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What is customer segmentation?

Posted on: June 9, 2022
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Customer segmentation is an exercise carried out in digital marketing to understand a brand’s audience. It is one of many data analytics practices that supports both small businesses and leading companies in their marketing efforts. Data analysts are often specifically employed to carry out this work. Ultimately, if you better understand your customer base, you can communicate with them more effectively on everything from new products to special offers and promotions.

Customer segmentation takes into consideration demographic data such as age, gender, spending habits, and personal interests. Whichever customer groups an analyst looks at in their segmentation strategy will then lead to customer profiles based on where these demographics overlap. Businesses like ecommerce retailers generally have a lot of unsorted data that has accrued over the years but are unsure how to mine it for insights. A data analyst with a strong background in data science can help to organise data sets to answer queries that the client may have about their customers, while also uncovering new information that they might not have considered. 

It’s important to understand: 

  • How recent the data is
  • Where it’s coming from and how it’s being aggregated
  • How relevant the data being collected is to the business
  • Whether the data can answer the client’s questions
  • Whether the data can point to new customers

Why customer segmentation is important

It’s important for a business to segment customers so it can tailor its messaging to each identifiable group. These groups can help to define certain personas that represent particular segments, for example, women in their 40s who are high earners and prioritise health and fitness. The business can then create a marketing strategy based on the specific customer journeys of the personas rather than a one-size-fits-all approach. 

So for instance, a set of customer loyalty emails will be different for different groups based on how much they have spent. This creates a better customer experience and can retain customers rather than leading them to hit the “unsubscribe” button because they don’t find the marketing to be relevant.

Popular types of customer segmentation models include:

  • Behavioural segmentation – tracking actions and habits via feature and product use
  • Psychographic segmentation – based on personality, attitude, values, and interests
  • Values-based segmentation – analysing economic value as a group to the business
  • Technographic segmentation – use of software or app via desktop, mobile or tablet
  • Geographic segmentation – defined by town, city, or county
  • Needs-based segmentation – must-haves and needs of specific groups
  • Demographic segmentation – filtering data such as age, gender, income, education, marital status etc.

Although grouping the data tends to define different segments that share common characteristics, there is the opportunity to spot outliers. Even though these can be anomalies, they can also highlight lack of representation in certain groups and direct the business to potential customers or subsets that they had not considered.

Because social media plays such a large part in marketing and communications, demographic profiling can help with targeted marketing on various social media platforms using PPC (pay per click) ads as well as regular posts. LinkedIn, TikTok, Instagram, Facebook, YouTube, and Twitter all attract different age groups with different affinities and different behaviours. Marketing messages conveyed through each platform should be slightly different rather than duplicating posts and companies may elect not to be present on platforms that are not used by their target audience.

Market segmentation can and will change and should be reviewed with every new product development, if the business is struggling, or if the entire portfolio of products or services goes through a rebrand.

What is CRM?

CRM stands for customer relationship management. It’s an area of marketing that champions the importance of customer segmentation. Customer data is golden to CRM and CRM teams will spend time analysing and understanding who their best customers are and why. Surveys and market research may be carried out as well as close monitoring of social media to record what customers are saying and thinking about the brand publicly.

The churn rate in marketing relates to the rate that a business loses customers. This is also sometimes called attrition rate. If a business is losing customers, it’s helpful to understand where in their lifecycle they’re dropping off. This can often happen with new customers who may have received promotional offers as first-time buyers but who don’t want to pay full price for products. Maintaining them in the long-term is the challenge, especially when there are so many competitive online stores.

In values-based segmentation, the number of purchases is a prime factor in determining customer value. The ideal customer is one who spends regularly over a prolonged period. Customer lifetime value (CLV) is the predicted sum total of all profits from a particular customer. It’s not easy to calculate this figure but customer retention that offers an above average CLV is the ultimate goal of CRM. Transactional segmentation or RFM (recency, frequency, and monetary) modelling also looks at spending patterns and behaviours of customers.

There are many software options for customer segmentation, some of which integrate CRM and CMS (content management systems), and marketing activities including social media posts and emails. These include HubSpot, Experian, Qualtrics, MailChimp, and SproutSocial.

How to define customer segments

There’s no right or wrong way to define segments. The customer segmentation models provide a template and the business’ long-term goals and unique position should be taken into account when going through a segmentation process. For example, if the business wants to expand, does it need to target customers in a younger demographic? If customers are primarily based locally, how can the business reach those further afield? If there are too many one-time buyers, how does the business build loyalty beyond pricing alone?

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Could expertise in analytics and customer segmentation be your niche? Find out how you can study while you continue to work with a 100% online MSc Computer Science with Data Analytics from Keele University and apply your skills as you develop your new career.

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