When choosing a conversational AI platform, you should consider a platform with a variety of features. A conversational AI platform can enable your business to automate conversations with customers, answer questions, assist employees, create leads, and assist on various communication channels. But it’s not as simple as comparing a list of features.
Each platform has its own unique AI features, integrations, pricing structures, security measures, and customization options. An effective plan for a small company might not be sufficient for a bigger company. Similarly, one might turn to an enterprise platform, but it is not necessarily needed by a company that has only a simple website assistant. The best way is to list your business goals and then analyze each platform to see if it has the features you need. Here is what to look for before you decide on what Conversational platform you will work with.
What Is a Conversational AI Platform?
Conversational AI platform is software which gives the possibility for business to develop, deploy, manage and enhance AI-driven conversations. These conversations can take place on the website, mobile apps, or any other communication platform within the website.
Conversational AI platforms use computer-based technologies like machine learning and big language models, which can deal with customer questions and give them helpful answers.
Businesses can use conversational AI for:
- Customer service
- Sales and lead generation
- Product recommendations
- Employee support
- Information retrieval
- Automated workflows
At ChatbotsAI.net, we explore how conversational AI and AI chatbot technology can help businesses create more useful and efficient customer experiences.
What to Look for in a Conversational AI Platform
Start With Your Business Goals
Determine the business objective you want to achieve with conversational AI before comparing platforms.
One example is a business that wants to decrease the number of repetitive customer service requests that their human agents have to deal with. Still another enterprise could require an AI assistant that filters leads and plans sales consultations.
Ask yourself:
- Who will use the platform?
- Which conversations should it automate?
- What channels will customers use?
- What systems must it connect to?
- How many conversations do you expect?
Evaluate Natural Language Understanding
It’s fairly common for customers to ask questions in slightly different sentences. They may use slang, misspell words, ask follow-up questions, and provide incomplete information. These messages should be understood by your AI platform and the intent behind them.
Consider testing any platform that you are interested in with your real-world customers. Don’t do all of the demonstrations prepared.
Check whether the system can:
- Understand different ways of asking the same question
- Maintain context across multiple messages
- Handle follow-up questions
- Recognize user intent
- Ask for clarification when necessary
- Respond appropriately when it does not know something
A platform that provides “smart” answers that don’t reflect customer intent will add to the issues.
Check AI Model Flexibility
Various conversational AI solutions may utilize separate AI models or offer businesses a selection of AI models to pick from. AI models can come in all shapes and sizes, and so does their flexibility, as different models have different performance, cost, speed, language support, and capabilities.
A platform that offers several models can provide your company with choices when your needs evolve. For simple queries, you might be able to use a faster and cheaper model, and for more complex queries, use a more sophisticated model. It is, of course, important to also know how the platform processes any model changes. The pace of change is rapid in the realm of AI technology, and it is crucial to have a clear plan for implementing new features or capabilities that do not significantly impact the customer experience.
Look at Knowledge Management
The conversational AI should be able to get the correct data regarding your business.
Look for platforms that can connect with sources such as:
- Websites
- FAQs
- Product documentation
- Internal knowledge bases
- Customer support articles
- Company policies
- Product catalogs
- Business databases
This data should also be easily accessible from the platform to enable it to be updated. When the return policy is updated, your AI assistant shouldn’t keep providing information to customers according to the previous rules.
Certain platforms are retrieval-oriented, that is, they seek out pertinent content prior to composing a response. This can assist to anchor the answers in the context of your content, instead of just the AI models general knowledge.
Consider Integrations
Essentially, it makes the most sense when a conversational AI platform can integrate with your business systems in place.
Depending on your organization, you may need integrations with:
- CRM platforms
- Help desk software
- E-commerce systems
- Marketing platforms
- Customer databases
- Scheduling tools
- Analytics platforms
- Communication systems
For instance, integrating an AI with a CRM system can help gather leads and pass them along to the sales team immediately.
Regardless of what platform you plan to buy, make a list of the systems that you use and what those systems should interface with the AI. Next, check if integrations can be used as is or if they must be custom-developed.
Check Omnichannel Support
Your customers may use more than one channel in relation to your business.
A conversational AI platform may support channels such as:
- Websites
- Mobile apps
- Social messaging
- SMS
- Voice
- Business messaging platforms
If you have customers on different channels, try to think about the consistency of the experience on the platform. But don’t pay for Omnichannel functionality just because they sound like the things they think you might want to use. Select channels to match how your customers behave and your business objectives.
Evaluate Human Handoff
Do not let the AI handle all the conversations in your business. One good trait of a good AI is the ability to know when to answer questions and when to hand it over to a human customer care representative. The system should be able to recognize conditions that demand the involvement of the human and make the transition as simple as possible.
Look for features such as:
- Human agent escalation
- Conversation history
- Support ticket creation
- Team routing
- Agent notifications
- Context sharing
Customers should not have to repeat information they already provided to the chatbot. Preserving conversation context can make the handoff faster and less frustrating.
Prioritize Security and Privacy
Conversational AI systems are capable of managing many customer data points. This places emphasis on security and privacy.
Before choosing a platform, understand how it handles:
- Customer data
- Conversation history
- Data storage
- Data retention
- User permissions
- Encryption
- Access controls
- Third-party integrations
If your business is regulated or requires the handling of sensitive data, there could be more compliance requirements.
Never use a platform because it’s in use. Check its security policies and see if they align with your security needs.
Assess Scalability
A platform should support your business as it grows.
Consider how it handles increases in:
- Conversation volume
- Users
- Websites
- Communication channels
- Languages
- AI usage
- Business integrations
What works for a smaller customer service team won’t necessarily work for a larger business with thousands of conversations a day.
Inquire about volume limits, performance, pricing increases for higher volumes, and how easily new capabilities can be added.
Compare Analytics and Reporting
Analytics will give you an overview of how all the operations are taken and whether the conversational AI platform is giving value to both the clients and the business.
Useful metrics can include:
- Conversation volume
- Resolution rate
- Escalation rate
- Customer satisfaction
- Response time
- Lead generation
- Conversion rate
- Frequently asked questions
These analytics will also give you an idea of what should be improved on the platform. If there are some questions that are repeatedly asked and the platform cannot give an answer, then you do an update, and everything gets back to running as normal.
Consider Conversation Design Tools
Good AI responses are not bound to be a good customer experience. The speech must be thoughtfully planned.
Look for tools that allow your team to control:
- Welcome messages
- Suggested prompts
- Conversation flows
- Error handling
- Clarification questions
- Escalation rules
- Tone and language
Your platform should help you create clear and easy-to-follow conversations to give both your clients and team an easy time. Avoid complicated chatbots since they will confuse the clients about what to do and how to follow the conversations.
Review Pricing and Total Cost
Conversational AI platforms have various pricing models. Some charge per use, conversations, AI usage, features, and/or a mixture of these.
Compare prices by looking at the total price, not the initial price advertised.
Account for:
- Subscription fees
- Conversation volume
- AI model usage
- Integrations
- Development
- Implementation
- Support
- Additional channels
- Premium features
A platform that costs more per month could pay off in the long run if it takes work off your hands and works well with current systems.
Test Before You Buy
Running a demonstration is a great way to see what a platform can do, but conducting tests in real scenarios provides a much better picture.
Make up a test set from the customer’s actual questions. Add simple requests, complex questions, follow-ups, spelling errors, unclear requests, and questions that are beyond the scope of the chatbot.
Measure:
- Response accuracy
- Response speed
- Context handling
- User experience
- Human escalation
- Integration performance
Frequently Asked Questions
What is the most important feature of a conversational AI platform?
Unlike some features, which are relevant to all businesses, there is no one accurate feature. Some key features to consider include strong language understanding, reliable knowledge management, integrations, security, analytics, and human handoff.
Can conversational AI work with a CRM?
Yes. AI assistants can gather, update CRM data, qualify leads, and assist with sales processes through various platforms providing CRM integrations.
Can conversational AI replace human agents?
No, conversational AI can handle a lot of things, but human interactions are still needed to make complex decisions and solve situations that the AI cannot handle.
How do I test a conversational AI platform?
Test the platform’s knowledge, outside-of-scope handling, integrations, and escalation system, the speed, and the ability to handle customer requests not in its scope of knowledge using actual customer questions.
Conclusion
When selecting an AI for conversations, you must consider something other than a chatbot. The right conversational AI platform should be able to understand the client’s needs and also know your business and its ins and outs. This will allow good flow in conversation and understanding of what the client needs. It’s also important to evaluate any potential platforms by real customer situations before committing to it for long.
This can uncover some restrictions that might not be apparent in a product demonstration. You can learn more here about conversational AI, AI chatbots, customer service automation, and other technologies at ChatbotsAI.net. By carefully selecting from the beginning, you can ensure that your business can have meaningful conversations with AI, and its complexity is not an issue.
