Three tips to help your e-commerce app achieve outstanding results
The first step in personalization is to find out. What problem customers want the brand to solve for them. After the drama “Crash Landing on You” produced. By South Korean film and television giant CJ. ENM was broadcast, the outfit of the heroine Son Ye-jin became a hot. Topic of discussion among the audience, so various brands. Rushed to buy it, including the well-known South Korean e-commerce company Gmarket . With the theme of Son Ye-jin’s matching outfits , a special marketing. Activity page has been established , focusing on clothing. Accessories and beauty products similar to those in the drama. This marketing campaign combines social media. Data and peripheral product promotion experience to allow consumers to revisit classic Korean dramas while emulating Son Ye-jin’s style.
Deeply cultivate the local area and understand the market
In 2022, Appier assisted a well-known e-commerce brand to use dynamic creative optimization (DCO) in a single marketing campaign, producing more than 1,500 hyper-personalized Double 11 Singles’ Day advertising materials in a single day. This marketing campaign successfully used DCO America Cell Phone Number List and the powerful AI-driven audience identification function provided by Appier to successfully achieve an investment return of 11.4 times. If that’s not exciting enough for you, Appier also found America Cell Phone Number List a whopping 83% difference in conversion rates between dynamic and static content. This means that the consumption habits formed by consumers during the epidemic have not disappeared, so they will prefer brands that can display the most suitable products at the right time and place, rather than being blindly loyal to a single platform.
Embrace personalization and customize user experience
Appier is also working with a well-known Romania Phone Number List large-scale e-commerce group in South Korea to create marketing campaigns. The engineering team builds algorithms and continuously optimizes them, mainly providing user models and optimized recommendation functions. Whenever a user sees an ad, they are paired with dozens of product recommendations that are most likely to convert. Once you reach sufficient scale, you can build a near-complete model of every past ad interaction and calculate conversion rates, successfully reducing cost per acquisition and increasing average price per customer.
