The customer is always right. Uh, no... what if the customer wants something that’s bad for your business? Then, that customer is right… and wrong. Problem is, how will you know? This is what having a customer data strategy is all about. Deep, effective analysis of customer data can yield insights that help your business grow by focusing on the right customers with profitable products and services you know they want. Executing a successful customer data strategy can be challenging, but there are proven best practices to help you leverage customer data for increased profitability.
First, the Customer Data Strategy Must Align with Your Business Strategy
There is no such thing as a standalone customer data strategy. Well, there is, but it’s not much help to you. Harnessing customer data means putting it to work in the service of your overall business strategy. Let’s say you are in the banking industry. Your business strategy might be to gain as high a share as possible of a customer’s financial service needs. Your path to achieving this goal is to upsell additional products and services. The checking account holder becomes a credit card customer, starts to utilize the account, then becomes a buyer of an auto loan, then an investment services client, and so forth.
Your customer data strategy needs to support the bigger goal of successfully upselling your customers. Customer data is essential, because without it, you will waste a lot of money trying to upsell the wrong customers with the wrong products. The issue is that even though you already have a customer, there is a quantifiable cost to the upsell process. It may involve sending direct mail advertising, calling them on the phone and on and on. It’s not free. You want to ensure the upsell “cost of customer acquisition,” is as low as possible.
To profitably upsell banking services, you need to build the logic to determine the most qualified segments and then score their propensity to acquire new product opportunities. For example, if a customer only has $20 in his account and never uses it, then he is a not a good candidate for an investment advisory service. At least, he doesn’t appear to be one... analysis has shown that it can be far more profitable to get a current customer to first utilize a “zombie account,” before upselling the “next best” investment offer. This is where customer analytics can help.
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Is Your Customer Analytics Treading Water?
You just finished analysis on your entire customer base. You looked at their demographic characteristics, behaviors, interactions, financial holdings, and cross-referenced it with valuable external data sources. Voila, your upsell is in the bag. Maybe, maybe not. You have a good idea of who to target and with what. Now you must avoid “treading water” by following the same routines as everyone else.
Your competitors already target your customers and market to them in the same way you do. When your customer gets an ad from your company for a new service, you compete with everyone else for his business even though he’s already your customer. How can you stand out?
One secret to success is to use customer data in ways that stretch beyond the normal boundaries. For example, you can use basic analysis to identify potential credit card customers. But by adding data for social media sentiment and past purchase behaviors, you can design more relevant, tailored, and dynamic digital customer experiences. You might see that the customer likes to travel and the data indicates they may be taking a trip soon. You can now provide a tailored experience around travel products and market the airline reward credit card to this person. This may seem obvious, but the industry is notorious for dumping money into overly broad campaigns. Using data for more tailored experiences can be the difference in tens of millions in revenue.
The Customer Data Strategy
A customer data strategy takes some effort and investment to realize. Even if you’ve already started, the following practices are ways to improve:
- Keeping an open mind—this is a subjective, but an important aspect of being more customer-centric. It’s smart to be open to new ways of looking at customer data and exploring new uses. Seemingly irrelevant data streams might make a big difference in your outcomes.
- Building a data warehouse and/or data lake—to perform customer analytics, you need to have all your customer data, along with external data sources, in a single place. This usually means setting up a data warehouse, a data lake, or both.
- Setting up the analytics capability—you need specialized tools and people to analyze customer data. This should include the means to visualize data and report on analytical findings.
- Implementing Master Data Management (MDM)—for best results, your data should be clean. MDM takes care of deduplicating your records, among other data quality management processes. This helps you avoid miscounting the size of your customer list and other costly mistakes.
A customer data strategy can be a powerful element in your business growth plan. Knowing your customers helps you grow the relationship and retain them over time. It enables profitable upselling and more. We have worked with many companies on the design and implementation of customer data strategies and customer analytics. To learn how we can help you become more data-driven in your customer relationships, let’s talk.
Written by Kevin Claybon
Senior Principal, Customer Analytics
Topics: customer experience