While mass marketing tactics are still able to get results, the assumption that simply everyone will be interested in buying what you are selling is a time-consuming, inefficient and expensive strategy.
Instead of a ‘one-size-fits-all’ approach, successful segmentation clusters your customer data into groups sharing the same properties or behavioral characteristics, helping to drive dynamic content and personalization tactics for timelier, relevant and more effective marketing communications.
However, for segmentation to be used correctly, it needs to take into account that different customers buy for different reasons, and marketers need to intelligently apply a number of considerations that could affect their purchasing decisions. A Harvard Business School professor even went as far to say that, of 30,000 new consumer products launches each year, 95% fail because of ineffective market segmentation.
There are many reasons why companies fail at targeting the correct customers. It could be an assumption that segmentation is based entirely on demographics, or that segments have been defined too broadly. It could be that there is no strategic goal, like lead acquisition or customer retention. Or, it could be that the lack of a Single Customer View and siloed data has resulted in an inaccurate or misinformed understanding of your consumer base.
What are some of the most common segment descriptors?
A more sophisticated approach to segmentation demands contextual understanding and a view of the bigger picture, Big Data sample sizes and advanced analysis tools to define groups.
While you are unlikely to use all of them for every one of your marketing campaigns, customers are often grouped under the following categories:
- Demographic – basic personal information, including age, gender, income and education. For B2B, this can include employee numbers, SIC codes, and sales size.
- Geographic – specific areas where customers or businesses are located, broken down international region right down to a rural area.
- Behavioral – How customers are using your products and what type of user they are. It can also include customer transactional behavior, such as browsing, spend by category, sentiment and price points.
- Lifestyle – Customer habits and pastimes, including sports, hobbies, fashion and holiday preferences.
- Psychographic/Attitudinal – Including social status, perception of the world, values and lifestyle.
- Preference – This can cover communication preference opt-ins, as well as which of your channels (such as online, through an app or in-store) they prefer and the time/day they are most responsive to your messages.
- Loyalty – For companies with loyalty programs, this can include customer activity and points earned/redeemed. Alternatively, it can be a recency, frequency, monetary (RFM) score.
- Value – The current value and future value (or lifetime value) in term of revenue or profitability of an individual customer.
How can segmentation benefit your business?
Segmentation allows businesses to make better use of their marketing budgets, gain a competitive edge over rival companies and, importantly, demonstrate a better knowledge of your customers’ needs and wants. It can also help:
- Marketing efficiency – Breaking down a large customer base into more manageable pieces, making it easier to identify your target audience and launch campaigns to the most relevant people, using the most relevant channel.
- Determine new market opportunities – During the process of grouping your customers into clusters, you may find that you have identified a new market segment, which could in turn alter your marketing focus and strategy to fit.
- Better brand strategy – Once you have identified the key motivators for your customer, such as design or price or practical needs, you can brand your products appropriately.
- Improve distribution strategies – Identifying where customers shop and when can informatively shape product distributions strategies, such as what type of products are sold at particular outlets.
- Customer retention – Using segmentation, marketers can identify groups that require extra attention and those that churn quick, along with customers with the highest potential value. It can also help with creating targeted strategies that capture your customers’ attention and create positive, high-value experiences with your brands.
How can segmentation software help?
Segmentation doesn’t have to be difficult, as the right software allows you to easily segment customers into relevant groups for business intelligence, as well as enrich your records with aggregated third party data to further improve your results.
A solution like BlueVenn, for example, enables marketers to easily find and analyze their customers using Venn diagrams, maps, and interactive charts and graphs – without a need to create complex algorithms.
LIVE NEXT at: 11am EDT / 3pm GMT on November 2, 2017
Register to watch how to combine customer analytics and real-time, omnichannel customer journey tools to create personalized and contextual customer experiences in this BlueVenn Customer Data Platform software demonstration. In the session we’ll define how to:
- Use predictive analytics to make real-time decisions that positively affect the customer journey
- Improve targeting of campaigns using customer segmentation and RFV analysis
- Use real-time personalization to better engage customers
- Integrate online and offline channels into the BlueVenn Customer Data Platform to create a true Single Customer View