Single Customer Views and why you need one

Data analytics abound. From e-tailers examining our purchases, to Google reviewing and recommending our search content, to understanding football teams and individual player performance. Our data is being analysed all the time. Often with the intention to get to know us better: to recommend our next action, our next purchase or just understand what we are like as a consumer.

Businesses like to steer and marshal prospects and customers into defined groups and segments, based on basic information such as locational demographics, purchase history or actions. I like to think of myself as an individual. Unique. My activity history, of course, would group me with other ‘similar’ individuals. This level of customer segmentation is useful, but it’s not the best method of targeting customers with specific or generic offers.

Let’s take an example. Over the years, I’ve attended a number of music events at the heavier end of the scale. However, I find I’m often sent ‘targeted’ email promotions for generic pop concerts. I’m reasonably eclectic when it comes to music but would never attend a pop concert (until my daughter grows up and drags me to one). These emails are always deleted immediately, and will likely lead to me unsubscribing when I get a spare minute, so the communication is effectively detrimental to what the sender is trying to achieve.

Having worked with many businesses and countless datasets over the past 20 years. I often find that businesses silo data into different platforms, designed for their respective core functions, such as online purchasing, web site activity, email communications, consumer surveys or loyalty schemes.

These disparate systems typically have no clear data link. And they should. They should at least link email addresses, names or addresses with exact or fuzzy matches. Because a Single Customer View (SCV) is increasingly crucial in terms of both outreach and data analytics.

A Single Customer View for pinpoint customer segmentation

A Single Customer View (SCV) is designed to draw in data from multiple sources, and match relevant data using a number of matching technologies. These technologies include in-depth fuzzy name and address matching, name and email matching, household matching, and core ID matching. The SCV then uses the results to create your individual customer profiles.

From here, all relevant data is linked to create an SCV database. This database allows you to see all your customers comprehensively, examine exactly what they have done in the past, and explore exactly what they have purchased or interacted with.

Using this data, you can create a next best action that is unique to each customer, not just a generic customer segment. Creating detailed pictures of your customers in this way will improve your data quality overall, and with it, the strength of your campaigns.

Deep customer knowledge drives conversions

The most successful marketing systems I have seen and used all have a solid, dependable SCV as the data source behind them, which is why I am such an advocate of them both as a business person and as a consumer.

I’m more than just a data segment. Send me offers based on what I have browsed and my previous purchases and previous offers I have interacted with, not based on them individually. If you do this, you will get more from your customers. Not just purchases but brand loyalty, because you’ve taken the time to know the individual.

For more insights into and information on best practice data management, explore our Knowledge Hub. Otherwise, get in touch with one of our friendly experts to discuss how Data HQ’s strategic data solutions can help you and your business.