✔️ How to derive actionable insights from metric analysis.
✔️ Operating on-site banner campaigns that do not compromise UX/UI.
✔️ DINT's unique strategy of sending Friend Talk messages after personalized messages, resulting in a visit rate of 40-50%.
Today, we're diving into the story of DINT, known as the brand loved by celebrities. DINT is a fashion brand that remains in the spotlight due to its trendy styles, including the luxurious attire worn by 'Penthouse' star Kim So Yeon, who played Cheon Seo-jin, and the elegant ensembles of 'The Glory' actress Im Ji Yeon, who played Park Yeon Jin. Additionally, DINT recently sponsored the wardrobe for the lead character Hong Hae In in the drama 'Queen of Tears,' further establishing its reputation as the go-to fashion brand.
DINT garnered huge attention recently when Lee Boo Jin, the Samsung heiress wore a DINT dress. With its expansion into the Southeast Asian market and the launch of a popup store in Paris in 2023, DINT has ventured into the European market for the first time. DINT is renowned not only for its excellence in providing a personalized shopping experience through its online store but also for attracting attention across various sectors. Get insights into the practical personalized shopping implementation tips that DINT is actually applying.
Hello, Team Leader Kim Jihee. Could you please introduce yourself and provide an overview of DINT?
Established in 2009, DINT places customer satisfaction and confidence enhancement through fashion as its primary corporate values. To achieve this, the brand offers a variety of styles for TPO, a premium production line called 'MADE BY DINT,' and a special line named 'KELLY SHIN' designed for special occasions.
Do you have any special marketing strategies that have evolved the brand image over the past 15 years?
The key lies in making every aspect of marketing data-driven, from decision-making and strategy formulation to execution and result analysis. We always rely on user data analysis to discover the marketing initiatives that are most pertinent to our customers. Personalized CRM has seamlessly integrated into the data-driven marketing process. Recently, we've been leveraging Datarize's message campaigns to encourage repeat visits and purchases by analyzing the characteristics and funnel of new customers who were attracted by Lee Boo Jin, the Samsung heiress and the president of Hotel Shilla, wearing DINT clothes.
It can be considered a key tool for encouraging repeat purchases. In particular, DINT has a large number of customers who have made purchases at least once, and the repeat purchase rate among these customers is also high, ranging from 60% to 70%. These customers have the advantage of being able to analyze each individual's shopping cycle, consumption preferences, and interests in specific clothing items, unlike new customers. In other words, it enables more detailed and personalized marketing strategies. As a result, through data analysis, we enhance shopping satisfaction by providing personalized product recommendations and styling tailored to individual needs. In essence, all of these processes can be summed up in one term: CRM. Optimized marketing tailored to existing customers is a strategy that DINT cannot afford to overlook.
"Analyzing segment indicators is especially effective for re-engaging churned customers."
We are leveraging target customers with high scores based on Datarize's Conversion Probability Score* criteria. Recently, we've been analyzing customer segment data to send messages to dormant or churned customers.
[Types of Ecommerce CRM messages tailored to target customers at DINT]
* The Conversion Probability Score offered by Datarize: It is a value calculated based on all actions taken during a site visit to determine how closely it aligns with the behavior patterns of other buyers. A higher Conversion Probability Score indicates that the visitor has progressed further toward making a purchase. With just a slight nudge, customers who are hesitant to buy can be encouraged to complete their purchase.
Comparative Visit-Purchase Segment Analysis: March 2024 vs. June 2023. Notably, the percentage of inactive customers has decreased significantly.
Recently, we've been closely monitoring the visit/purchase segments in the Datarize Analytics menu. Through this metric, we discovered that the segment of "Deep Sleepers (customers who haven't visited for 2 years)" has a significant proportion. This highlighted the importance of Ecommerce CRM targeting long-term inactive customers. Given the positive outcomes from ongoing CRM campaign efforts targeting active customers, this year we aim to shift our focus towards inactive customers for our CRM campaigns. If it weren't for the visit/purchase segment, we might have missed out on a significant portion of customers.
Above all, directly classifying customer data and having indicators that allow us to see the current customer segment status at a glance without having to set them up has been a great help in identifying the brand's strengths and weaknesses. We have developed a marketing strategy that leverages strengths even more effectively and addresses weaknesses, allowing us to operate a more sophisticated and effective execution of CRM.
I heard that customizing on-site banners posed many challenges.
Yes, DINT is a brand that places great importance on UI and UX. We pay a lot of attention to banners and pop-up windows as well. Therefore, we have always been careful when displaying marketing messages such as on-site banners within the website. However, most solutions did not allow customization of banner images and were displayed in a format that filled the entire page, so we couldn't utilize them for a while. Due to this issue, we couldn't market to incoming customers, which was quite disappointing. However, while facing this challenge, we heard that Datarize allows for customization, so we decided to implement it.
How are you currently utilizing on-site banners?
Datarize allows for customization according to the DINT brand image, ensuring that banners are displayed only at the bottom of the page to avoid disrupting users' shopping experience. Therefore, we can showcase various banners without concerns about disrupting the shopping experience.
We display personalized product recommendation banners such as [Recommend best products], [Recommend products related to the purchased product], and [Notify customers of Social Proof for products they're viewing]. For non-member customers attempting to make a purchase, we utilize banners for encouraging membership sign-ups with notifications of membership benefits, as well as reminders for secret coupons targeting customers who haven't made purchases for a while, aiming to activate dormant customers. Once set up, tailored messages are automatically displayed to the target audience, allowing for a variety of messages to be displayed without any hassle.
"Based on insights from the funnel analysis, we plan the on-site banners."
To efficiently execute our on-site banner campaigns, we monitor funnel metrics, which are fundamental to data-driven marketing. We frequently review visualized funnels within Datarize and promptly apply recommended actions to improve conversion rates at each funnel stage. Being able to easily send messages based on metrics—whether it's targeting specific funnel stages for improvement or catering to individual interests—has felt highly efficient from a cost perspective as well. We primarily utilize tactics such as recommending products to customers who have abandoned their cart or checkout to enhance funnel metrics.
You are also utilizing various CRM campaigns through Kakao Friend Talk channel. Doesn't it require a lot of resources?
In the past, setting up Friend Talk messages involved manually configuring messages, extracting audience databases, analyzing results, and it was quite complex. Sending target messages through the Kakao platform was doable, but it required a lot of resources to manually classify customer databases and set up audiences. I've tried using third-party solutions, but the process was the same - from setting up audiences to creating content and scheduling deliveries, everything had to be configured manually by the staff. Now, with Datarize, everything from audience selection, content creation, operation, to result analysis is automated, reducing resources by more than half. By simply clicking the ON button for the campaign, we can go live and quickly send out a variety of messages.
"As a result, it has a significant impact on bringing back churned customers."
We primarily send Friend Talk messages to customers who tend to drop off at cart or checkout page. This campaign has shown a high success rate with a visitation rate of approximately 40-50%. And we're also incorporating insights gained from the visit/purchase segments into our Friend Talk messages, sending sharper, more targeted messages. We're reducing the segment proportion by continuously sending personalized messages to long-term non-visiting or high-churn customers.
At the time of sending personalized messages, we notice a significant change in traffic, with an increase of around 70-80% compared to the average. Furthermore, we often see the products recommended through Friend Talk messages quickly becoming best-sellers, providing tangible evidence of their effectiveness.
“The answer lies within the data.”
Using Datarize has highlighted the importance of data-driven actions beyond simply displaying on-site banners and sending messages. Datarize provides easy access to various data metrics such as key indicators, visit/purchase segments, cohort metrics, and funnel metrics all at a glance. Analyzing all the data, including those that were initially deemed less important and pushed down the priority list, allowed us to gain insights into customer needs from a wide range of perspectives. Additionally, we were able to easily identify areas where our website was lacking. Developing marketing strategies grounded in a profound comprehension of our customers and our business has elevated our approach to an entirely new level. These days, whenever I face challenges at work or need to make decisions, I instinctively turn to Datarize's analytics. It frequently offers valuable insights or solutions.