The Importance of Knowledge-based Customer Recognition

Most of us have experienced the acute embarrassment of forgetting someone’s name. It can be awkward, uncomfortable, and downright offensive.

For a cataloger, being unable to recognize a customer goes far beyond faux pas. Inaccurate customer data leads to wasted resources, mediocre marketing efforts, and unhappy consumers.

Customer and customer-value recognition – the ability to recognize a customer’s value to the business as accurately, quickly, and thoroughly as possible in every interaction – is vital to the success of any business. But an increased focus on customer lifetime value has yielded disappointing results. Moreover, all customer data integration approaches are not created equal.

It sounds simple, but in reality, dozens – even hundreds – of factors might determine customer value. Each layer provides additional insight into consumer needs and behaviors. Such recognition allows businesses to discern and anticipate the specific needs and desires of their customers to better serve – and sell to – each one.

Unfortunately, most businesses don’t do this well. One study conducted by Bain & Co. revealed that, of the over 350 firms surveyed, 80% claimed to deliver a “superior experience” to their customers. But when the customers in question were surveyed, they revealed that only 8% of the firms actually succeeded. So, what kinds of tools help a business really know its customers?

There are many approaches to customer recognition, and to streamlining dozens of disparate data sources. Some businesses try to gather and manage customer data on their own, essentially making the best of what they’ve got. Of course, if you’ve ever called an acquaintance by the wrong name, you already know that an educated guess can backfire.

Even if a business could have access to perfect customer transaction information, that information would still provide only a glimpse of overall customer behavior. What are your customers doing when they’re not interacting with your business? Who else are they buying from? What kind of relationships do they have with your competitors? No transaction history can answer those questions. Only external, multisourced, historical data can do that.

Another approach to customer recognition is to use a knowledge-based system to guarantee information accuracy. Such a system relies upon a comprehensive, well-maintained database to complement what a firm already knows about its customers, with pre-aggregated data and insights that are otherwise not visible to the firm.

A knowledge-based customer recognition system ensures accuracy, freshness, and richness that is otherwise impossible to achieve. It provides the customer-value insight that your business or organization needs to recognize perfect candidates for up- or cross-sells and drive successful retention initiatives. Knowledge-based recognition is the key enabler to predicting, prioritizing, and optimizing investments of all types.

Today, knowing customers and their value is more important – and more difficult – than ever. Modern consumers can swing from one end of the value spectrum to another, scrimping on some items and splurging on others. A customer can be high value in some areas, but not in others. These pockets of inflection present increased customer value recognition challenges.

One of those challenges is data complexity. Customer data is complex due in part to the nature of names, how we use them, and how businesses record them. For example, one individual name can vary with first name, last name, middle name, initials, nickname, maiden name, married name, professional title, academic title, and suffix. Remembering one name is hard enough. Try remembering six – all for the same person.

Complexity and accuracy issues also apply to customer contact information – address, phone number, and e-mail lists. This data is ultra-dynamic, impacted by the many changes consumers go through in the course of their lives.

A study completed in 2002 by The Data Warehousing Institute titled “Data Quality and the Bottom Line” stated, “The problem with data is that its quality quickly degenerates over time. Experts say 2% of records in a customer file become obsolete in one month because customers die, divorce, marry and move.”

So assume that your company has 500,000 customers and prospects. If 2% of these records become obsolete in one month, that is 10,000 records per month or 120,000 records every year. Meaning in two years, about half of all records are obsolete, if left unchecked.

Disparate sources also present a problem. An organization’s customer contact and customer value information is often included in millions of data points from hundreds of disparate sources. Businesses and organizations must consolidate this frighteningly fragmented – and often out-of-date – information into an accurate, centralized tool in order to know their customers.

A knowledge-based approach completes and enhances this process by complementing internal resources with fresh, enriched data and by providing tiebreaker data – unavailable internally – to help businesses compile rich, meaningful customer information.

The benefits of excellent customer data are real, and businesses all over the world are experiencing the incredible results. If your business isn’t one of them, you – and your customers – are missing out. Put excellent customer data to work for your business to really know your customers. If you don’t, someone else will.

Lance Osborne is Acxiom Corp.’s CDI solutions marketing leader.

Related Articles:

Using Customer Knowledge to Optimize Channel Performance
Storehouse: Crme de la CRM
Building a Holistic Customer View

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