Customer:
Our client runs an e-commerce retail brand in the UAE and sells products of multiple categories like fashion, accessories, and lifestyle goods. They have a worldwide customer base because they offer the best quality products at wholesale rates, and hence run mainly on an online store and a mobile app.
No doubt, they have a strong presence in urban areas, but today’s customers expect quick replies and fast problem solutions, and they are lacking behind in this. Currently, they are investing more in digital campaigns, paid ads, email marketing, and social media to create a good online presence, but their customer service method is still outdated.
Customers need to reach them through email, call, or wait for their turn to solve the query.
They used to receive lots of queries during the peak time, like Black Friday, Cyber Monday, or festive sales. This made customers wait long hours for responses, agents repeated the same answers for common queries, and many shoppers abandoned their carts simply because they couldn’t get quick help.
Soon they realized they needed a virtual assist app for their online store to respond to the customers on time and enhance satisfaction. They searched for the best mobile application development company and found us online. During the first call, the client came up with multiple questions, like:
- How secure are AI-powered virtual assistant apps?
- I want to build an AI virtual assistant app — where do I start?
- How much would it roughly cost to create an AI-powered virtual assistant for my business?
- How long does it usually take to develop an AI virtual assistant app?
A Challenge to Build an AI-Powered Virtual Assistant App Platform:
The main challenge was that our client was not able to give enough time to every customer to solve their queries and respond to them on time due to their manual customer support. Sometimes they need to hire more support agents during the festival and sale time. Also, it was difficult to hire an experienced support person who responds to customers professionally. This was messing up with everyday operations and making them realize that just online presence is not enough; strong customer support is equally important. They also noticed a few bad reviews on Google regarding their poor customer service.
Developing a custom AI assistant that understands natural human language and responds in a relevant way was a big task for us. This needed lots of data training with multiple customer queries and questions to train the AI model on how to reply to specific queries. We also needed to ensure smooth integration with the client’s existing e-commerce platform, CRM, and inventory system. Since the brand was expanding globally, the assistant must support multiple languages and reply accordingly. Another tough thing was building a secure payment feature to allow customers to complete transactions directly through the assistant. Above all, data security and privacy for sensitive payment and customer details were non-negotiable priorities.
Best A Virtual Assistant Platform Solution Implemented By Our Team
We started with detailed research to study customers’ pain points and understood where they were facing issues during shopping. Then we made a list of key situations where an AI assistant could make the biggest difference, such as product discovery, cart checkout, and order tracking. The client was concerned about the mobile app development cost, hence they asked us whether they should hire an Android app developer or a specific iOS application development company, we suggested a cross-platform solution.
Our AI engineers implemented a natural language processing (NLP)-based chatbot that could handle FAQs, product searches, and order-related queries. We trained the assistant on the client’s product catalog, policies, and common customer questions.
We also added a functionality of smart recommendation, which will analyze customer behavior and offer personalized product suggestions. We integrated automated push notifications to some questions, like Where is my order? Can I change the delivery time and date, etc? Plus, we added multi-lingual support to serve other countries in the future.
Key Features of Virtual Assistant App:
- Personalized Product Recommendations: It will suggest products based on browsing history, preferences, and previous purchases.
- Cart Recovery & Checkout: It reminds customers about abandoned carts with personalized messages and motivates them to complete the checkout process.
- Real-time order updates: We connected the app with the client’s logistics system to give live updates about their orders and shipping status.
- Multilingual Support: Customers from different regions and cities can switch the language and shop in their own language comfortably.
- CRM & Inventory Integration: As it is also connected with CRM and the inventory system, it will always show product availability, pricing, and order details.
- Voice Command Support: You can also search products, track orders, or ask queries through voice command.
- Payment method: You can pay through customer support or select your convenient payment mode, like UPI, debit, credit, and more.
Result of AI Virtual Assistant Application:
As a leading mobile application development company, the launch of this AI-powered virtual assistant app had a transformational impact on our client.
- Average response time reduced from 2-3 hours to less than 5 seconds.
- Customer support costs have been reduced by 40%.
- Personalized recommendations increased sales by 18%.
- Checkout support and reminders reduced cart abandonment by 25%.
- Customer satisfaction improved by 30% due to faster resolutions.
- The client can now handle thousands of queries during peak sales without downtime.
- The client’s business expanded into non-English-speaking markets due to multi-lingual support.
Technologies and Tools:
- Frontend: React Native
- Backend: Node.js, Python
- AI & NLP: Google Dialogflow, TensorFlow, OpenAI GPT APIs
- Database: MongoDB, MySQL
- Cloud Services: AWS
- Payment Integration: Stripe, PayPal API
- Notifications & Messaging: Firebase
- Analytics: Google Analytics
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