Two technologies are making every business owner excited right now-
Artificial Intelligence (AI)
Machine Learning (ML)
It won’t be too much to say that ML and AI have gradually advanced successfully to become a valuable asset in every business. Research shows that around 85% of executives all over the world believe in using AI for organizational productivity and competitive advantage.
When you decide to leverage AI technologies for multiple applications, you need the best chatbot for business. Hence, these 7 requirements will tell you how to choose the best chatbot architecture for your enterprise :
1. A Single Chatbot Should Execute Multiple Tasks
You can’t compromise with this functionality as it will help you streamline and track multiple functions simultaneously. A multi-purpose conversational AI can complete a wide range of tasks related to customer support, marketing, sales, reputation building, and more. But for that, it should be easy to deploy across multiple systems and channels.
Make sure you get a ready-to-use platform to address various use cases like support, lead qualification, and more. Along with that, it should also come with the scope of customization, so you can align it with your processes and workflows easily.
Here’s what you need to look to go beyond chatbot with a multitasking conversational AI platform:
Building conversation flows without any coding
Drip Campaign setup – Broadcast and Campaigns
Intent analysis and entities
Advanced report and dashboard
Easy Integration API’s
2. Omnichannel Integration for Cross-Channel Support
As you want a single bot for multiple functions, it needs to have omnichannel features. Find an AI-powered chatbot platform that you can deploy on your website, social media channels, digital ads, mobile messenger apps, and other platforms. Make sure its user interface is flexible enough to provide a top-notch experience across all channels.
When choosing a chatbot for customer service, you should find one with cross-channel support as well. The bot must bridge the gap between multiple digital platforms in terms of conversations with users. This means that your bot can remember users and their interactions even if they switch from one channel to another.
3. Speech Recognition and Natural Language Processing
The scalability of a chatbot for business depends on its training - which is why you need to ensure that your bot platform incorporates speech recognition and natural language processing. This technology will decide your bot’s ability to maintain conversations accurately via chat and/or voice.
A conversational AI platform having speech recognition and NLP tends to deliver the best experience. Such bots can understand the intent and emotions of a user in real-time, which allows them to respond accordingly.
4. Conversational Intelligence and Memory
The platform must have the intelligence and memory to understand, remember, recollect, and regularly learn from user inputs, information, and data collected during customer interactions. This property also involves the ability to pick and hold on to the context throughout its interaction with human users. This is when ML, NLP, and NLU technologies play a huge role.
5. Lead Assessment and Validation
Talking about a multi-purpose AI chatbot won’t make sense if you neglect this factor. There are so many channels you want to target, which would bring you leads 24*7 from all directions. But not all of them will be relevant for you to follow. Hence, you need an automated system for assessing and validating lead information.
Choose a chatbot for lead generation that can do this in real-time while interacting with a user. Integrating such a platform with your CRM and ERP systems will help you have a well-segmented view of good and bad leads in one place.
6. Industry Knowledge and Ongoing Support