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Market Segmentation

Market segmentation involves dividing customers into groups of people with similar characteristics. This makes your marketing more effective with smaller targets.  Segmentation ranges from identifying customer attributes to complex aspirations and attitudes. The objective of segmenting the market is to maximise the return from your marketing spend by tailoring your offering to each group.

Completion of Firmographic Information

Market segments refer to firmographic or demographic indicators such as your customer’s location or industry. Yet many businesses do not even have complete information on their customers. This is where JTA can help by completing the information from third-party databases such as Dun & Bradstreet.

Using our text-matching processes we can lookup customers in the database and return the intelligence to your systems. In addition, we can deploy web scraping techniques which can effectively search for your customer online and then extract intelligence from the web pages found.

Understanding Customer Behaviour

Internal sales data can be used to understand the behavior of each customer. When analysed using the right techniques the data starts to reveal patterns that cannot be discerned by the human eye. Obviously every customer’s behaviour will be unique but the techniques we use will allow us to see similarities in these behaviors. We use these similarities to place customers into groups. The number of groups is very important in determining the final benefit from the clustering and this decision is an important part of any segmentation project.

Once we have decided on the clusters we identify the attributes that are common to each. These attributes help us to attach a cluster name to each of our client’s customer records.

Example in the Software Industry

During a recent project we analysed customers who installed our client’s software on their computers. We were able to find customers who had experimented with the software but ultimately not invested. We also found customers who made a steady flow of purchases but it was hard to predict what was driving the purchase.

The key was finding a group of customers who made a significant investment in the software. When we did a further analysis we found that these customer shared certain attributes.

The Secret Recipe to Success

  • Segmentation does not need to be complex to be effective.
  • Finding and recording any missing customer attributes is an important first step.
  • Experimentation with the data is needed to reveal clusters.  This experimentation should consider a variety of metrics and use different clustering algorithms to tease out the clusters from the data.
  • It is very important to decide on the number of clusters to use.
  • We must understand the behaviour of each cluster and be able to describe it and identify it.

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