Segmenting Your Customer Data
According to marketing guru Professor Malcolm McDonald “Correct needs-based segmentation is the bedrock of commercial success”.
Customer segmentation is a method of classifying your customers into differing groups, typically to allow for targeted and personalised marketing. Standard customer segmentation can be completed manually, however this typically lacks accuracy and precision, and can end up requiring a lot of resources to complete efficiently.
Here we’ll look at using artificial intelligence (AI) and machine learning with the segmentation process to get the most out of your data and resources, and guide you towards achieving your business goals. These ‘segments’ can be as straightforward as segmenting your customers by simple demographics such as gender or age; however, for B2B and larger B2C companies, customers could be split by more complex variables such as their historical behaviours.
By having the ability to target specific groups of people with specific interests, you’ll have a greater ability to cross-sell and up-sell your business products. When sending personalised content to a customer, not only will they have an increased probability of buying your product, but they also develop greater brand loyalty towards your business as the customer feels more appreciated and valued.
Segmentation Using AI & Machine Learning
The ability to segment your customer base will come down to the amount of data you have available on them. If you have limited data sources, such as names and email addresses, you may at best be able to segment through gender. However, the likelihood is this is not the case; your business probably has copious amounts of data available, but you don’t know how to use it.
You can try and face this problem by labelling your entire customer database by hand, which may be a viable option for smaller businesses. However, once you start to grow as a business and develop a larger customer base this will become increasingly difficult. This is where machine learning can come into play. With the aid of bespoke software, your business will be able to determine target groups and even re-label customers that have been incorrectly segmented in a considerably reduce time period, alongside greater accuracy.
Customer Segmentation Software Processes
There are four stages of development when segmenting your customer base using bespoke software; pre-processing, modelling, evaluation and transformation.
Pre-processing – Initial cleaning and transforming of your data is required to make the process function. A ‘gold standard’ training set will also need to be identified for later use.
Modelling – Algorithms would be run to identify what variables are important to your segmentation. These are then scaled in order of importance and applied to the ‘gold standard’ training set so the model can understand what properties are common for your segments.
Evaluation – Using a confusion matrix, previously incorrectly identified contacts can be identified; this data can also be used to identify the accuracy of the model. When the data set contains unbalanced data across segments a statistical coefficient can be implemented to account for class imbalance.
Transformation – Output data is finally achieved. You’ll now have your customers segmented in accordance with your ‘gold standard’ training set.
Reaping the Rewards
If you’ve managed to segment your customers effectively, you’ll be able to target them with personalised content. However, just because you’ve grouped your customer base doesn’t guarantee automatic success. You’ll still need compelling, personalised content delivered through interesting streams to get the greatest return on investment.
If you believe that customer segmentation using AI may be of interest to you get in contact with us. Objective Computing specialises in software development and data analytics.
Look out for our goody bags as you take your seat at the event! They contain an opportunity to win a Fitbit just by identifying the solution to the puzzles!