In today’s omnichannel world, the business challenge is to understand customers and their individual needs perfectly to be able to address them adequately via the various channels available. One key factor is the targeted and effective customer segmentation, using modern marketing technologies.
According to Aberdeen Group analysts, online retailers can increase their click-through rate by 14% and the conversion rate by 10% with effective segmentation, and such a success is mainly based on an increased customer understanding, thanks to modern IT analysis methods.
In the process, online customer profiles are analyzed automatically and divided into individual groups, based on individual criteria such as purchasing behavior, purchasing power and product interests. In a next step, the segments identified can be addressed properly according to their needs.
Virtual customer consultation
As everywhere nowadays, the individual is at the center and virtual consultation increases in popularity. Customers benefit from tailor-made product recommendations and discounts, which ensures a high customer acceptance of segment-based marketing measures.
The automated analysis of the Customer Journey provides the basis, with information about e.g. which products the customer has recently viewed, bought, or removed from the shopping cart.
This information can again be used to create automated omnichannel campaigns which manage to address selected segments of the customer base, inform them according to their interests and lead them to the desired platforms, where the customer can then continue his Customer Journey through other requirements-specific recommendations in real-time and on-site.
Long clicking through cluttered shopping websites is therefore a thing of the past and customers can concentrate on the products that are of real interest to them. Furthermore, since all purchase information is again incorporated into the segmentation, it is possible to prevent that buyers receive offers of the product they already bought again and again. Instead, the dealer offers added value when recommending matching articles, for instance, to the purchased suit the matching tie, and showcases that the right segmentation in the run-up is decisive.
Better customer engagement
For such kind of 360-degree view of customers, manufacturers of online marketing solutions are increasingly focusing on segmentation models such as Engagement Recency Frequency Monetary Analysis (ERFM).
In combination with modern technologies, it helps to predict future activities and makes personalized and automated recommendations easy. The method checks the entire data set regarding point of time and channel of the last interaction with the online shop.
Unlike the traditional RFM analysis, used for analyzing customer value, interaction is not limited to the purchase, but expressed in a variety of ways: From "I am looking around" visits to the online shop, to sharing and mentioning in social networks, activities on the company's website or interactions with the customer service.
Each online shop decides on its own which time intervals between the interactions are relevant as engagement segment. In addition, the data set is analyzed with the help of automated algorithms for the respective purchasing behavior (e.g. 20% of the customers first looked at X, then Y). In addition, there can be extra information about the last purchase, the quantity of orders and the sum of money all purchases made. That’s why, for example, a VIP, active, or inactive customer segmentation makes sense. Sociodemographic data, such as gender, place of residence and occupation, can also be included and expanded as required.
Subsequently, the more qualified and clustered customer groups can be addressed target group specific with suitable communication campaigns, such as personalized discount promotions, individual product recommendations or a gift proposal for XY, the better the marketing performance. And without doubt, the adoption of a cloud marketing software makes a lot of sense here as well due to ‘predictive real-time analytics’.
It is simply a fact that not every customer is equal and we know that it is above all about the appreciation and loyalty to customers. Whoever often spends or a lot of money in a shop, should therefore not only receive material goods, but also individual attention.
Hence, the combination of automated segmentation and an eye-to-eye approach in the sense of a classic one-to-one marketing style is most suitable.
By Daniela La Marca