Don’t Underestimate the Power of Your Data

“Garbage in, garbage out.” You may have heard this crude phrase in the past and, although it is somewhat simplistic, it does send an important message to companies that want to compete using information-driven marketing.

Data integrity promotes customer analysis, and leveraging your customer information is a key element in building a profitable business. When data is accessible, accurate and up-to-date, a company can analyze it for actionable customer insights. When applied correctly, these insights can identify opportunities, fuel innovation, and ultimately lead to improved marketing performance.

Data is the key to customer intelligence
Customer intelligence is an extremely powerful business asset. Companies that use it to gain a competitive advantage have a comprehensive plan for capturing it, mining it, and using it to make better decisions. Some best practices include:

the development of a customer information review discipline that is committed to the ongoing growth of the company’s data assets
the creation of a data asset scorecard that provides a consistent approach to measure the value of data assets and informs investments in new information sources
a regular information consumption audit, exploring how the business intelligence, predictive analytics and marketing measurement business practices are leveraging the data assets

Marketing analytics validate new data assets
As a long-time marketing analytics professional, I have often found myself acting as a conduit between marketing and IT, conscious of the needs of both business functions. I highly recommend that data assessments be conducted from this same vantage point. Investments in new data hygiene and data collection procedures need to consider fully their expected IT costs balanced against the expected business benefits of each new data asset.

The marketing analytics function, in particular, is uniquely positioned to evaluate the incremental value of new or improved data assets. Leading data-driven marketing companies depend on analytic tools (such as propensity models, segmentation schemas and customer lifecycle frameworks) to make a variety of informed decisions pertaining to customer strategy, customer valuation, value proposition, targeting and tailoring, contact management and marketing measurement. To gauge the value of new data assets, tests can be constructed that assess their impact on the performance of these tools before a broad investment is made across the entire customer base or in assorted operational activities.

If you use this approach, you will be able to confidently state that your company benefits from a “data in, insights out” approach, which is a far better alternative to the garbage analogy.

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Posted by on 11/06/2009 10:08 AM

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