Understanding customer segmentation
Getting to know your target audience intimately is key to good marketing and successful sales strategies. One of the problems that many businesses face is feeling forced to use marketing messaging that will appeal to everyone but ends up speaking to no one because it is too broad. Customer segmentation is the solution to this problem as it allows you to target specific groups of existing or potential customers.
What is customer segmentation?
Customer segmentation is the act of organising customers based on a shared set of characteristics and behaviours. It offers retailers the opportunity to market to specific groupings of customers in the most effective way and relevant way.
Benefits of customer segmentation include:
- Being able to do targeted marketing strategies and messaging for specific segments
- Helps to personalise the customer journey
- Better understanding of your customers to harness brand loyalty
- Can be used to manage resources by focusing on the most lucrative segments
- Inform decisions on enhancing your products
- Choosing the right channels to target specific segments
- Uncovering new opportunities as you explore your segments
What are the main types of customer segments?
Deciding what type of segments you should focus on will be largely determined by the data that you are able to access. This data may be captured through customers making orders, signing up to subscriptions, activity on site, surveys, market research and many other data sources.
The main types of customer segments include:
- Demographics (age, gender, marital status)
- Geography (Country, city, town)
- Psychographic (personality, attitudes, values and interests)
- Technographic (mobile/desktop use, apps, software)
- Behavioural (Frequent actions, purchasing history)
- Needs based (pain points or problems usually identified through market research)
- Value based segmentation (economic value)
How to segment customers on Shopify
There are a number of approaches that can be taken to customer segmentation such as basing it off of lifetime value, RFM (Recency, Frequency and Monetary), customer longevity, etc.
An example of a customer segment would be any customers that have placed more than 5 orders with you that also have an average spend of over €50.
Shopify’s Updated Segmentation
In March of 2022, Shopify rehauled their prior customer segmentation interface. The ‘saved searches’ feature that was previously used has now been migrated to a more advanced customer segmentation panel.
Filters are the means by which customers are identified in a given segment. They consist of a:
- Filter Name
The filter name is a unique identifier for a filter. The complete filter list can be found in Shopify’s documentation or by clicking the filter icon in the top right corner of the customer segment panel.
Additionally, you can create filter names from metafields.
The operator is a character that represents an action e.g. “=” is used to highlight that the filter name must be equal to the following value.
Lastly, the value can be factual (a number being used to identify a specific order value) or inferred (predictive spending tier).
To put it all together, using a portion of the example above, we have “abandoned_checkout_date >= 30_days_ago”
- Filter Name: abandoned_checkout_date
- Operator: >=
- Value: 30_days_ago
- Result: This segment will pull all customers that abandoned the checkout process more than 30 days ago.
Lastly, we may want to link a series of filters. This can be done by using “AND” or “OR”.
- Using AND between filters will create a segment that satisfies both filters.
- Using OR between filters will create a segment that satisfies either of the filters.
These can be combined to create a segment that has multiple filters that must be matched as well as optional filters.
Customer segments are updated automatically so whenever a new customer matches your criteria, they will be auto-added to the segment. Similarly, if they no longer match the criteria then they will be auto-removed.
Customers can belong to multiple customer segments as long as they match the criteria.
Pre Made Segments
Shopify offers a range of filter templates to help kickstart your exploration of the new segmentation. These templates are accompanied by an explanation on what each template does as well as a button to quickly add the template to your segmentation workspace.
Predictive Spending Tier
For stores with > 100 sales, Shopify offers a ‘predictive spending tier’ feature. This classifies your customers into three different categories (High, Medium, or Low) based on the amount it is expected a given individual will spend.
These values are decided based on analysing customer data for the following points:
- Customer purchasing frequency
- Customer average basket value relative to the store global average spend per order
- Number of orders placed by the customer
- How recently did the customer place their prior orders
Retailers now have the ability to utilize predictive spending tier values in the segmentation creation process. For example, if you would like to specifically target your high-value customers then you can include the following to your customer segment editor:
predicted_spend_tier = ‘HIGH’
Want help developing your Ecommerce strategy?
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