Customer service provider [24]7 ports its chat bot/live agent service to Facebook Messenger

Tag team offering is the latest sign that the popular messaging app is becoming a major channel for customer interaction.

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Move over, telephone.

Facebook Messenger in particular, and messaging apps in general, are on their way toward becoming the main live communication channels for brands talking to customers.

In the latest sign of this trend, customer service provider [24]7 has announced the port of its dual chat bot/agent service to Facebook Messenger. A customer first encounters an automated chat bot, which then hands off to a human if things get too dicey.

The Campbell, California-based company has been employing that tag team approach on many of the 200 web sites for which it provides messaging service. It’s now porting the same dual service as Messaging for Facebook Messenger, VP of Product Marketing Brooks Crichlow told me, so that the conversation could follow customers through channels they already own.

[24]7 says that this is the first instance of a chat bot-with-live-agent customer service on Messenger.

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The customer service uses of Facebook’s app are bursting out all over. TechCrunch reported Friday that the social networking giant is going to announce API tools and other support for building chat bots at its F8 conference this week. The aim: to allow businesses of all kinds to employ automated response systems for customers and would-be customers.

Facebook is also reportedly ready to launch live chat buttons for websites that can bounce over to the Messenger app or Messenger on the web. This builds on last year’s F8, where Facebook began the push to turn its Messenger into a customer service channel.

In covering last year’s conference, our reporter Greg Sterling wrote:

“I asked about automation vs. live human support. Facebook stressed that it was up to the partner but the company’s preference was for human customer service and support vs. chat bots.”

The [24]7 dual service offers both.

In a typical use case, a customer might complete a purchase at an electronics web site, for instance, and check a box on the page asking that post-order status and follow-up customer service be sent through the Facebook Messenger app.

The same conversation that’s available through the app is also available through Facebook on the web, in chat. The check box for further communication through Messenger only shows up on the web page if the user is currently logged into Facebook.

A written message about the status of the order, then, would be available to the user through the Messenger app or Facebook chat. If the user sends a question about return policies to the app or chat, the [24]7 chat bot parses the text for keywords and returns the most relevant reply. Machine learning behind the chat bot is intended to improve its responsiveness to different queries, which are being parsed for keywords.

But if the user messaged something the chat bot can’t handle, a [24]7 Decision Engine makes the determination about whether to call a live agent. Crichlow said that a brand can determine the threshold for the toss.



If the messaging is transferred to a human, the agent’s dashboard is populated with customer relationship management (CRM) data showing, for instance, the customer’s purchase history. The chat bot only has access to the user’s name.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About the author

Barry Levine
Contributor
Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.

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