Queenit
CommerceIntroduction
Queenit provided by Rapport Labs is a fashion e-commerce service for women in their 40s and 50s. Queenit’s goal is to enable all women in their 40s and 50s to become more beautiful in an easy and convenient manner.
Overview
Queenit provided by Rapport Labs is a fashion commerce service for women in their 40s and 50s established in September 2020. Their aim is to help all Korean women in their 40s and 50s become more beautiful with ease and convenience. As an app representing users in their 40s and 50s, more than 80% of the app’s users are 45 years old or older. Based on its set of customized strategies through customer data, the app is showing an aggressive growth of 1,700% annual transaction increase, cumulative app downloads exceeding 3.2 million, and being named the Google Play’s Best of 2021.
Challenges
Queenit is an company with a strong need for internalized data analysis functions. Therefore, the company needed its own dashboard built from the data collected with MMPs as well as advanced data export and free utilization of data integration to other solutions.
Solutions
Building a Data Pipeline by Using Airbridge
Queenit mainly uses Airbridge for exporting data and building a data pipeline with the exported data. After Airbridge collects data on which ad from which media channel brought each user to the app, Queenit loads the data onto its own database to link the data with the event data from its products for in-depth analysis.
As a method of collecting user traffic data, Queenit uses Airbridge tracking links for ‘Share Product’ CTA in its app. Using the Airbridge tracking link makes it possible to collect data not only for general traffic but for traffic generated through the sharing function without building a separate system.
After collecting data, Queenit uses the data export function for a seamless data pipeline. For example, Queenit links Airbridge to Google Cloud Platform (GCP) through API. It was relatively more convenient to build a data pipeline since it is possible for Airbridge to export data in batches.
Queenit’s Analysis for How Customers in Their 40s and 50s are acquired to Their Services and Relevant Marketing Strategies
Analysis of Queenit’s traffic with Airbridge led to the insight that traffic generated through Organic media is greater for Queenit’s services than traffic generated through Paid media. This could be interpreted as word of mouth being an effective means of introducing consumers in their 40s and 50s to Queenit’s services, and this led Queenit to choose the strategies of focusing on user traffic generated through organic media rather than using a specific tool for search engine optimization (SEO) or allocating great amount of resource to app store optimization (ASO).
That’s why Queenit is using content strategies tailored to their target group - consumers in their 40s and 50s - in marketing creatives. Queenit uses elements of slow and clear, large letters preferred by consumers in their 40s and 50s rather than flashy and speedy content often used in performance marketing. Queenit is currently interviewing two to three users per week for further insights into content.
“Mobile app marketing without mobile attribution software is like spending money with your eyes closed. If you are a company new in app services, Airbridge is a choice you would never regret. Even when a great amount of traffic is generated through marketing campaigns, it does not always lead to a stable number of user acquisition and using the services. Since Airbridge charges based on MAU, I believe it is a worthy choice for startups in their nascent stages needing aggressive UA marketing.” - Hee-Min Choi, CEO at Rapport Labs
Results
Queenit is expanding into new fashion categories—including golf wear, outdoor apparel, and cosmetics—with the goal of becoming the leading fashion brand for consumers in their 40s and 50s. To support this growth, Queenit plans to launch a web platform in 2022, building on the success of its existing mobile app.
