Cut support costs with a window into contact center dark data

Key points to unlocking your customer service dark data:

Contact center is the heart of your customer conversations where brand loyalty relationships can be built or broken costing $9.7 million/year due to bad data
True cost of bad data: customer churn, agent attrition, & operational efficiency & time
Simplify the complexity to understanding your conversational data customer service topics and reasons to improve customer service

What does customer service have to do with dark data?

Language data exists in vast quantities across the digital world but hasn’t traditionally been a source of insight
Customer service unstructured dark data examples: call-center transcripts, text messages, survey responses, customer reviews, emails, documents, and more
The challenge: bringing order to the chaos of dark data problems—too much data, inaccurate data, & poor data quality
Example of challenge: manual review of transcript data that costs you time and resources
Example of solution: simplified and automated process to understand your contact center conversations and customer service topics across channels with your agents and bots
The result: data sources become functional & insightful to improve customer service vs. dead weight

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Bound by API constraints (e.g. limited adjustable parameters, guardrails imposed by creators, compute time - e.g. 20 seconds per prompt)
Prompt engineering isn't a solved problem and may not be fully optimizable in principle due to the natural language format
Traditional NLP methods offer precise control over pipeline/output + are more optimal in some cases (e.g. topic clustering for vectors)

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