The COVID-19 pandemic has altered the way we work, interact, behave, and respond, both to one another and to the market. These changes have driven businesses to rapidly adopt digital technologies, particularly conversational AI and chatbots. What began as a toolset for crisis management – especially in healthcare, per the World Economic Forum – has evolved into an enterprise-wide strategy. Yet the technologies are still new to many organizations. While the pandemic has been a good trigger for enterprises to channel resources in conversational AI, their challenge now is to leverage and scale it for their future business needs.
Conversational AI: During the Pandemic
During the early days of the pandemic, it was paramount for enterprises and brands to communicate effectively with customers, employees, and partners. Conversational AI emerged as a prominent tool in informational bots that shared information about the disease and busted myths. Examples include the WHO Bot or the Clara bot to self-diagnose symptoms.
As the lockdowns, social-distancing norms and job losses caused anxiety issues, sentiment-driven bots gained traction. Research shows that people today are seeking more help for mental health and associated increases in social ills, such as substance abuse and domestic-, race- or gender-based violence. This has led to the adoption of many sentiment-driven bots for mental and emotional wellbeing.
And as digital communication became the only realistic channel for regular communications, Facebook and WhatsApp messaging has increased more than 50%. Enterprises have noted this, deploying consumer-engagement bots and chat solutions over websites, Facebook, WhatsApp, Instagram etc. to communicate effectively with customers.
Conversational AI: Beyond the Pandemic
But what happens next? It is evident that the pandemic has had a lasting impact on consumer behavior. A study suggests that consumer behavior has changed forever, with the impact continuing well beyond the lockdowns. More than 40% of survey respondents believe they will resume normal activities only once authorities deem it safe or a vaccine is in place. Enterprises must adapt to these market dynamics and adapt digital channels to remain relevant. Here’s how they can embrace and scale several conversational AI use cases.
These chatbots have largely been deployed for crisis management, but as users get comfortable with the technology, they have a natural inclination toward using it for other information. Enterprises can anticipate this demand by extracting more from their existing investments and deploying these bots in the following ways.
- Enterprise Virtual Assistant: Chat assistants used during the crisis can learn new information on company policies and IT infrastructure, serving as an Enterprise Virtual Assistant to help employees find quick resolution to FAQs, IT support and maintenance, and HR shared services.
- Cognitive and AI Search: With data and content shooting high in the enterprises, companies need a rich searching experience through the data libraries. These more-humanized searches can be accomplished by combining conversational AI, which brings in domain ontology and context, with cognitive search frameworks, which bring rich searching mechanisms through structured and unstructured datasets.
The same bots being used to understand people’s mental well-being have the potential to interpret users’ emotions and reaction toward enterprise offerings. Such business-ready use cases include:
- Augmenting Call Centers and Social Media: Bots can improve conversations with call-center customers by identifying sentiment and suggesting possible resolutions to the agents. The same can be done on social media, empowering the company to understand users’ sentiments (positive, negative, sarcastic, sad, etc.) and react accordingly.
- Emotional Analysis: Augmenting the bots with vision-based cognitive services can help detect human emotions and reactions. For example, while tasting a particular food, if the customer finds it too salty and gives subtle visual cues, these micro-expressions can be monitored and evaluated to make the appropriate adjustments.
Consumer Engagement Bots
These bots are commonly extrapolated to deliver digital interactions, management, and commerce. Some of the less-considered by equally powerful additional opportunities are:
- Lead-Management Bot: As call volumes surge on digital channels, chatbots can be incorporated into the sales funnel by integrating conversational AI with a CRM. This can help enterprises ensure no leads are missed, trigger pre-set algorithms for follow-up, engage leads with a customized experience, and weed-out cold or uninterested leads. Ultimately, this can lead to higher conversion rates as the bot learns from previous interactions and responds appropriately.
- Conversational Commerce and Voice-based Shopping: Customers want to perform all transactional steps as simply as possible. Conversational AI bots must be ready to identify user intents and be able to serve the best possible resolution or action to it. Voice-based shopping does exactly that by enabling home assistants to add routine purchases to the shopping cart and place the order. With a Microsoft Bing Ads study showing more than 40% of respondents have tried to make a purchase using their voice, this functionality can’t be overlooked.
In this time of crisis, technology has helped brands adapt to mutating consumer behaviors and reestablish their connection with customers. Conversational AI has emerged as a platform for communication, interaction, commerce, and service. Enterprises has driven much of this growth, and that trend will continue; the chatbot market is projected to grow at a compound annual growth rate of 29.7% between 2019 and 2024. To capitalize on this new technology beyond the pandemic, enterprises need to strategically invest in it, explore new use cases, and scale conversational AI across their businesses.