My first interaction with a chatbot was seven years ago. A comical avatar popped up when I was trying to renew my auto insurance and offered help. But help it did not. I still gave the brand brownie points for trying to engage, because back then it was a novelty. But we can all agree that no chatbot is scoring any brownie points today, no matter how cute it is. Customers chase value in every interaction, even if it’s with a bot. Businesses plan for a state where chatbots deliver significant business and experience impact but seem to hit a brick wall when scaling chatbots to do more.
In 2019, 69% of global data and analytics decision makers whose firms were adopting automation said they have implemented or plan to implement chatbots in the next 12 months.
Yet most businesses struggle to scale past proofs of concept and pilot deployments and get to the promised land of reduced contacts and optimized costs. The most-cited hurdles to scale are:
- Not enough volume.
- Chatbots are only programmed for information delivery.
- The effort to maintain and update chatbots is substantial.
- Insufficient ROI.
There’s no magic fix for scaling chatbots.
To hit efficiency metrics, chatbots need a degree of training, hand-holding, and structured back-end support — much like human agents. We should also not forget that chatbot ROI is not limited to volume deflection. They are super useful in managing contact center productivity, agent assistance, and customer experience.
Successful chatbot deployments hinge on better architecture and orchestration and conversational design. Focused interaction flows and solid knowledge management are critical for chatbot performance and adoption. My new report on “How To Scale Your Chatbots” explores some of these ideas, user stories, and best practices that will help plan for scale from the onset. Let me get you started with two thoughts:
- Enterprise knowledge cannot be an afterthought if you’re serious about scaling chatbots. Are your knowledge systems part of the chatbot design?
- Contact centers are the least common denominator between your customers and the chatbots and are the most powerful source of insights on what works and what needs fixing. How are they contributing to your chatbot program?
As you head into 2020, this report will answer some questions on what needs to change and hopefully guide you to adopt some practices to accelerate and scale your chatbots.
Happy to talk more or answer any questions via inquiries and advisory.