EatEasy serves as an online food delivery app based out of Dubai. The company has partnered with numerous restaurants in the city for whom it collects orders and delivers them to thousands of customers every day. Their entire business model is based on providing top-notch customer service to customers, from the ease of placing orders on their application to the swift delivery of the requested order.
As an emerging company in UAE, EatEasy has a growing customer base leading to an increasing need for efficient order management. Eat Easy has already partnered with more than 4000 restaurants across Dubai. Considering its scale, it witnesses a high volume of users and subsequent orders on its app, which only grows as it adds more restaurants. The app experiences more than 1500 queries a day during peak hours and weekends. These queries range from tracking orders, refund/cancellation of orders, order placing, etc. To provide timely and reliable support, Eat Easy has a team of 14 agents who answered these queries via its Zendesk’s live chat tool.
The problem was that EatEasy’s Zendesk tool wasn’t integrated with its internal system and hence, didn’t offer the ease of customisation and flexibility that the company sought. The agents had to use two portals, the first one was their internal system to keep track of incoming orders, order status, etc., and the second one was Zendesk’s live chat tool to communicate with the customers. Using two portals for support meant the agents had to manually fetch customer data from their system before replying to their customers on the live chat tool, which consumed time and was simply inconvenient.
While the company strived to ensure the highest support standards for their customers, offering them at scale was becoming challenging owing to its growing size. The small team of agents was overwhelmed and worked tirelessly to provide quick responses and answer every customer. Most of the queries they received were repetitive, either relating to tracking orders or order placing, cancellation, etc. Due to this peak volume, customers usually had to wait in long queues before connecting to an agent.
Taking into account these growing challenges, EatEasy’s CEO, Mr Safarath, aimed to look for a more inclusive solution that automates and takes over mundane support queries and helps make their support solution scalable.
While searching for a solution, he read about chatbots and their prominent role in customer support. He figured bots would offer the flexibility of automation wherever needed and be tailored to their use case.
As their team did not have the experience of building bots, Safarath began looking for a done-for-you service company that could take up the entire project of designing, building, and managing the bot solution for them. And this search led him to WotNot. After speaking with the WotNot team, Safarath got educated on the best chatbot solution to mitigate his growing support challenges. We also discussed how a solution could be integrated with their existing systems to ease the user experience of the agents and reduce the time to first response.
It was WotNot’s ability to deliver a personalised solution, their industry experience, and their customer-first approach that assured us in choosing them.
Eventually, Safarath was confident in collaborating with WotNot. It ticked all the boxes, especially in terms of having the expertise to design a bot and provide an end-to-end offering.
The EatEasy team had detailed discussions with WotNot about their bot objectives and how they wanted the flow to be experienced by thousands of their customers.
After understanding the business objectives and the pain points of their support agents, it was pretty evident that the chatbot solution was required to provide the following benefits,
Mobile app support
Integrate with their internal system
Handle mundane queries
Handoff unique queries to agents
Be available and scalable at a moments notice
With this, WotNot’s team of conversation designers began designing a chatbot that met the above criteria by closely coordinating with the Eat Easy team.
Also, as the majority of Eat Easy’s customers spoke Arabic, it was crucial that the bot spoke in the Arabic language as well, supporting the RTL of the chat. The chatbot would smartly understand the customer’s language preference on the mobile app, and the bot would interact with the customer in the same language.
A bilingual bot in English and Arabic allowed us to up our game in customer support and provided an excellent conversational experience to our users.
When the customer begins interacting with the bot, the bot greets the visitor and shows them a list of areas where the bot can assist them. The most frequently asked queries were one of the below options,
Placing an Order
Knowing about Eat Easy Points
Miscellaneous issues (Payment issues, order tracking, order issues, etc.)
Every option had a pre-defined flow designed for it which would fire once each option was selected.
The chatbot was integrated with Eat Easy’s internal systems. Hence fetching the order status or performing any other action was easy, owing to the API integration. And this integration was also provided on the live chat portal, where the agents could seamlessly get to know the Customer or Order ID of customers who are speaking with the bot. It helped eliminate the need for the support agents to juggle between two tabs on their devices and instead have everything on just one screen.
With the data available from Eat Easy’s previous vendor, the chatbot was trained to answer the most commonly asked questions. In case of a unique query that the bot wasn’t qualified to answer, it would smartly route the chat to the right agent in the right team. That agent would then manually continue speaking with the customer to resolve their queries.
This handoff helped support agents be free from all the mundane queries asked and instead only get involved only when there is a complex problem that the chatbot could not solve.
There were also metrics available of the support agents so that the support managers could review the performance of support agents and provide them with feedback to improve their performance.
The chatbot was also routinely trained every few weeks so that its knowledge base gets richer and adapts to any new question asked.
Availability of support agents, which was a concern previously, was also addressed with the chatbot. Because of its nature of being a computer program, it would be available 24/7 to answer any customers’ queries. Coupled with WotNot’s infinitely scalable architecture, the chatbot would handle high peaks of traffic at a moments notice. This was very helpful as Eat Easy would routinely roll out offers, leading to a spike in traffic.
Our support team is happy, and so are we. We’ve optimised both time and money without compromising on our support quality.
Following the solution, Eat Easy was also able to optimise its support costs. Most of the interactions were happening with the bot, and within a year, it experienced the following numbers:
250K+ Queries Automated
40K+ Hours Saved
<1s Time to First Response
68% of queries addressed by the bot
In the future, EatEasy expects an even higher volume since it has partnered with more restaurants. With an increase in operations, it also expects an increase in customer queries. The road ahead for WotNot is to facilitate an architecture that can handle a higher volume of conversations for Eat Easy to achieve scalability.