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Introducing the Path Analysis Interface for Teradata

Introducing the Path Analysis Interface for Teradata

Path analysis is central to many of the analytic challenges we tackle in the field. Think for a minute about the questions you are likely asking about your business that involve a path around a particular event.

“What are common paths to purchase?”

“What paths help me predict customer churn?”

“Why do customers call support after they’ve already browsed my website for answers to their questions?”

“Which medical procedures typically precede this specific procedure?”

That’s why we are introducing the Teradata Path Analysis Guided Analytics Interface. This web-based interface puts path analysis into the hands of business users so they can find opportunities to better market to their customers, improve operations and mitigate potential issues in their customers’ journeys. And they can perform the analysis themselves, without coding, in a matter of seconds to minutes.

Key highlights of the interface include the ability to:

  • Visually explore journeys by simply selecting a few parameters from drop-down menus and clicking “Show Me.”

  • Interact with visualizations including tree, Sankey, sigma, and sunburst diagrams and bar charts.

  • Identify individual customers on specific paths and export lists for follow-up.

  • Now available for both Teradata and Aster databases.


Since we rolled out the Aster version of this interface last year, we have implemented it at customer sites within several verticals, and many more are taking notice. It has been amazing to see how fast the interface gains traction after customers see how easy it is for them to get to valuable insights about their customer paths.

If you are interested in exploring customer paths, this interface is a great way to do so — quickly — while putting power into the hands of business users.


Portrait of Ryan Garrett

(Author):
Ryan Garrett

Ryan Garrett is senior business development manager for Teradata Field Applications. His goal is to help organizations derive value from data by making advanced analytics more accessible, repeatable and consumable. He has a decade of experience in big data at companies large and small, an MBA from Boston University and a bachelor’s degree in journalism from the University of Kentucky.
  View all posts by Ryan Garrett

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