The COVID-19 pandemic and the movement for social justice are spurring seismic market changes. Consequently, companies are grappling with a few pertinent questions: Which groups of my customers are driving most of my company’s revenue growth? Which customer groups are the heaviest users of my products? How can I effectively prioritize my product portfolio and make the best use of my marketing budget? Having a customer segmentation strategy will help answer these questions.
Companies struggling with rapid change need to understand which products are resonating with customers, which aren’t, and how to communicate effectively with customers to stay relevant and competitive. By having an intimate understanding of the unique needs and pain points of different customer groups, you can better tailor the product portfolio and future digital product development efforts.
Gone are the days when demographic consumer segmentation based on age, gender, geography, and income helped drive bottom line results. The market today requires an intrinsic, intuitive understanding of customer attitudes, motivations, influences and values. Understanding who your customers are, how they think and what they are going through using psychographic segmentation allows you to build intuitive customer experiences, personalized to meet the needs of specific user and customer groups.
Leading with a customer-first mindset through properly-applied segmentation can help your company realign and optimize product portfolios and enable strategic decision making across product owners, product technology and marketing teams.
For example, Nerdery partnered with a multi-national media agency who has been core to helping brands understand what people watch and what they buy. However, as the media industry is rapidly shifting with the consolidation of media channels, the company decided that they needed to realign with a customer-first mindset.
To better understand their customers and enable stronger decision-making across their diverse markets and product portfolios, they challenged us with the task of building mathematically-validated user personas. Through a multi-phased study with qualitative and quantitative research methods, our team provided insights into each personas’ unique decision frameworks and most-utilized technology tools. As a result, this allowed the company to derive a deeper understanding of their customer segments and boost their business strategy.
Nerdery’s experienced Insights Team stands ready to help you design and execute best-in-class segmentation studies powering customer-first strategies that drive results and help you spot patterns in the data.
Contact us to talk through your customer segmentation strategy.
There’s more than one way to begin to understand your different groups of customers based on the cognitive factors driving their behavior. Each method has its own advantages and drawbacks and should be employed based on how you intend to leverage the consumer segments to drive your business (such as portfolio alignment, new product development, marketing strategy).
Created by conducting interviews with groups of users, personas are a great way to explore attitudes, values and interactions. They offer a quick means of understanding where the wind is coming from in terms of behavior and sentiment.
The main drawback with qualitative personas is that they are not representative, or may not accurately reflect the diverse characteristics of your customer base. For this reason, it can be difficult to apply the lessons learned for strategy, marketing and product decision making.
Levels up your segmentation strategy by combining qualitative and quantitative methods. The process typically begins with qualitative interviews. Insights gleaned from the qualitative process are tested using a quantitative survey with a representative sample of customers. This allows you to reliably estimate the proportion of your market each customer group represents for marketing and strategic product decision making.
AI/ML (artificial intelligence/machine learning) segmentation not only explains the what and the how, but also the why behind individual behaviors, powering dynamic and intelligent strategies for micro-segmentation and the creation of hyper-personalized product and digital experiences. Today, organizations are applying natural language processing (NLP) to text data (such as comments on feedback forms and in chat sessions, and to practitioners’ notes and patient communications in healthcare) to uncover sentiments and values and reveal customer groups.