Customer service is important for any product, whether it is a software product or physical product. We’ve all had experiences with customer service, where we were made to wait in line to speak to a representative and the wait time may go for 30+ minutes. For those who don't have much time to wait on the phone, they often opt to use online chat, automated messages, or system FAQs. But the quality of support from these static or rules-based support systems is very general and does not solve customer issues effectively.
Exceptional customer support can significantly contribute to brand building, customer identification, increased sales, customer retention, as well as uncovering opportunities for upselling and cross-selling. With good customer support, customers will not hesitate to give valuable inputs that can lead to product ideas. It can lead to building new or enhancing existing products. This will save product builders a lot of time in doing customer study. The feedback and input from current customers complement external customer studies and research effectively. Good customer support also helps to make better business decisions based on data.
With the advancement in technologies, the support has come a long way. Now with the Large Language model (LLM) such as GPT, LLaMA, Google Flan, etc., taking over the world, everybody is looking towards the next phase in customer support.
With LLM models, the customer support can be personalized and unique as per the user. AI based systems are going to be advantageous in many ways.
- Chat and email replies can be automated and personalized.
- Issues can be correlated and grouped.
- Anomalies can be detected faster and accurately.
- It can provide better insights on product performance and feature usage, allowing teams to focus on building features that truly matter to customers.
- Available 24x7x365 days.
- It can be deployed at a faster rate than training a human being.
- Will reduce the number of people needed to provide the support over the phone, chat, or email. The time saved on this can be used by humans to do more innovation for their product.
- As the models mature, it will get better. The solution will become cheaper over a period.
- Language translation becomes easy.
Training these LLMs is time consuming, costly, and not many companies can do it. But there are models such as Meta LLaMA, Google FLAN that are pre-trained on various sizes. LLaMA is available trained with 7B, 13B, 33B, and 65B parameters. FLAN is trained with up to 137B parameters. Systems learn from each interaction and learn more with each interaction over course of time, this makes responses/interaction a lot more accurate and advanced. It is impossible for humans to get trained with this much volume of information. In order to get a better result from these LLM systems, the prompt generator (input) to those systems must be meaningful. The more personalized the prompt generator, the better the results from the LL systems. The companies that find a niche with prompt generators will be in an advantageous position. This can make a real difference in customer support with the AI based systems that will help them with customer acquisition, retention and lower churn.
CuVo is committed to making a difference in customer support and product insights. Its leading AI based customer service solution can help companies and product builders make a difference. Companies can focus on building their businesses and CuVo can help take care of the customer support. If you would like to explore how AI can help with your product building or customer support, we are eager to help you and be part of your success journey. Let us talk.
