Systemic issues–like login not working on your web service or eCommerce shipping problems in a warehouse–may cause lost revenue and customers. That is why it is important to quickly pinpoint this type of problem clusters. Manual ticket tagging is slow, expensive and the results are inconsistent. Automatic feedback categorization service fixes this problem in real-time, accurately and feasibly.
Are you able to detect systemic issues quickly?
Does it take too much time to detect systemic issues? Do your support agents manually tag tickets? Can you easily and fast make sense of Net Promoter System or Customer Effor Score response text comment fields? If these questions hit a pain point, we have great news for you. We have created an integrated Etuma-Zendesk solution that solves these problems.
Never leave the platform you are familiar with
This all is simple and easy. Etuma is an embedded analytics solution: your agents (or you) never have to leave the Zendesk platform. Etuma runs in the background taking care of the tedious task of tagging your tickets or NPS comment fields.
And, you don’t have to worry about the text analysis code frame maintenance. Artificial intelligence, machine learning, and Etuma's computational linguistics experts take care of that.
This is how it works:
- Zendesk administrator creates a field in Zendesk for text analysis results (one-time task)
- Zendesk administrator gives Etuma user name and API key (one-time task)
- End-customer complaint or (NPS) survey text field comes into Zendesk
- Etuma fetches that ticket (text comment) from Zendesk either in real-time or set intervals
- Etuma categorizes the text comment by industry specific code frame and sentiment
- Etuma returns the analysis results to the created field (Step 1)
- Customer can use the analysis results to create ticket routing rules and to visualize the analysis results in Gooddata.
Ready to reduce manual work and find
out faster what is bothering your customers?