TARGETING & ANALYTICS | Improving your single most important analytic
The 5 Steps for Effective Segmentations
- Align segmentation design to business strategy
- Start simple
- Continually measure performance
- Consider all available data
- Improve through test and learn
The importance of customer segmentation to business strategyBy Brian Jones
Segmentation in its simplest form is about putting customers into “like” groups. It’s truly one of the most powerful analytics. At the core of its strength is its ability to support businesses in the laser focussed targeting and managing of their customers.
With the amounts of information increasing, segmentations are about to get smarter. Big Data is creating unique opportunities. And advantage will go to companies that are able to aggregate vast amounts of information that build predictive segmentations.
But it’s critical to get your segmentation right because in a customer centric world, customer segmentation has become an integral part of business strategy.
What’s right for your brand?
Think of airlines and their frequent flyer programs. With a program in place, an airline can easily identify their “best customers” and understand their needs. This understanding enables them to deliver a different experience vs. those delivered to their “next best customer”. The strategy is clear in this example. It’s to protect and reward their best customers, in order to retain them. This is a simple segmentation to address an important strategy, and supporting a strategy is exactly what a segmentation should do.
Most businesses can identify their best customers or their most profitable ones. So segmentations don’t have to be complex to work, they just have to be right for your business. What’s right for your business is dependent on your businesses strategy. Building a segmentation that supports your strategy is key. By “support” I mean it provides direction on achieving your goals and objectives, as well as helps to measure your progress. Therefore, when developing your segmentation think how you will use it and the decisions it will help you make.
Segmentation requires customer data, and often starts with sources of data simple to access. If you’re looking for a less complex segmentation, and your strategy is “growing existing customer spend”, then look to your customer lists. If those lists identify information such as who the customer is, the amount spent, and on what and when they spent it, then you are clearly on your way with one of the most basic, but nonetheless effective segmentations. It’s called an RFM segmentation. RFM stands for Recency (when they last bought), Frequency (how often do they buy), and Monetary Value (what they spent). These pieces of data can reveal considerable insights that help manage customers in a more relevant way. In their simplest form they are used to know how often to mail and when to mail, after the “who” to mail has been determined. Executing against an RFM will help increase number of customer transactions and their size.
While an RFM can be effective and simple, it is merely one of dozens of ways to segment. Others range from basic demographic segmentations through to more complex segmentations that cluster behaviours, attitudes, opportunity, benefits, needs, life-stage, and channel shopped. These are just a few. Segmentations can also be overlaid with other segmentations enabling you to narrow targeting which adds more relevancy to your marketing. Think of the value of overlaying a Heavy/Medium/Light buyer segmentation with a buyer demographic. “Weighting” the demographics through purchasing information helps further define what your customers look like, and provides greater insights on where to invest your marketing dollars and what message to deliver.
Improving segmentation performance through loyalty programs
Customer loyalty programs provide rich customer data bases, which can be leveraged to create very effective segmentations. Loyalty cards have a unique identifier which is the loyalty card number. Whenever you buy a product and use the card, the purchase is linked to you. Businesses store this data in their data bases, and leverage the power of analytics to introduce insights into their organization.
Some retailers have become great users of loyalty program data. For example, drug stores can use their customer loyalty data bases to segment customers by life-stage. Life-stage is an ideal segmentation for a drug store as it enables them to target their customers with offers that are relevant to their stage in life.
Here’s how it works….what we buy tells the retailers a lot about ourselves. The first purchase of razors and shaving cream or feminine care, or the purchase of baby food or incontinence products – all speaks to our life-stage and our needs. The ability to manage the customer based on this knowledge helps drive customer value. For example, baby food buyers are of considerable value to a drug store. The range of products they require is wide and deep, and their frequency of shop and transaction size is high. Therefore, a drug store will want to engage this customer segment and earn their loyalty. With the customer insights they can begin to market products and services that specifically address their needs, and do so at the right time. This will help drive the customers’ experience, increase loyalty, drive transaction size, and grow the customers’ life time value.
Taking it to the next level
When attitudinal data is overlaid with behavioural data, more refined segmentations can be created. The combination of the two can begin to deliver a greater one-to-one marketing experience which drives campaign performance. Attitudinal data, like behavioural data, is also inherent in a shopping basket. For example, those who purchase a disproportionate amount of health food products can be put into a “healthy” segment. When combined with those purchasing baby food, you start to get a clearer picture of your customer. Data could confirm that the customer is an active female in her early 30’s whose health conscious attitude will likely be reflected in what she feeds her infant. This type of information becomes a marketers dream. Everything from what to market to them and how often to market to them becomes clearer. Knowing the customers’ life-stage ensures retailers are relevant to their customers which drives engagement and loyalty while ensuring their marketing dollars are spent in the most efficient way. Highly relevant marketing has proven time and time again to increase the performance of marketing campaigns. As we all work our way through our teens, 20’s, 30’s and so on, the products and categories we buy provide all types of information for retailers that ensure the experience that we have as customers is relevant to us.
In a customer centric organization, the customer segmentation becomes core to the enterprise strategy. Therefore how you segment your customers becomes a very strategic decision. The key is access to great amounts of customer data. The more the information can be linked back to a customer, the better. Having access to both attitudes and behaviours for example helps you to define segments while providing guidance on messaging content, offers, and frequency. Consider the value of data provided through customer loyalty programs, specifically those programs that link purchases back to an identifiable individual.
Lastly, explore other sources of data, perhaps those available through your vendors, or through deep search engine technologies. Big data creates great opportunities in this area. The more data you have the greater opportunity to build highly competitive smart segmentations that support competitive differentiation while delivering your goals and objectives.
Brian Jones is the Principal of Active Data (www.active-data.ca) as well is an Associate of Alpha Insights (www.alphainsights.ca). Brian can be reached at email@example.com. View Brian’s profile athttp://ca.linkedin.com/in/brianjones99/, or reach him directly at firstname.lastname@example.org
Active-Data is a consulting company that helps organizations innovate through optimizing the value of available data, and we do this with one purpose in mind; to drive a businesses profitability.