In the current hyper-competitive business environment, understanding customers' changing tastes and purchasing behavior is extremely important! Companies that do not track changing consumer wants and needs have seen their fortunes decline. KODAK is just one example, but a very good one to underscore this point. Failure to understand and predict consumers' buying trends toward more technologically advanced digital cameras led to the company's bankruptcy.
Know more about a vital marketing strategy of customer segmentation and analytics solutions.
Most companies today make tremendous efforts to track consumer behavior. Meticulous recording and utilization of consumer digital body language serve as the keystone of the process. The advent of the internet and mobile technologies has changed consumer behavior – they search online, educate themselves on the pros and cons of products, compare prices, and evaluate vendors for timeliness and customer service. They actively seek coupons and collect feedback from friends on social networks.
In doing so, the consumer leaves a trail of breadcrumbs all over the internet. Astute businesses collect, analyze, and utilize the digital body language of the customer to improve their marketing activities. There are several ways to collect and analyze customer data – web crawling, browser-based JavaScript, server log mining, and geolocation tracking in malls and stores. Most companies use a data warehouse to store data and analyze it to identify patterns in customer purchasing behavior. Effective utilization of this information can lead to revenue-generating promotional activities for the company.
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All promotional marketing activities are expensive since the response rates are very low. You cannot send a letter or catalog to every customer in the country, as it will be cost-prohibitive. To make these promotional activities cost-effective, it is essential to segment customers so that promotional plans can be directed towards selected, potentially profitable customers.
Segmentation is the process of dividing a large customer base into smaller subsets with everyday needs and priorities. There are several conventional methods of creating segments, such as Geographical Segmentation, Demographic Segmentation, and Behavioral Segmentation. However, more sophisticated methods currently used in the market include statistical techniques such as K-means clustering and hierarchical clustering. An interesting and upcoming technique of segmentation is "Micro-segmentation". It is utilized to understand individual customer behavior and to make personalized marketing offers.
When using these methods, companies should consider the ideal characteristics of the segments, such as:
- The segment should be measurable and profitable.
- Stable across time
- And every consumer in the segment should be easily reachable.
We will focus our discussion on the segmentation method commonly utilized by most b2c companies. In the retail industry, companies primarily focus on customers' transactional behavior to create segments.
Recency, Frequency, and Monetary (RFM) are the leading indicators used to segment consumers.
Few marketers use these individual indicators, while others combine customer segmentation and analytics techniques to implement their marketing plans.
Traditionally, more recently active customers are considered more critical. Some marketers divide customers by the recency of their purchases. e.g., customers who purchased during the last 12 months, 13-24 months, and 25+ months. Marketers use predictive modeling techniques such as linear regression and logistic regression to score their consumer base.
Finally, consumers are segmented by their geography, such as zip codes and households. These groups are then combined to make several mini-segments. These resulting segments are considered potential consumers and are targeted for the company's promotional efforts.
The performance of these customer segmentation analytics solutions and promotional strategies is measured for each segment, against the metrics such as:
- total revenue generated,
- the average revenue per customer,
- Cost of the promotional activity.
This report is then used as feedback to improve the marketing strategy continually. Segments evolve based on performance feedback, recent trends, and experimental testing (A/B testing).
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It is worth considering those consumer segments that are not current and active buyers; they may represent potential defectors to competitors. Knowledge of their purchasing behavior and transactional data can help target and attract them through selective marketing strategies.
Hence, marketing strategies that leverage customer segmentation analytics can be a win-win for both the company and the consumer, as the company can promote the right offer to the right consumer at the right time. The consumer may eventually respond to the offer by purchasing without being bombarded with junk mail.
