Better Beats Bigger Data, Every Time.
Given the relationships between disparate data types aren’t always clear (much less actionable), the underlying data models grow murkier as more “fuzzy” data is added to the database. In this context, “fuzzy” refers to the implicit value it has in a structured or statistical application to target messages.
The reports they generate may be highly engaging and interesting (see "Analytics Isn’t Reporting"), even as they reduce the probability of successful outcomes of database marketing.
5. Bigger Isn’t a Silver Bullet: Specialization vs. Generalization. With the advent of a Big Data industry, pundits, generalists and traditional agencies, have all volunteered opinions. This cacophony leads to adding more and more to the mix ― compounding all the issues we’ve already covered herein. This underscores one of the top challenges in utilizing data ― it’s not just the tech, it’s people. There is an overwhelming shortage of talented and experienced individuals who have the marketing, database, technology and analytics experience to convert data to insights and those insights to profits. True Data Athletes are in high demand. Put another way, generalists and opinions don’t cut it. Utilize specialists and pare the scope and expectations of your database marketing to the level of talent you have or can realistically budget to engage.
While there are many challenges to utilizing data to create leverage in your business, the opportunity is clear and expansive.
Here’s the simplified checklist for marketing executives on how to overcome the common challenges in leveraging data to create marketing and business value:
• Begin with a pure business outcome as the first thing you decide. What will success look like after you’ve implemented your database marketing solution?
• Align your data collection methodically with your objectives. If it’s not clearly necessary, throw it away ― or store it somewhere else.
• Be patient and thoughtful upfront ― and capture the data in a schema or data model that supports the kinds of questions and queries you realistically expect to ask and answer of your database.