The future of automation? Customer-focused
In a post-covid world, smart businesses aren’t just implementing conversational AI to deflect customers. At a time when customer experience is well on track to eclipse price and product, automation has to do more than just save businesses time and money — it also has to help you better serve your customers.
They’ll be most comfortable speaking with a virtual agent if they feel like it actually understands them. And when it comes to trust in conversational AI, research confirms that usability is queen. And usability is powered by accuracy.
Create better bot conversations
Introducing our new Training Center
How can you help your virtual agent interpret incoming messages as accurately as possible? The key ingredient to empathetic and efficient bots is Natural Language Processing, or NLP. It’s what sets apart a new generation of highly sophisticated virtual agents from earlier, more limited chatbots, just like engines separate a jumbo jet from a paper plane.
The thing about natural language? It can be emotional, full of typos, and spelled all kinds of ways — because human talk is creative, varied, and messy.
Turn your bot into a lifelong learner
Just like humans, virtual agents continue to refine their communication skills over the course of a lifetime. They just need a little help from their friends — or your company’s AI manager. By optimizing your AI model through training, you are broadening your virtual agent’s vocabulary, and turning your bot into a lifelong learner.
So where can you sign your bot up for classes?
At our new Training Center.
If you think of yourself your virtual agent’s coach, then the Training Center is your premium gym, with all the top-notch equipment you need to whip your AI model into shape and help your bot grow even smarter.
You’ll achieve this in three key ways:
1. Message Training: Review real messages from real conversations in real time, and use advanced search to find the most impactful messages to train.
2. Intent Training: Focus on existing intents that need further training, and let the AI suggest which messages should be trained to which intents. Then, dive in and clean your data.
3. Confusion Matrix: Spot overlapping intents and fix them on the fly.
The best part about these features? Absolutely no coding necessary. Just drag and drop to train your messages to an intent, and fix intent confusions with only a few clicks. Then, lean back and let your AI do all of the heavy lifting for you. So you can gain maximum results with minimum effort.
The better your AI model, the smarter your bot, the happier your customers.