The Fourth Industrial Revolution is upon us, bringing technologies such as AI, IoT, and blockchain. More than ever, businesses need to consider how to best leverage these solutions, reimagining the way they operate an intelligent and integrated customer experience.
Preparing businesses for tomorrow with conversational AI
One such solution to consider is conversational AI and the use of text and voice-based messaging apps to automate communications between businesses and their customers. As consumers continue to make greater use of these channels, businesses can seize the opportunity to integrate conversational AI technologies.
Distinctive new conversational AI channels
Smart chatbots. Powered by AI, smart chatbots are designed to automatically mimic a human response. These chatbots can message back and forth with customers throughout their commerce journey while also gathering data and generating a more personalized experience. Through sentiment analysis, the chatbot can classify user messages as positive, neutral, or negative and craft appropriate responses. For instance, a chatbot can ask customers for a product review; if the review is negative, the chatbot can follow up to determine whether or not the customer would like to open a service complaint. Recommendations from the chatbot can become more sophisticated as it continues to learn about the customer’s behavior and buying patterns.
Voice technology. Voice technology, enabled by AI, represents the next major disruption to the more traditional commerce channels and presents consumers with a new mechanism for purchasing. The general awareness of voice technology is high among consumers, thanks to the rise of smart speakers, and allows ease of purchasing, particularly for those with limited access to storefronts or who face online purchasing challenges, such as the growing number of consumers with disabilities.
To help ensure the success of voice technology backed by AI, B2B and B2C solutions need to focus on the following:
- Refine the algorithm: A combination of customer account information, purchase history, voice commands, and other inputs should be used to create a personalized experience for consumers.
- Tailor the conversation to the customer: Voice assistants need to adapt to customer requirements during conversations in order to refine the product matrix accordingly.
- Improve voice biometrics: Solutions that can capture nuances around languages, accents, and regional dialects will see increased customer satisfaction due to smoother user experiences.
PwC’s vision for conversational AI
PwC recognizes conversational AI as the next natural interface for business transactions. To meet business outcomes and help drive profits, PwC’s blueprint consists of four main business components:
- Enterprise systems. Identify the systems to be integrated with the e-commerce solution and the integration touchpoints for the conversational agent.
- Conversation interface. Identify the stimulating points in a customer’s e-commerce journey where the conversational agent needs to make intelligent decisions.
- Language processing capabilities and actions. Determine the sophistication level for machine learning, intent recognition, and dialogue management.
- Development and management needs. Establish business processes and the norms for data security and testing.
A conceptual solution for conversational AI
PwC recommends the following approach.
- Requirements and technical specifications. Identify target consumers and potential costs, brand risks, and benefits from automation, and lay out the capabilities and functionalities for the e-commerce and conversational Al solutions that satisfy these requirements.
- Script design and data collection. Determine the conversational AI domain, automation tasks, and conversation process flow, and collect dialogue data that reflects these design goals.
- Architecture. Design architecture that includes front-end conversational components and back-end components, with integrations to the e-commerce solution and databases.
- Development and testing. Develop the language capabilities of the conversational Al solution and the features of the e-commerce storefront, and test and refine the solution.
- Deployment. Deploy the storefront and conversational Al solutions and ensure that integrations with front-end interfaces and back-end enterprise systems are stable and secure.
- Management and security. Manage the e-commerce site and conversational Al solution for quality control, perform software maintenance when required, and ensure that data is being collected and secured
- Analysis and reinvestment. Track performance, review conversation logs and usage metrics, and update the conversational Al and e-commerce solutions with new data and design insights.
PwC’s modern delivery framework for agile transformation
To help you create an end-to-end solution, PwC has developed a modern delivery framework: AIRe (Align, Innovate, Release, Evolve). AIRe is business-led, collaborative, and aligned with the business objectives that drive predictable value, speed, focus, and agility. AIRe incorporates industry-standard agile development approaches, such as scrum and Scaled Agile Framework (SAFe), with PwC proprietary techniques, such as BXT, for delivery and digital accelerators.
By focusing on significant planning, review, and organizational readiness, PwC can help businesses successfully design, adopt, and execute an agile transformation.
Get to know how to build chatbots with SAP Conversational AI in order to improve your customer and employee experiences by signing up for our Webinar session on March 3.
This article is adapted from a publication by PwC and is published by permission.