Marketing Automation Utilizing Rule-Based Segmentation

Marketing automation is what Enalito does effectively and perfectly for online stores. It takes command of everything that a business needs to focus on and delivers the solution without placing any hassle on the retailer. An automated solution makes it easy for businesses to focus on what they should be focusing on: Revenue. Everything else is analyzed and maintained by automation in order to provide only those solutions that can benefit the business.

As far as customer segmentation is concerned, marketing automation excels at making it easy while doubling its effectiveness. Rule-based segmentation is forming customer segments on the basis of a rule. Such rules can be anything in the possibilities of a retail business. For example:

A retailer wants to form a customer segment of those customers who haven’t bought a single item in the past three months but have browsed the store many times. The retailer wishes to send a campaign to each customer of that segment, so they could buy and contribute to the business. But the retailer doesn’t have a marketing automation tool and hence can’t realize which product should be campaigned to each customer on the basis of their detailed behavior. So, the retailer sends a generalized email to each customer of the segment, campaigning a product that a customer may be interested in or maybe not. By doing so, the retailer is risking on three things that wouldn’t have been an issue if the retailer had marketing automation at work. The three risks taken by the retailer are:

  1. The customer behavior and customer data changes with time, so the customers who are part of the customer segment now may not be behaving the same way for the next month and further. If there is no automation in the process then how effective is the customer segment for the present campaigning, it will not remain the same in the time to come. 

A few customers with non-buying behavior for the past three months might make a purchase after the campaign, while few of the same customers who were browsing for the same time might quit the store after receiving the campaign. Such continuous changes in customer’s behavior are not easy to track without automated assistance and it’s risky to try different campaigns on the same segment from time to time.

  1. Customer segmentation makes it easy for businesses to target a bunch of customers like it would target a single one, and this is where the lack of automation turns a nightmare for businesses. In the absence of marketing automation, retailers make a mistake of assuming all the customers in a segment are interested in the same product. So, retailers send a generalized email offering the same product to different customers in a segment, which results as a useful email for some customers but spam for others. By doing so, the retailers commit a serious mistake of sending useless emails to customers who might be strong prospects for buying another product.
  1. Suppose there are 20 product opportunities that can be tried to yield sales from a customer segment. But in the absence of automation, the retailer has to figure out by self to use which of the opportunities to get better results. Most commonly, a retailer commits another mistake in an attempt to grab all opportunities. Customers have an interest level for the products they like, and if they’re offered things they don’t like; they will leave.

To grab all the existing opportunities, a retailer campaigns all the 20 products to each customer of the segment. As a result of which, the uninterested customers not only avoid purchase but may also leave the store forever. If marketing automation is in place, it would suggest the best of those opportunities which can attract customers on the basis of their own interest in the products.

Customer segmentation can be done easily on basic levels but to implement it effectively; automation is quite necessary. In the absence of automation, the benefits of customer segmentation get infected by assumptions and inaccuracy. To figure out a customer segment based on behavior is somehow possible but making as many rule-based segments required for the healthy growth of a business is possible through adopting a marketing automation tool.

Enalito is a complete marketing automation tool that excels in creating and managing rule-based customer segments and far many things beyond this. Its Machine Learning (ML) capabilities assist online stores to have a profound automation that can analyze customer behaviors, create effective rule-based customer segments, handle and manage them while updating them automatically with changing time and customer behaviors.

With the powerful aid of Machine Learning backed Enalito, an online store can remain hassle-free from every and any retailer problems that can come up in the formation of segments, their management, effective campaigning to them and yielding the best ROI from the marketing dollars.

In addition to the impactful Machine Learning technology, Enalito is powered along with the RFM methodology that provides a strong analytical foundation to the AI and ML backed product suite. RFM methodology gives depth to the behavior analysis through which the behavioral values and scores are obtained to implement effective customer segments and measurement of their performance over time.

 Let’s get further ahead and know about the details of using RFM methodology for rule-based (dynamic) segmentation.

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