24[7] combines realtime analytics with web chat

OVUM VIEW

Summary

In January 2013 the analytics vendor 24[7] announced a new product, 24[7] Assist, which combines its realtime analytics capabilities with proactive web chat. The product enables contact centers to better understand customer needs and determine the most suitable time to initiate a web chat. The vendor believes that by using existing data to initiate a web chat contact centers will be able to improve the likelihood of a sale or help a customer with a support issue. It believes that analytics should be the basis for all customer support interactions, as it can create a personalized and generally better customer experience. Ovum predicts that web chat will rapidly become one of the top choices for support, alongside email and phone, and believes that agents will need better guidance for handling communications across text-based channels. Overall, 24[7] Assist is a timely addition to the vendor’s predictive multichannel contact center platform.

Web chat is gaining prevalence as a support channel

Customers already begin many of their interactions on the Web or via a smart device, and web chat is a logical support channel; it offers minimal disruption to their online experience and yet they are able to obtain personalized, relevant information. Ovum predicts that over the next two to three years web chat will gain mainstream adoption for support among customers and service centers. Ovum’s market forecast data suggests that enterprise spending on chat will grow from $271m in 2012 to $325m in 2013, at a rate of 20% in North America and Western Europe. While social media is also taking hold as a customer support channel, web chat offers a more familiar environment for customers and an easily manageable platform for agents, who can handle two or three chats simultaneously. It is also easily integrated with social media, voice, and knowledge articles.

24[7] Assist allows customers and agents to connect at the most opportune times

As 24[7]’s Assist solution combines web chat with predictive analytics it can pinpoint the most profitable or useful point to begin a web chat. Enterprises can track customer behavior on a website before they engage in a web chat in order to link behavior to questions or to predict the nature of an interaction. By using existing customer data to assist agents, contact centers can improve customer satisfaction across any channel. They can route interactions more effectively and provide agents with relevant information, and help them to determine whether an interaction will be sales support or a technical website issue. Communications are kept within the enterprise walls, and it is therefore easy to record conversations, analyze information after the interaction, and ask customers for quick feedback or resolution satisfaction.

Enterprises will still need to determine how to balance inbound and proactive chat sessions. For example, they need to decide whether to offer inbound chat to all customers all of the time, or to use analytics solutions to provide the chat option for particular customers. The addition of realtime analytics to customer service in general makes it easier to predict customer intentions and offer support when needed. This will help boost sales and customer satisfaction by giving customers proactive assistance without bombarding them with requests to chat.

Chat should also be integrated with knowledge management and phone support

Web chat needs to be linked with existing online channels and enterprise information in order to ensure a cohesive customer experience. Enterprises should integrate chat with knowledge management, as well as core routing and phone support. By integrating web chat more fully with customer service, agents can offer assistance around online technicalities, create cobrowsing sessions to assist with form completion, and connect to a voice call where appropriate. Chat should ultimately make it easier for customers to remain in their channel of choice and get support with minimal disruption to their web or mobile session. However, the customer experience is affected by many different interactions with an organization. Realtime analytics should be part of a cross-channel contact center strategy rather than used to improve siloed channel interactions.

APPENDIX

Author

Aphrodite Brinsmead, Senior Analyst, Customer Experience and Interaction

aphrodite.brinsmead@ovum.com

Further reading

Leveraging Web Chat to Optimize the Customer Experience (January 2013)

2013 Trends to Watch: Customer Experience and Interaction (October 2012)

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