The Power of Contact Metadata

The first step in analyzing call center customer conversations is simply capturing the calls, emails, chats, or other interactions along with any associated metadata (agent ID/name, agent group, time and date, customer ID, etc), and then ingesting or mining the data with speech analytics. Speech analytics captures customer conversations and associated metadata regardless of channel, as well as across multiple contact center sites and locations. For large enterprises with multiple call centers, being able to pool their interaction and contact metadata into one system is critical for understanding the true customer journey.

Speech analytics also converts those conversations, online chats, emails and so forth into a consistent format for analysis, making it easier for managers to mine the interactions and metadata for patterns and trends, issues and opportunities. Contact metadata (agent, group, line of business, customer identifier, IVR path, etc.) provides your call center team with an even greater ability to analyze your conversations. Metadata can be used to filter your searches and data visualizations, target categories and scores to certain conversation sets, compare and correlate various metrics, and identify root cause of various issues. For instance, a collections agency can use metadata to evaluate their agents for infractions such as the absence of compliance script language.

A search can determine the exact moment that infraction occurred, what kind of language led up to the infraction, and how the agent handled the call after the infraction. The metadata can be used to determine if one agent in particular seems to struggle consistently with compliance issues or if the problem is much bigger and more than one agent has multiple infractions during their calls.

Metadata does not have to be limited to that information which is captured at the time of the interaction or by the contact capture system. External data that can be associated with any interaction can also be ingested in the speech analytics system through post processing. For example, CRM data such as whether a sale occurred and for what dollar value can be attached to the call record for future reference. This information can be used to better understand what is happening within your sales conversations, allowing analysts and supervisors to discover sales best practices by analyzing and correlating behaviors on contacts that end in a sale compared to those that do not, even if the sale doesn’t happen within the initial call.

With contact metadata, call centers are able to drill down into the details of each call or text-based interaction, giving insight into how both your customers and call center agents behave. Armed with that data, analysts and managers can create better agent training programs, focus on improving the customer experience, and ensure compliance across the board.

 

 

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The Forrester New Wave™: AI-Fueled Speech Analytics Solutions, Q2 2018

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