Prepare for the New Database Approach
The forces behind this upheaval are recent advances in database technology, specifically in customer data enhancement - the process of supplementing a marketer's customer data with additional demographic, lifestyle and behavioral information such as hobbies, home size or type of car driven.
Thanks to these innovations, traditional string-based comparative file matching, which brings together only similar customer records, is crumbling before the onslaught of knowledge-based matching, an approach that matches not only similar data, but also dissimilar and historical representations of client records.
Knowledge-based matching uses customer data integration software capable of linking individuals across multiple sources regardless of the variations - including discrepancies in name, age and marital name change - that thwart old-style string matching, which generally stops at the household level. Customer data integration software enables with astonishing speed and accuracy what marketers could only dream of before: a single, up-to-the-minute customer view.
Already, marketers using this new knowledge-based approach are realizing a match rate (the measurement of how much data is applied to records submitted for append) that is 5 percent to 25 percent higher than anything traditional string matching can produce. Overall, file match rates are achieving the remarkable range of 93 percent to 95 percent and beyond.
Moreover, data coverage has skyrocketed, because knowledge-based matching returns a significantly higher "depth per element" percentage. Thus, marketers get back more of the data elements requested per record, and far fewer of the blank fields that commonly frustrate users of string matching.
Matching the right offer to the right customer. For direct marketing, this database revolution is an unparalleled opportunity arriving at a critical time.
Accurate, timely enhancement data let marketers match the right offer to the right prospect at the right moment. Now you can recognize your most profitable customers and tailor your message to them more exactly. You can determine those most at risk of churn or attrition, and initiate retention efforts. You can pinpoint those most susceptible to cross-selling or upselling, and fashion precisely targeted campaigns to win them over.
Also, because of the much clearer focus that knowledge-based matching provides, DMers can squeeze more money from limited budgets and build stronger profit margins for the future.
But more than anything else, this new matching methodology lets you maximize your customer relationship in ways never before possible. You at last can fulfill the old sales maxim: know thy customer.
How to evaluate a data provider. Given this technological turmoil, how can you locate the best provider for your data enhancement needs? It is difficult. Data providers are notorious for unsubstantiated claims. One may tout, "Our consumer database includes over 1 billion source records." Another counters, "Ours covers 95 percent of the adult consumer population." Rarely can they verify their numbers.
And in any event, sheer size in a data product does not guarantee better coverage or data accuracy for the end user; often, it is more reflective of the provider's inability to deal with duplicate records.
Besides, what matters most is the accuracy and depth of the results you receive.
Here are some questions to ask any prospective data provider. The company's answers can go a long way in helping you make a smart, informed choice.
1. Does the provider have a strong stance on consumer privacy? Many providers talk a good game on privacy, but don't withstand close inspection. Ensure your would-be data provider's products comply with all the current privacy laws. Find out how early the company entered the privacy debate. Does it have a chief privacy officer, and when did it create such a position?
Privacy legislation has changed considerably in recent years and will continue to do so. Your data provider should be on the leading edge not only of understanding privacy laws, but also helping craft legislation. It should be able to accommodate consumers who opt out of marketing databases and to educate and notify customers of legal changes in the use of personal data. To protect yourself, you need a data provider firmly committed to consumer privacy.
2. Where does the provider's source data originate? A good data provider should be versed in the methods of data acquisition used by its data compilers. It should regularly audit its compilers and validate the accuracy of the data. The end product should be multi-sourced. If you note a reluctance to discuss this subject in detail, steer clear of the provider.
3. Does the provider measure itself against the industry? Any legitimate data provider should recognize industry standards and actively gauge the performance of its data against other providers in order to identify potential source problems.
4. How does the provider match its data to your file? The revolution we have discussed begs this question. Does the provider use a "string matching" approximate logic, or does the provider apply data to your file using a knowledge-based approach?
This list is by no means exhaustive, but it contains the key points that should be considered when choosing a data provider. If your prospective provider can answer these questions to your satisfaction, you can expect to help lead the consumer database revolution rather than become one of its casualties.