Market Segmentation: Psychographic + Behavioral Segmentation

8 Min. Read

The increasing costs of social advertising and the huge reduction of social organic reach, in combination with the consequences of a mobile first world, causing falling engagement and shorter time on page. 

This perfect storm has meant that eCommerce is becoming more competitive, and to counter greater competition, greater specificity in audience targeting is needed.  This is only possible through market segmentation, leveraging both psychographic and behavioral segmentation of your data to build better customer profiles.

Interpreting your data is just the first step in getting to know your customers (KYC), a path that leads to a long list of to-dos, tasks necessary to improve personalisation and win more sales.

Improving ecommerce data visualization and data analysis tools are displacing data analysts for the task of interpreting data, utilizing both predictive and prescriptive analytics. Ultimately, every Shopify store can now use driven decision making to drive sales just like the large brands.

So what exactly is market segmentation and how should it be carried out?

eCommerce Market Segmentation

What is Market Segmentation?

Market segmentation takes the entirety of your target audience and segments it into subsections based on the various types of data available.  These data types ideally would include the following:

  • Demographic data – defines the characteristics of a population. This includes age, gender and income bracket (widely, freely available via Google analytics).
  • Psychographic data – defines a persons likes, lifestyle, values, interests, beliefs and personality with the purpose of determining pain points and potential ways to motivate them towards purchase via a conversion funnel. 
  • Behavioral data – grouping customers through patterns of behavior through tracking technology, – enables store owners to understand what customers are doing on your website across all devices (also Google Analytics)
  • Geodata / geographic data – data related to location relative to position on earth over time (Google Analytics)

When the above types of data are combined it provides the means to generate more powerful customer profiles.  

Two of the four types of data, geodata and demographic data, are relatively easy to come by, and are straightforward to understand (Google Analytics data, Google Ads data, social media advertising data).  While useful, these two types of data are insufficient to build effective buyer personas.  The other two types of data mentioned above, Psychographic and behavioral data, are essential, but more difficult to obtain and interpret. 

Psychographic data is by far the most challenging to obtain and is usually only done with a specific goal in mind.  This is simply because such data is considered deeply personal and obtaining it can feel invasive for customers.  Therefore, pursuing such data too aggressively can be counter productive, especially when consent is not expressly given or when the visitor does not realize they have given consent. 

That being said, in certain use cases psychographic data is invaluable. One obvious use case would be to develop buyer personas for brand research with the goal to create a brand personality and strategy for developing brand relationships.

Store Branding + Branding Relationship

When building a brand, from the outset, psychographic data is heavily relied upon.  For example when using Jurgian Archetypes to determine the ideal customer, the brand should reflect, appeal to, and represent the ideals of the customer.  

However, archetypes are just a guideline, a crutch, not to be leaned on without further evidence. 

In order to know who to appeal to, assumptions should not be made, but rather, customers psychographic data should be collected in order to test any hypothesis related to ideal customers personality traits, beliefs or ideals.

When you consider that your branding is the fundamental backbone to your marketing efforts, used on your website, videos, pictures, products, – branding is added literally everywhere, – it is essential to get it right first time.  

While you can look to larger competitors, carrying out detailed competitor research to base your brand on, you will still need to test how your customers see your brand.  

So how do you go about collecting psychographic data for this purpose?

What is psychographic profiling?

Psychographic profiling involves collecting data that is traditionally not available elsewhere, it includes highly personal information including personality traits, values, attitudes, interests, and lifestyles of consumers.  The collected data enables psychographic segmentation, – the filtering of customer data based on these psychographic custom field data.  

This type of data can be obtained in ways including:-

  1. Survey Data, customer surveys and questionnaires either online or in-person. This could be via an SaaS tool, by email or on website. Or by phone for example.
  2. Marketing Automation – Form data with custom fields progressively collect more and more data about the customer until a complete psychographic profile is collected. The bit by bit is the secret sauce here, because a single simple question, is far less scary than a long customer survey.  These questions can be inserted anywhere, on any relevant content on your website.
  3. Paid market research – Market research firms should use scientifically rigorous data collection methods using focus groups to validate any hypothesize.
When psychographic data about your customers is collected routinely, it enables the refinement of personas, and consequently audience targeting along with the personalization of content.  

What is Psychographic Marketing?

Simply put, for the purpose of eCommerce, psychographic marketing is the use of psychographic data and psychographic segmentation to target audiences in order to persuade customers to buy. 

The goal is to provide a buying context most relevant to the website visitors, (reflect their situation) using a brand personality the buyer can identify with.  This can be achieved by displaying messaging (video, audio, text and images) that leverages psychographic data to appeal to the customer. 

This is achieved by collecting data that helps to identify pain points, and motivation, which in turn enables the seller to personalise the product, to sell it in the context of a solution to the pain point.  

While intelligent guess work can identify these pain points through trial and error, there is a big difference between knowing and guessing.  Either way, AB testing is needed to validate pain points (customers motivation) and to test the outcomes in messaging.

An Example of Psychographic Segmentation

There are examples of psychographic marketing all around us.  Large brands are well known for their psychographic marketing efforts, bohemoths such as Apple, Ikea, Dove or Audi, they all leverage psychographics to better appeal to their target audience.  They use archetypes or a combination of archetypes in their branding and communication.

What is Behavioral Segmentation

Of all the types of data, behavioral segmentation is the most useful for the purpose of market segmentation and targeting.  It is just as it sounds, behavioral segmentation creates groups individuals according to their pattern of behavior. For example, segmenting visitors by the product category they are looking at, and the products they viewed makes it easy to re-engage with highly specific offers related to those items.   That being said, his data is most valuable when combined with the other types of market segmentation data. Consider the following customer journey.

  1. A User visits blog page after searching for a solution to a problem on Google Search. From the search query we might know:-
    1. The product and potential use case of the product. From Google the person clicked on a page with a specific meta description and so, some context is available it is likely to be relevant to their interest/need/job to be done.
    2. The location of the visitor (Geodata / Geolocation data)
    3. Demographic data from Google analytics includes
      1. Age
      2. Interests
      3. Gender
      4. Device Used
      5. Time on page (indicator of interest level and level of understanding
      6. New/returning customer (therefore better understand what type of content to supply)
      7. Level of content (advanced content = greater understanding, content contains links to easier level of content )
  1. From this blog page the user clicks on a link to a product review, – from this action:-
    1. We have verification of item use case (context use case in article was valid, however the visitor could have subscribed or liked the page)
    2. The visitor knows what item he/she wants
    3. We know what other products to dynamically recommend
    4. We know the price range to target
    5. We know the item brand

The above scenario highlights that blogs (the content you create) can be a source of both psychographic data and behavioral data although it can be difficult to separate the two sometimes. Each piece of content can teach you something about the customer reading it.  

Tip: Create different streams of content, each specifically designed to teach the customer at differing levels (stages of awareness) for each of your customer personas, by doing so, you can better target them and assist them to find what they want, – faster. In the same way you can use social media to create content, (articles, polls etc) or to share your blog post to drive traffic to it via targeted advertising. 

Additionally, at any point during the customer journey we can interact with the visitor to gain additional information about their interest via live chat or by a simple popup question.  

During the entire journey the goal should be to collect behavioral and psychographic data via micro conversion points, to collect more information about the customer with every interaction.  This should be incentivized with free content or perhaps a discount on shipping or purchase value.

Top 10 Reasons to Segment Your Market

  1. To Research Market Positioning of your product.
  2. Customer Analysis (KYC) – Improve your service, know and give them what they want.
  3. To Improved Targeting and Optimization (CRO)
  4. Channel Selection – Target niche channels
  5. Improved ROA of Advertising – Higher converting content.
  6. Get higher quality leads – Know how best to help!
  7. Branding / Rebranding – customer tastes change!
  8. Finding new niche areas and audiences to target.
  9. Increase relevancy, engagement + Retention with targeted content + offers (personalisation of customer journey with targeted conversion funnels, USPs + micro-conversions)
  10. Build trust, Get Repeat Sales and Advocates.
All of these points require market segmentation, – combine data types for better personal targeting.

How to Define Customer Personas.

Using your data, define your types of customer/potential customer and segment the mix of data types that fits each customer type (persona) and specifically, ask the question what other pieces of data, not just that would be needed, but what might be useful.  Then determine the potential source of each piece of data.

If you don’t have the necessary data, ask how can it be obtained?  Part and parcel of this endeavor is understanding the implications of privacy rules and regulations.

Once you have the data, determine how best to combine it for holistic display and to accurately carry out customer analysis.

In the use case of Shopify eCommerce, Conversific can supply a holistic view of both Google Analytics and Shopify data, thereby greatly improve data visualization, interpretation and consequently assist you to make better marketing decisions.

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