Anyone who thinks that data is the currency of the 21st century, will certainly also believe that the famous hay stack is as valuable as the needle – it all depends on the concentration of what can be filtered out of the data.
Data speaks louder than words
People love collecting, they always have. A passion that’s not even that new is the collection of data. Thanks to digitalization, we are actually talking “big data” now, meaning huge amounts of data which can’t be analyzed without mechanical help.
Such huge amounts of data can contain valuable information. For example, how many people abandon their filled shopping cart while online shopping. Or at what time (24/7) most people buy chocolate. When used internally, these data can particularly help you to get away from general statements about customer behavior and turn your attention towards the concrete behavior of your customers. Why? Because different companies have different target groups and demographics. For example, American customers are a lot more experienced and active in social media compared to the more reserved Europeans.
Customer analytics – what it is
Customer analytics describes the utilization of externally and internally generated customer data to optimize marketing, sales and support. Or, in other words, to get to know the customer and his needs better.
A customer doesn’t always get in touch with you directly with his specific issue or problem. Actually, sometimes he might not know himself what his issue is. Or what led him to look for photo frames right after buying a snorkel.
The analysis software doesn’t know either, but when a great number of customers show a similar shopping behaviour, a smart marketing expert can sell these products for example as a holiday package with a targeted cross-sell-offer.
Customer analytics – how to do it right
Key for successful data analysis is to maintain focus. If you don’t know what goals you are pursuing with customer analytics and what exactly you want to learn about your customers, you risk collecting data that are completely useless. Those data will be sitting in the cloud or on a local computer, taking up space while involving substantial cost without ever influencing one single business decision.
Speaking of data, one thing’s for sure: Companies who fail to ensure a high level of data quality by using numerous double, old or wrong data sets, will be left behind.
In short, even though – or actually because – customer analytics is being hyped so much, one has to plan it well. It is best to start with a clear in-house strategy. Before you start collecting, it’s worth taking a closer look at the mountains of data already generated and often unsorted. Once they are cleaned up and evaluated, the continued data collecting becomes easier. By the way: ideally, your data analysis is directly linked to CRM systems and marketing automation tools, so that certain results can be automatically included in customer processes.
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