Customer support, a domain dealing directly with the users, faces backlashes from every unsatisfied customer. With issues here and there in SaaS products, as per the users, your product needs a system that streamlines everything and automates processes. Talking of automation, that can be done with an intelligent technology like artificial intelligence in the frame.
To say that AI has modified the face of customer support and user engagement is an understatement. With assistance for sentiment analysis, automating from the rigid chatbots, and responding in less time, everything has changed for the SaaS product. Where once support needed an extensive team with thousands of people, the human intervention is now limited.
Keeping that in mind, businesses and enterprises have been introducing AI in SaaS to bring forth efficiency, reduce human intervention, and provide users with an augmented support experience. That being said, it is seen that decision-makers are moving ahead with the implementation and development of their SaaS and investing. However, if you have doubts in the context of AI for SaaS, here we bring forth a bifurcation that can assist in ensuring that decision-making becomes easier for you. With this guide on the use cases and benefits, we will assist you in contemplating better.
Imperative Use Case of AI in SaaS Products
Since businesses have been integrating AI into SaaS, they often take assistance from AI development services provider with an extensive understanding. They ensure to integrate features and functionalities that change the experience overall and offer users SaaS-based convenience in issue resolution.
1. Assisting Users With Conversational AI & Chatbots
The first AI-focused revolution that changed the SaaS market for customer support was the introduction of an AI chatbot into the solution. With the users interacting with a conversational chatbot using the chat history, personalization focused on solving the issue, and not offering rigid prompts, the experience changes and brings forth a solution in just minutes rather than hours. This leaves users with no frustration but satisfaction and fixes them with the brand for the long term.
2. Personalization at Scale
With frustration comes anger, and that can lead users not to look for anything but the customer support options. In those situations, with personalization at scale, the AI-powered virtual assistants can recommend to users onboarding steps, essential guides, and troubleshooting assistance that match their needs. Rather than occupying a human for such, AI leaves the segment of intervention behind and brings in automation overlapped with personalization.
3. Continuous Learning from Customer Interactions
While the rigid chatbots depended on prompts and would not offer better solutions after a point, the AI does not go through that. With AI in SaaS as a customer support agent learns every day with the continuous user interactions. Based on the interaction, it can assist someone else tomorrow in less time. This way, the AI model constantly trains itself with the received data and comes to better conclusions with time.
4. Categorization and Prioritization for Intelligent Ticket Routing
Oftentimes SaaS support system receives emails from customers based on the issue they are facing. It can either be to flag a glitch or send a strongly worded feedback on a feature. While this can be the sentiment, both need to be resolved by different departments. Now, also consider that a lot of people might be sending in emails, and leave a huge window for the feedback to get lost in the depths of a mess.
With AI in SaaS for ticket routing, the systems become easier to manage, categorize, and send forward to the department. This way, people get responses just in time to feel that they are valued by the SaaS company.
5. Detecting Frustration or Satisfaction in Customer Tone
Detecting emotions is one of the achievements AI has made so far. Consider that oftentimes, the user is frustrated with something and needs a fix for that. But that can only be expressed through words. In those cases, the AI has a subset, NLP, natural language processing, that analyzes the human sentiment and lets the decision-makers know about the feedback. This way, SaaS owners can work on the issue if it arises from a feature or a functionality, and fix it to gain the trust and change the users’ sentiment towards it.
Conclusion
That being said, it becomes clear that the AI has been modernizing the customer support and changing the user experience based on it. With features like sentiment analysis, AI-powered chatbots, and personalized recommendations, the pace is changing and bringing in the wave of innovation. Keeping that in mind, it is time for SaaS businesses to make decisions that align with their users and have a perception understanding to make the SaaS experience better. With an industry-leading AI development services provider by your side, you can bring the imperative transition with valuable industry insights and experienced experts.