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AI Follow Up

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Traditional Chat Widgets

AI Chatbots

Pre-Set Responses:
Traditional chat widgets are built on simple, rule-based systems. They use pre-defined scripts to handle common inquiries, offering a limited range of responses. This means they can only answer what they were specifically programmed to handle.
Linear Interaction:
These widgets typically guide users through a fixed path, offering limited options to choose from. If a user asks a question outside the scope of the predefined options, the bot often fails to provide a helpful answer.
No Learning Ability:
Traditional chatbots do not learn or improve over time. They can't adapt to new questions or changing user needs without manual reprogramming.

Natural Language Processing (NLP):
AI chatbots use NLP to understand and process human language more naturally. They can comprehend context, slang, and even tone, allowing for more dynamic and fluid conversations.
Adaptive Responses:
Unlike traditional bots, AI chatbots can generate responses based on the context of the conversation. They can answer a wide range of questions, provide personalized recommendations, and handle complex queries without predefined scripts.
Continuous Learning:
AI chatbots are built with machine learning capabilities, meaning they can learn from each interaction. Over time, they get better at understanding and predicting user needs, improving their effectiveness and user satisfaction.
Personalization:
AI chatbots can tailor their responses based on user data, preferences, and previous interactions. This creates a more engaging and relevant experience for each user.

Example Scenarios

Traditional Bot

AI Chatbot

Product Inquiry:

"Please choose from the following options: 1) Product details, 2) Pricing, 3) Store locations."

"Sure! What kind of product are you looking for? We have several options based on your recent searches."

Complex Queries:

Struggles or fails to answer questions outside its programming.

Understands complex queries, such as, "Can you recommend a gift based on my last purchase?" and offers tailored suggestions

Customer Engagement:

"Thank you for your inquiry. Have a great day!"

"Thanks for reaching out! By the way, if you liked what you bought last time, you might love this new product we've just released!"

Never miss a customer call

Answer calls without picking up the phone. Engage callers immediately by texting

answers to frequently asked questions in their voicemails.

WATCH DEMO

Your New Virtual Receptionist

Your new virtual receptionist

Receptionist answers calls when you're out of office, closed or just busy on the phone. All missed calls and voicemail transcriptions are delivered to you in a centralized inbox.