Data Mining Market Research: Theory & Techniques

Same Data. Different Perspectives. Better Predictions


Jigsaw Puzzles. Excitingly addictive brain power enhancers or pestering contraptions of doom?

Either way, everyone has some form of Love/Hate relationship with the puzzle game. The objective being to take a pile of raw pieces and eventually form a complete (IF you’re lucky) big picture.

Just like with the tricky interlocking puzzle, every project or task to be completed has a beginning, a middle & an end. Without one, the other two make no sense.

Some people start by defining the outline and working within in a somewhat systematic process. Others hunt for their first 2 connecting pieces and expand from that focal point.


No matter the Standard Operating Procedure (SOP) your mind decides to implement, the puzzle’s “big picture” is incomplete with any missing pieces. To some, the whole thing even becomes obsolete!


The same can be said with your business’ Market Research efforts. You’ll need to:

  1. Specify & Outline your objectives so you’ll know what is needed to achieve your business’ KPIs
  2. Obtain & Analyze your market data (groundwork of Market Research)
  3.  Develop & Prepare how you’ll execute/use the data
  4. Report & Present the data gathered



Data Mining


To achieve more concise Marketing Research (a more efficient & effective way to complete the puzzle) you may want to conduct a little Data Mining. Finding a more substantial foundation of data patterns means generating more helpful analysis reports.


Put it this way, the deeper you dig, the more you uncover!


Digging deeper into your database of information for the buried, yet no less valuable, patterns & trends will give your experts a clearer picture.


What is the big picture?

Whatever your business objectives, KPIs and other conversion goals are.

For Example: If you sell a product to consumers, you can go beyond just viewing your market’s demographics. Create a better plan of action for selling the product by digitally tracking and deciphering individual behavioral patterns of specific demographics.



Techy Techniques


  1. Regression Analysis. Using an equation to form a linear model that better predicts the responsive relationship between dependent and independent variables.


  1. Clustering Analysis. An ideal segmentation technique that collects data into clusters of categorized information to pinpoint any patterns in behavior.


  1. Classification Analysis. Another categorization function that classifies collected data to help predict outcomes of targeted groups (classes) per data record (case).
    • Ideal technique for Churn Analysis & reducing marketing costs


  1. Association Rules. Observing the relationships between specific variables to discover common trends connecting objects or actions.
    • Ideal for forecasting & pricing promotions strategies


  1. Sequencing Mining. Noting any hidden statistical patterns whose values are sequential. Typically used to analyze how consumers progress through relative processes.
    • Consider processes like website Attribution & E-Commerce


  1. Anomaly Detection. Observing any outliers to the data’s predicted pattern to monitor potential concerning activity.


Each of these functions (techniques) use comprehensive algorithms that increase predictability while potentially decreasing risk & cost.

Remember, with Data Mining, you’re getting stronger predictions and clearer descriptions. Invest in your business’ future today!

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