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[24]7 Assist: Chat Drives Improved Customer Engagement and Increased Revenue


Presented By: [24]7.ai

247.invite.productreview.dec2014It happens to us all. We log onto a website and before we can even look around, a chat bot pops up to ask “Can I help you?” As we quickly click “No, Thank You,” we already have a negative first impression.  Besides being intrusive, this approach to chat is outmoded and ineffective. It isn’t that consumers don’t like chat: a June 2014 Datamark Incorporated survey found that 25% of customers preferred to contact customer service centers via chat, higher than any other channel besides voice. But to make it work, organizations need an intelligent solution that is not based on old technology or guided by inflexible business rules.

“The problem is that while chat solutions have been around for about ten years, most products have not essentially changed,” said Leslie Joseph, Senior Director, Product Marketing for [24]7. “Many companies are still using the same technology as they did when Britney Spears was the most popular female recording artist.” 

A specialist in customer engagement for customer service and sales, [24]7 has perfected a solution that they see as the future of chat. Introduced in 2013, [24]7 Assist offers a series of experiences on a single platform for different channels. Assist takes much of the guesswork out of customer service by predicting and anticipating a customer’s intent, enabling businesses to make the right connections at the right times on the right devices. [24]7 Assist uses predictive data and real-time decisioning to automatically improve outcomes and leverages machine-learning to continue to make them better over time.

“Assist stitches channels together in real time,” said Joseph. “Customers start on a company’s website or on social media. They might try online self-service or escalate to click-to-call to get to the voice channel. They may go to an IVR that has natural language capabilities where they can receive visual content or visual voice alternatives. Assist supports omnichannel visitor journeys that seamlessly move between these touch points to chat with full context of prior interactions.  The software not only pays attention to what a person is doing but takes into account what similar customers have done. It reviews interaction data to determine whom to invite to chat, when to intervene, how to engage, and what to recommend.”

[24]7 Assist makes predictive chat available on every device from desktop to mobile, both as web and native experiences. It employs ongoing scoring of customer intent to predict propensity to purchase. The solution offers real-time model-driven targeting that provides business flexibility and allows organizations to effectively optimize against multiple outcome-goals compared to business rule-based software. Chat invites are algorithmically personalized to the specific customer’s predicted intent.

Assist also helps chat agents be more effective. During the design process, [24]7 consulted with their own agents and those of their clients as well as UX specialists, behavioral experts and data scientists to develop the most efficient interface design and workflows with guided assistance. “Training chat specialists had been a task with a steep learning curve,” said Brooks Crichlow, VP of Product Marketing for [24]7. “Now agents have can see customer histories on a single screen and the solution can automatically recommend the right question, based on on-the-fly text mining and analysis of chats. Recommendations are adaptive to different stages of an in-progress chat. Supervisors and team leaders can monitor agent performance in real time, using data leveraged on the agent side. Active dashboards and alert systems provide detailed performance analysis. The models learn from each chat and from agent ratings to increase the accuracy of subsequent recommendations.”

[24]7 offers its Assist chat solutions available on an outcome-oriented basis. Ongoing optimization is built into the system with no hidden costs or change fees. “We focus on helping companies build acceptance of chat, as well as higher CSAT and NPS ratings,” said Crichlow. “One Australian wireless carrier had a 19% increase in chat acceptance and others have had dramatic decreases in drop-off rates due to our design that supplements text chat with rich interactive content.” But the most important measure of success for [24]7 Assist is driving incremental revenue directly through chat. “We’ve had clients report that up to 30% of their incremental revenue can be traced to our solution,” said Crichlow.