Big Data and Marketing: How to Distinguish Relevance

//Big Data and Marketing: How to Distinguish Relevance

Big Data and Marketing: How to Distinguish Relevance

Big data, a pool of data used for analysis and insight, can mean something different to each company. As a person gets dressed for work in the morning, the clothing he or she is wearing is part of big data. Retailers collect big data and use it to market their products. It gives insurance companies a reliable way to decide which applications are ready to process and which clients need to schedule an in-person meeting with an agent. Patient information including clinical, billing and scheduling from hospitals is big data. It can be used to predict which patients may require future care. With such a broad definition and versatile functions, big data can be a challenge. It is important to distinguish the origin and meaning of data in order to apply it to marketing strategies. 

Oftentimes it is praised as powerful tool for marketers. Jerry Thomas, Contributor to MarketingProfs, noted some common conceptions of big data: more data is better, volume and variety in data create new sources, big data can answer questions and predict the future.

"Is Big Data an accurate picture of the future, or is it simply a mirage shimmering in the distant desert heat? Is it the pathway to ultimate truth, or is it only a bandwagon of exaggerated promises and illusory dreams?" said Thomas.

Little Data Solves Big Problems
Confusion around big data can be produced by its quantity. The onslaught of big data grows with every moment. It is available 24 hours a day. Thomas looks to little data to solve big problems.

"You don't have to boil the ocean to determine its salt content. You don't have to eat the whole steer to know its tough," said Thomas.
He considers some of the most "trustworthy data" to come from three little sources:

1. Experiments rank highest on the list of resources that provide data. Experimental data is produced by a measurement or experiment and is classified as qualitative or quantitative. Qualitative research is conducted through participants and is aimed at understanding human behavior. Quantitative research is obtained through measurements to uncover facts about social phenomena.

2. Survey research conducted by credible professionals, who are objective third parties, can provide concise and valuable information. According to the Bureau of Labor Statistics, survey researchers design and analyze factual data that can include preferences, beliefs, desires and opinions. Survey data is relatively inexpensive compared to other methods.

3. Marketing mix modeling, a blend of an analytic database, normalizing or organizing databases and statistics to highlight helpful variables for a business. Types of data that are included in marketing mix modeling include economy, industry, category, advertising, product and market.

"Despite the marketing hoopla and the gurus touting Big Data, Little Data often provides a more accurate basis for sound corporate decision-making," said Thomas.

In addition to the aforementioned resources, Thomas stated sales, eye-tracking data and social media are credible means to track big data. He believes small data like sampling theory could be more affordable and less overwhelming than big data. Whether a business chooses big or little data for marketing purposes, it's important to understand the source.

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By |2017-01-05T18:51:48+00:00October 6th, 2014|Printing Industry News|Comments Off on Big Data and Marketing: How to Distinguish Relevance

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