CASE STUDY

Restaurant Chatbot Helps BookMyTable Increase its Booking Rate by 45% in 3 Months

Expertise Delivered

Frontend

Backend

Industry

Hospitality

Our client,

The client, BookMyTable, is a UK-based CTRM vendor (Central Telephone Reser- vations Management) dedicated to the hospitality industry. BookMyTable han- dles more than 5 million reservations for restaurants across the UK.

BookMyTable has a dedicated team of highly skilled and trained reservationists assigned to each restaurant to handle reservations.

BookMyTable uses IVR service to route the calls and queries to the reservation- ists appointed for particular restaurant chains. They also measure and monitor inbound call activity and provide analytical reports with details such as frequency of calls, booking demand, table optimization rates, and more.

Abstract

Our client provides booking and reservation services for restaurants across the UK. This required them to use IVR to route calls to the reservationists of the particular restaurant chain. The reservationists would then reserve a table/make a booking and manually update the system's details.

This proved to be expensive and time-intensive for our client as the process depended entirely on reservationists' manual work. Maruti Techlabs designed an AI-based chatbot solution, which automated the entire process. This helped our client save time and costs as well as increase bookings and revenue.

Challenge

BookMyTable’s existing business model required a highly skilled workforce due to complete dependency on the reservationists' manual work. As the people could handle only a limited number of calls at a given time, business operations would take a hit during high-volume calls.

Customers had to face longer wait times of 6 to 8 minutes, resulting in poor customer experience.
This resulted in missed reservation opportunities during peak hours and the holiday season. It also proved to be a significant roadblock in scaling business operations and overall business growth.
Onboarding new restaurants also proved difficult due to challenges related to recruiting, training, and upskilling new reservationists for each restaurant.

Solution

Looking to automate and scale their operations, BookMyTable set out to search for a chatbot development partner. They partnered with Maruti Techlabs to build an AI-based chatbot solution. The chatbot leverages the no-code chatbot platform WotNot, along with Natural Language Processing via Dialogflow, which helps understand contextual nuances and the different ways in which users frame queries.

The chatbot was further integrated with FavouriteTable.

The AI chatbot takes care of the following things-

Checking Availability - Customers can now get a quick insight into the availability of restaurants at a given date/time, allowing them to plan well. The chatbot is well-integrated with the client’s database to automatically update table availability and time-slots without manual intervention.

Make Reservations - Using the AI chatbot, customers can immediately make a reservation without the need to wait endlessly on long queues or calls.

Modify a Reservation - Customers get the ability to quickly modify their reservations without any hassle of communicating with agents.

Cancel Reservation - Customers can cancel their bookings through the chatbot. With the chatbot being integrated with the backend system, it easily enables the canceled tables to be termed available in the system instantly.

Confirm a Reservation - Customers get reminders via text or email to confirm the reservation on their said date, which can be allotted to another customer if unconfirmed.

Answer FAQs - The AI chatbot saves a lot of time by answering FAQs about different restaurants’ timings, promotional offers, etc.

Menu Offerings - The AI chatbot also shows popular items on the menu according to the customer's past orders. This personalization of customer experience increased repeat business for our client by 55%.

Review & Feedback - The bot also collects feedback in a non-invasive manner. It urges the customer to rate the services in the chatbot interface itself, thereby making the process of feedback collection less intrusive and more intuitive.

Simplify your operational tasks with our reliable bot as your trusted assistant.

Don't take our word for it, take theirs!

Technology Stack

Results

✅ Turn-around time for reserving a table decreased by 75% (from 6 minutes to 90 seconds).

✅ The number of bookings after implementing the bot increased by 45% in the first three months.

✅ Repeat business increased by 55%.

✅ Hiring new agents per quarter used to cost $15,300/agent. ($17/hour * 900 hours in a quarter).

✅ Every quarter, they used to hire seven employees.

✅ $1,08,150 saved per quarter on hiring and training of new hires. ($150 to train each employee, so [150 x 7] + [15,300]).

✅ The solution helped some employees to be shifted to other business-critical activities.

Our Development Process

We follow Agile, Lean, & DevOps best practices to create a superior prototype that brings your users’ ideas to fruition through collaboration & rapid execution. Our top priority is quick reaction time & accessibility.

We really want to be your extended team, so apart from the regular meetings, you can be sure that each of our team members is one phone call, email, or message away.

Our Process

When building a chatbot, we keep dedicated business goals in mind to achieve seamless performance across channels along with optimum automation. A natural conversation flow ensures that client expectations are met for tone, tasks, implementation, and so on.

Evaluate Use Cases

Conversation Flow Design

Evaluate Use Cases

Our team analyzes the applicable use case, business objectives, target users, competition, and prospective market segment, to determine the implementation framework.

Conversation Flow Design

At this stage, our conversational experience designers step in to channel the voice of the business. They work in tandem with the development team to create a procedural flow of dialogue that determines tasks, bot personality, tone, and context of the conversation.

System Integration

After the conversation flow is formalized, our team enables seamless integration with other enterprise software (CRM, HRM, Payment Processors, Analytics tools, etc.), company knowledge bases, backend system, and target chatbot platforms in order to automate workflows and optimize bot functionality.

Training

Chatbots are constantly evolving and learning. Much like humans, they can effectively self-learn under supervision through quality training data in order to fix errors, excel at personalized communication, discern user sentiment, and follow business processes with ease.

Testing

In this phase, we rerun conversational flows, integrations and business scenarios through various test cases to achieve desired bot performance and bug-free implementation. Finally, user testing as well as application testing, is done, to cap the development process.

Deployment

This is the release phase everyone is waiting for. The intelligent bot is deployed on the company’s preferred platforms and is ready to interact with users in the execution environment.

Monitor and Optimize

Once published, the bot performance is monitored by analyzing conversation logs and usage insights to fix breakage points and reduce abandoned conversations. Analytics also help measure the bot’s ROI and run A/B tests to further optimize the use case, conversation flow and customer experience.

Evaluate Use Cases

Our team analyzes the applicable use case, business objectives, target users, competition, and prospective market segment, to determine the implementation framework.

Conversation Flow Design

System Integration

Training

Testing

Deployment

This is the release phase everyone is waiting for. The intelligent bot is deployed on the company’s preferred platforms and is ready to interact with users in the execution environment.

Monitor and Optimize