An artificially intelligent receptionist, provides your company with a new, quick-learning “staff member.” Bowie, like Siri and Alexa, is a bot that responds to and books customers via text, Facebook, and web chat. As a result, your front-desk staff will spend less time on the phone or computer and more time on your clients and the studio experience. Messenger[ai] works around the clock to free up your employees and bring your company into the future. But, because we understand that every business is different, you can tell your AI receptionist exactly what to say for anything beyond the basics.
Here are four strategies for making your bot the master of your front desk.
Spend some time with your new employee Messenger[ai] quickly becomes an expert on your business once it is set up.
The bot learns about your services, schedule, and staff availability directly from your business software. If your software is up to date, Messenger[ai] only requires a one- to two-hour onboarding call to get started. Messenger, like a new human employee, requires additional training to truly understand your business and customers. To help the bot reach its full potential, you must first prepare it for questions that your customers may have that aren’t covered by your scheduling software.
This includes teaching your bot to recognize the different ways clients ask similar questions. Customers may inquire, “Do you have any specials?” and “Do you offer makeup application?” If you own a salon and offer a “The Madonna” special that includes a makeup application and a blowout. Messenger can decipher both with your help by classifying “The Madonna” as a “Makeup,” “Blowout,” and “Special” service so that your AI knows how to respond.
Create the bot of your dreams.
Messenger is a bot, but it can exhibit human-like traits. Personalize yours to match the look and feel of your company in order to connect with your customers more effectively. You can change the name, photo, and voice of your bot to match the branding of your company. This could include emoji, slang, and so on, depending on your brand’s voice and tone. Give your AI a personality that your customers will adore.
Create a collaborative team of data scientists, IT professionals, and end users that includes policies and procedures.
Most organizations recognize the importance of collaboration between data science, IT, and end users, but they don’t always follow through. Effective departmental collaboration is dependent on clearly articulated policies and procedures that everyone follows in the areas of data preparation, compliance, speed to market, and machine learning.
Make use of life cycle automation tools.
If you can automate some of your big data, AI, and ML life cycle maintenance functions, do so. Handoffs between data science IT and production can be automated using automation software. It makes the deployment process much easier.