Five Ingredients for Successful NLU

Too many businesses have implemented AI “pilots to nowhere”. Many lack a comprehensive approach to natural language understanding (NLU). And with customer-facing AI, customer experience is just too important to deliver only half solutions. So what are the key ingredients of NLU?

Ingredient 1: Intent Classification

To understand the intent of customer questions with high precision, deploy multiple AI classifiers in tandem. Be sure to select classifier combinations that best serve your industry or use cases. Of course, implementing effective NLU means accounting for curveball questions…

Ingredient 2: Semantic Search

Semantic knowledge graphs implemented in parallel to classifiers can help companies tackle a wide array of questions with AI. This means fewer agent escalations, higher automation rates, and higher customer satisfaction.

Ingredient 3: Tone Analysis

This allows your AI to interpret feelings via a customer’s tone and respond appropriately. Frustrated customers may just need a simple path to resolution, while happy customers might be receptive to an upsell. Tone analysis means you can deliver an automated experience without compromising a personal and empathetic brand voice.

Ingredient 4: Sentiment Analysis

Sentiment analysis allows for an even more granular view into your customer’s feelings. It deciphers between satisfied and elated, discontent versus fury, and determines how best to engage a customer.

Ingredient 5: Emoji Analysis

Some say it’s hieroglyphics reincarnated, emojis represent natural language in perhaps its most modern and informal manner. In short, emoji analysis can make communication easy for customers. Associating emojis with tone and sentiment can again allow automation to adapt to a customer’s disposition. Without these five key ingredients of NLU, your AI might simply fall flat for your customers.

Is your company ready to up its NLU game?