Five best practices in behavioral segmentation
How should organizations embed segmentation to become highly relevant?
By Talha Omer
To marketers, it is fairly well established that enticing all customers with the same offer or campaign is useless. The No. 1 reason why people unsubscribe or opt-out is due to irrelevant messaging. A while back marketers moved to grouping customers on the basis of certain metrics that gave a bit more context to the marketing strategies. Example: offering an entertainment service to customers who: 1. use a lot of MMS for sending videos and pictures, 2. download songs using GPRS, and 3. have a very high ARPU (average revenue per user).
Segmentation drives conversion and avoids erosion. That’s a bold statement, but the reality is that “monotonous” subscribers do not come to your organization to make an activity. Your organization does not exist for a singular reason either. The core drivers of behavior are very different for each core group of subscribers. When you look at all that in aggregate you get nothing. You think “average duration of calls” means something or “revenue of calls” and “overall duration of calls” give you insights, but do they? Probably not much.
The problem is that all business reporting and analysis is data in aggregate, e.g. total number of daily calls, total daily revenue, average monthly call duration, total weekly volume of GPRS, overall customer satisfaction and many more — gigabytes of data reports and megabytes of analysis, all just aggregates. The tiny percent of time that the analyst does segmentation, it seems to stop at ARPU. Segmenting by ARPU gives you segments, but they are so basic that you will not find anything in there that will get you anything insightful.
So how can you make sure you are highly relevant to drive conversion and avoid erosion? If you want to find actionable insights you need to segment your data. Only then will you understand the behavior of micro-segments of your customers, which in turn will lead you to actionable insights because you are not focusing on the “whole” but rather on a “specific.”
The power of segmenting your subscribers is that you get a 360-degree view of your customer while exploring such questions as, “Whom am I going to sell a certain product to?” To answer this and similar questions, we’ll focus on the five best practices in behavioral segmentation.
Best practice No. 1:
First, discover the client’s business. Start with questions, not the analytical model.
Business leaders feel frustrated when they don’t get insights that they can act on. Similarly, from the analyst’s point of view, it can’t be fun to hold the title of “senior analyst” only to be reduced to running aimless analytical models. Hence, the most important element of any effective analytics project is to discover the client’s business dynamics by asking real business questions, understand those business questions and have the freedom to do what it takes to find answers to those questions by using analytical strategies.
You need to ask business questions because, rather than simply being told what metrics or attributes to deliver, you need business context: What’s driving the request for the model? What is the client really looking for? Once you have context, then you apply your smart analytical skills.
The business questions should have these three simple characteristics:
- They should be at a very high level, leaving you room to think and add value.
- They should have a greater focus on achievable steps because each step enables you to focus your efforts and resources narrowly rather than implementing universal changes, which making every step easier to accomplish.
- They should focus on the biggest and highest-value opportunities because the momentum of a single big idea and potentially game-changing insight will incite attention and action.
The goal of business discovery is to pull an analyst up to do something he does less than 1 percent of the time in the analytics world — look at the bigger business picture. It is nearly impossible to find eye-catching actionable insights if you just build a model straight away. Efforts will be wasted and the project will stall if you don’t start by asking business questions. Along with wasting resources, failing to ask the right business questions up front risks creating widespread skepticism about the real value of segmentation analytics.
The reason for asking business questions can be summed up in one word: context. We are limited by what we know — and what we don’t know.
Best practice No. 2:
Reconcile the data, build business-relevant segments. Have an open mind; too many or too few natural segments may be just right.
Big data is getting bigger. Information is coming from instrumented, interconnected systems transmitting real-time data about everything from market demand and customer behavior to the weather. Additionally, strategic information has started arriving through unstructured digital channels: social media, smart phone applications and an ever-increasing stream of emerging Internet-based gadgets. It’s no wonder that perhaps no other activity is as much a bane of our existence in analytical decision-making as is reconciling data. Most of the things don’t seem to tie to anything; each time you present the outcomes, the executives are fanning the flames of mismatched numbers.
All of the attributes created for any analytical project are available to the stakeholders via standard BI reporting — simply compare the attributes with the reported numbers. If the numbers are off by less than 5 percent resist the urge to dive deep into the data to find root cause.
A comprehensive agenda enables the reconciliation of the numbers. A senior analyst at one company, for example, stated that they were blindsided when it came to reconciling the data. But once they started checking every number to the ones reported to the business they found themselves able to go forward.
Cluster techniques transform data into insights. Cluster techniques are a powerful tool to embed insights by generating segments that can be readily understood and acted upon. These methods make it possible for decision-makers to identify customers having similar purchases, payments, interactions and other behavior, and to “listen” to customers’ unique wants and needs about channel and product preferences. As an analyst, you’ll no longer have to hypothesize the conditions and criteria on which to segment customers. Clustering techniques provide a 360-degree view of all customers, not just a segment of high-revenue customers.
Running the statistical process for clustering customers creates clusters that are statistically significant. The question then becomes, Are the clusters significant from a business perspective? To answer that, ask the following questions:
- Do you have enough customers in a segment to warrant a marketing intervention?
- What, and how many, attributes do they differ on? Are those attributes business critical to warrant different segments?
Once the above questions have been sufficiently answered, the project team can determine if there are customer behaviors important enough from a business perspective to explain a marketing initiative.
Best practice No. 3:
Refresh the segments. When to revise segments to ensure they are always actionable.
Segmentation sets the stage for how the organization is going to behave for a given time period. This is analytics at its best and one of the most resource-intensive analytics initiatives that will add huge value. As executives start using segmentation more frequently to¬†inform day-to-day decisions and strategic actions, this increasing demand will require that the information provided is recent and reliable. Therefore, it is necessary to keep the segments up to date.
A senior executive told me his company built a perfect statistical model that created highly actionable segments, but it soon became useless because a majority of subscriber profiles had changed over time. This was due to the dynamic and competitive market the segmentation was focused on. In such environments, new campaigns, pricing and products are launched every day, causing instant behavioral changes and hence accelerating the model decay. The executive said they had to streamline the operational processes and automate them so that the company could rebuild segmentation every month. At one time they even considered drawing real-time segmentation since the benefits they reaped were unparalled.
Therefore, to keep the three gears moving together — up-to-date segmentation, actionable insights and timely actions — the overriding business purpose must always be in view. New analytic insights are embedded into the segments as business changes, as new products are launched and as new strategic developments happen, and a virtuous cycle of feedback and improvement takes hold. It starts with a foundation of analytical capabilities built on organizational context that delivers better insights, backed by a systematic review to continuously improve the decision process.
Best practice No. 4:
Make segments come alive. Analyze segments to drive actions and deliver value.
New methods and tools to embed information into segments — analytics solutions, inter/intra-segment highlights, psychographic and demographic analysis — are making segments more understandable and actionable. Organizations expect the value from these techniques to soar, making it possible for segments to be used at all levels of the organization, e.g. for brand positioning or allowing marketers to see how their brands are perceived.
Innovative uses of this type of information layering will continue to grow as a means to help individuals across the organization consume and act upon insights derived through segmentation that would otherwise be hard to piece together. These techniques to embed insights will add value by generating results that can be readily understood and acted upon:
- Intra-segment analysis evaluates the preferences of a segment, such as the highest proportion of revenue is realized from calls during the night, etc. Measuring the proportion of traffic of an attribute for a segment will tell you the inclination and motivation for that segment.
- Inter-segment analysis reflects actual rank of a segment for an attribute across all segments — a technique that would give you the best/worst segments with respect to a particular attribute, e.g. highest revenue, second lowest GPRS users, etc.
- Psychographics and demographics analysis is a fantastic way to understand the demographic (male, female, age, education, household income) and psychographic (Why do they call during the night? What do they use Internet for?) makeup of any segment. For example, if you are interested in the technology savvy segment, targeted surveying of each segment and analysis will tell you what zip codes these subscribers are likely in, why they are using so much GPRS, what websites they visit, etc.
Once you establish the segments, you may then merge and/or discard segments that are business insignificant. The rule of thumb for merging segments: If you believe that you cannot devise distinctive campaigns for two segments, merge them.
These methods will make it possible for decision-makers to more fully understand their segments of subscribers and boost business value. Businesses will be able to listen to customers’ unique wants and needs about channel and product preferences. In fact, making customers, as well as information, come to life within complex organizational systems may well become the biggest benefit of making data-driven insights real to those who need to use them.
Best practice No. 5:
Speeding insights into the segmentation process. What segmentation-focused companies do.
Most often, organizations start off their segmentation analysis by gathering all available data. This results in an all-encompassing focus on data management — collecting, reconciling and transforming. This eventually leaves little time, energy or resources to focus on the rest of the segmentation process. Actions taken, if any, might not be the most valuable ones. Instead, organizations should start in what might seem like the middle of the process: implementing segmentation by first defining the business questions needed to meet the big objective and then identifying those pieces of data needed for answers.
By defining the business objective first, organizations can target specific subject areas and use readily available data in the initial analytic models. The insights delivered through these initial models will identify gaps in the data infrastructure and business processes. Time that would have been spent collecting and pre-processing all the data can be redirected toward targeted data needs and specific process improvements that the insights identify, enabling a successful segmentation.
Companies that make data their overriding priority often lose momentum long before the first iteration is delivered, frequently because a data-first approach takes too long before delivering an actionable segmentation. In cases where the market is very volatile, by the time you deliver the segments, time for “refresh” arrives and you are back to square one. By narrowing the scope of these tasks to the specific subject areas needed to answer key questions, value can be realized more quickly, while the insights are still relevant.
Organizations that incorporate segmentation must be good at data capture, processing and have plenty of space available in their warehouse. In these areas, they must outperform the competition up to tenfold in their ability to execute. Time to market is very little. Market dynamics change quickly in highly competitive and saturated markets.
Set Yourself Up for Success
Remember, segmentation analysis is a tough game. The good news is that this is very far from daily business reporting and analysis. It requires more intense and focused effort, and it truly is advanced analysis. Not every company will be ready to leverage all of the above practices. The reader is encouraged to perform a self-critical analysis of your own abilities before you go into segmenting your subscribers, even though the upside is literally huge sums of money and a strategic advantage that will influence your fundamental business strategy in a very positive way.
For your company and business, maybe revenue from off-net calls is not as important as duration of calls, the number of MMS, the volume of GPRS or bundled subscriptions. Understand what your business is, what are the areas of strategic focus, and then segment away.
Likewise, the more you understand what your customers are doing, the more likely it is that you’ll stop the irrelevance of your marketing campaigns. You’ll also likely find the optimum balance between what you want to have happen and what your customers want. You’ll make happier customers, who will in turn make you happy.
Summing up, start on the path to segmentation, keep everyone focused on the big business issues and select the business problems that segmentation can solve today with new thinking and a framework for the future. Build on the operational and strategic capabilities you already have, and always keep pressing to embed the insights you’ve gained into your business strategy.
Talha Omer is an analytics professional and researcher. He currently serves as an analyst at a major telecommunication company. He holds a Master’s degree from Cornell University in operations research. He can be reached at firstname.lastname@example.org.