CUSTOMER SEGMENTATION:
10 POWERFUL METHODS
UTILIZING CUSTOMER BEHAVIOR DATA
By Adrian Brady-Cesana
Effective Customer Segmentation is an absolute must and is integral to any enterprise
success today. However, many companies fail to derive the powerful impact of this process
because they are still using traditional segmentation approaches, without leveraging the
breath of customer data and advanced analytics techniques available today.
And that’s because they are not using a modern behavioral segmentation approach.
Traditional segmentation focused mainly on who customers are, based on demographic
attributes such as gender or age, or firm types, such as size or industry.
SO WHAT IS BEHAVIORAL SEGMENTATION?
Behavioral segmentation is about understanding customers not just by who they are, but
what they do, using insights that are based on patterns of behavior displayed by customers
as they interact with a company/brand or make purchasing decisions. It allows businesses
to divide customers into groups according to their knowledge of, attitude towards, use of, or
response to a product, service, or brand. This different segmentation enables you to
understand how to address the particular needs or desires of a group of customers, discover
opportunities to optimize customer journeys, and quantify their potential value to your
business.
THESE ARE THE MAIN ADVANTAGES OF SEGMENTING CUSTOMERS BY BEHAVIOR:
- Personalization: understanding how different groups of customers should be targeted with different offers, at the most appropriate times through their performance channels, to effectively help them advance towards successful outcomes in their journeys.
- Predictability: historical behavioral patterns can be used to predict and influence
future customer behaviors and outcomes.
- Prioritization: making smarter decisions on how to best allocate time, budget, and resources by identifying high-value customer segments and initiatives with the greatest potential business impact.
- Performance: monitoring growth patterns and changes in key customer segments over time to gauge business health and track performance against goals. This means quantifying the size and value of customer segments, and tracking how positive and negative segments are growing or shrinking over time.
10 POWERFUL BEHAVIORAL SEGMENTATION METHODS YOU CAN USE
TO BETTER UNDERSTAND YOUR CUSTOMERS:
This list is NOT mutually exclusive. Behavioral segmentation types can vary greatly
depending on your business, and one or more of these segmentation methods can be
utilized at the same time or combined with other types of segments.
- PURCHASING BEHAVIOR:
How do customers behave differently throughout the path to purchase?
Purchasing behavior can help us understand how different customers approach the purchasing decision, the complexity and difficulty of the purchasing process, the role the customer plays in the purchasing process, important barriers along the path to purchase, and which behaviors are most and least predictive of a customer making a purchase.
2 WAYS TO USE PAST BEHAVIOR TO PREDICT FUTURE OUTCOMES:
- Using past purchases to predict future purchases
- Using behavior along the path-to-purchase to predict the likelihood of completing a purchase.
6 BEHAVIORAL TYPES MARKETERS NEED TO UNDERSTAND
in order to identify key obstacles that need to be removed from the path to purchase:
- The “Price-conscious” buyer is a bargain hunter looking for the lowest possible price.
- The “Smart” buyer is a thorough, meticulous researcher who wants to understand every intricate factor, before committing to any single one.
- The “Risk-averse” buyer is a cautious, economically-careful shopper, who struggles to pull the trigger on a purchase without the proper insurance, such as a good, hassle-free return policy.
- The “Needs-proof” buyer is a shopper who needs confirmation that the product is popular and backed up by claims of her peers.
- The “I’ll get it later” buyer is a shopper who lacks urgency.
- The “Persuadable” buyer is an impulse shopper that is highly susceptible to cross-sell offers.
Using customer behavior data that encompasses interactions across all channels over a longer period of time, you can discover a great deal about how different customers approach a purchasing decision.
2. BENEFITS SOUGHT:
What primary benefits are different customers seeking during a purchasing decision?
When a customer places a much higher value on one or more benefits over the others, these primary benefits sought are the defining motivating factors driving the purchase decision for that customer.
For a B2C company a consumer could buy toothpaste for different reasons: whitening teeth, teeth sensitivity, flavor, or price. For a B2B software company, benefits sought might be specific features or capabilities, ease-of-use, speed or accuracy-related benefits, or integration with other tools.
Understanding each customer behavior allows you to group customers into segments in order to personalize your marketing.
APPLYING THIS METHOD TO ACQUISITION AND RETENTION OF HIGH-VALUE CUSTOMERS:
Identifying desired benefits may also be predictive of a customer’s likelihood to purchase, or of their potential lifetime value, or even their likelihood to churn. Examples of how benefits can be analyzed within this context:
- What were the benefits sought for prospects that ended up purchasing? That did not purchase?
- What benefits are most and least important for your highest lifetime value and most loyal customers?
- What benefits are most and least important for low lifetime value customers or those that churn?
- How do these benefits match up with your strongest value propositions and differentiators?
With this knowledge, you can increase conversion rates through more personalized journeys and also have a clearer understanding of which customers to target for acquisition and which messages to use to attract them.
3. CUSTOMER JOURNEY STAGE:
Which stage of the journey is a new or existing customer currently in?
Building behavioral segments by customer journey stage allows you to align communications and personalize experiences to increase conversion at every stage. Moreover, it helps you discover stages where customers are not progressing, so you can identify the biggest obstacles and opportunities for improvement.
But segmenting your customers by journey stage is not easy.
In most cases one or two behavioral data points are not enough to accurately identify a customer’s current journey stage.
The most effective way to accurately determine a customer’s current journey stage is by leveraging all of a customer’s behavioral data across channels and touchpoints, so you can build weighted algorithms based upon patterns of behavior over time.
Also, do not make the mistake of assuming customers will just naturally transition to the next stage in their journey as time passes. Once again, behavioral data is the only way to get the truth, or at least as close to it as possible.
4. USAGE
How often (and how much) are customers using your product or service? How are they using it?
Usage behavior can be a strong predictive indicator of loyalty or churn and, therefore, lifetime value.
SEGMENTS BASED ON QUANTITY OR FREQUENCY USAGE:
- Heavy Users (or “Super Users”) are customers that spend the most time using your solution and/or purchase most frequently. These tend to be your most avid and engaged customers, who can also often rely most on your product/service.
- Average or Medium Users are customers that semi-regularly use or purchase, but not very frequently. Often these can be time or event-based.
- Light Users are customers that use or purchase much less in proportion to other customers. Depending on your business, this could even mean one-time users, but again, it depends on the relative usage to the rest of your customer base.
These usage-based behavioral segments are invaluable for understanding why certain types of customers become heavy or light users. By segmenting in this way, you can test different actions and approaches to increase usage from existing customers and attract more new customers with a higher likelihood of following the same usage behavior patterns as your super users.
Over time, it’s critical to monitor changes in customer usage behavior. This way you can identify problems and opportunities at both an aggregate level (to gauge overall business performance) and at the individual customer level (to identify, for example, if a customer might be at high risk of churning).
SEGMENTS BASED ON QUALITY OF USAGE:
While quantity and frequency of usage can certainly be valuable behavioral segments, high usage does not always translate into most value delivered, both to the customer and ultimately to your business.
For example, a SaaS customer might have a ton of product usage behavior, but in reality things might not be as peachy as they appear on the surface. Perhaps they are not using the product as effectively as they could be; they are only leveraging a fraction of the most important features or capabilities in the solution; or they are only using the product now because they have to, but are unhappy and looking to switch to a competitor in the long-term.
While this customer might fit the criteria of a “heavy user” segment, in reality they aren’t getting enough value and are likely to be at high risk of churning.
5. OCCASION OR TIMING-BASED
When are customers most likely to make a purchase or engage with a brand?
- Universal occasions apply to the majority of your customers or target audience. Holidays and seasonal events are a typical example, where consumers are more likely to make certain purchases around the holiday season or at certain times of the year.
- Recurring-personal occasions are purchasing patterns for an individual customer that consistently repeat over a period of time, which could range from annual occasions such as birthdays, anniversaries or vacations, monthly purchases such as business travel or even daily rituals such as stopping for a cup of coffee on the way to work every morning.
- Rare-personal occasions are more irregular and spontaneous, and thus more difficult to predict, such as attending a friend’s wedding.
TARGETING SEGMENTS BY SPECIFIC TIMES OF DAY OR WEEK, ETC.
Behavioral patterns in individual customers’ preferences for reading email, browsing social networks, researching products and consuming content are all examples that can be leveraged to help marketers understand the best days and times to target different customers with offers.
TARGETING SEGMENTS BY TIME ELAPSED SINCE PRIOR PURCHASE OR ACTION
For example, a customer could be much more likely to purchase again within the weeks or months following an initial purchase, or conversely, much less likely to make an up-sell or cross-sell purchase until a certain amount of time has passed since an initial purchase or renewal.
6. CUSTOMER SATISFACTION
How satisfied are your customers, REALLY?
NPS surveys and other similar customer feedback mechanisms are certainly valuable methods for helping to gauge customer satisfaction, but you can’t rely on these alone.
That’s because typically only a fraction of customers participate. Also, regardless of the frequency of running surveys, a significant amount of time is always left in between data collection points, during which a satisfaction level can drastically change. And finally, NPS as a customer experience metric does not accurately reflect customers’ changing needs and experiences at different stages of the customer journey.
There are many data sources available – such as call centers, support portals, help forums, billing, CRM systems, and social media – through which customer behavior can be tapped to measure a customer’s true satisfaction at any given time.
By segmenting your customers by satisfaction, you can decide on the appropriate set of actions for each segment and then quantify and prioritize them by their potential business impact.
7. CUSTOMER LOYALTY
Who are your most loyal customers? How can you maximize their value and find more customers like them?
Your most loyal customers are the most valuable assets to any company (arguably with the exception of its employees.) They are cheaper to retain, usually have the highest lifetime value, and most importantly, can become your biggest brand advocates; the ultimate goal of every customer relationship.
Through behavioral data, customers can be segmented by their level of loyalty to help you identify your most loyal customers and understand their needs to make sure you are satisfying them.
A few classic B2C examples of such programs include airlines’ frequent flier programs, “platinum” credit card members, or preferred guests at hotels and casinos.
Use customer loyalty behavioral segmentation to yield valuable answers to important questions such as:
What are the key factors and behaviors along the customer journey that lead to loyalty?
Which customers are the best candidates for loyalty or advocate programs?
How can you keep your most loyal customers happy and maximize the value you get from them?
8. INTEREST
What are different customers interested in?
Interest-based behavioral segmentation can deliver personalized experiences that keep customers engaged and coming back for more.
Netflix, Amazon, and Spotify use recommendation engines for suggesting content and products entirely based on customers’ behavioral interests.
One of the great advantages of interest behavior is the ability to implicitly connect specific interests with other potential related interests.
9. ENGAGEMENT LEVEL
How engaged are your customers? Who are your most and least engaged customers?
How you define “engagement” will vary based on your company and your role. If a customer has positive experiences with your brand, and as a result is willing to interact more frequently and spend more time engaging with your brand, this is usually a good sign of positive outcomes to follow.
The more time a customer spends engaging with your brand and having positive experiences, the more likely that:
- Trust is increasing.
- A positive perception of the brand is developing.
- Their brand relationship is strengthening.
- They are considering making a purchase.
Engagement is a valuable metric in both pre-and-post-purchase realms of the customer journey.
You can measure engagement on the individual customer/contact level, on the overall company or account level, or both. Segmenting your customers by their level of engagement is hugely valuable for understanding which customers are most and least engaged with your brand at any given time and why and, most importantly, figuring out what you’re going to do about it.
10. USER STATUS
What type of relationship do different customers have to your business?
While there are many different possible user statuses you might have depending on your business, these are a few of the most common examples:
- Non-users
- Prospects
- First-time buyers
- Regular users
- Defectors (ex-customers who have switched to a competitor)
LEVERAGING THE RIGHT TECHNOLOGY
Finally, without the right technology in place, it is incredibly difficult (bordering on the impossible) to be truly successful with behavioral segmentation today.
Google analytics, advertising platforms such as Google Adwords and Facebook, and marketing automation systems are all examples of tools you can (and should) leverage for analyzing, segmenting and targeting customers based upon behaviors.
However, these tools can only deliver a fraction of the value and capabilities covered in this post. They do not provide you with the cross-channel journey data you need to build comprehensive behavioral segments or the journey-driven insights you require to orchestrate actions based on each customer’s overall experience.
Customer journey orchestration software enables you to improve personalization decisions across each of your touchpoints, providing a seamless experience to every customer. Sophisticated solutions allow you to activate new or update existing audiences defined by customer attributes and behavior. Leveraging a platform that prioritizes journeys, rather than interactions within siloed channels, will help your enterprise deliver the best possible experience to customers based on their unique goals and needs.