They called them “Soccer Moms” because they were North American middle-class suburban woman who spent a significant amount of their time transporting their school-age children to their youth sporting events or other activities.Intense media interest stemmed from the media’s belief that soccer moms had become the most sought-after group of swing voters in the 1996 elections. In the end, suburban women favored Clinton by 53 to 39. Categorizing just people without looking at their “behaviors” like political party affiliation, family party affiliation, group membership and previous voting behavior determined caused a major debacle in the prediction.
Not just in elections this is even done in the day to day marketing of products.
Yes, gone are the days when a customer was identified as: married, has children, lives in an upscale neighborhood, reads Time magazine and wears a Rolex. Now, customer profile entail aspects such as no. of daily customer visits to the site for the last two months, items purchased by the customer in the last one week etc.
Let us start giving names to the types of customer profiles. Identifying a customer by their attributes is called as “Demographics Segmentation”; to be precise, demographic segmentation consists of dividing the market into groups based on variables such as age, gender, family size, income, occupation, education, religion, race and nationality, whereas identifying customers by their behavior is behavioral segmentation.
Demographic segmentation is simpler because of the ease with which data is available but in reality has it solved the problem? Not really no. Researches back from 1960 show that demographic variables play only a remote proxy role for identifying differences in buying styles and decision processes. Behavioral segmentation, on the other hand, gives a better hit rate by taking into account the occasion, benefits the customers sought, user rate, user status, loyalty status and buyer readiness while formulating a marketing communication.
For example, let us compare two people, Rohit and Raghav. Rohit is a Gen Y bachelor living in a posh neighborhood with a Social grade B (Intermediate managerial, administrative) and with a lifestyle of a mainstreamer. Fortunately or Unfortunately, Raghav also has almost the same characteristics of Rohit. And this for a fact would force and push a marketer to go and sell a product of the same segment, let us say in this case an advanced smartphone. But, what is the proof that Raghav would buy what Rohit buys?
In most cases, both might not end up buying the same product though they might belong to the same neighborhood, same age group, sex, income group, social class and life style. Because, Raghav, “behaviorally” might want his phone for business purposes, so he might not choose a different brand. Or Rohit might choose to buy it during a festive season while Raghav might not wait for the event to happen. Or Raghav might generally be a highly loyal customer to any brand he buys and therefore he would end up buying a same brand which he currently has. Isn’t that true?
Yes, these are quintessential facts about customers that need to be leveraged for selling a product which you wouldn’t otherwise use if you are just looking at the demographic variables.
But does that mean, demographic segmentation which we have been doing since time immemorial is not good? Demographic variables do explain broad behaviors but they play a weak role in explaining brand preference, product purchasing, innovation, adoption, Channel-use and technology uptake and that can be attributed to the evolution of the world in broader terms.
To be particular, customers nowadays are more individualistic, market literate and are influenced by channels of convenience and therefore to run a successful marketing campaign with a better return on investment, it is just not enough to stop with demographic segmentation. Data Analytics plays as a major enabler for this targeted marketing and without which these will only remain as valuable information without insight or impact.
At BRIDGEi2i, we have worked with a multinational corporation that uses direct response infomercials and multilevel marketing to sell fitness products and helped them understand different customer behavior patterns and group all customers having homogeneous behavior for efficient targeted marketing. At the end of the project, we were able to profile people into different groups which were obtained after analysis of the behavior of the group. We were able to recommended new products for “Recent, regular, high valued customers” and active lucrative promotions for “Old, onetime, low valued customers”, which done otherwise would not have delivered desired results. Behavioral segmentation is the way to go in this new era of diverse customer preferences.
If you have an alternate viewpoint, please drop a comment!
This blog is written by Alagiri Samy, Analytics Consultant at BRIDGEi2i
About BRIDGEi2i: BRIDGEi2i provides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. Our analytics services and technology solutions enable business managers to consume more meaningful information from big data, generate actionable insights from complex business problems and make data driven decisions across pan-enterprise processes to create sustainable business impact. To know more visit www.bridgei2i.com
The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.