Say Ads are Now Intrusive
In 2018, worldwide social media engagement is expected to reach 2.5 billion people. The way that customers are interacting with brands is shifting to mobile and social. Consumers are self-aware, sophisticated, and digitally connected. Businesses like Apple, Google and Amazon are anticipating the moves of the digital consumer, offering greater convenience and personalization in exchange for data and personal privacy. Digital Segmentation Models allow businesses to tap in to mobile and social resources to find more effective platforms for customer engagement (Wharton Press). Businesses must recognize their targets and tailor messaging for that customer segment.
Customer segmentation is a marketing tactic used by businesses to divide customers in to groups based on similarities in customer profiles. This allows businesses to created more targeted messages to each segmented target group with the goal of maximizing the value of each touch point. To compete and succeed in a market, a business must collect and analyze customer behavior data using digital marketing tools.
When initially defining customer segments, it may be easiest to break up the target customer segments based on demographics, income, geography, and other behavioral or habitual factors. Elizabeth Bell at Bridge has compiled a useful list of the 5 most common customer segmentation factors. The issue with this method is that there can be movements among segments over time, particularly with the fast-paced nature of digital consumers. It can be difficult to consider the path that each customer has taken to reach their current segment.
Marketers often personify and distill each customer segment in to one individual – this is a tactic utilizing a consumer persona. Brand identities are comprised of two components, the brand persona and the targeted consumer persona. Creating a targeted consumer persona is a dynamic strategy for better defining customer segments. Xtensio and Hubspot both have persona creators that may help a business create a persona for specific customer segments.
Segmentation does not have to be limited to B2C applications, companies looking for segmentation in the B2B space can substitute consumer demographics for “firmographics” or characteristics of business behavior. B2B International emphasized the use of statistical techniques such as factor analysis to study firmographics. Statistical methods for customer segmentation are explained in this article by Paul Hague and Matthew Harrison.
Although it’s easy to use a ‘gut feeling’ when defining and targeting customer segments, analyzing data can confirm or alternatively pose new options in your customer strategy. Using data to anticipate the interests, goals and behavior of the consumer, a business can decide what marketing messages to create and how to optimize the marketing channels used to communicate. Just like in B2B segmentation, using statistical methods to cluster groups or find correlations between customers can be a great way to analyze your segmentation strategy.
Analytics requires engagement – create a customer feedback loop to give your customers a voice in their purchasing experience. Follow up with all feedback, negative and positive as it can help you improve your targeting, conversion process and customer service. If your business is transparent with the intentions for gathering customer data, you will receive more participation and will ultimately have more success using that data for marketing decisions. Create dashboards or incorporate third party data applications like a CRM to organize user experiences.
Marketing is no longer operating in a funnel, instead marketing operates in the Customer Decision Journey (CDJ). Attentiveness to customers combined with data analysis will also help you predict trends. Anticipate emerging segments and position your messaging accordingly – A dynamic approach to customer segmentation will help your business communicate with an increasingly connected audience.