Targeting and Positioning: Customer Engagement Strategies

Targeting and positioning strategies are widely used by marketing managers and CMOs with the intention of attracting, engaging and retaining customers. With these strategies, marketing departments identify and segment the target audience, offer personalized and relevant messages, and position the brand in a unique and attractive way.

Discover how targeting and positioning impact Customer Engagement.

To achieve their goals, marketers focus on using data and analytics to execute smart decision making and develop effective marketing campaigns. targeted marketing that also improve the user experience (UX), allow to improve the brand positioning or increase the effectiveness of their customer retention strategies.

Introduction to digital marketing targeting and positioning

Targeting and positioning are two complementary concepts. Also known as market segmentation, targeting is a segmentation strategy that aims to identify specific groups of consumers with similar characteristics, interests or needs.

Data analysis in marketing has been used for a long time and successful targeting requires that the data is correct, so that the brand’s message reaches the target groups to whom the message is addressed. The data used for targeting and profiling include demographic, geographic and behavioral segmentation of users.

Positioning, on the other hand, is based on the way in which a consumer perceives a certain brand or product. In this case, the marketing department tries to develop a unique image and value proposition that differentiates the company from its competitors in the market. To this end, and in order to improve the customer loyalty strategy companies make use of personalized content marketing strategies and automated marketing campaigns.

Audience segmentation

Within the usual In marketing campaign strategies, targeting takes on vital importance in audience segmentation. In this case, the marketer divides customers into different homogeneous groups with similar characteristics, interests and needs in order to create more effective and personalized marketing campaigns.

The most commonly used segmentation variables are age, geographic location, gender or purchasing behavior.

Personalization in marketing

In either strategy, the objective is to treat the customer in a personalized way. And the fact is that personalization in marketing is one of the challenges facing CMOs. by constructing a highly personalized message, the customer develops his or her loyalty to a certain product or brand not only will prevent you from being tempted by another competing brand, but you will also be able to act as a ambassador of a specific product of the company.

This personalization should cover the different channels through which the customer is reached. In other words, so-called omnichannel marketing attempts to provide content, messages and offers tailored to the consumer from all channels through which each customer operates and focusing on what the customer really wants.

In this way it is possible to develop email marketing campaigns campaigns that offer customers personalized product recommendations or use customer behavioral data and preferences to strengthen engagement in social networks.

Data use and analysis

Whether it is a matter of attracting new customers or building loyalty among existing ones, it is necessary to offer a great user experience (UX) that must necessarily go through data analysis. The Digital Customer Engagement by aggity platform allows you to create personalized experiences tailored to the interests of users or develop real-time actions in response to user interactions, thanks to its use of analytics combined with Artificial Intelligence tools.

Such a solution enhances the so-called customer journey which is the process a customer goes through from the moment they become aware of a brand until they complete a desired action, such as making a purchase.

Measurement and optimization

Thanks to their use of automated marketing, these types of tools also make it possible to extract all kinds of data on the performance and results of a given campaign or to discover the reasons why a given customer has made a return. Thanks to these advanced features, the marketing department can make much more effective decisions in subsequent campaigns.