Looks like TLA is starting to mean Two Letter Acronym, eh?
I believe MI and CI are refinements of Business Intelligence disciplines specific to Markets and Competition, respectively.
MI usually refers to market intelligence as you mentioned. Market intelligence is the evolving best practices around taking market research content and putting it to work to identify opportunities and threats within the market landscape. There are providers of syndicated data that focus on providing geographic and demographic information to companies and industry associations so they can better understand the size and makeup of the markets in which they compete or serve. So market intelligence is knowing all the details about how big a market is, where the populations are dense geographically, where the income levels are high/low, where ethnicities are predominant and where they are not, where luxury products are a hit, and where low cost value products are a hit., etc.
BI is the classic business intelligence and usually refers to knowing about YOUR customers. Who are they, where do they land within the above referenced markets, what are their buying tendencies, what is their price sensitivity, which of your products seem to hit the spot with which of your customers out of which stores, etc. Then map that trending information to the intelligence you know about the bigger picture markets in which you are competing or are planning to compete.
CI is competitive intelligence when used in context of MI and BI. Customer intelligence would be a subset of the knowledge you have from the business intelligence disciplines. Competitive intelligence is focusing on the intel you can gather about your competitors, their products, their customers and the markets in which they compete. The idea is to get better at mapping the competition's products, markets and customers to your products and customers and your understanding of markets. Then you compare and contrast the relative strengths and weaknesses at each mapping pair. From here you can drive back into the business intelligence arena with recommendations based on where you think you can score big.
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This was first published in September 2003