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How AI in Travel Apps Boosted Engagement by 70%?
Patient Inflow
Before
%
After
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Key Metrics
- Customer engagement boosted by 70%
- 4.4+ rating and 100,000+ downloads for the scaled-up travel apps.
- ROI boost by
%
Objective
- To enhance and scale web and mobile travel apps with AI Integration.
- Boost User Engagement via chatbots, automated planners, or analytics, leveraging AI.
Key Highlights
- We helped the travel company secure a 70% increase in user engagement.
- Increased User engagement and, hence, maximum conversion was achieved via an enhanced AI-integrated travel app for on-demand travel services
Project Background
Client Background
Client Industry: Travel Industry
Location: Timbuktu, Mali
A tour and travel company based in Timbuktu, Mali, was losing clients because their competitors had started using AIs in their digital identities, i.e., websites and apps.
AI assistance is important in Africa, where tourists often encounter limited facilities, extreme weather conditions, language barriers, and health concerns.
Objectives:
- The tour and travel wanted to scale their web and mobile apps.
- And since AI was in demand across the globe, they wanted to inculcate it to bring the positive change in user engagement and experience.
Challenges
Outdated Apps
The travel firm had web and mobile apps, but they were outdated and lacked personalized travel experiences.
Meanwhile, 2025 is about catering to hyperpersonalized customer experiences to ensure customer retention and business growth via the latest travel app growth strategies.
Difficulty in Catering to 24×7 Customer Support
Hiring customer support agents to deliver 24×7 support was becoming quite difficult for the client and draining a massive chunk of their budget.
Currency Exchange System
After landing in another country, every tourist wants to go for currency exchange, but they do not know the varied currency rates across various locations in that city.
For example, airports are the costliest, while better rates can be found in a market.
Real-time Travel data fetching
Tourists want real-time pricing of flights, trains, buses, taxis, hotels, and other travel services to make the best travel decisions all along their journey.
But hardly any travel app provides such features.
Solution
Solution Provided
- Our sales team, project manager, and business analyst went on a discovery call.
- Wildnet’s software consulting division was roped in to bring the AI revamp of the clients’ web and mobile apps.
- The goal was to simply change the customer experience by catering to them the personalization and 24×7 guide needs.
- It was achieved via AI in travel apps by the incorporation of chatbots, itinerary planners, push notifications, and more that will adapt along the way by learning about the users via ML (machine learning) and Natural Language Processing (NLP).
- Ideal tourist personas were crafted to design the App and test the scaling of web & mobile apps and their future feasibility.
- Finally, AI in travel apps functionalities were implemented to bring about the immense positive changes in the user engagement of the client.
Strategies Implemented
- Our software consultants and developers knew they had to bridge the gap between the older web and mobile apps and the future-ready AI in travel apps.
- They started with personalization of travel experiences by using ML and NLP to learn about the tourism pattern in Africa for the past 10 years and superimpose them on the ideal personas of tourists.
- To deliver real-time responses, AI chatbots as well as virtual assistants were leveraged so that no customers feel left out or have to wait for working hours to commence.
- Dynamic pricing was leveraged if the customer made changes to their itineraries.
- Real-time currency rates across the cities were displayed to help the users make the best transactions.
- AI was also used to make users & their data more secure by bringing in bot checkers, sporadic behaviour alerts, and real-time tracking.
Technologies Used
- Web app technology stack used React for the frontend, Firebase for the backend, MongoDB for the AI database, and AWS for the cloud support.
- Mobile app technology stack used React Native for the front end, Firebase for the backend, MongoDB for the AI database, and AWS for the cloud support.
- For AI functionalities, TensorFlow/PyTorch was used for deep learning, Hugging Face Transformers for NLP, along with other AI tools.
- APIs used were GraphQL for AI’s data fetching, Kafka for AI-driven events, and RESTful APIs for other integrations.
Major Features of the AppsÂ
- AI-powered real-time information
- Automated Itinerary Planning
- Hyper-personalized User experiences
- 24×7 Customer Support
- APIs to allow user feedback and ratings for Travel Vendors
- Vendor apps to rank vendors accordingly.
Development and Implementation
Process
-  The client’s ask was not simple, as it required scaling of mobile and web applications using AI in travel apps.
- This meant that the scaling-up process would need to use the legacy systems and upgrade them to an extent that could handle AI.
- Their previous apps were dismantled and divided into pieces or parts, each having separate functionality to bring in the microservices architecture.
- Microservices architecture helped in working on each function separately without disturbing the other functions and delivering a 100% uptime.
- After taking all the useful aspects of the previous mobile and web apps, AI in Travel Apps was brought in via a step-by-step process using the agile app development methodologies.
- This allowed timely completion of each required AI function discussed above while keeping the tour client in the loop for their real-time feedback.
- The development took roughly 3 months, and then rigorous testing and quality assurances were undertaken.
- This ensured that the newly scaled web and mobile apps cater to the AI in travel apps in all possible conditions for its users, aka the tourists.
- After the deployment of the Engaging Travel Apps, the upgrade of the Mobile and Web apps was relayed to the users via in-app notifications and pop-ups on their travel booking website.
- One month of complementary post-launch support was rendered to remove any bugs in the real time.
Team Involved
- Â 1 Business Analyst
- 1 Project Manager
- 2 Frontend Developers
- 2 Backend Developers
- 2 AI Engineers
- 1 Cloud Engineer
- 1 DevOps Engineer
- 1 Database Engineer
- 1 Content Writer
- 1 Graphic Designer
- 1 QA/Tester
4 months
Application Screenshots
Results
Quantitative
Results
- 70% hike in Customer Engagement
- The scaled-up apps have a 4.4+ rating and 100,000+ downloads on the Play Store and App Store.
- ROI boosted by 500%.
Qualitative
Results
- Users prefered AI support to human customer support, helping decrease the immense budget for human customer support.
- A lot of tour guides and vendors wished to be a part of the AI in Travel Apps experience delivered by the client’s tour apps.
Client Feedback
and Ratings
- Â The client is over the moon and on their way to becoming the best tour company in western Africa via one of the best travel apps.
- They have rated our software consulting services 5/5.
Future
Plans
- The client now wishes to market themselves across the world using the 360-degree digital marketing services provided by Wildnet.
- Â They are currently finalizing a year-long upgrade and maintenance contract for their mobile & web apps with our Design and Development division.
