1. How do I blend data platforms, from channel to data management to analytics?
2. How do I ensure data quality at every point where new customer intelligence interacts with my brand?
Often there is a data strategy, but too often there is not a data quality and governance strategy to flow with co-existing, disparate data entry. Whenever data points are integrated, there needs to be discovery, staging, parsing, appending and validation to go along with the effort. Any investments in marketing analytics, automation and execution depend on having such a regimen in place—and, increasingly, in real-time platforms.
Organizations need to be honest with themselves regarding their data quality and certain of the quality of their data sources. Definitions must be in place to specify when "good" is acceptable and "great" necessary.
3. With the proliferation of channels for consumers, how do I know how to deploy interaction and messaging to those that matter most?
Today's consumers are multichannel shoppers. But multichannel does not just mean multiple distribution channels. Consumers learn about products and services using a wide scope and then shop through a narrower array of channels. Buying is done through an even smaller sub-set of channels.
To be truly multichannel, marketers must consider where consumers go to learn about products, what their behaviors are and where they shop and eventually make a purchase. Individual channel choices are situational. Figuring all this out requires a thoughtful combination of market research, social media marketing and database analytics. The answers can be found in discovering what consumers are doing so that you might communicate with relevant messages through the channels they prefer.




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