American Multinational Technology Corporation Gains More Value from Social and Security Data

This company produces computer software, consumer electronics, personal computers, and related services. Here’s the story of how InMoment partnered with them to solve for greater access and value from social data.


InMoment designed a custom solution so the company’s customer market research team could:

  • Reduce survey spend by substituting social signals where possible
  • Run better surveys by identifying insight gaps
  • Help leadership teams make better-informed decisions around marketing and product strategy

“InMoment is the only vendor we’ve seen that can offer the flexibility that is required to support our complex product line.” – Senior Market Research Manager

Envisioning an Integrated Social and Survey Data Stream

The brand’s customer market research (CMR) team helps managers across the company make better decisions regarding product and market strategy.

Previously, the CMR team listened to Voice of the Customer by designing, distributing, and analyzing a wide range of surveys. But, as part of a push toward optimization and continuous improvement, the team began working to integrate a new type of customer data: social media content.

To demonstrate value from the project, the CMR team needed to:

  • Effectively filter social content to only extract relevant data.
  • “True up” social data with survey responses to explore the feasibility of reducing their survey spend.
  • Easily configure flexible one-off analyses while also establishing and validating long-term trends.

Traditional social listening tools didn’t offer the customizability and scalability the team needed to achieve its goals. So, it turned to InMoment for a “custom” solution.

InMoment’s Custom Solution Strategy to Optimize Social Data

First, the customer market research team extracts a subset of social comments from an InMoment-built data warehouse based on the products and brands they want to know more about. Then, the team used InMoment’s application to analyze this data and understand what people are saying, how they feel, and why they feel that way.

Next, the CMR team validates the results and then relates the net sentiment score to quantitative LikertTM Scale survey data. This approach allows the team to compare and contrast what people say in structured surveys versus what they say in both structured surveys and an unstructured social media environment.

Finally, the team identifies common themes, topics, and correlations in the social data, then aggregates the information to use as a reliable, immediately actionable proxy for customer survey responses weeks ahead of receiving actual survey results.

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