We Built Conversational Flight Search for Airlines. Your Small Business Needs Conversational Commerce
Most businesses miss a critical gap: the space between what customers want to say and what your system requires them to input.
Building conversational flight search for airlines taught us that users don't want to fill out forms with dropdown menus. They want to describe what they need in natural language. "Flights from Miami to Madrid, under $500, business class, two travelers, next month" should work, and with conversational commerce, it does.
AI-powered search and conversational commerce transform customer interactions. AI's real value isn't just in answering questions. It's in understanding complex, natural language queries and turning them into actionable results. Yet most small businesses are still stuck requiring customers to navigate forms and filters.
The Expensive Mistake
Customer: "I need an appointment tomorrow morning"
AI Chatbot: "Our hours are 9 AM to 5 PM. You can book appointments by calling during business hours or visiting our website."
Customer: [Leaves and books with competitor]
Traditional chatbots provide information but don't help customers take action. Conversational commerce bridges that gap by understanding natural language queries and either completing tasks or guiding customers to the right place with the right information already filled in.
The Airline Industry Lesson: From Forms to Natural Language
In traditional flight search, customers face this:
- Select departure city from dropdown
- Select destination from dropdown
- Select departure date from calendar
- Select return date from calendar
- Select number of travelers
- Select class (economy/business)
- Click search
- Filter results by price, time, airline
- [... navigate through multiple pages of results]
With conversational flight search and AI-powered search:
Customer: "Flights from Miami to Madrid, under $500, business class, two travelers, next month"
System: [Searches flights matching all criteria, returns results with live pricing]
Results shown:
- Flight 1: $487, 8:15 AM departure, 1 stop, 9h 30m
- Flight 2: $495, 2:30 PM departure, non-stop, 8h 15m
- Flight 3: $489, 10:45 AM departure, 1 stop, 9h 45m
Customer: [Selects preferred option, gets redirected to airline's booking engine with all details pre-filled]
The difference? The system understands complex, multi-criteria queries in natural language, searches in real time, and presents relevant results. This enhances customer experience by eliminating form-filling friction and making product discovery seamless.
The Technical Shift: From Forms to Natural Language Search
Traditional search systems work like this:
- Require users to fill out forms with specific fields
- Force navigation through multiple dropdowns and filters
- Return results that may not match what user actually wants
- Hope user refines search or gives up
Modern conversational commerce platforms work differently:
- Parse natural language queries using artificial intelligence
- Extract multiple criteria from a single sentence (dates, price, preferences, quantity)
- Search inventory or database in real time matching all criteria
- Present relevant results with key information
- Enable seamless handoff to booking/purchase flow
This isn't just about better natural language processing. It's about understanding customer intent and reducing friction in the discovery phase. These systems enhance customer satisfaction by making product discovery and search feel natural, like talking to a knowledgeable assistant.
What Conversational Commerce Looks Like
Restaurant (Traditional):
Customer visits website → Clicks "Reservations" → Fills out form: date, time, party size → Submits → Waits for confirmation email
Restaurant (Conversational Commerce):
Customer: "Table for 4 tonight around 7"
System: [Searches availability, finds options]
System: "I have 7 PM and 7:30 PM available. Which works better?"
Customer: "7"
System: [Redirects to booking page with date, time, and party size pre-filled]
Result: Faster path to booking, enhanced customer experience
E-commerce (Traditional):
Customer: Navigates to website → Uses search bar: "blue shirt" → Filters by size, price, brand → Scrolls through pages of results
E-commerce (Conversational Commerce):
Customer: "Blue button-down shirt, medium, under $50, cotton"
System: [Searches inventory matching all criteria in real time]
System: [Shows 3 matching products with prices and availability]
Customer: [Clicks preferred option, goes to product page]
Result: Instant product discovery, improved shopping experience
Service Business (Traditional):
Customer: Fills out contact form → Selects service type from dropdown → Waits for response
Service Business (Conversational Commerce):
Customer: "I need a quote for kitchen remodel, 200 sq ft, mid-range finishes, next month"
System: [Searches available contractors, pricing, schedules]
System: [Shows 3 options with availability and estimated pricing]
Customer: [Selects preferred option, gets redirected to booking with details pre-filled]
Result: Streamlined customer interactions, better customer service
The Psychology: Why People Hate Forms But Love Natural Language
Users don't want to navigate forms. They want to describe what they need.
Every form field is a chance for abandonment. In flight search, we found that each additional required field increased abandonment by roughly 12%. Complex forms with 8+ fields lose most users before they even see results.
People search with intent:
- They know what they're looking for ( most of the time 😅 )
- They have multiple criteria in mind
- They want to see relevant options quickly
Traditional search forms add friction. Conversational commerce removes it by letting customers express their needs naturally, creating better customer interactions and improving customer service through enhanced product discovery.
Why Integration Matters
Basic chatbots need a knowledge base and simple website integration. Conversational commerce platforms need access to your inventory, pricing, availability, and business logic. They need to search your systems in real time and return accurate, up-to-date results. This enables seamless product discovery and customer interactions through messaging apps, text messages, and web interfaces.
This requires deeper integration. It's also why it delivers real value.
Start Simple
Begin with high-frequency search scenarios:
- Product search: "Blue running shoes, size 10, under $100"
- Service search: "Plumber available today, licensed, 5-star rating"
- Appointment search: "Haircut next week, afternoon, with Sarah"
- Inventory search: "In-stock laptops, 16GB RAM, under $1500"
Target understanding 80%+ of natural language queries correctly. If a query is too complex or ambiguous, ask clarifying questions rather than guessing.
Don't pretend your AI can search things it can't access. "I can help with that" followed by "please use our search form" is worse than no AI at all.
The Competitive Reality
Amazon: Natural language product search. Google: Conversational search across services. Kayak: Natural language flight search. These companies leverage conversational commerce to enhance customer experience and improve shopping experience through better product discovery.
The same artificial intelligence and natural language processing tools these companies use are available to everyone. Voice assistants and messaging apps enable real-time customer interactions through text messages and voice.
Measure Search Success, Not Just Engagement
Track what matters:
- Query understanding accuracy (did the system understand the request?)
- Search-to-result relevance (are results what the customer wanted?)
- Time-to-results (how fast are results shown?)
- Conversion rate (do customers proceed after seeing results?)
- Abandonment points (where do customers drop off?)
Target: 80%+ of natural language queries understood correctly, with results shown in under 3 seconds.
Airlines learned this the hard way: customers don't want to navigate complex forms, they want to describe what they need and see results. Every search that requires form-filling is friction. The benefits of conversational commerce include improved customer satisfaction, enhanced customer experience, and better product discovery.
Your customers don't want to fill out forms. They want to describe what they need, see relevant options quickly, and take action. Conversational commerce enables natural product discovery and streamlines customer interactions through messaging apps, text messages, and web interfaces.
Key takeaway: Stop requiring customers to navigate forms and filters. Build AI that understands natural language and searches your systems intelligently. The difference between "Please fill out this form" and "Here are your options" is the difference between losing customers and keeping them.
Next step: Identify your most common customer search scenarios. Map how customers currently find what they need. Identify where natural language search could replace forms and filters.
