Narvar Bot for Messenger: Improving Post-purchase for Consumers on Facebook

Facebook Messenger just announced their new directory to connect businesses with service providers like Narvar to help them make the most out of what the platform has to offer. We’re thrilled to be included in this directory for Messenger platform developers!

Building loyalty after the purchase

Retailers and consumers alike have evolved to fit the new paradigm of digital retail. Instead of the traditional brick-and-mortar experience of immediate gratification, there’s an experience gap between clicking the “buy” button and receiving your goods. That gap creates a new “moment of truth”: a time of high anticipation which retailers have the opportunity to fill with a branded experience to keep customers excited about their purchase and build an emotional connection with them. Consumers have made it clear they now expect this level of transparency from retailers, and reward them with loyalty.

As consumers shift their communication preferences, time, and mindshare to new channels, smart retailers are moving to meet them where they are already spending 75% of their time: on messaging apps. To help our retail partners extend their post-purchase experience to serve Facebook members in this new channel, we launched the Narvar bot for Messenger in October 2016. Rather than encouraging customers to call support or visit a general FAQ page, retailers can send proactive delivery updates and personalized messages through Messenger. Our bot answers common natural-language questions about tracking and delivery, personalized to that customer.

“Bots improve the post-purchase experience and help us be there when our customers need us, every step of the way until shoes are on their feet,” says Brian Seewald, VP of Digital at DSW. “The shopping experience doesn’t end when the customer clicks “Buy.” We want to stay top of mind for customers by providing order updates and sharing real-time information and support.”

Consumers are quickly adapting to bots

Despite some reports to the contrary, consumers already seem to accept artificial intelligences as anthropomorphic entities in the right circumstance. The way people talk to Siri, Alexa and “the Google lady” is a testament to the conversational tone and engagement which comes naturally when an interface responds as a human would. Obviously it helps that users can simply talk to these AIs, but what about when they must input by typing, which is abstracted from normal human interaction?

Although SMS usually has a human on the other end when used for personal communications, it is still perceived to be primarily a transactional channel, perhaps due to the fact that commercial entities often use it for one-way notifications and alerts, or because of the structured nature of messages (e.g. “text 123 to vote yes, 456 to vote no”). Messenger, on the other hand, seems to have transcended this base utility with chatbots which blend the natural, real-time responses of AI with the conversational aspects of a messaging platform. Case in point: we’ve found that a large number of customers who don’t have further questions will still respond to the Narvar bot’s status updates with a thumbs-up or “thanks”, acknowledging its helpfulness as they would a person. We do not see a similar reaction when people are provided the same information via SMS.

When customers ask questions adjacent to package tracking detail but outside its purview, the Narvar bot can help direct them to the solution. For example, it knows to send the customer to the appropriate page on the retailer’s website when they ask about store hours and to the carrier when they want to re-route a package. Its focused scope has helped the Narvar bot be successful on the Messenger platform, and has been rolled out to almost 370 major retailers including Macy’s, GameStop, and DSW, powering millions of chatbot interactions in just a few months. We’re excited to grow our bot’s capabilities to make this interactive post-purchase experience even more valuable to consumers.


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