There are best practices for approaching chatbots and virtual assistants as organizations move to a scenario where tasks happen transparently behind natural language interfaces. We explain some of the opportunities and pitfalls.
Chatbot use is on the rise, and the use cases are growing. According to Gartner, by 2021, more than 50% of enterprises will spend more each year on bots and chatbot creation than traditional mobile app development.
In a recent blog, Gartner Brand Content Manager Kasey Panetta said, “Individual apps are out. Bots are in. In the ‘post-app era,’ chatbots will become the face of AI, and bots will transform the way apps are built. Traditional apps, which are downloaded from a store to a mobile device, will become just one of many options for customers.”
Chatbots and virtual assistants such as Alexa are being interwoven into consumer lifestyles. KPMG Digital Enablement Managing Director Michael Wolf says his company sees tremendous potential on the B2B side.
“B2B chatbots and virtual assistants could be the interface across multiple systems,” said Wolf. “We’re seeing a lot of growth in that, and the enterprise platform companies are making investments there, either acquiring the capability or acquiring the platforms to do that stuff.”
Implementing chatbots and implementing virtual assistants differs, based on their respective designs and capabilities. Traditional chatbots are script-based, so they respond to pre-programmed inputs. Virtual assistants utilize machine learning to continually improve their ability to understand and respond appropriately to natural language.
“One of the problems with bots is modeling what they think customers want rather than training the system with real people, not just employees and customers, but the person asking the questions. What are they asking? How are they asking it?” said Wolf. “If you just try to follow your same traditional route paradigms without concentrating on learning and design thinking, you’re going to get less desirable outcomes.”
Expanding B2B use cases
Like other forms of automation, chatbots and virtual assistants are seen as human-augmenting technologies that enable humans to focus on less repetitive, higher-value tasks.
David Nichols, Americas Innovation and Alliance Leader for EY Advisory sees numerous opportunities for B2B chatbots, including internal employee communications, most HR interactions, and everyday interactions such as checking invoice status, delivery status and updates, and customer service interactions.
“The biggest challenge with B2B companies is getting suppliers and customers to use the Chabot functionality,” said Nichols. “Also, B2B companies don’t usually place the same priority on customer personalization as B2C companies. As a result, the customer service interactions at B2B companies don’t usually have the same level of detailed customer segmentation and interaction history. This will present a challenge when developing the use-cases and scenarios for the bot conversation flow.”
In HR scenarios, chatbots provide intelligent means of re-engaging with candidates, specifically sourcing, screening, and updating candidate information.
“[Using] other methods these interactions can take days to weeks for an organization to handle,” said Chris Collins, CEO of recruitment automation company RoboRecruiter. “Chatbots significantly increase the speed and scale that you can operate down to hours and combined with AI can keep the data active.”
That could lead to more positive recruiting experiences for candidates, contract workers, and employers. Similarly, from an outward-facing standpoint, chatbots and virtual assistants could improve brands’ relationships with customers.
“It might seem counter-intuitive that an AI-driven chatbot can help companies build relationships with their customers, but remember, the ‘Millennial Mindset’ is quickly becoming the dominant purchasing orientation, and those customers want to efficiently self-service,” said Anthony Smith, CEO of CRM solution provider Insightly. “In 2018, B2B chatbots will be utilized not only for lead generation, but also as virtual business assistants and they will handle different tasks such as scheduling and cancelling meetings, setting alarms etc.”
Depending on the enterprise applications chatbots are integrated with, they’ll be able to undertake more complex tasks, such as placing orders, invoicing and other B2B activities that are time consuming and usually require precision. However, there are challenges,
“Integrating chatbots with the major payment systems and with social media is tough and it will probably take time, but once this is covered, chatbots will be able to take orders directly through social accounts and that will be a revolution,” said Insightly’s Smith.
Application integration is critical
Automating business processes requires tight integration with enterprise systems. Exactly how many and which systems depends on the purpose of the chatbot. However, because user experience is vitally important, it’s critical to understand what the users of such systems will want to do with them.
“Some are just trying to redo web and mobile rather than using a design approach to using this,” said KPMG’s Wolf. “There’s an assumption because it’s not visual, it doesn’t involve design.”
In B2B contexts, there are a lot of repetitive tasks that take place within businesses processes, some of which require integrations with different types of systems.
“The injection of the chatbot is allowing consumer-like experiences. ‘I want my ERP to feel like Google
and ‘I want my CRM to feel like Amazon’ is a constant discussion for my customers,” said KPMG’s Wolf. “Applying an enterprise chatbot is obvious in that scenario.”
The end goal for virtual assistants is orchestrating everything necessary to answer a query or execute a request, which can involve a complex web of interconnections among disparate systems.
In short, the best way forward is iterative because requirements, technology and user expectations are constantly changing.
Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include … View Full Bio
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