Normally, when you search for a product online, you face complex forms with numerous filters. Take a real estate platform as an example, where the interface seems quite simple at first. However, when expanding more options, multiple additional fields appear, which can be frustrating and time-consuming.
Many users find it tedious to fill out so many filters. A more efficient alternative is to use Artificial Intelligence (AI) to simplify this process. Instead of manually selecting each field, the user could provide a single free text, from which the system would automatically extract the necessary parameters. This way, the search interface would be reduced to a single input field.
Implementing an AI algorithm can represent a challenge in both time and costs. However, instead of completely replacing the traditional search structure, the filter system can be maintained and AI used to interpret the free text and convert it into filterable parameters.
At Q2BSTUDIO, specialists in development and technology services, we have worked on similar AI-based solutions to improve the user experience. By applying advanced models like GPT-4-Turbo, we can extract and structure relevant information from common text. For example, if a user writes "Looking for a 2-bedroom apartment in Texas under $2,500/month, pet-friendly, with a balcony and parking," the AI can automatically interpret the location, price range, property type, number of rooms, amenities, and other key details.
We can even enhance this functionality by adding options like excluding certain locations or specific preferences. If a user mentions they are not looking for properties in Austin or Dallas, the system can recognize and apply these filters automatically.
Another advantage of this approach is the possibility of integrating voice recognition, which would make the search even more intuitive and closer to a conversational experience similar to speaking with a real estate agent. Additionally, by collecting anonymous user data, patterns can be analyzed and recommendations progressively improved.
At Q2BSTUDIO, we bet on innovation in digital interaction. The key to successful adoption is to offer this functionality as a beta option, allowing users to choose between the traditional method and AI-powered search. With proper A/B testing, we can measure metrics such as search time, conversion rate, and user satisfaction to determine which method is more effective.
The future of technology leads us toward smarter and more conversational interfaces. As more people become familiar with AI chats, the preference for these methods will grow. Thanks to these solutions, at Q2BSTUDIO we help companies transform the way users interact with their services.
