As a UX researcher, I want to understand how campers think about and experience the online booking process. 

Specifically, I want to explore what expectations they bring in, how they navigate the system while booking, and how they feel about the outcome once it’s complete. 

My goal is to identify both recurring patterns and outlier frustrations that shape the overall booking experience.

Understand campers’ expectations, navigation behavior, and emotional outcomes across the online booking journey so you can spot common patterns and outlier frustrations that shape the experiene.

Split by timeline to capture the full journey.

Before Booking

• What do campers expect from the booking process.

• What information do they need up front.

• What motivates platform choice.

• What emotions or concerns they bring in.

During Booking

• How they search and filter.

• Which UI elements help or hinder.

• Where errors and surprises occur.

• How they make tradeoffs when the ideal site or dates are unavailable.

After Booking

• How confident they feel about the reservation.

• Whether outcomes matched expectations.

• What they would change next time.

• Overall satisfaction and likelihood to recommend.

Survey format

• Target completion under ten minutes.

• Mix of closed questions for quant patterns and a few focused open ends to capture nuance.

• Use device-appropriate design. Most campers will answer on mobile.

Sampling and distribution

• Recruit on social media. Ask within 7 to 14 days of a reservation for a fresh recall.

• Include both peak and off-peak seasons.

• Balance by experience level, party type, device, and platform used.

• Channels: post-booking email, in-app prompt, community groups, park newsletters.

Incentives

• Keep it simple. Entry into a camping gear raffle or a small discount on a future booking.

Data quality controls

• One attention check.

• Detect straight-lining and very fast completes.

• Block duplicates by user ID or email hash.

• Require a minimum character count on the key open end.

Quantitate:

• Create journey scores by averaging item ratings for calendar, map, filters, speed, transparency, rules, and checkout.

• Build a Friction Index. Combine difficulty rating, reported errors, and abandonment intent.

• Run MaxDiff to rank feature importance. Use hierarchical Bayes if your tool supports it.

• Segment by planning style, device, party type, and platform. Compare satisfaction and friction across segments.

• Flag outliers. Look for the bottom decile on satisfaction or confidence to identify extreme pain cases.

Qualitative

• Thematically code the two open ends. Start with buckets like availability anxiety, map confusion, price surprise, account friction, payment failure, rules clarity, confirmation gaps.

• Pull verbatims that illustrate each theme. Keep one or two short quotes per theme.

• Map themes to journey stages to expose where issues cluster. 

Turn insights into personas

• Use k-means or simple rule-based clustering on planning style, device, flexibility, and feature importance.

• Expect at least three mindsets to emerge. Early Planner, Last-Minute Scrambler, Tradition Keeper often appear.

• Validate by checking each cluster’s distinct pain points and satisfaction.