AWS has shared a demo of how Amazon Connect customers can blend the solutions available to them and “easily” create customer self-service journeys.
Keith Ramsdell, Principal Product Manager at AWS, led the demo, which the cloud giant shared on its social channels after AWS re:Invent.
In doing so, Ramsdell first explained how AWS breaks down customer journeys into four main areas of consideration and how users must address each specific area to maximize their self-service journeys
- Proactive Customer Engagement: Companies should reach out to customers before they contact their centers, whether to inform them of service issues, outages, or offers.
- Omnichannel Engagement: Customer experience and service teams cannot operate under a ‘one size fits all’ approach; they must blend modalities to deliver the best-fit experience.
- Issue Resolution: Companies should implement structured, efficient processes for assisting customers in addressing their problems, which should make it easy for customers to determine the problem and fix it.
- Back-Office Process Automation: By simplifying follow-ups, agent evaluations, and overall performance assessments, businesses will encourage a more seamless self-service journey.
For Ramsdell, an effective self-service customer journey contains elements of all four of these considerations. During the demo, he explained:
When we built Amazon Connect, we focused on weaving these capabilities together from the ground up, making it easy to inject AI at every part of the experience.
“We aimed to let you [Amazon Connect users] decide when and how to use these capabilities.”
The Right Tools for the Job
In order to assist users with implementing AI across their journeys, Ramsdell points to the Amazon Connect Flows solution, a no-code, low-code drag-and-drop tool that lets users create workflows for anything from IVRs to process automation.
In a nutshell, AWS promises: If you can outline a step-by-step guide, you can build these workflows.
Additionally, users can enhance these workflows through features such as “customer profiles”, which helps personalize automated customer journeys.
The AWS man expounds on some of these innovations, detailing how AWS’ text-to-speech feature creates a consistent brand voice, its conversational AI facilitates natural dialogue, and its Amazon Q and Contact Lens provide advanced analytics and generative AI (GenAI) capabilities.
Ramsdell states that these tools are designed to suit businesses of all sizes, and all allow users to customize their AI integrations in order to better understand and improve customer interactions.
Another feature that helps businesses design and manage their self-service journeys is AWS’ Conversational AI bots.
The bots support dynamic, human-like conversations in over 25 languages and are easily configurable for tasks like flight booking and utilizing utterances and prompts to effectively handle customer intents.
While all of these features are useful, Ramsdell emphasizes the importance of the flow designer, which ties these capabilities together and enables the creation of sophisticated experiences via its no-code interface:
With just a few clicks, you can save and publish these experiences, transforming traditional contact center operations into seamless, AI-powered customer interactions.
AWS further expanded on its conversational AI capabilities at re:Invent. To catch up on all the contact center announcements, check out our article: AWS Gives Amazon Connect a GenAI Facelift, Makes 10 Big CCaaS Announcements
