Many organizations take marketing data as the primary source of customer data, including demographic, technographic or intent. This data is usually collected through web interactions, surveys, or CRM.
Yet, (marketing) organizations seem to ignore customer conversations as one of the valuable data sources. Customer conversations can provide a lot of insights whether they are sales calls, onboarding, or simple support calls.
The critical difference with data extracted from conversations is that it is explicit, in other words, customers actually tell organizations what they think and feel.
There are many reasons behind not leveraging this type of data, few of them being impracticality, unscalability, and cost.
Thankfully, there is a solution which does all the heavy lifting for organizations in terms of gathering customer data: conversation intelligence.
How does it work?
Any type of customer conversation can be ingested and processed through conversation intelligence. This technology recognizes what is being said by using transcription or speech-to-text. Then, it gets analyzed in a contextual understanding engine, which is part of AI.
The key here is that conversation intelligence detects beyond what is being explicitly said in a conversation.
Finally, the output or the insights are generated based on what was processed. Outputs include questions asked, summaries, sentiment, predictive insights and many more. William Vuong, Head of Marketing, Symbl.ai, adds:
"The key takeaway is that conversation intelligence does not just convert something into text, but also understands the context, for example, when and how something is said between multiple speakers across different channels."
Use in Marketing
Organizations can use conversation intelligence to extract intent and feature-specific insights from conversations.
