If businesses had the time and ability to meet each of their many customers, they certainly would. It would provide invaluable information into exactly who they are, what motivates them to make purchases, their spending behaviors, and so much more. Unfortunately, that isn’t reality. Businesses must rely on buyer personas – semi-fictional representations of ideal customers based on data from existing customers – to guide the direction of marketing and sales.
Buyer personas are a great starting point for better understanding customers and attracting new ones, but they come with many pitfalls: a survey conducted last year found 60% of business respondents were unhappy with the fact that their buyer personas were based on sales intelligence and product management, as well as company goals. To really hone in on customer behavior, businesses must set their own goals aside and come face-to-face with their data. Get started with these four steps:
#1: Do a Data Cleanup
If your closet is a mess, how easy is it for you to find quality pieces to wear? Probably pretty hard. The same scenario applies to data as well: discovering quality information about existing customers is impossible to do if your data is a mess. Performing a data cleanup should be the first priority for any analysis initiative.
Data cleanup includes, but is not limited to, reformatting fields, standardizing addresses, de-duplication, fixing email domain spelling errors as well as other typographical errors, abbreviation harmonization, and more. Most of this is done through an audit, which uses methods to determine data anomalies as well as contradictions.
A great way to halt getting to know your true customers is by offending them or giving any indication that you don’t know who they really are. Think about it – connecting with customers is all about personalization and encouraging them to stay loyal despite having plenty of other options. Without clean data, businesses run a great risk of having incorrect values in first name, last name, and even salutation fields. Some employees even use these fields to make personal notes that they never suspect will be seen, such as “Jane Doe Bad Tipper” or “Sue Smith Rude Customer.” These errors can render personalized campaigns not only useless but insulting as well.
Companies may think their data is accurate and providing good customer demographics because they are using a CRM. While CRMs should provide customer snapshots by collecting purchasing and marketing information in one place, it only happens if they are executed correctly. Even a dedicated, robust CRM may collect inaccurate information simply through typographical errors or intentionally false information entered by the customer. Add the tendency for sales representatives to keep “secret” databases and lists outside of the system, and data can easily become jumbled or lost. Performing a data cleanup can offer a fresh start, along with the confidence that comes from knowing that the data being used for personalization is truly accurate.
#2: Perform Data Appends to Enhance Existing Lists
Sometimes, the key to finding your real customers lies in filling in the blanks on existing data. This is especially true for small businesses or startups that are beginning to collect customer information but are nowhere near the point of having enough data to truly create a good buyer persona.
When these types of scenarios arise, data appends can be a great way to find out more about current customers. Complex and diverse outside sources are gathered based on criteria a business would like to target, such as household data, and are appended to existing customer data. Some examples of data appends include phone numbers, age, IP addresses, income, children, business size, number of employees, industry type – the options are endless! Businesses can even take an address and reverse-append the information to find contact information. These data appends allow businesses to jumpstart their customer profiling and quickly move on to appropriate marketing decisions.
True personalization can increase sales and return visits by 20%.
#3: Narrow Down Location by Performing Profile Reports
For direct marketing efforts where spending is limited, determining the best geographic areas to target can optimize budgets and help gain a better understanding of valuable customers. This can be done through consumer or business profile reports, which take customer lists and clean them by predominant zip code areas. These profile reports eliminate outliers and then determine common predominate demographics or firmographics that highlight key customer elements. Penetration rates of these customers are also determined to score a list of best customers in an area. In addition to learning where the most valuable customers live, an added benefit of this service is its cost: typically, it is inexpensive to append and provides a concise analytical report that helps businesses make better marketing decisions long-term.
#4: Locate Valuable Customers Through Segmentation and Analysis
One of the most powerful predictors for purchasing behavior is analyzing how recently a customer made a transaction. When paired with two other key indicators – frequency and monetary—it becomes an RFM segmentation. By using existing sales data, RFM segmentations can pick out which customers will be the most valuable long-term. It’s also a great way to either validate current customer assumptions or correct buyer personas before marketing budgets are drained on the wrong people. Information gathered from these segmentations can be used to make further decisions on cross-selling, renewal campaigns or even just marketing plans for the next quarter.
RFM segmentation easily adjusts to many types of products and industries. For example, a company may choose to look at the frequency of web site visitors as part of their analysis or take items saved to a wishlist but not purchased as part of their monetary analysis. While not the be-all and end-all of analysis, RFM segmentation can help management make decisions best for customer growth and can be used as a predictive model when other options are not available.
While looking at data can seem intimidating and scary, it’s worth the work: true personalization can increase sales and return visits by 20%. The more time businesses spend avoiding their data, the farther away they get from meeting their real customers.
If you are struggling to make sense of the customer data you have, the C.TRAC Direct team may be able to help.
