Rezo.ai has been supporting some of India’s largest logistics companies to create a smart workforce and reduce operational costs by 20-30% this festive season.
For these companies, Rezo.ai has efficiently brought down customer query resolution time by 4X – resulting in repeat customer orders and retention along with significantly increasing agent efficiency.
Speaking about the feat, Rashi Gupta, Chief Data Scientist & Co-founder, Rezo.ai said, “Rezo.ai adds a strategic value to the business when it comes to engaging with customers and creating a distinct experience for them. We leverage proprietary algorithms built using next-generation technology – AI, NLP, NLU to train models from unstructured voice and text data. These models once trained for an enterprise get deployed as virtual agents with the ability to talk and revert to customer queries just like the enterprise’s “best agent”. These models are designed to scale without a ramp-up period, provide a fast and consistent response to customer queries and save significantly on operational costs.”
This ground-breaking solution assists businesses in identifying the causes of slow sales as well as elements that would help them accelerate sales by assisting them ineffective customer interactions.
Investments in digital technologies such as AI for customer-facing business functions are on the rise in the logistics sector. Rezo.ai has been seeing immense traction and interest from domestic as well as global logistics companies.
Rezo.ai enhances the customer experience (CX) with in-built Robotic Process Automation (RPA) and also analyzes customer–agent interactions whilst training the agents accordingly.
Companies in Logistics and several other industries rely on contact centers for handling customer service requests, queries, and escalations.
By partnering with Rezo.ai, clients could see drastic improvements in customer satisfaction. The solution can assist agents and can also run in a fully automated manner. The agents can handle 2.5x the volume and with an automated system, exponential volumes can be handled with ease.