The AI boom is well underway. In 2018, 15 percent of Americans reported that they had interacted with a company’s chatbot—an automated, web-based conversation platform—in the prior 12 months. Further, 35 percent of Americans indicated that they would use a company’s chatbot to resolve a problem or obtain detailed information on a subject of their interest.
With some 75 percent of employees reporting that their organizations have begun or plan to automate select business processes in the coming year, there is little question that the rate of automation in business is accelerating. As such, businesses that have not yet invested in basic automation systems like consumer-facing chatbots must now grapple with the question of whether to invest time and capital into the development of such systems.
It’s imperative for leaders of these organizations to conduct a thorough cost-benefit analysis outlining the potential value adds and cost losses that would accompany the decision to employ bots. While chatbots promise to augment customer service and optimize the sales pipeline, they come with several potential drawbacks, including low-quality customer service and ambiguity around KPIs (key performance indicators)—both critical considerations for leaders who care about achieving long-term success. With that said, the best chatbot solutions improve the customer experience to drive sales.
The Best Chatbots Accelerate Organizational Goals, Sales, and Customer Experience
Any thriving organization’s success is in some part attributable to team members’ collective commitment to shared organizational goals. Once leaders have pinpointed and articulated their organization’s KPIs—three to five meaningful, memorable, and measurable topline priorities—they can take action to align AI and sales excellence around these objectives and cultivate KPIs for achieving them.
A complementary approach to KPIs is the world of OKRs, or Objectives and Key Results systems, that was created by Andy Grove of Intel and taught by John Doerr, author of Measure What Matters. Grove interestingly believed that every person should set their own goals and execute on them. One interesting way to look at the OKR/KPI approach is to see the KPI or indicator as the intermediary success component. Set objectives, create KPIs that tell what is on the way, and measure to see if the key results are achieved.
The ability to automate some degree of progress toward the achievement of OKRs and KPIs is among the foremost advantages of deploying chatbots. For example, if one of an organization’s KPIs is achieving 15 percent year-over-year revenue growth, a chatbot’s ability to handle the front end of the sales pipeline by fielding users’ questions, providing access to information about the business, and generating leads will help the organization raise conversion rates and, as a result, clear this benchmark.
Since chatbots don’t require lunch breaks or sleep and are always “on,” they further accelerate the rate of progress toward the achievement of KPIs. Bots’ ability to promote business success at all hours serves as a benefit not only to organizations themselves but also to consumers who may be seeking information at a moment’s notice.
In fact, a recent survey confirmed that consumers see “24-hour service” as the greatest benefit of chatbots. “Getting an instant response” was identified as a major benefit of chatbots as well, with 55 percent of survey respondents highlighting this value add.
The ability to operationalize the initial steps of the sales process (and quite possibly many other steps) with minimal human intervention is another clear draw of employing customer service chatbots. Leaders who may have previously been forced to expend significant resources on securing new talent to perform these steps can rest assured that a bot can manage several touchpoints in the sales pipeline on its own—with lower overhead costs, to boot.
When Chatbots Go Wrong
As the AI algorithms powering chatbots and other consumer-facing platforms become increasingly capable of learning from and evolving in accordance with historical data, unfamiliar problems will arise for the businesses employing these systems.
The downfall of Microsoft’s chatbot Tay in 2016 is among the most poignant examples of such pitfalls. Within mere hours of the bot’s launch, the machine-learning algorithms that powered it had ingested a wealth of data from Twitter, causing the bot to tailspin into racist, sexist babbling. As a result, Microsoft was forced to take the chatbot offline after less than a day.
The story of Tay serves as a testament to the growing need for establishing clarity regarding KPIs when it comes to the use of AI in business. AI in business—beginning with the chatbot revolution—requires KPIs from design and development through to real-life application and performance assessment.
Keeping Chatbots in Check with Organizational KPIs
The debate surrounding who—or what—should take responsibility for the behavior of AI systems is becoming a hot-button issue, with many calling for more stringent industry regulations or even the development of federal or international codes of AI ethics.
Unfortunately, most of the media hype surrounding the issue has focused on cases like Microsoft’s chatbot fiasco—that is to say, it has amounted to retroactive handwringing. Moving forward, organizational leaders should take charge of guiding the conversation around AI KPIs in a new direction: forward.
It is a mistake for leaders to think of KPIs as inherently punitive or retroactive. Instead, leaders invested in the future of business (which will inevitably involve bots and other AI systems) must view KPIs as a critical component of any ethical, successful company culture, and must cement it as part of their organizational consciousness from the get-go. Leaders should define KPIs with their teams using an agile approach that ties to top needed results. In short, KPIs are defined early on and consistently reaffirmed, rather than one that is made only at the beginning of the year.
When employees take responsibility for delivering on KPIs and client expectations ethically and effectively, they avoid relying on chatbots or other technology to do their jobs for them. Rather, they ensure that these systems work with them, operating in a way that promotes both the KPIs and goals of their organization.
This is all to say that the debate surrounding whether it is the duty of policymakers, computer scientists, industry regulators, or AI systems themselves to be accountable for bot behavior becomes less pressing when businesses make personal and team KPIs integral to their cultural identities.
Determining When to Implement a Chatbot
As the corporate landscape at large continues to shift toward higher levels of automation, there may be no better time than the present to implement chatbots. The best chatbots provide a minimal maintenance means of engaging potential leads, ushering leads through the education stage of the sales pipeline, and responding to customer service needs. In many cases, bots promise to expedite the achievement of KPIs and increase overall operational efficiency.
That said, it is vital for organizational leaders to remain nimble enough to troubleshoot bot-related issues at the drop of a hat. If they put in the legwork to establish KPIs in the workplace, organizational leaders can feel confident that their chatbots will work in harmony with their employees to meet customer needs, embody cultural values, and achieve or even surpass desired business results.
