matchmaking

How does Data Mining help businesses?

by Bernardo Becerril

The hidden stories in databases

Data is everywhere. It refers to any piece of information collected for reference or analysis.
The Merriam-Webster English Dictionary defines data as: “factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation”.

Now, data by itself may not say anything. It is not until it has a been organized, analyzed and studied properly, that it provides useful and valuable information.

Data mining is part of the process of climbing steps in a ladder that leads to informed decision making. The first step being data, or raw-data (unprocessed information), until it becomes mined data or discovered knowledge, the last step. The higher you climb the ladder, the better you can see through information, and better decisions can be made.

Then, ‘what do you mean by knowledge discovery?’ you may tell me. Knowledge is discovered, in the sense that it is already there, in your information or data. After processing the information adequately, through processes and technology that may include data cleansing, statistical and mathematical methods, algorithms, data tells its stories. One of the most common process for knowledge discovery in data, is data mining.

Data mining, according to this useful UCLA Anderson article, refers to:

“the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both.”

Knowledge is power. For companies, knowledge equals business intelligence, revenue increase, more effective barriers against competitors. However, sometimes it is difficult for business and companies to handle their own information in such a way that it actually provides meaningful, updated and valuable information and not just a pile of documents, virtual or physical, that just stack up and gather dust (physical or digital).

I’m going to talk about the main outcomes of Data Mining for Trade Fairs.

One of the (many) stories hidden within your information is Attendance Profiles. Imagine that, after mining your Registration Information, you could have a segmented database, by demographics, behavior, and establish clear clusters of the different people that attended the show. Paradise for the Marketing team, isn’t it? With this detailed profiling, they can send specific contents targeted to specific audience, or send specific product brochures, or make a clear hierarchy of hot and less hot leads.

Another (great) story that data wants to tell you is KPI definition. One powerful reason that endangers event growing is the lack of proper Key Performance Indicators (KPI) definition and monitoring for measuring how the show is doing at any specific point in time. KPIs are values selected to indicate if the show is growing in the right path or is at some kind of risk and must be followed up closely in order to take decisions on time before any damage occurs.

When selected correctly and followed closely, KPIs are the eyes and ears of show directives and managers and where strategies must be put in place for gaining advantage or reducing risk.

Do you have other examples of the results of Data Analysis or Data Mining? Do you think I’ve missed something? Want to learn more of our Data science-based solutions for trade shows?

Bernardo Becerril  / ACOB

December, 2016