Customer Satisfaction Survey: Is it too soon?

Every good customer survey should be utilized with proper timing. This is a critical factor which ultimately determines how effective your survey is. The issue of timing should include both when to do it and how often, as well.

In reality, you should be committed to gaining an understanding of what your customers think about your products and services. You should be excited to get insight into what to adapt in order to get more customer satisfaction. However, presenting a customer survey too soon is like a half-baked cake. Continue reading

4 Main Types of Segmentation in Market Research Analysis

Segmentation is the process of dividing potential markets or consumers into specific groups.  Market research analysis using segmentation is a basic component of any marketing effort. It provides a basis upon which business decision makers maximize profitability by focusing their company’s efforts and resources on those market segments most favorable to their goals.

There are four main types of segmentation used in market research analysis: a priori, usage, attitudinal and need.

a priori (most commonly used)

a priori is defined as relating to knowledge that proceeds from theoretical deduction rather than from observation or experience. For purposes of market research analysis this means making certain assumptions about different groups that are generally accepted as pertaining to that group.  For example, deducing that adults over 50 are not as tech savvy as twenty somethings is a safe assumption based on the reasoning that high tech devices were not as widely available to the older generation than they are to the younger. However, be careful to check your assumptions since they can change over time. In 30 years, that statement may no longer be true.

Usage Segmentation (also used frequently)

Usage segmentation is completed either by decile or pereto analysis. The former splits the groups into ten equal parts and the latter distributes according to the top 20% and the remaining 80%. Usage segmentation helps to drill down more deeply then a priori because it indicates which priori group is the heaviest user of your product.

Attitudinal (Cluster analysis)

Using cluster analysis to create customer psychological profiles is difficult because it is limited by the input data used.  Demographic data is the least helpful, whereas preference data (scaling) is better suited toward this type of analysis.

However, once a usage segmentation is created, it’s exceptionally helpful to know the motivating factors behind the purchasing decisions of the heaviest users of your product.

Needs Based Segmentation

Needs based segmentation is the concept that the market can be divided based on customer need.  This type of analysis is used to develop products that sell rather than trying to sell products a business developed.

Needs based segmentation uses conjoint analysis to separate the groups according to functional performance.  Using cluster analysis, it’s goal is to determine the driving forces behind the performance data.

Knowing which segmentation to use is often as critical as the analysis itself because it is driven by cost and the stated business goals of the decision makers.

Is Customer Segmentation Analysis still relevant?

Today, it is possible, certainly in a telecommunications, banking, retail or other online environment, to collect a vast amount of information about your customers. The question is, what sort of survey analysis to apply to it. Additionally, is customer profiling and segmentation still a good approach to organizing this data and to then interacting with groups of customers?

Of course, there are many approaches to using your accumulated data, some of which may be better than segmentation in delivering sales or marketing returns, or improving other areas of customer relationship management.

Nowadays, companies such as Amazon, tailor their advertising to individuals searching for books online: a technique known as ‘mass personalization’.  And for many companies, this approach is gaining more emphasis than traditional techniques.

Amazon is frequently cited as an example of good personalization.  As an on-line retailer, they are well positioned to take advantage of such techniques, but there are remarkably few good examples of mass personalization in an off-line environment (I do not remember any direct mail in my mail-box, for example, which gave me the feeling that I was very targeted).

The truth is, a lot of the time, companies sit on a goldmine of information and fail to exploit the opportunities for powerful communications with their customer base, or the opportunity to create highly desirable products and services based on the information they have available.
Profiling and customer segmentation do work – the problem is, a lot of companies don’t use them effectively and so end up seeking the next big thing.

Personally, I do not believe that companies will totally move from a segmentation based approach to a mass personalization approach right away, but it is true that the targeting power that can be gained by combining traditional segmentation analysis (based on large volumes of historical data), with the real-time analysis of what a customer is doing on the Internet, plus where they are located (when they are using the Mobile Internet) cannot be under-estimated.

So it seems that both traditional segmentation and the newer mass personalization methodologies may have their benefits and while, for some companies customer segmentation may no longer be required, I feel safe in the knowledge that for many, it is still a valuable tool and one that will remain relevant for quite some time.

PAI would welcome the opportunity to demonstrate how PAI’s mTAB™ service can help you to establish and analyze your own customer segmentation of the marketplace.  Please visit the PAI Website to learn more about us, or to schedule a no-obligation demonstration.