization’s marketing program – as marketing decisions should be based upon the needs of a target market.

You may recall from your initial marketing studies, that the marketing concept is built around understanding the needs of consumers – that is particular target markets – and developing a marketing mix of them more effectively that meets their needs more effectively than competitors.

Please see this article on examples of segment profiles for more information.

What information do I need to develop a segment profile?

An effective segment profile requires access to consumer information. There are two ways to generate this information:

  1. The first is from the firm’s own customer database. If you use customer database information, then you can create segment profiles of your existing customers. Obviously, this approach does not give any insight into non-customers which may also be in your target market.

However, the advantage of this approach is that the firm will typically have quite detailed information quickly available, including purchase behavior and customer value and, of course, the data is already available and free to access for the firm (provided it is in a data analysis friendly structure).

  1. The second source of information for segment profiles is obtained from market research survey data. While this approach is clearly more expensive than utilizing the firms own customer database, survey data is also able to provide a profile of the typical consumer in the marketplace, whether or not they an actual customer of the firm.

This is important if the company has interest in expanding its target market or reaching consumers and do not currently deal with the company – which will be generally the case for most firms.

While market research surveys are not as precise and accurate as customer database records, particularly when it comes to purchasing behavior and history, they do allow the ability to ask additional questions and gather information that would not be typically recorded in a customer database.

Please see the article on different ways to segment the market.

Step 1: Summarize your consumer data in an Excel spreadsheet

The first step in developing detailed segment profiles is to place your data into an Excel spreadsheet. Typically we need the data to be placed into a scale as this will summarize and categorize the different consumers more effectively. For example, instead of listing a consumer’s individual age, you would code the consumer into an age group as shown in the following diagram.

You will then need to enter your data into an Excel spreadsheet with the name of the segmentation variable at the top of the column and then the information for each individual consumer listed underneath.

In my example, you can see that I’m using 10 variables to describe the consumer – starting with income, then age, all the way across to a measure of of lifestyle.

Please note that the headings that you use will relate to the aspects of the consumer information that you have available. This means that your listing of variables is most likely to be unique to your particular customer database or market research survey set.

You will also note that under each variable name there is a small triangle indicating access to a drop-down menu. This has been constructed by setting up filters on Excel once the data has been entered. This is very easy to do using the Data/Filter options menu in Excel. To set up the filter, you simply highlight all the data, then go to Data in the top menu, and then select filter in that menu.

For more information here is a link to an external site specializing in Excel (Microsoft support site).

Step 2: Construct your segmentation tree (or trees)

To construct a segmentation tree, you need to consider which of the variables (that you have access to) would make the most sense in terms of differentiating between consumers in the marketplace.

Ideally you are looking for a final set of market segments that are relatively distinct from each other.

Generally, firms will use a trial and error approach – constructing multiple segmentation trees and looking at the end market segment profiles, before finalizing their market segmentation approach. Typically firms look for a selection of variables (segmentation bases) that have some relevance to their marketing activities, brand and/or overall value proposition.

In my example, I have used three age groups and a simple measure of loyalty. As you can see, this creates six market segments. I could continue the process by adding another segmentation base, but then I would have 12 market segments. Typically large firms or brands would look at 10+ market segments, but smaller firms need to be more selective as it can become inefficient to segment the market too precisely (as quite small market segments are created).

Important note: You do not include all of your variables as segmentation bases (to construct your segmentation tree) – generally you should pick two of three relevant variables as the bases. But you will include all the variables and information when you outline the segment profiles.

Step 3: Filter your consumer data to separate each branch of your segmentation tree

In my example segmentation tree above, the first of my six segments consists of consumers aged 18-30 years, with a high level of loyalty.

Therefore, I use the built-in functionality of Excel to select those consumers only. I click on the triangle (drop down menu) and then select the relevant age codes, as shown here.

I then repeat the same process for selecting the more loyal consumers and Excel filters out all the consumers that do not match and only the consumers that fit my segmentation base are remaining on the worksheet.

I can then copy/paste that segment’s information/data to another worksheet so I can then construct the segment profile.

I simple repeat this process for all six market segments (or how many segments that you will be using) to separate each segment’s data into its own worksheet.

Step 4: Build your segment profiles

You should now have each segment’s data in a separate worksheet on your Excel file. And you can then work out the percentage of the segment’s consumers that are in each of your scaled categories, as shown in the example above.

In this case, you can see that this is the younger age group, with higher loyalty segment. I have used the built-in functionality of Excel (conditional formatting) to color code the profile to make it easier to examine. For example, this segment tends to have a good income, many come from a particular geographic location, and so on.

You will need to repeat this step for each segment and construct multiple tables like the one above.

You may want to also add graphs and even images to your final segment profiles, but your data table in Excel will be the central piece of your segment profile.

Step 5: Compare to other segments and to the average consumer

This final set in the segment profiling process is to check that your segment is distinct from the other segments and from the overall market. If this is the case, each segment profile should appear to be quite different and somewhat unique. It will also help you identity how (and perhaps why) the segments differ – which is likely to be a helpful insight into improving your marketing effectiveness.

The simplest way to examine the level of distinction between the market segment and the overall market is to simply compare the percentage differences (using our scaled data). Again we can color code the output to allow fast and efficient analysis to be undertaken.

A free Excel template for the segment profiling process

Instead of working through all these step from scratch, a free template is available for download on this site.

Related articles

Segment profile sections

Understanding segment profiles

Brand personas

Construct a Segment Profile within Minutes

 data, segmentation  Comments Off on Construct a Segment Profile within Minutes
Jan 082018
 

Building a Segment Profile

If you have consumer data, then you can create many segment profiles!

If you have access to market research survey data or a customer database, then building segment profiles are very quick and simple to do using a Excel spreadsheet. Here is a free Excel template that has been built to allow you to create segment profiles quickly and easily.

segmentation tree template

What is a Segmentation Tree?

A segmentation tree (please see relevant articles on this website) is simply splitting the overall market or customer database into segments, usually through a series of dichotomy choices.

That is, consumers with a high or low level of awareness of our brand, or older or younger consumers, and so on. The free template has the filters and comparison points already established and all you need to do is drop in your consumer data and then select which segments you want to review and the segment profile is produced automatically.

What is a Segment Profile?

A segment profile is a detailed description of a segment, or a target market, based upon all the information that we know about the segment. Segment profiles are typically constructed from rich consumer data and include a variety of demographic, geographic, behavioral and psychographic information.

Large organizations with extensive customer databases will be able to develop very rich segment profiles. Usually these segment profiles form the basis of a firm’s target market/s and issues to help further understand the market and to develop the firm’s marketing strategies.

Video on the Excel template to develop your Segment Profiles

Here is a YouTube walk-through of how to use the free Excel template to construct segment profiles, using a segmentation tree approach. This template will help you develop many segment profiles within a few minutes from the same data set.

Alternate Ways to Create Market Segment

 segmentation  Comments Off on Alternate Ways to Create Market Segment
Feb 012016
 

How can I create market segments?

There are multiple approaches to creating market segments, from simple “guesswork” to more scientific data-driven techniques. On this website you will find an article that addresses the two main market segmentation tools – namely segmentation trees and cluster analysis. But the purpose of this article is to explore the for/against of a broader selection of market segment approaches.

Main approaches to market segmentation

Let’s start by outlining the main choices you have when you need to construct market segments:

  • Using management knowledge, expertise, experience
  • Arbitrarily using segmentation bases, or some form of generic market segmentation
  • Using a segmentation tree – with or without consumer data
  • Using an internal customer database or a formal market research study
  • Visual means – using two variables only
  • Copying/modeling competitor’s approaches to forming market segments
  • Market research firm segments

Using management knowledge, expertise, experience

Utilizing existing management understanding of the marketplace is a very acceptable way of generating market segments – provided a mix of experience managers are used, and provided that the team works towards a new/different segmentation approach (as opposed to their traditional segmentation structure).

The advantages of this approach to market segmentation include:

  • It is a very fast, efficient and cost-effective approach, as it can be undertaken in a day or less,
  • It should generate “buy-in” and “ownership” from the management team, as they have created the segments,
  • The market segments are more likely to be aligned to the firm’s position and approach to marketing strategy,
  • It may leverage marketing insights gained by the team over many years of experience.

But there are also numerous disadvantages of this approach, namely:

  • There is no statistical basis (at this stage) for the formation of these market segments – so they may/may not be viable (see effective criteria for segmentation),
  • The management team is more likely to structure the segments on a fairly generic approach,  which may lack insight or competitive uniqueness.

Arbitrarily using segmentation bases

This approach to market segmentation simply involves going through the standard list of segmentation bases, and just selecting one or more bases without any real justification. A common approach here would be to segment the market on an age basis, or on a geographic location basis, or even by light/heavy users.

Please note there is nothing inherently wrong with this approach, and it is probably reasonably widely practiced in the marketing community. Certainly it is an easy, low-cost and fast approach, but can lack any underlying justification or connection to the actual market situation.

Using a segmentation tree – with or without consumer data

Segmentation trees are discussed in another article on this website. The principle of a segmentation tree is to slowly break the market into sets of consumers by applying a different segmentation base one at a time.

These can be constructed with or without consumer data. With the data, the sizes and buying potential of each market segment can be identified. Without the data, the various segments are essentially “guesswork” – however, the data may be applied at a later time to help validate the segmentation structure.

The advantages of segmentation trees are:

  • Every consumer in the marketplace is included, as the tree starts with a view of the total market
  • Usually multiple segmentation bases will be used – which is always a good approach in order to get a good understanding of each potential target market
  • The logic and construction of the market segments is clearly recorded/documented, which allows for the fine-tuning of market segments (through the reallocation of the tree’s “branches” at a later stage)
  • If the firm/brand wants to expand into another market segment, then a related “branch” on the tree is often a good option
  • Segmentation trees allow marketers to adopt a trial/error approach to initially structuring market segments

The disadvantages of segmentation trees are:

  • Not every segmentation base may be appropriate to use in this manner
  • It is possible to utilize too many segmentation bases, which can create too many small market segments

A free Excel template to help you build segmentation trees and develop segment profiles is available for download on this site.

Using an internal customer database or a formal market research study

The use of actual consumer data to form market segments is becoming more common, primarily due to the increased availability of the data. Many firms now have some form of customer database that is suitable for marketing analysis – and, likewise, many firms can now implement an online market research survey quickly and easily to capture relevant data. In fact, even marketing students undertaking assignments can also use online surveys to utilize some real data.

Cluster analysis is the statistical technique used to group consumer data points into related “clusters” – which we call market segments (essentially groups of related data points).

Cluster analysis has the advantages of:

  • Being able to sort through a large amounts of consumer data,
  • Quickly look for similarities across a range of marketing variables,
  • Quickly consider different segmentation structural approaches and the use of different bases,
  • Provides an output of segment measures for each market segment.

However, there are some limitations with its cluster analysis, which include:

  • The marketer needs to know how to interpret some of the output,
  • Unfortunately, clustering relies upon access to consumer data – and the more valuable data for segmentation – psychographic and behavioral variables – may not always be available.

Please note that I have a related website that discusses the concept of cluster analysis and provides a free Excel template  to practice clustering. Please visit Cluster Analysis for Marketing for more information.

Visual means – using two variables only

cluster analysis data set graphIf you have access to some relevant consumer data – you can plot the variables onto a scatter chart (two variables at a time) – and you should be able determine potential market segments on a visual basis.

Take this scatter graph as an example – where two variables (labeled X and Y) are plotted for each consumer (the small red squares) and the average for all the consumers is shown as the larger red circle.

You might be able to distinguish clusters (sets) of consumers – these indicate potential market segments.

Take a look at the next diagram where an attempt has been made to identify four market segments.

cluster analysis data set graph groupedThe visual approach to market segmentation is a good approach if you only want to consider two variables.

You can use Excel to create several of these charts using different variables fairly quickly. And because they are based on actual consumer data, you should be able to construct measures of each segment.

The main disadvantage with this approach is that you are limited to two marketing variables only.

 

Copying/modeling competitor’s approaches to forming market segments

Quite often aspects of a firm’s marketing strategy and its various promotional campaigns are “borrowed” from a competitor. No doubt you have seen similar TV commercials produced by different firms.

Therefore, the same approach can be used for market segmentation purposes, particularly in a situation of competitive rivalry – where the competing firms look to attack/defend each other.

It is also a good approach for a smaller firm that may not have the need to be overly sophisticated with their approach to segments – so mirroring the approach of the major players should work well for them.

However, it leads to a “me-too” situation unless the marketing strategy is somewhat unique. Therefore, this approach is a poor choice for newer firms and those players seeking to be more innovative in their practice.

Market research firm segments

The final approach to be considered is using the “standard” market segments that have been identified (and studied) by market research firms and other marketing and analytical consulting firms. An example of this – which is commonly found in marketing textbooks – is the Values and Lifestyle segmentation (VALS) approach.

“VALS segments US adults into eight distinct types—or mindsets—using a specific set of psychological traits and key demographics that drive consumer behavior.” – Please see their website for more details.

The main advantages of this approach are:

  • The segments have already been identified and tested
  • The segments are based on “true” variables that drive consumer behavior
  • There is a tremendous amount of supporting data that can be accessed

Obviously the downside of this approach is that many other firms use the same segmentation structure – so if you’re looking to a new way of thinking about the market, this is not for you.

Using Cluster Analysis for Market Segmentation

 data, segmentation  Comments Off on Using Cluster Analysis for Market Segmentation
Jan 302016
 

Introducing cluster analysis

There are multiple ways to segment a market, but one of the more precise and statistically valid approaches is to use a technique called cluster analysis. Cluster analysis is a tool that is used in lots of disciplines – not just marketing – basically anywhere there is lots of data to condense into clusters (or groups) – what we call market segments in marketing.

Let’s not be too concerned if the technique sounds too challenging – it’s actually quite straightforward and easy to understand – and you should get a lot of value from using the technique. So let’s start at the beginning – a cluster is a related set of data, things or objects. You might have heard people refer to a group of stars in the sky as a “cluster of stars” – just a group of stars that appear to sit together.

The same concept applies to the market segmentation process – in that we are trying to group consumer data (their behaviors, needs, attitudes, and so on) into related sets. And to help to undertake this grouping (clustering) process, we use cluster analysis to review and create market segments.

A simple example of how cluster analysis works

cluster analysis example 3 segmentsTo get a quick understanding of how cluster analysis works for market segmentation purposes, let’s use the two variables of “customer satisfaction” scores and a “loyalty” metric to help segment the customers on a database. Let’s assume that we have customer satisfaction (CSAT) scores of 1 to 9 (where 1 = very dissatisfied and 9 = very satisfied). And we have similar scores for the customer’s level of loyalty (1 = high switcher-low loyalty and 9 = non-switcher-high loyalty).

This graph shows this customer database information mapped onto a scatter-plot graph. The red squares represent the scores of the individual customers and the large red circle is the average score of all the customers for CSAT (average = 5.05) and loyalty (average = 5.85).

cluster analysis example 3 segments definedBut if we look closely at the plot points – for the purpose of identifying clusters (market segments), there is a suggestion of three possible inherent market segments – this is done using a rough visual basis as shown in the next chart – which the same as above, except for the addition of a top-level segmentation approach (using the extra large circles).

You should be able to see that there are three clusters (segments) of consumers suggested by the data as presented. The black circle (top-right) appears to be loyal customers, with a high level of customer satisfaction. The blue circle (bottom-left) appears to be less loyal customers, with a lower level of CSAT. This relationship is probably obvious and to be expected – and our existing marketing programs (to existing customers) are probably built around this CSAT-loyalty correlation.

However – take a look at the red circle (top-right) – this segment consists of largely unsatisfied, yet quite loyal customers. This is an interesting finding and perhaps unexpected (somewhat of a marketing insight). This is one reason why looking at different approaches to market segments is often worthwhile.

Running cluster analysis on Excel

Note: In addition to this Market Segmentation Study Guide, I have also developed Cluster Analysis for Marketing – where you can download a free Excel template for quickly and easily running cluster analysis.

With the above example – because we are only considering two variables (CSAT and loyalty) – we can attempt to segment the customer data on a visual basis as we have done above. But if we have lots more customers to graph, or if we want to consider more than two variables to create the segmentation, then we can easily use the cluster analysis Excel template (see link above) to construct the segments and produce some helpful statistical measures.

market segmentation and cluster analysisThis new graph has been automatically produced by the Excel template – you don’t need to perform any calculations or even have a good knowledge of Excel.

As you can see, the Excel spreadsheet has classified each customer data point into a market segment (e.g. blue diamonds = segment 1), and it has also calculated the center (average) for each segment. In this case, the center (average of customers) in segment 1 is 7.40 for CSAT and 6.80 for loyalty.

What is really interesting is that segment 2 (black dots/circles) actually has a higher loyalty score (7.0) average than segment 1.

market segmentation and cluster analysis graphThis template for automatically running cluster analysis will also calculate the relative segment sizes for you and produce this graph as well.

As you can see, the segment positions are the same as the previous chart, but without the individual customer data (which is helpful if you have lots of customer data to simplify).

This graph – known as a segmentation map – also includes the size of each market segment, allowing you to measure and forecast the segment and its potential.

Related websites

Cluster Analysis for Marketing

All About Perceptual Maps

Understanding Customer Lifetime Value

 

Bring Your Own Persona

 example, segmentation  Comments Off on Bring Your Own Persona
Jun 232015
 

Knoweldge@Wharton originally defined the term BYOP as “identifying new segments by their digital engagement.”

According to Wharton, this persona is based on:

  1. digital capability and
  2. trust.

Using the Wharton definition, ‘digital capability’ is a consumers’ ability to maximise their usage of the latest technologies such as mobile apps, wearables, social interaction tools, video chat, mobile payments and location-based services.

‘Trust’ is the “willingness of users to share personal data and, in some cases, relinquish privacy in exchange for a perceived benefit.”

The grid in the below article link illustrates the various types of consumer profiles based on people’s degree of digital savvy, level of trust, willingness to share data and preferred frequency of interactions.

Using this insight to segment customers goes beyond socio-demographic data, because age, income and education are no longer reliable predictors of a consumer’s digital capability.

Read the full article at : Personas Must Better Define Digital Banking Consumer

Segmentation Critical to Data Analytics on Banking Consumers

 segmentation  Comments Off on Segmentation Critical to Data Analytics on Banking Consumers
Jun 172015
 

Age and income aren’t the only ways to break down financial consumers. This study’s segmentation model reveals some interesting differences in how people think about banking and relate to their primary financial provider.Saylent commissioned a study through Informa Research Services to assess consumer and small business banking preferences and the depth of relationships they have with their financial institutions. The research findings provide key insights into how different groups prefer to interact with their bank and the products and services they desire.The study breaks down participants’ responses into four distinct segments:

Source: Segmentation Critical to Data Analytics on Banking Consumers

An Example of the Segmentation, Targeting and Positioning Process

 example, positioning, segmentation, targeting  Comments Off on An Example of the Segmentation, Targeting and Positioning Process
Feb 112015
 


A good example of the STP process (segmentation, targeting, positioning) can be found during the Cola Wars in the 1980s between Coca-Cola and Pepsi-Cola. As you may be aware, Coca-Cola eventually took the dramatic act of reformulating their flagship Coca-Cola product and withdrawing it from the market to replace it with “new” Coke.

Please review this article for further information on the background factors that resulted in the development and launch of New Coke.

During this era, where Pepsi were quite aggressive with their marketing programs, including the Pepsi Challenge taste test advertising and the “choice of a new generation” positioning, Pepsi segmented the market on a very simplistic basis, using an attitude and loyalty segmentation approach.

Pepsi segmented the market into three consumer segments only, namely:

  1. Consumers with a positive attitude to the Coke brand and 100% loyal to Coke
  2. Consumers with a positive attitude to the Pepsi brand and 100% loyal to Coke
  3. Consumers with a positive attitude to both Coke and Pepsi, with loyalty to both brands, but switching their purchases between these two brands from time to time

It is in this third market segment that the battle for market leadership in the cola market was always waged, up to the New Coke decision in 1985. This switching segment were responsive to sales promotions consisting of point-of-purchase displays, discounts, general advertising, as well as personal factors such as mood, social situation, taste preference, and so on.

Therefore, the combined promotional budgets of Coke and Pepsi – which at the time were in the vicinity of $350 million per annum (with Coke spending $200 million and Pepsi spending $150 million) – were essentially targeting the 50% of cola drinkers that would switch between the Coke and Pepsi brands. There was less expenditure, because there was less marketing return on investment, on focusing on the brand loyal customers, as they were unlikely to switch their purchase preferences.

However, following the launch of the New Coke product, Pepsi modified their target market selection that started targeting loyal Coke drinkers (approximately 25% of the market). This is because there was dissatisfaction among existing Coke drinkers that the “classic” Coca-Cola product was no longer available in the marketplace.

As a result of this shift in target market selection, Pepsi positioned their product as the main reason that Coca-Cola replaced their classic Coca-Cola with New Coke. This positioning change is demonstrated in the following two TV commercials that Pepsi ran at the time. The first shows a teenage girl who is virtually discussing a breakup scenario and is emotionally upset that Coca-Cola has changed. This positioning is consistent somewhat with Pepsi’s youth target market at the time.

However, the second TV commercial shows an older demographic of very traditional and loyal Coke drinkers. It is tapping in nicely into the dissatisfaction among Coke drinkers. This is particularly highlighted in a line in the Pepsi TV commercial where Wilbur says “they changed my Coke”. The key word here is the word “my”– which demonstrates the mood of the time that Coca-Cola belonged to the consumer market, not to the company. Following this decision, and the relaunch of “classic” Coca-Cola, Coca-Cola’s management did recognize that they were caretakers of an American icon.

You can view both of the Pepsi TV commercials at the bottom of this page.

This change in marketing strategy by Pepsi in response to the competitive action by Coke, clearly highlights the three steps of segmentation – targeting – positioning. By a change in the segmentation view, and the selection of a new target market, the company is enabled to construct a modified market positioning, which should have the effect of increasing market share.

Related topics

The positioning of Coke and Pepsi during the Cola Wars
The positioning goals of New Coke
The background factors to the New Coke decision