AI Generated Audiences Impact

This is April (TIA) is one of Indonesia’s largest fast fashion brands, with conventional stores in all major cities. When the Covid 19 Pandemic strikes, TIA stores see a drop in foot traffic. With lockdowns and social distancing measures in place, a drop in foot traffic resulted in a significant drop in sales.

With fewer customers visiting physical stores, TIA, like many other traditional fashion stores in Indonesia, has had to shift its focus to e-commerce in order to remain competitive.

This is April has partnered with AiSensum as their Performance Marketing agency to establish a strong online presence through the use of their E-Commerce platforms (Website and various marketplaces).

This is April has an extremely large database of transaction data. AiSensum can generate audiences by discovering and targeting potential buyers using data analysis and machine learning.

Our Algorithm analyzes enormous quantities of TIA transaction data to develop detailed profiles of their potential clients, which are then targeted with personalized marketing campaigns. This might result in improved sales and a higher return on investment for the business.

AI Generated Custom Audiences

By analyzing transaction data to find trends in purchase behavior, the AiSensum Algorithm generates targeted audiences. To build multidimensional client segments, AiSensum combines two segmentation algorithms, NMF and RFM.

NMF segmentation enables TIA to find and classify related products by identifying patterns and linkages in data that are not immediately visible. It can also be utilized to uncover new market sectors that are currently untapped.

RFM stands for Recency, Frequency, and Monetary Value. This method examines three main aspects of a customer’s buying history: how recently they made a purchase, how frequently they make purchases, and how much they spend. RFM enables TIA to construct customized marketing strategies that appeal to their various degrees of client loyalty and enhance conversions

Clustering algorithms grouped customers into segments based on common characteristics, whether it based on product or customer Recency, Frequency, & Monetary value.

Our Algo predict which customers are most likely to target with specific product or product combinations

Segment characteristics also used to match Ad Platform keywords & interest with the AI generated audiences.

Translating Data into Creative Contents

AiSensum Algorithm identify breakthrough products from the transaction data. Our PM Team implemented Persona based creative to give suggestion to This is April how the creative content should be, to appeal to the selected audience.

Breakthrough Products will be matched with TIA buyer persona to create Persona Based Creative.

These combinations of product & persona are used to guide the content creation by setting the theme, storyboarding, and final execution of creative content