In this article you will learn:
The pandemic was enough for us to see significant changes in consumer behavior. In an EY Future Consumer Index, consumers would fall into four main categories: “Cut deep,” “Stay calm, carry on,” “Save and stockpile” and “Hibernate and spend.”
More than one-quarter of consumers told EY that they fall in the "cut deep" category, spending less all around on things such as groceries, clothing, footwear, and leisure activities. The changes in consumer behavior were enough to make marketers take notice, and dramatically change how they reach and engage with customers. Old customer segmentation models are broken due to the pandemic and continue to degrade post-pandemic.
Brands that are succeeding now are using updated customer segmentation tools to better engage with consumers in an effort to incentivize increased purchasing and inspire greater loyalty.
In this article you will learn:
- What is Customer Segmentation Software?
- Methods and Techniques of Customer Segmentation
- Customer Segmentation Strategies
- Customer Segmentation Benefits
- Why Customer Segmentation Software Doesn’t Go Far Enough
What is Customer Segmentation Software?
Customer segmentation software and cloud-based solutions enable you to separate your customers into groups by certain traits they share. These traits can be as simple as gender, demographics, and income, or more complex views of purchasing patterns, interests, personality, or habits. These tools can help you collect and integrate data from a wide variety of sources, then you can use customer segmentation analytics to determine commonalities among groups of customers to which you can market.
The combination of these tools will enable you to more accurately tailor your marketing offers and promotions to the interests or needs of specific customer groups. The more information you have about the right customers for your brand, the better. One study noted that 81% of consumers were willing to share more information about themselves so they can receive personalized offers or promotions. However, some customer segmentation tools are limited, since they can only deliver broad views of customer groups, rather than the granular insights that will enable a high level of personalization, even down to a segment of one.
Methods and Techniques of Customer Segmentation
There are a variety of ways that you can segment customers. Here are eight different models that could be applied in any customer segmentation strategy:
- Demographic Segmentation
- Geographic Segmentation
- Psychographic Segmentation
- Technographic Segmentation
- Behavioral Segmentation
- Needs-Based Segmentation
- Value-Based Segmentation
- Customer Journey
- Customer Lifetime Value
Much of this information can be culled from a company’s loyalty program and analysis of customers’ interactions with your brand in stores, online, through customer service, via social media, and through surveys. But you can also gather data from third-party sources, such as broader consumer trends, location data, and website browsing history, to combine with personal information to develop greater insights on the value of particular customer segments.
Segmentation can take a few forms. What most are familiar with is macro segmentation, which uses basic demographics to divide the customer base into five to 10 groups. This approach can fall short because the groups will often still be so diverse, it is difficult to know what drives these individuals. Microsegmentation breaks these groups down into smaller cohorts using additional attributes like lifestyle, interests, and purchase and/or search behaviors, among other factors. By digging deeper, marketers can design promotions that are more relevant to these smaller, more targeted groups. However, micro-segmentation can be difficult because it has traditionally relied on manual processes to build and send promotions, limiting the number of segments that can be effectively managed to between 10 and 30.
The ultimate goal is to achieve a segment of one. This is where artificial intelligence and machine learning (ML) combine to eliminate many of the manual processes and automate offer creation and execution on a 1:1 level. This extreme level of customer segmentation can lead to proven revenue growth of up to 10%, an amount that is two to three times higher than those that rely on segmentation alone.
Customer Segmentation Strategies
Customer segmentation tools offer brands a data-driven way to make key decisions that will help them meet their business goals. For example, they could play a role in growing the customer base, encouraging greater loyalty among existing customers, and increasing sales and revenue from new customers.
Companies generally use customer segmentation techniques to:
- Prioritize new product development efforts
- Develop customized marketing programs
- Choose specific product features
- Establish appropriate service options
- Design an optimal distribution strategy
- Determine appropriate product pricing
If consumer response to the COVID-19 is any indication, it’s important for consumers not to assume that customers’ segments will always remain the same. Consumers' needs and preferences may slowly evolve as their lifestyles change, such as getting married or having kids. Or they could dramatically shift overnight as in the case of the pandemic, where we now see more people seeking greater value in their purchases or adjusting their shopping patterns to ensure their personal safety. You’ll want to continue analyzing customer data and revamping segmentation to ensure your brand is delivering the most relevant messages and offers, continuing to reach the right customers, and fine-tuning promotions to turn low spenders into high spenders.
Customer Segmentation Benefits
Establishing segments can be helpful to moving towards personalization, but it isn't as simple as it seems. If one or more of your segments change, there is a chance that it could create a domino effect. The best strategy is to use one that can offer an individualized experience. But a customer segmentation tool can help deliver a number of benefits for your brand. If segmentation is done correctly it can help you:
- Learn about your customers on a deeper level so you can tailor messaging, offers, and promotions to their unique needs and challenges
- Create targeted campaigns and ads to resonate with customers
- Convert targets
- Improve customer satisfaction
- Improve customer service and support efforts by anticipating challenges different groups may experience
- Increase customer loyalty with customized content and interactions
- Understand who your most valuable customers are and why
- Communicate with segments of customers via preferred channel or platform.
- Meet specific customer segments where they are
- Identify new opportunities for products, support, and service
Why Customer Segmentation Software Doesn’t Go Far Enough
Segments give your brand a unique experience to subgroups and can continue to break down into macro segments or micro-segments, helping to improve results. However in many cases, techniques such as micro-segmentation, which categorize customers based on a complex set of attributes, and smart segments, which use AI tools to examine available data and use that to decide how to divide customers, can create unnecessary complexities for loyalty marketers and confusion for brands, rather than creating the personalized experiences consumers crave.
Instead, brands would be better served by creating large business segments to organize campaigns and broader corporate objectives. By clearly defining large segments such as net-new customers, brand advocates and lapsed customers, marketers and business leaders can focus on long-term strategies to improve business results and design programs that help achieve them.
Brands that establish those larger business segments can then use advanced marketing automation and dynamic offer platforms to achieve true 1:1 personalization and ensure your marketing efforts align with, and can adapt to meet your business goals.
Discover how brands are using platforms like Formation to perform this personalization while leveraging AI and machine learning tools to organize existing customers and automate personalized offers at scale.