Quality Assurance Lead
We didn’t hesitate when we were invited to participate in Google’s Business Messages “Build-an-Agent” competition. Launched last November and open to all registered Business Messages partners, the contest would let us show off our skills creating and deploying a real-world agent (not a demo) with a trusted brand. We also leapt at the chance to team with our client Columbia Sportswear, whose current [24]7.ai chatbot was already running on Google’s Business Messages. We call that a win-win.
Columbia knew an enhanced chatbot would enable the company to create even better customer experiences. And, like us, Columbia recognized the Build-an-Agent contest as a fantastic opportunity to showcase its brand. Our product and business groups, which were already closely aligned, quickly began work on this new project.
Columbia expected the chatbot enhancements to include improved visual journeys; new intents to address a top customer contact issue (order status); and an immersive, guided customer shopping experience that takes customers straight through checkout without involving a live agent. Together, we set out to make it happen.
Spoiler alert: Our joint entry won one of only five awards in the Build-an-Agent contest’s Tier 2 category—additional proof that [24]7.ai Conversational AI technology is the best in the business.
The winning [24]7.ai-Columbia chatbot enables complex transactional journeys including Shopping and Track Order flows, which incorporate robust features such as Quick Reply chips, Rich Cards, Carousel Cards, and Rich Hyperlinks. The overall effect is to limit the abandonment rate and increase containment.
After greeting a customer, the chatbot displays Quick Reply chips for the most common user questions—enabling customers to make fast and easy decisions by selecting, rather than typing, their questions.
Track Order flow: Following each customer selection, the chatbot provides additional Quick Reply chips. When appropriate, the chatbot delivers Order details and Shipment tracking information on a single card.
Shopping flow: The chatbot acts a shopping assistant, providing recommendations based on the customer’s gender, category, and subcategory selections. The first view displays “Most Popular” items but the customer is free to navigate to other options.
All contestants in our category (Track 1) were judged on:
Furthermore, all contestants followed the Business Messages Brand Playbook’s design guidelines and best practices; made use of all, or most of, Google’s Business Messages features including typing indicators, avatars, rich content, and requesting a live agent; and measured the agent’s consumer and/or business impact.
Congratulations to the [24]7.ai team!
And of course congratulations to the Columbia team as well!
To learn more about chatbot creation and [24]7.ai Conversational AI technology, check out the resources below, email us, or visit our Contact Us page.
• Web page: [24]7 AIVA Conversational AI—Chatbot Technology with NLP
• Web page: [24]7 Conversations™—Conversational Messaging Chatbot and IVR
• Blog: Chatbot Building: Design and Development Process
• Blog series: Personality in Conversational Interface Design
• Ebook: So You Think You Want a Chatbot?
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