AI-driven Travel Shopping: Lessons From Wizz Air (2024)

Pre-travel shopping, the use of AI, personalized experience, happy customers, and new revenue stream…

Yes, we agree, it sounds like a set of words with a vague idea behind them.

But if you combine all of these elements together, you will get an online platform designed to enhance passengers' pre-travel shopping experience with personalized recommendations. This is exactly what Wizz Air did.

Wizz Air just launched WIZZ Shop&Fly, an e-commerce platform that uses AI to make the pre-travel shopping experience super personalized and convenient.

This new platform sets a whole new standard for customer experience, totally changing how people shop before they fly, and makes Wizz Air a pioneer airline company that provides such a tailored shopping service.

In the not-too-distant future, competition will push travel companies to rethink their customer service standards.

So, if you want to be ahead of the game, now is the very time to take a close look at Wizz Air's strategies and explore how your company can adapt its approach to offering customers a personalized shopping experience.

In this article, we:

• delve into Wizz Air's groundbreaking concept
• extract valuable lessons we can learn from Wizz Air's forward-thinking strategy
• outline the steps you need to follow to build a Wizz Air-like AI-powered pre-travel shopping solution.

AI-powered iOS app for the cosmetics industry built by Onix-Systems

What's the Secret Behind Wizz Air's Pre-Travel Shopping Concept?

Teaming up with InterLnkd, an intelligent shopping partner, Wizz Air is about to change the game.

Wizz Air introduced Wizz Shop&Fly, an innovative online shopping platform that allows passengers to browse and purchase a wide range of fashion, beauty, and retail items from over 20,000 options before their flights.

Wizz Shop&Fly

What makes Wizz Air's initiative so special?

It's their focus on making things uniquely yours and super easy. The platform uses AI technology to analyze various factors, including passengers' travel destination and previous shopping behavior and then suggests stuff just for you.

It's so simple and brilliant, don't you think?

This level of personalized service doesn't just make shopping highly relevant – it adds value to Wizz Air's customers' travel experience. Customized to assist with pre-trip preparations, the platform enhances the excitement and planning process for their upcoming vacation.

So, what can we gather from all of this? The success of their innovative approach lies in offering unique customer service unparalleled by others. And to achieve this, the company teamed up with a firm specializing in innovation.

Outsourcing development to another company was a strategic development approach that offered several benefits, such as access to specialized expertise and accelerated development timelines.

What About Business Benefits?

Wizz Air has demonstrated how to seamlessly incorporate advanced technology into a well-established business, resulting in impressive benefits.

Thanks to AI-powered personalized recommendations, passengers get a customized shopping experience that simplifies their trip preparation, making it a breeze.

And for Wizz Air? Well, they're seeing more cash flow from extra purchases, standing out in a crowded market, and learning useful information to improve their service.

It's a win-win that makes traveling with Wizz Air even more enjoyable and helps the business grow while keeping customers happy.

How can I create a pre-travel shopping platform similar to Wizz Air's?

Are you looking to follow in Wizz Air's footsteps? It's quite possible and not as daunting as it may seem.

In a nutshell, to replicate Wizz Air's success you need to:

• analyze your users' pain points
• perform a competitive analysis
• budget your resources
• team up with reliable tech experts.

In Wizz Air's case, they teamed up with InterLnkd, an intelligent shopping mall partner.

InterLnkd's AI-powered product matching engine offers a wide range of products, from fashion to beauty, including popular brands. Using specific data points called MotiVatedData™, the engine cleverly matches the perfect products with each customer's booking.

MotiVatedData™ is like a tailor-made collection of data points that the InterLnkd engine carefully creates to match each customer's tastes and shopping behaviors.

Thus, InterLnkd trained their machine model specifically for Wizz Air's audience, ensuring the shopping experience perfectly caters to their unique preferences and requirements.

This explains what happens when you team up with a tech company offering a ready-made solution. However, the process will be entirely different if you're considering developing a custom model designed specifically for your business.

Below, our experts provide some educated tips on how to build a Wizz Air-like pre-travel shopping solution from scratch. We guide you through each step in detail.

1. Come up with an idea based on grounded analysis

In making any big decision, starting with a thorough analysis of the concept is crucial.

We're pretty confident, like 100% sure, that Wizz Air kicked off its development process by diving deep into its business and what its customers were struggling with.

This kind of research gives you the insights to truly understand what your customers need and how to meet those needs best.

By analyzing the product's current state and understanding consumer pain points and needs, Wizz Air realized that providing a personalized shopping experience for passengers could be a game-changer.

When you begin your collaboration with the AI development partner, like Onix-Systems, during this stage, the company's specialists will help you to:

• get a better understanding of what lies ahead for your product
• define potential risks and issues
• provide ways to solve those risks
• create flawless experiences to satisfy particular user requirements.

2. Having a dependable team is the foundation for achieving 90% of success

Once Wizz Air knew what its users were looking for, they partnered with InterLnkd to launch a dedicated e-commerce store using InterLnkd's white-label AI solution.

It might look like this:

1. Wizz Air researched potential partners, evaluating their capabilities and solutions.
2. After a thorough evaluation, Wizz Air chose InterLnkd. They negotiated the terms of their partnership, including project scope, timeline, and financial arrangements.
3. InterLnkd began customizing its white-label AI solution to meet Wizz Air's specific requirements and integrate it into Wizz Air's existing systems.

But if we talk about custom machine learning solutions (this means you'll get a model that's uniquely yours, and no one else can reproduce the results), the development process requires:

• a detailed plan for development
• outlining key features
• setting clear priorities and deadlines
• choosing the best technology to use
• collecting and structuring input data
• refining and organizing data for accurate model development
• fine-tuning the model to optimize its performance
• deploying an ML solution to the production environment

To handle all these tasks effectively, you need the right expertise:

• Project manager who oversees the entire development process, coordinates team efforts, and ensures timely delivery.

• Software developers who are responsible for coding and implementing the platform's features and functionalities. This includes front-end developers and back-end developers.

• AI engineers who develop and implement machine learning algorithms and models to power the personalized recommendation engine.

• UX/UI designers who design the user interface and experience, ensuring it is intuitive, user-friendly, and visually appealing.

• Quality assurance/testers who test the platform thoroughly to identify and fix any bugs or issues before deployment.

• DevOps engineers who manage the deployment, operation, and maintenance of the platform, including infrastructure setup and automation.

• Database administrators who design, implement, and maintain the database architecture required to store user data and product information.

• Security experts who ensure the platform's security by implementing robust authentication, authorization, and encryption measures to protect user data and transactions.

Note:

Creating a custom ML model might seem daunting compared to a white-label approach.

However, a custom ML model:

• allows for precise customization to fit your business's unique needs and objectives, resulting in more accurate and relevant predictions or recommendations.

• provides greater control over the development process, enabling you to incorporate proprietary data and algorithms that may give you a competitive edge.

• ensures data privacy and security by keeping sensitive information within your organization, minimizing the risk of data breaches or leaks.

• adapts and evolves alongside your business, ensuring continued relevance and effectiveness over time.

• supports scalability, allowing the model to grow and adapt as your business expands and your data volume increases.

3. Prioritize functionality that aligns with your users' needs and adds value to their experience

The functionality directly impacts user experience and determines the success of your product.

Similar to Wizz Air's approach: To keep up with industry trends, they focused on understanding users' needs and creating innovative solutions to address them, setting themselves apart in the market.

Want to create a compelling and differentiated AI-powered pre-travel shopping platform that resonates with your target audience?

Rhetorical question!

Well, taking inspiration from WIZZ Shop&Fly, our experts prepared a list of functionalities that you can integrate into your own product:

• Profiles and user segmentation. Machine learning analyzes customer data and creates detailed profiles based on past bookings, purchase history, and travel preferences. This allows for personalized marketing and individual product recommendations.

• Seamless integration with booking systems. Integrate with airline booking systems to synchronize travel details and offer relevant products based on flight itineraries.

• Recommendation systems. Advanced recommendation algorithms recommend products tailored to the user's preferences. They employ collaborative filtering, content-based filtering, or hybrid approaches to predict and showcase items relevant to a traveler's unique trip.

• Forecasting and analytics. Models for predicting product demand based on various factors such as destination, season, and current travel trends. This helps optimize inventory and advertising strategies.

• Dynamic pricing models. Applying machine learning algorithms to adjust product prices in real-time based on factors such as demand, competitor prices, and inventory levels. This can maximize revenue by ensuring competitive pricing.

• Chatbots and virtual assistants. Integrating AI-based chatbots to provide real-time customer assistance, effectively responding to product, service, and company policy inquiries.

Read also: How to Create a Chatbot: The Ultimate Development Guide

• Sentiment analysis. Analyzing customer sentiments through reviews, social media, and other sources to understand customer satisfaction and areas for improvement.

• Natural language processing (NLP). Using NLP to understand and process customer feedback or reviews allows the system to continuously improve recommendation accuracy and customer satisfaction.

4. Your tech stack is the toolkit that empowers your team to turn ideas into reality

Don't underestimate the power of a well-chosen tech stack – it can make or break your project's success.

Building an AI-powered pre-travel shopping platform like Wizz Shop&Fly requires a carefully selected set of technologies to ensure seamless functionality, personalized recommendations, and efficient operation.

Our experts share a list of technologies, leveraging which you can build a robust, scalable, and efficient solution:

• E-commerce platform

To run a successful online shop, you need a solid e-commerce platform that can handle product listings, inventory, transactions, and user accounts smoothly.

Platforms like Magento, Shopify, or custom-built solutions are essential for creating a secure marketplace, managing orders, and integrating with payment systems effortlessly.

• Frontend and backend development

To create a user-friendly interface and handle the backend operations, you can use technologies like HTML, CSS, JavaScript, React, Angular, Node.js, and Python. These technologies ensure the platform is responsive, easy to use, and capable of processing data efficiently.

• AI and machine learning

At the heart of the platform lies AI and ML algorithms, which analyze user data, shopping patterns, and preferences to generate personalized recommendations.

Natural language processing, predictive algorithms, computer vision, data mining, and intelligent process automation enable the platform to understand user behavior, predict their needs, and offer tailored suggestions, enhancing the shopping experience.

• Cloud computing infrastructure

To ensure your platform runs smoothly, consider hosting it on cloud services like Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform.

These cloud options offer flexibility, reliability, and cost-effectiveness, allowing you to adjust resources based on demand and ensuring top-notch performance even during busy shopping times.

• API integrations

To provide a seamless shopping experience, it's crucial to integrate third-party APIs for services like payment processing (Stripe, PayPal), shipping (FedEx, UPS), CRM (Salesforce, HubSpot), social media (Facebook, X), etc.

APIs make communication between different systems smooth, enabling features such as real-time order tracking, secure payment processing, and personalized customer assistance.

• Security measures

Implementing robust security measures, such as encryption, authentication, and authorization protocols, is paramount to protect user data and ensure compliance with privacy regulations.

Technologies like SSL/TLS encryption, OAuth, and JWT tokens help secure user transactions, sensitive information, and communication channels.

5. Collect relevant data sources to train AI algorithms

Remember the Wizz Shop &Fly's main idea? Yes, it's a passenger's pre-travel shopping experience with personalized recommendations. To ensure your users receive these tailored recommendations, you need to leverage relevant data sources and train AI algorithms.

Here's what the data collection process may look like:

• User preferences. Gather data on user preferences related to travel, shopping, and product categories. This can include information such as preferred destinations, travel dates, airline preferences, shopping habits, and favorite brands.

• Historical booking data. Gather past transaction data to grasp user behavior and preferences, including flight bookings, ancillary purchases, product preferences, and buying frequency. Analyzing this data reveals patterns and trends for developing personalized recommendations.

• Product information. Gather comprehensive product information from various sources, including product catalogs, supplier databases, and external APIs. This data should include product descriptions, images, prices, availability, and user reviews.

• Data security measures. Implement strict security measures to safeguard collected data against unauthorized access, breaches, and cyber threats.

• Data quality assurance. Conduct data validation, cleansing, and normalization to remove duplicates, errors, and inconsistencies. Validate data sources and verify the integrity of collected data to ensure its suitability for training AI algorithms.

• Continuous data monitoring. Implement data analytics tools and dashboards to analyze user interactions, product performance, and platform usage patterns. Use insights from data monitoring to refine AI algorithms, improve recommendation accuracy, and enhance user experience.

These are the key aspects of development you should be aware of.

Don't forget: to keep everything on track and running smoothly as we've outlined, it's essential to choose a reliable technical partner who understands exactly what needs to be accomplished and how to go about it.

Onix-Systems Can Help You Build a Wizz Air-like Personalized Pre-Travel Shopping Platform

We could talk all day about our experience, but our work speaks louder than words.

Check out our portfolio to see what we're all about.

1. The leading ingredient transparency solution for the cosmetics industry

We built an iOS mobile app powered by AI and data science that helps people choose skin care products based on their age, unique skin type, needs, and lifestyle. The consumer-facing solution also recommends products to users based on their individual needs.

2. Replacing faces in a video stream

Our team created a solution that replaces a character's face with the user's face in a short, comical video.

3. LSTM news categorizer

The Onix team built the LSTM News Categorizer and language detection model, allowing users to seamlessly access categorized news, boosting engagement within the client's app.

To learn more about our experience, see what projects we do here.

To Conclude

In this article, we've covered the critical aspects of creating a personalized pre-travel shopping platform like Wizz Shop&Fly. However, keep in mind that this process can vary based on your specific circ*mstances.

Some steps might be slightly different, and that's perfectly normal. Every project is unique, so it's natural for things to vary based on your individual needs and situation.

Whether you:

• need machine learning consulting services
• want to build an online shopping platform from scratch
• have any other software development needs

Feel free to contact us!

FAQ

What is the cost of your machine learning development services?

The cost of machine learning software can vary widely depending on complexity, customization, features, and the development approach.

We offer free one-hour consultation, 1 week of demo development for $400, and 1-3 months of ML solution development for >$10,000 per month. For long-term development, it's better to request a quote since it requires details for accurate estimation.

What custom machine learning solutions do you build?

We build various machine learning solutions tailored to specific industries and use cases. Some of the machine learning solutions we offer include:

• predictive analytics

• custom Llama and BERT solutions

• NLP solutions for tasks such as sentiment analysis, language translation, chatbots, and text summarization

• computer vision applications for image recognition, object detection, facial recognition, and video analysis to extract insights from visual data

• anomaly detection systems to identify unusual patterns or outliers in data, helping detect fraud, faults, or anomalies in various processes

• recommendation systems that analyze user behavior and preferences to provide personalized recommendations for products, content, or services.

What steps should I take to initiate the development of a Wizz Air-like AI-powered pre-travel shopping solution with Onix-Systems?

All you need to do:

Just share your idea, and we'll analyze it and schedule a call to get started on bringing your concept to life.

Get in touch with us here!