“As a leading online apparel retailer with many campaigns on different platforms, it took us a lot of time to optimize performance. With Alavi, we can now do this in minutes, as well as identify products to market. It has helped our returns grow significantly every month.”
Salik Gadit – E-commerce Manager
- With competition on pay-per-click ad platforms becoming especially fierce, clothing brand J.’s marketing returns were declining while budgets were skyrocketing.
- Using Alavi’s data science capabilities, J. was able to identify and focus its marketing spends on audiences that had high probability of converting, which boosted it returns and growth.
The Battle Is Online
Established in 2002 with the aim of reviving South Asia’s rich textile heritage, the apparel retailer J. is today one of the region’s most successful brands. Catering to both women and men, the company operates over 100 local stores as well as another 20+ internationally in the UK, Australia, Canada, New Zealand, the UAE and Qatar.
With the internet revolutionizing shopping all over the world, J. launched its own e-commerce store. However, in recent years, with the number of brands selling online increasing almost exponentially, getting consistent growth has proved to be very difficult. This is because the competition on pay-per-click (PPC) advertising platforms (like Google and Facebook) has been especially fierce with marketing returns declining and budgets skyrocketing.
A New Weapon
To fight rising marketing costs and reignite growth, J. knew it needed to optimize its PPC advertising and set itself two main goals: reduce cost per acquisition (CPA) for existing customers and acquire new ones with a controlled return on ad spend (RoAS).
To do this, it turned to data science, a tool that had helped many companies around the world solve similar problems. However, the cost of setting up its own data science team was prohibitively expensive. Fortunately, there were new marketing technologies that could help. After weighing the pros and cons of many of them, the company chose the advanced online targeting application, Alavi.
Offering both artificial intelligence (AI) and machine learning capabilities, Alavi was not only affordable but could quickly and easily integrate with the brand’s existing infrastructure and ad platforms. Upon connecting Alavi, its AI engine analysed a variety of variables from its marketing and customer data to identify audiences that were highly profitable and worth investing in. The insights Alavi provided helped the company target desirable cohorts with pinpoint accuracy and eliminate ones that had very little chance of converting. It also assisted the marketing team in developing ads that would improve engagement with the audiences it recommended so the company would get better returns.
Working with Alavi’s customer success team, the apparel brand launched a series of campaigns that were closely monitored to test the application’s effectiveness. In just 4 weeks, the Alavi.ai-assisted campaigns delivered results that not only exceeded expectations but broke existing standards: CPA was reduced by 77%, average order value grew by 50% and RoAS increased by 300%.
Buoyed by their success, J. is now gearing up to test Alavi.ai’s other advanced features, such as data-driven attribution modelling and engagement optimization. The battle for online success in the apparel industry requires strong allies, especially ones you know you can count on.