The Big Break: Identifying Patterns in Your Customer Portfolio
As any pool shark will tell you, winning a game of pool means understanding the angles, envisioning the possibilities, and staying one shot ahead. Succeeding in business is no different.
Winning a match against the competition takes a mix of strategic thinking, mastery of the landscape, and excellent timing. With so much at stake – cash flow, profit margins, customer satisfaction, retention and investor relationships – it’s no wonder that navigating risk effectively and identifying opportunities can make you feel like you’re sweating in a smoky pool hall with all eyes focused on your next move.
Customer Segmentation Definition
Customer segmentation is the process of dividing the available data you have on your customers into categories, and then analyzing those categories to glean insight into buying patterns and drive top-line growth. There are endless ways to mix and match data points for customer insight, but finding and aligning on a customer segmentation strategy that positively correlates with purchase behavior requires a strong command of enterprise data, a dash of math, and a sprinkle of art.
How Finance Contributes to Customer Segmentation
What does customer segmentation have to do with enterprise finance? Returning to your pool table, take a look inside the rack. All the balls seem neatly grouped together. It’s like your customer data; for now, the chaos of the data is artificially contained in the rack, and it looks orderly. Think: CRM, ERP, back-office system. But your data probably isn’t orderly. It may be hidden in some sleepily contained system, possibly aging, waiting to be segmented effectively and wielded in a winning game. In order to win, you have to break into your data and start taking shots.
Finance arguably owns more insight than any other group. You have a deep, familial intimacy with corporate controls, systems and technology, budgets, customer behavior, resource requirements, processes and organizational goals. Your first move is the data break. The balls will scatter, and your job is to pick stripes or solids and get them into the appropriate pockets. Your customer data will likely be just as disordered and overwhelming, but segmentation is the pool shark business leader's strategy to get there.
3 Benefits of Customer Segmentation
First, a look at the game itself. What are the primary benefits of a customer segmentation solution? Finance has the power to drive three things: increased cash flow, collaboration, and profitable growth with analytics.
1. Increased Cash Flow
Uncategorized, unclean, and unmanaged customer data presents obstacles to increasing cash flow. Segmented appropriately, clean data will command unique treatments and targeting strategies to uncover customer buying patterns. Are your customers in B2C retail on the slow-pay track? Dedicate resources to keep an eye on them or create an automated industry alert to use in the sales process before extending credit, to reduce DSO. Do you find that you have the lowest market penetration in Canada, but that Canadian customers are the least likely to default?
2. Increased Collaboration with Marketing & Sales
Segmentation allows you to define and align on the key attributes that unite your customers, but performing it in a Finance silo, perhaps as an exercise in departmental efficiency, may result in a poor customer experience. Have you ever made an executive decision to dedicate more time and resources to accounts that you later discovered were not being marketed to or managed effectively because they were not deemed a priority? Other departments may have different segmentation strategies – and likely their own data sources and visualization techniques as well. Collaboration isn’t just a benefit for companies; it’s a benefit for customers. Work together to define the messaging, resource constraints, treatment and service package as a management unit that commands the greatest value from and for your customers.
3. Profitable Insights
Profitable growth is the byproduct of effective strategy, and what strategy can be effective without galvanizing the opportunities within your current landscape? Segmentation is more than uncovering customer buying patterns; it’s also about action and forward movement. For example, you see that your least profitable customers are taking up 80% of the time of your collection agents and 50% of the time of your customer service staff, and that you have 300 sales account managers dedicated to them to manage their influx of complaints and requests. Yet, they comprise approximately 2% of your total customer base and incur negative returns. Or, in another example, segmentation efforts based on aging reports alone may keep your receivables from sinking your ship, but they won't help you maximize opportunities or innovate on your approach to risk management. That kind of fluid, cross-functional customer insight can make for more profitable and productive operations.
4 Customer Segmentation Assumptions to Avoid
Assumption #1: Only Visible Customer Data is Useful
A Finance leader may understand the intricacies of data visibility and accuracy better than most. After all, SEC filings and Sarbanes-Oxley are legally binding reminders of how important visibility and accuracy are. Yet bias is inherent in data analysis. Embracing customer data visibility means understanding and accounting for the quality, composition, velocity, origin, and human manipulations of the data within your scope of decision-making. Ask yourself, "What's not visible here?"
The reality may be that your data is housed in different systems that do not talk to each other. Alarmingly, only 38% of companies share results of their analytic insights outside their departments, according to Dun & Bradstreet's 2016 Enterprise Analytics Study. Questioning what's visible early and often is a true pro tip. Once you can see all the balls on the table, the possibilities open up. You aren't limited to looking at your customer segmentation strategy within the realm of financial ratios or payment behavior. A wealth of CRM data, industry profiles, social feeds, contact history, and business linkages will enrich the way in which you run the business.
Assumption #2: All Data is Equal (and More is Better)
Each time a business transaction takes place, be it a customer service call, a supplier shipment, or a stocked piece of inventory, a record is (hopefully) generated somewhere. It goes without saying that these records should be procedurally linked within an ERP or other system. When a company goes to link any of its clean data with systems and data sets that aren't as closely scrutinized, things can get messy - the CRM, for example, can be a place fraught with bad data. Ensure that duplicate records are accounted for, that data cleansing processes are understood and that linkages between departments and groups are identified prior to any segmentation efforts.
Another temptation when performing enterprise-wide customer segmentation is to assume that more is better but layering too much data may yield a false narrative. For example, you may decide to further segment and profile your customers utilizing their full credit limits by also looking at their likelihood to go out of business. Add information such as a score for propensity to buy and customer satisfaction, and your segmentation efforts can soon lose focus and gain complexity. So, take some time to revel in the analytics available to you and establish what the best metrics are for measuring your desired path.
Assumption #3: The Past is More Important Than the Future
Behavioral and descriptive analytical exercises typify the extent of many organizational efforts to segment customer data. It's the data devil you know, after all. It's far easier to segment your organizational data based on what's currently inside your systems. Just like any good game of pool, though, you have to develop an intuition about your opponent's next move and how you will need to adapt.
Predictive and prescriptive analytics ask your data, "What next?" Don't be afraid to do some scrappy modelling on optimal pricing trends or on supply chain formations to scope out what the future might look for you. While what you have in your history is valuable, the audience watching you play pool cares only about your next move.
Ultimately, avoiding these common customer portfolio mistakes in preparing to segment your target audience will significantly increase your chance of doing it right the first time.
How to Improve Customer Segmentation Analysis
When you start seeing wins from your effective customer insight strategy, it may be tempting to look at them in celebratory isolation. Yet, the true pool shark isn't a pool shark until a pattern of winning has been established and can be shared with others.
The final step in an effective customer segmentation strategy might be the most important of all: reporting on your results.
Finance lives and breathes reporting. No other group is more familiar with the importance of data quality, visibility, and governance. Indeed, finance is uniquely poised to understand and use customer insight to drive value. Finance's close eye on the management of daily business, alignment of employee incentives, and establishment of strong controls are all deeply impacted by the portfolio segmentation strategy.
Here are a few efficient ways to determine the effectiveness of customer segmentation analysis and reporting.
1. Simplify Performance Insights
Possibly one of the most difficult aspects of conveying information using data is effective communication. Finance is deeply familiar with the importance of choosing the right metrics to report on and the art of conveying them in an understandable way. Yet, it's extremely easy to under-communicate, mis-communicate and to over-communicate. Choosing and monitoring the right set of customer metrics is critical to change management and effective reporting. Operate with the mindset that you’re seeking to find the fewest possible visualizations, metrics, and data points to convey a single view of the truth about how your customer insight strategy is performing. Be careful about pre-defining what you want your story to be and using the data to back that story up.
2. Visualization of Customer Segmentation Data
Visualization is much more art than science. Behind effective customer data visualization, again, is the art of strong communication. When you create your final reports, think about both your audience and how meaningful the information is. Strive to make any of your data visualizations graspable within 10-15 seconds, or less. The richness of the story you need to tell with data will be lost if your audience is struggling to interpret your graphs and pie charts.
3. Flexible Customer Segmenting Reports
Retaining simplicity and strong visualization takes powerful discipline. While reporting on trends over time is crucial to business success, it's equally important to be able to drill down into patterns or move up a level to identify the behavior that's driving your portfolio segmentation strategy. Technology and integration play a strong role in making your reporting efforts simple enough to be meaningful while flexible enough to provide more information where needed.
4. Deliver Meaningful Customer Insights
Lastly, it's critical to deliver your reports in a meaningful way. While spreadsheets and paper reports continue to be used in day-to-day business life, it makes sense to implement flexible tools to share and interpret data on a cross-functional basis. Tools such as cloud-based dashboards continue to gain popularity due to their simplicity and ability to be customized. Co-creating and driving excitement behind an executive dashboard that illustrates the effectiveness of the portfolio segmentation strategy will drive both alignment as well as a mutual understanding of the business reality.