Customer analysis may be the most important market segmentation analysis you can perform for your business. Without it, trying to find new customers, or selling more services to existing customers, will likely have limited success. Unless you really get to know your customers, your business won’t be a in position to meet their needs.
The traditional approach to customer analysis is often driven by marketing because this team needs to understand the customer to target them directly. But in performing customer segmentation analysis, marketing teams have too often limited themselves to tools that access only a small fraction of the information available for customer analysis—like surveys or digital search records.
Marketing teams, like all other groups, do much better with more customer information. Much of this insight is buried in other departments, like operations, customer support, finance, and sales.
Businesses need to mine information from everywhere in their organization to make truly smart, strategic, data-driven decisions. Doing so can enable companies to develop much richer and more accurate customer segmentation analysis from which to build multi segment marketing. Employing advanced data segmentation techniques in all types of marketing research and customer segmentation analysis can mean the difference between sure success and stagnation.
First some definitions
What is customer analysis? Customer analysis is a process where companies try to infer customer behavior based on data they have collected for the purpose of informing product, marketing and sales decisions. It is closely tied to market segmentation analysis.
What is segmentation analysis? Segmentation analysis
is a process of splitting a market into sub-segments based on similar characteristics, with a goal of finding high potential opportunities for growth.
What is benefit segmentation? Benefit segmentation uses the specific benefits or outcomes associated with a company's product in order to divide customers for a target market.
So, what precisely should analytics be used for? The short answer is, everything. There’s not much that can’t be better understood, more intelligently used, or made more efficient by integrating good customer segmentation analysis.
Most businesses should first and foremost use analytics for reporting. It’s crucial that your organization have access to consistent data everyone agrees is correct and up-to-date. An ad hoc or inconsistent approach to data reporting will inevitably create data silos, which will, in turn, lead to different versions of the truth, some of which will be treated as gospel within your organization.
Such multiple versions of the truth can only increase friction between teams, which in turn creates confusion, delays, and/or questionable decision-making. Further, data siloes often lead to, or worsen, a culture of corporate isolation and collaborative breakdown—all of which will make ad hoc reporting and data silos more prevalent. It’s an ugly, dangerous, and wholly avoidable cycle of data misuse and misunderstanding.
The second is to report only with specific aims in mind. Running reports just to have some numbers to pass around at that next big meeting is a temptation that should be avoided. Indeed, since reporting is so crucial to business success, it should only be performed when you’re looking for detailed information on how well—or how poorly—your campaigns and other initiatives are performing. Reporting should answer specific questions, in other words.
And the only way to be certain your company is accessing accurate, usable data is through using a system enabling automated record linkage between lower-level data sources and top-level reporting. This will help you understand exactly why you’re seeing certain high-level results. If your reporting lacks automated connections between source data and reporting, you will experience extra friction whenever you try to perform