Here’s how you can save 9000+ manhours with AI Chatbots | Escalon Services
Escalon Services is an essential business services company providing back-office services which are essential to maintaining a company, from CFO services to accounting, payroll, and HR. They currently serve a clientbase of 3000+ clients across 22 countries.
Being an INC5000 company, Escalon Services was growing at an unprecedented rate, adding new clients every week. Their existing product had multiple dashboards which gave their clients an overview of the health of their business, and the financials, along with department related data.
The reports and data on this dashboard were limited to what Escalon would show to their customers. As a result, for a custom report requirement, or in order to drill down further into the data, clients would have to either email Escalon’s support team, or wait on call, until a customer service representative was assigned to them. Due to a high turn around time, both these scenarios were resulting in a very poor customer experience.
With this chronic operational muddle, Ruby Sahiwal, CEO of Escalon Services started searching for a solution that could help the company address this problem statement.
Returning to the drawing board, Escalon realized it needed a scalable way to address the problem of personalized communication.
Escalon’ team came across WotNot’s blogs on customer service automation using conversational AI during their research, and connected with the team to arrive at a solution.
WotNot’s team examined the problem, and proposed an AI-based chatbot solution, which would help address the issue of scalable customer support with round the clock availability. This chatbot would provide a single cohesive user experience for all queries.
Minimizing customer support requests and giving our customers the best possible conversational experience, on autopilot, was the goal for this project.
As a pilot project, it was decided to train and deploy the bot to cover only accounting services. Based on the results, the bot would be subsequently implemented across all service offerings.
Escalon provided the WotNot team with a list of frequently asked questions, and a few ways in which the same queries were asked on email/call in a different way. Using this data, WotNot built the knowledge base of the chatbot with a set of intents, utterances, responses and entities which would be the heart of the chatbot solution. The chatbot was further integrated with Quickbooks, which was used to manage their client’s accounting data, in order to pull and push relevant data.
Escalon deployed WotNot’s in-app support bot, so users could launch an in-app conversation without exiting the application. Customers would authenticate, and log in to their dashboard, open the chatbot and type out any accounting related query. The AI-based chatbot solution would understand the intent behind the query, and see if it matched its knowledge base. The bot would then fetch the relevant response, along with dynamic values from Quickbooks database.
Customers could frame the query in various ways and still be able to receive the right answers. The Natural Language Processing(NLP) was smart enough to discard spelling mistakes or sentence framing to identify the customers intent.
The turnaround time to get queries answered is now reduced to a few seconds, which otherwise would go upto hours or even days at times depending on the complexity of the query.
Even though they had locked down the scope, they were willing to accept requirement changes. The team went above and beyond to make sure that the final product is viable, secure and addressed any and all concerns of our team during the handoff, which we appreciate.
Escalon has now been using WotNot for about a year to listen and talk to its customers. In addition, this has paved the way for the team to develop more positive working relationships with its customers. “WotNot has truly helped in changing our conversations,” Rubi says.
Overall, implementation of the chatbot has resulted in,
Reduced the daily inflow of tickets at the customer support center
Faster TAT (Turn Around Time)
Bot saved 9,375 man hours, thereby reducing significant
Predictive Analytics queries to get data from multi- ple systems was achieved. (e.g., Do I have enough money to process payroll?)
Increased handling capacity as the major answers are provided by the bot, and only a limited number of chats were transferred to support reps
Regardless of what your company does — even if your audience is behind a computer screen 24/7 — personalized conversations are key to customer retention and higher NPS
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