A New Way to Understand Customer Satisfaction

Learn Data Science
Teradata Employee

If you’re responsible for customer success, you know how important customer satisfaction metrics are in gaging and improving customer retention and lifetime value. But typically, these metrics are calculated with narrowly focused point solutions or complex analytic packages.

At Teradata Aster, our customers are looking at their customer data in a whole new way to predict satisfaction scores.

Our customers have found that point solutions – while perhaps satisfactory for the specific problem they are solving – provide limited development capabilities and make it difficult to factor in data sources beyond those for which they were originally designed. Leveraging analytic packages like R and SAS, data science teams have built incredibly insightful customer satisfaction models. But data science skills are in short supply, and executives and analysts are often left wondering about the impact of slight tweaks to the models and whether new data sources would add value – not to mention whether sampling techniques miss key activities in the data.

So what’s different about how our customers look at customer satisfaction? Consider these four points:

  • They can incorporate all customer and product/service data. Our CSI solution is built on the Teradata Aster analytics accelerator, which is designed for all data types at scale. Your scoring rules can leverage text from support emails and call center notes as easily as web logs and product usage data. And you can run your models across terabytes or petabytes of data.
  • Our Guided Development Interface makes it simple to create complex rules with no SQL knowledge. Imagine creating scoring rules that run across massive data sets without writing any SQL, MapReduce or statistical code.
  • You can leverage multiple analytic techniques under the hood with ease. Most enterprise executives and are paid to generate and act on insights. They aren’t paid to figure out the most elegant way to nest text analytics into a path & pattern analysis.
  • Our customers operationalize customers satisfaction insights with simple execution and access for business teams in Teradata Aster AppCenter. Just press “run” on your custom CSI app within AppCenter for the latest scores. Or adjust parameters to look at scores from a year ago based on a different set of logic. Either way, the power is in the hands of business users and executives.

We dove into details on the above points in a webinar earlier this month. Enterprises operate in a manner in which small improvements can mean big changes in terms of real dollar impact. Imagine the impact of better understanding your customers' happiness. To learn more about how Teradata Aster lets you create extremely actionable customer satisfaction scores leveraging all data types at scale, watch the webinar recording or email me at ryan.garrett@teradata.com.