Why Segment Customer Data?


Data is probably one of the most important aspects of any digital strategy at the moment and it goes hand in hand with segmentation. So in this perspective it is the ability to carve up data based on a set of data points such as age, gender, last visit, points balance (loyalty program) etc... These segments can then be used for online and offline customer engagement.  Many organisations already carry out segmentation on their data but a large proportion still have not adopted this strategy. For those that do the benefits are realised quite quickly and for those that fail to segment their consumer data they are missing out on revenue opportunities. Data segmentation is an ever evolving area especially with the advent of big data platforms and new data acquisition services so this area is a key one to focus on.

In a recent study results showed a 40% increase in effectiveness in marketing by using segmentation. Key reasons for segmenting customer data are to target customer groups with greater accuracy, to analyse customer data to find patterns and help identify new or evolving strategies, and to enable detailed specific insight.

Let's look at an example, a set of anonymous users visit your digital property but do not actually purchase any service or products however of that group a percentage visit regularly and some not very often. From an anonymous user perspective you can define these as two distinct segments based on recency or frequency of visits. So would it not be useful to interact with both groups but present different content, offers or prices as it can be hypothesised that the more frequent users have a higher propensity to purchase. Once the results of this targeting are tested and known you can go one step further, knowing that a user has purchased, you can then link this data to the frequency of visits and to their characteristics of location, age, gender etc. This is the foundation of segmentation usage.

There are two modes in which segmentation can take place, both are highly effective although not always practiced.

1. The first and most common approach is to take the data and push it into an offline data store/warehouse where it can be segmented and then used for reporting or targeting purposes. In the targeting approach users can be allocated into segments, which can then be used for engagement. Once user segments are identified they can be extracted and then used either in marketing communications such as email (the most common approach) or segment matches can be fed back into the operational systems where interactions can be updated to allow engagement. For insight, segmentation can then inform predictive models and further propensity analysis to provide refined targeting (a topic for another day). These segments can be based on previously created customer classifications or can be used to analyse detail customer dimensions to provide insight. The types of interactions can vary from changing price points on products and services to cross selling items that are typically purchased together.

2. The second mode mentioned earlier and not well established yet is real-time segmentation. This is where user data segment dimensions are applied to users in real-time and if a match occurs an action takes place, for example if a user is browsing certain content on a news site such as cars and travel they are of a certain demographic, they are instantly provided with a relevant offer as they conform to a defined segment. The possibilities here are endless as this segment matching can also push app notifications or near real time email communications. However the key point here is that rather than waiting to process the segment offline and send out communications such as email that may or not be read, the engagement takes place immediately providing higher conversion opportunities and improves stickiness for the customer.

Whichever approach is undertaken the value of targeting based on segmentation is widely accepted as a mechanism to increase engagement and in turn growth of conversions.

Evolok provides one of the most advanced Real-time targeting engines in the market place, To find out more just get in touch.

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