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Using real-time data enrichment for better customer insights

This article was based on the interview with Daniel Erickson of Viable by Greg Kihlström for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:

Real-time data enrichment for insights is a powerful tool that allows companies to gather and analyze customer feedback in a more efficient and accurate manner. This process involves the use of artificial intelligence (AI) to extract valuable information from various sources, such as chat transcripts, survey responses, and customer reviews, and enrich it with contextual data.

One company that specializes in real-time data enrichment is Viable, as Daniel Erickson shared in the podcast interview. They integrate with different platforms and pull in data as conversations are happening. For example, when a chat ends in Intercom, the transcript is sent to Viable, which then identifies the different topics discussed by the customer, including bugs, complaints, feature requests, and compliments. This process is repeated for every conversation, survey response, and review, ensuring that all data is enriched in real time.

Once all the enriched data is gathered in one place, Viable generates periodic reports using AI-generated insights. These reports highlight the top complaints, compliments, requests, and questions from customers. By using large language models like GPT-4, Viable is able to deeply understand the context of the data, resulting in more granular insights compared to a manual process.

The philosophy behind this approach is AI-human augmentation. Humans alone can perform at around 80% efficiency, and AI alone can also perform at a similar level. However, when AI and humans work together, their performance can reach up to 150%. This means that every team within a company can access customer feedback that helps them achieve their specific goals. For example, the marketing team can use the feedback to craft better messaging, the product team can identify gaps in the product and add more features, the sales team can address objections, and the customer experience team can build better macros and responses for customer support requests.

From the customer’s perspective, real-time data enrichment offers the potential for a more personalized and relevant experience. Companies can use the insights gained from customer feedback to better understand their needs and preferences, and tailor their products and services accordingly. However, it is important for brands to be mindful of the frequency and relevance of the surveys and requests for feedback. Customers are often inundated with surveys, and brands should strive to only ask for feedback when it is truly necessary and meaningful. Sending generic surveys without considering the specific circumstances of the customer’s experience can lead to survey fatigue and a decrease in response rates.

In conclusion, real-time data enrichment for insights is a valuable tool for companies to gather and analyze customer feedback. By leveraging AI analytics, companies can gain valuable insights into customer sentiment, prioritize feedback based on customer personas, and make data-driven decisions to enhance the customer experience. As the importance of customer-centricity continues to grow, AI will play a crucial role in helping companies stay agile and responsive to customer needs.

House of the Customer by Greg Kihlström is now available.
House of the Customer by Greg Kihlström

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