by Dave Smith

Develop a decision framework for enterprise chatbots and conversational experiences

Jul 27, 2017
IT GovernanceTechnology Industry

Enterprise chatbots are critical for digital workplace transformation. They can access status and workflow data, perform tasks automatically, respond to text or voice commands, plan and schedule interactions, and contextualize events within internal and external business processes.

chatbots chatbot bot
Credit: Thinkstock

In speaking with enterprise business leaders in a wide range of organizations, the number one priority has been and still is improving and delivering a better customer experience. This is at the center of all business strategies. In fact, if it is not, I dare to say, you do not have a real people-centric business strategy. So it’s no surprise that we are now witnessing the synergistic rise of artificial intelligence and AI-enabled chatbots to provide conversational experiences for users and customers. Enterprise chatbots have to be implemented with the primary purpose of providing conversational experiences for internal users and customers.

Enterprise chatbots are critical for digital workplace transformation. They can access status and workflow data, perform tasks automatically, respond to text or voice commands, plan and schedule interactions, and contextualize events within internal and external business processes. Business and IT leaders need to act now to optimize how people access and share information for better business outcomes.

It is imperative that enterprises develop strategies around chatbots to remain competitive in the emerging digital landscape or risk falling behind. Chatbots can effectively help enterprises with the critical issues they face around collaboration, information access, customer experience, troubleshooting and support. While chatbots have been growing in popularity in the consumer space, the increasing interest in enterprises is a natural outcome. Companies are looking to develop their own chatbots to improve internal business processes and create better customer interactions and experiences.

Enterprises are also focusing chatbots on better interactions and experiences for partners and B2B customers in the overall ecosystem. It is in these external collaboration scenarios where a federation and integration platform is critical for enabling secure communications with business partners and external constituents. Some providers have come up with unique approaches, directly trying to address aspects of this with offerings such as 8×8 Sameroom and NextPlane nCore. 

Now while there is admittedly a lot of hype around chatbots, companies have to focus on the business case and purpose for implementing chatbots in the first place. The specific use cases have to be considered, with a focus on being able to measure the return on investment. The decision framework has to start with the business purpose, considerations around uncertainties and what might be difficult to quantify, costs, benefits and, finally, the measurable business value and outcomes.

Enterprise planners responsible for chatbot implementations should ensure that the communications and collaboration functions are integrated with business workflows, applications and processes and aligned with the underlying business purpose. The two overarching use cases will be internal and external communications. Planners should outline what falls under these two buckets for their specific organization. The ultimate goal is better customer and employee interactions. In fact, better employee interactions have a significant impact on customer satisfaction and aid in providing better and personalized conversational experiences for customers.

As planners develop a chatbot strategy, their decision framework should include specific questions about the use cases and functions that are needed. Planners should ask the following questions:

  • Are we trying to enable internal or external customer-facing communications with a chatbot?

  • How will the chatbots affect or improve the customer, partner or internal employee experience?

  • What business processes will it streamline or improve? Or replace?

  • What business applications will it need to integrate with (e.g., does it need to speak with a CRM application such as Salesforce, Box or Dropbox, or appear as a contact in a UC client such as Skype for Business, Cisco Spark or Unify Circuit?

  • What will be the data source or sources that will feed into the chatbot?

  • What are the enterprise security and governance requirements?

  • What is the cost to develop and implement a chatbot?

  • What platform will the chatbot be built on?

  • Where can you discover chatbots in a directory to serve different functions?

  • How will you provide customization and ongoing maintenance?

  • Also, you ultimately have to weigh the costs and risks versus the benefits and return on investment. If the chatbot reduces support personnel or increases sales, those are clear KPIs to measure.

I recently spoke with the CMO of a technology company who explained that one of their clients had written over 2,000 bots, and is now migrating them to a Microsoft platform. This has become a major effort, because the bots need to be only migrated, but also periodically evaluated and updated. The lesson here is that a chatbot initiative is an ongoing commitment, not a one-off project.

So while there are lots of considerations that should go into planning and your decision framework, the goal has to be people, customers, and their journey and experiences. The rise of messaging apps shows that consumers prefer real-time interactions that are more personalized and natural. People want conversations rather than cold interactions. Enterprise chatbot strategies have to be driven by a vision to create better conversational experiences that put the customer front and center. Also, it has to start by improving the communications experience of internal staff, in particular those that are customer facing. This requires a shift towards becoming a conversational enterprise with necessary data and information in the context of employee and customer interactions.