Customer engagement
Answer faster, and keep the customers you have
Customer teams still run on hold queues, scripted responses, and agents switching between systems to find one answer. Retention works from last quarter's churn report, and every customer gets the same offer.
AI changes what your team knows before the next contact. Predictive models route each call to the right queue and flag the customers likely to leave. They also pick the next best offer for each one. Generative AI drafts a response or summarizes the call in seconds, grounded in your own policies and history. Agents handle the routine questions end to end and hand off only what needs a person. Everything runs in your own environment.
Call center optimizationCall center optimization uses predictive and generative models to classify every customer contact, suggest the resolution, and flag the callers most likely to leave, so your contact center resolves more on the first call.Call summary and resolutionGenerative AI reads or listens to every recorded customer call, writes a short summary of what happened, and flags whether the issue was resolved so your team can follow up first.Content and product personalization for marketingPredictive models score which message, image, offer and product each customer is most likely to respond to, so every channel shows content built for them.Customer care agent and chat deflectionA customer care agent answers subscribers' billing, plan, device and outage questions in chat from your own care knowledge, with a source for every answer, and hands off the rest to a person.Customer churn prediction for banksAI customer churn prediction scores each bank customer's risk of leaving from transaction and behavior data, so your retention team can act while the relationship can still be saved.Customer retentionAI customer retention for insurers predicts which policyholders are likely to lapse or switch at renewal, and why, so your team spends offers on those worth keeping.Health plan member churn predictionA model that scores which health plan members are likely to leave before the next enrollment window, explains why, and ranks which retention offer each at-risk member is most likely to accept.Next best action and offerMachine learning that ranks the one offer, message or channel most likely to move each customer forward, so marketing sends one relevant action per customer instead of one campaign for everyone.Predicting the cause of a support call before it's askedAI predicts the likely cause of a customer's phone, broadband or TV issue from support history and network data, so agents resolve more calls the first time.Product recommendations and propensity to buyAI product recommendations predict which banking product each customer is likely to need next and how likely they are to take it up, so bankers and digital channels make offers that fit.Retail customer churn and lifetime valueA churn score ranks which shoppers are likely to lapse, paired with a lifetime value score for what each is worth, so retention budget goes where it saves the most.Support-call classificationFine-tuned small language models that read every customer-care transcript and assign it to the right category, so contact centers can route follow-ups and fix the causes of repeat calls at full volume.Telecom churn prediction and retentionTelecom churn prediction scores every subscriber's risk of leaving, explains why, and triggers the retention action most likely to keep them, before the subscriber calls to cancel.Telecom upsell and next best offerAI that predicts which plan, device, add-on or loyalty offer each subscriber is most likely to accept, and when, so marketing, care and retail present one relevant offer instead of the same promotion to everyone.Travel digital assistantA travel digital assistant is a conversational tool that answers traveler questions about bookings, changes, baggage, and loyalty from your own policies, then suggests options that fit each trip.
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