Neuron7 Customer Service AI Methodology
AI-Driven Customer Service in Just Two Weeks
Every organization’s customer service data sources and processes are at a different stage of AI-readiness. The diagram below shows the five-step Neuron7 implementation methodology. No matter where you are on the customer service AI continuum today, by the end of the first two weeks, your team will start benefiting from AI-driven issue resolutions.
The Neuron7 implementation methodology is a five-step journey:
- Kick-off – a two-week proof of concept project during which we activate your Neuron7 account, agree on the first customer service uses cases you’d like to address, connect Neuron7 to relevant data sources, and train it to support the use case(s).
- Initial Service Predictions – review initial Neuron7 intelligent diagnostic and resolution predictions for accuracy.
- Enable Power Users – Make changes, add data sources to complete coverage of the initial PoC use cases. Watch Neuron7 closed-loop learning increase the accuracy and abilities of your customer services AI.
- Rollout Phase 1 – Expand Neuron7 diagnostic intelligence to new customer service use cases. Roll it out to more customer service agents and technicians
- Rollout Phase 2 – Expand use case coverage completely, across the appropriate service tiers, products, and team members.
Neuron7 AI Readiness Module – No Data Engineering Required
The process is facilitated by an AI Readiness module, which ingests your customer service data (e.g., knowledge bases, product manuals, support call logs, engineering notes, etc.), analyzes it and readies it for AI. You do not need to perform any data engineering or data science; it’s handled for you by Neuron7.
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Ready for faster service resolutions? Contact us today to learn how Neuron7 captures knowledge to deflect calls, increase first call resolutions, power intelligent search, and help you do more with less.