AI Use Cases
Match expectations from both sides of a 2-sided online market
Match expectations from both sides of a 2-sided online market. Typically this goes beyond simple price matching and includes a variety of other variables that may have different levels of weighting to market participants.
Monitor customer experience across multiple channels to build holistic overview
Advanced analytics on all customer contact data across multiple channels (Including real world monitoring) to uncover insights to improve customer satisfaction and build a holistic picture of their status.
Tailor debt collection processes by identifying which practices are most effective for different segments of customers
Tailor debt collection processes by identifying which practices are most effective for different segments of customers. This is a sensitive process with occasional risks.
Optimise call routing based on customer characteristics potentially including expressed intent
Call routing (i.e. determining wait times) based on caller id history, time of day, call volumes, products owned, churn risk, LTV, etc. Route calls to most capable agent available and ideally leading to fewer agent-handled calls - hopefully leading to increased customer satisfaction and reduced handling costs.
Improve Interactive Voice Response (IVR) effectiveness
Improve IVR effectiveness through deploying voice to text and natural language processing (NLP) to better capture and enable response to customer queries. Understanding customer pre and in-call intent helps reduce time to serve and potential customer problems. This leverages Natural Language Processing (NLP) and machine learning to estimate and manage customer's intent on calls. In-call assessment enables multiple functionalities: e.g. call routing, issue triage, automated responses.
Automate customer service voice conversations with conversational agent
Automate customer service voice conversations through a conversational agent chatbot enabling high volume, fast reaction customer support. Unexpected questions will likely 'break' the chatbot system so consumers need to be clear that they are interacting with a machine.
Automate customer service conversations through a text chatbot
Automate customer service text conversations through a chatbot enabling high volume, fast reaction customer support. Unexpected questions will likely 'break' the chatbot system so consumers need to be clear that they are interacting with a machine.
Suggest potential customer question responses
Bots will listen in on agents' calls suggesting best practice answers to improve customer satisfaction. Putting the right data on the operator's screen to ensure they are prepared with the context of the call to speed resolution and maximise likelihood of customer satisfaction.
Translate languages in real time to facilitate understanding
Use AI to provide real time translation services. This has both B2C and B2B applications. Current depth of access on traditional language pairs - e.g. English: Spanish - are being extended to other languages, although many cross-translations pass through English.