Today, many organizations are starting to use voice or text-enabled chatbots for the first time or already have chatbot systems in place. In fact, Gartner said 25% of organizations are predicted to make chatbots their primary customer communication channel by 2027. This is because consumer behavior has shifted to primarily digital interactions and away from traditional customer support channels.
As a result of today’s digital landscape, consumers are now accustomed to immediate gratification and expect instant responses and resolution from customer support, which makes chatbots an ideal solution for brands to rapidly serve customers. Due to this rising demand for instant customer service, chatbot systems have become more sophisticated and consumers’ reliance on them is increasing. This increase in adoption has led to higher performance expectations for bots and if those expectations are not met, customer satisfaction and brand loyalty will suffer.
Below, we’ll look at three major challenges tied to the growing popularity of chatbots as they handle larger and more diverse groups of customers, and how business leaders developers and DevOps and customer experience (CX) teams can tackle these common challenges with a continuous testing approach.
The Pain Points of Adoption: 3 Key Challenges as Chatbot Usage Grows
As the popularity of chatbots explodes for customers around the world, the underlying systems that handle natural language processing (NLP), latency, data security and other functions need to be stronger. This is due to a growing and increasingly diverse demographic of users, many of whom are sharing more of their personal information to address a wider range of customer needs. Common chatbot pain points can be summarized by three overarching challenges.
Challenge #1: Chatbots must contend with a larger and more diverse base of customers
Chatbots that are voice or text-enabled must be smart enough to operate securely while navigating countless variations in spelling, a wide range of spoken accents and vernacular, background noise, static from bad connections and more. Even in a single language, there may typically be only four or five “intents” from most customers in engaging a chatbot, but those intents may be phrased in hundreds of different ways. Now, the global growth in adoption raises the chance of poor connections and exponentially increases the number of languages and variations in phrasing that a chatbot must understand and interpret.
Challenge #2: Customers are trusting chatbots with more personal and sensitive data
As chatbots become smarter and more trusted by customers to meet their needs, people are getting more comfortable giving their personal data to chatbots. That increases the number of situations where chatbots are working with personally identifiable information (PII) or other highly sensitive data. Especially given GDPR and other data privacy regulations being enacted worldwide, there’s added pressure to ensure a chatbot system’s handling of this data remains secure and compliant across all use cases and geographic regions.
Challenge #3: Modern chatbots require 24/7 availability and reliability
In an era of flexible work and millennial and Gen Z audiences interacting with bots after business hours and on weekends, chatbots can’t afford to work in shifts. Users may be spread across many time zones or around the world, meaning there’s always a sizable portion of customers awake, online and looking for fast and efficient service. Because of this, chatbots must be able to handle spikes and heavy traffic 24/7.
The executive takeaway from these challenges is that modern chatbot investments must be built around dynamic systems capable of adjusting to shifting customer usage and performance requirements.
A Continuous Testing Mindset is Required for Top Chatbot Performance
Fortunately, by honoring a few best practices and making the right strategic technology investments in automated artificial intelligence (AI) and machine learning (ML)-driven systems, C-suite leaders responsible for CX and the teams they manage can deploy chatbots capable of keeping up with the above challenges. Perhaps the most central element for success is to embrace a continuous testing approach.
For example, when a company is undergoing digital transformation and shifting its contact centers and supporting systems to the cloud, they are moving a significant amount of data, reimagining complex integrations and rearchitecting processes. In order to maintain application stability and existing integrations in the contact center, continuous testing is critical to ensure that an organization’s systems still operate effectively throughout the cloud migration process. With continuous testing, development and testing aren’t separate processes. The testing is automated and quality assurance is involved as developers submit code.
The most effective approach to continuous testing includes end-to-end analysis across all channels. Testing chatbot behaviors should mimic real-time customer interactions. This should include challenging scenarios such as unexpected user inputs and usage spikes at random times of the day and night. Automation is critical, especially in peak demand scenarios such as Black Friday, Cyber Monday, open enrollment, etc. Load testing up to 1,000-100,000 bot requests per second, or more, can help ensure companies will be able to handle the increased traffic. Ideally, the testing approach should be comprehensive to include automated NLP score testing, conversational flow testing and security testing and performance testing and monitoring.
By promoting the continuous testing approach across contact center operations, executives can empower their teams to build and maintain chatbots that remain optimized on an ongoing basis and that form an essential part of providing exceptional CX. This will make a huge difference in performance and reliability as systems scale and adapt to the evolving demands of a growing customer base.
Continuous Testing Elevates Chatbot Reliability and Value
High-performing chatbots and the continuous testing that keeps them optimized at those performance levels can benefit any company by lowering risks and enhancing revenue. Organizations that become adept at applying continuous testing avoid 90% of the downtime from high-severity (SEV 1) errors, which can result in saving $2.2 million in costs over a three-year period. When continuous testing touches every stage of the development process, it identifies issues earlier and helps strengthen an organization’s ability to innovate faster and service its customers effectively and profitably.
