Optimizing Salon Appointments for Seamless User Experience and Time Savings

What is Naie?

Naie is a salon appointment scheduling app designed to save users time by reducing the wait typically experienced at salons. It allows users to book appointments in advance, streamlining the process and ensuring a more efficient experience by minimizing the time spent waiting for their turn. The app aims to enhance customer satisfaction by offering a convenient, user-friendly platform for managing salon visits.

The Vision

Naie aims to evolve from a simple appointment scheduling app to a comprehensive platform for enhancing the salon experience.

The vision is to create an ecosystem where users can seamlessly book appointments, explore salon services, and access personalized grooming recommendations, ultimately fostering a community centered around beauty and self-care.

What is Problem

Salon customers often face long wait times and inconvenient scheduling due to unorganized appointment management, leading to wasted time and inconsistent experiences.

Long wait times at salons

Customers experience long waiting periods due to unpredictable foot traffic and the absence of a proper scheduling tool. This wastes time and frustrates users, particularly those with busy lifestyles who need quick services.

Inefficient appointment management

Salons face difficulty managing both walk-ins and scheduled appointments, leading to peak-hour overcrowding and underuse during slow periods. This creates stress for both customers and staff, impacting overall efficiency.

Lack of Appointment Transparency

Users have no way of knowing available time slots at salons, forcing them to visit without any information about wait times. This lack of clarity complicates planning and often leads to an unsatisfactory experience.

Inconsistent Customer Experience

Without an organized scheduling system, customers' experiences vary greatly depending on salon traffic, which can lead to dissatisfaction and a reluctance to return to the same salon.

Project brief

Project brief

Project brief

How might we reduce wait times and improve the salon experience for users by creating a system where customers can easily schedule appointments and salons can efficiently manage their operations?

Bussiness perspective

It will help salons efficiently manage customer appointments by offering better visibility into available time slots and reducing overbookings. This will improve customer satisfaction, leading to increased client retention and loyalty

Expectation

As the sole designer, I was responsible for:

Rather than delivering a fully developed app, the primary focus was on creating a functional prototype that could demonstrate the app’s potential to salon owners and users, while convincing leadership and stakeholders of its value in optimizing the salon experience.

Project timeline

Project timeline

Project timeline

The project timeline focused on gathering continuous feedback from stakeholders while ensuring the concept aligned with the product's goals and vision. As the sole designer, instead of prioritizing rapid delivery, I emphasized building a strong foundation that could support future development and growth.

Research

Research

Research

I began by thoroughly exploring the salon industry, focusing on both the customer experience and how salons manage appointments. This involved studying existing salon scheduling apps and similar service platforms to understand how they operate and what gaps Naie could fill to enhance the overall salon appointment ecosystem.

I worked closely with salon owners and staff who had an in-depth understanding of day-to-day operations to ensure I grasped all aspects of appointment management, customer interactions, and salon services. This helped me design a solution that would seamlessly integrate into their existing workflows.

I engaged closely with salon professionals who had a deep understanding of customer management and appointment scheduling to ensure I fully comprehended all the necessary features and services Naie needed to offer for both users and salon owners.

User segmentation

User segmentation

User segmentation

This research provided me with a solid understanding of the product strategy for Naie, but to make it complete, I needed insights from different user segments. I segmented Naie's users into two primary groups: salon customers, who are looking for a time-efficient and seamless booking experience, and salon owners, who need an intuitive appointment management system to optimize their daily operations and customer flow. These perspectives were crucial in shaping the final product design.

This insight helped shape our strategy to engage all user segments, ensuring that salon customers remain connected with Naie even after their immediate need of booking an appointment is met. Features like personalized service recommendations and appointment reminders were designed to maintain long-term user engagement.

Key takeaways from this understanding informed my next steps in secondary research.

Secondary research

Secondary research

Secondary research

I focused on exploring how competitors and similar salon booking platforms addressed user engagement and retention challenges. This included analyzing features like loyalty programs, personalized offers, and seamless booking experiences to understand how Naie could differentiate itself and keep users consistently engaged.

I also aimed to identify best practices and strategies for integrating gamification into Naie’s platform to enhance user engagement. This included exploring reward systems, appointment streaks, and loyalty programs that could resonate with both existing users and new customers, encouraging them to return and interact with the app more frequently.

Journey mapping

Journey mapping

Journey mapping

User flow for appointment booking

User flow for appointment booking

User flow for appointment booking

Information architecture (IA)

Information architecture (IA)

Information architecture (IA)

Low-fidility

Low-fidility

Low-fidility

Low-fidility: Usability testing report

Low-fidility: Usability testing report

User's feedback

High-fidility

High-fidility

High-fidility