Data science significantly improved the fashion brand’s online marketing.
- As online shopping booms in Pakistan, increased competition in the fashion space had raised Sapphire online marketing costs to unacceptable levels.
- Taking advantage of Alavi’s data science capabilities, Sapphire optimised its digital marketing campaigns which not only stabilised spends but also increased returns.
Launched by one of the biggest names in Pakistan textiles, Sapphire is a celebrated fashion brand known for exquisite designs at affordable prices. Built on an uncompromising commitment to quality, the company offers everything from clothes and shoes to bags and linen through its e-commerce site.
But with online shopping booming in Pakistan and barriers to entry relatively low, new companies are entering the fashion space all the time. There are already over 60 brands selling clothes online who get between 20,000 and several million site visits per month. Most of them are fighting to attract, engage, convert and retain the same audience segments.
This rapid increase in competition was a major challenge for Sapphire because it raised the company’s pay-per-click (PPC) marketing costs substantially on multiple ad platforms including Google and Facebook. Sapphire needed to find a solution that would help it both in the short term and the long term.
Getting Ahead with Data Science
By studying what was happening internationally, Sapphire’s management team fully understood the potential of data science and how it could substantially improve online advertising returns as well as deliver consistent outcomes. After weighing the pros and cons of investing in their own data science team, they explored marketing technology options with similar capabilities.
One ‘martech’ that caught their eye was the precision targeting application, Alavi. It performed predictive analytics using customer user behaviour, which would allow Sapphire’s digital marketers to quickly and easily target their most profitable audiences. This would help maximise the efficiency and effectiveness of their campaigns. Also, because it was developed for small and medium businesses, Alavi was affordable and had the potential to deliver results almost immediately.
An online application, connecting Alavi to Sapphire’s web analytics and marketing platforms (Google, Facebook etc.) was simple and fast. Once linked, Alavi’s artificial intelligence (AI) and machine learning capabilities started working right away. Using data science to analyse data generated from past campaigns, Alavi was not only able to identify the best audiences for Sapphire’s current efforts but also audiences for expanding and remarketing.
In just one quarter, on the campaigns Sapphire used Alavi, digital marketing spends were finally optimized. This resulted in bigger earnings from existing customers as well as the acquisition of many new ones. Thanks to Alavi’s data science capabilities, Sapphire beat its return on ad spend (RoAS) target by as much as 35% and increased its average order value (AOV) by 16%.
Use Alavi for Free Now
Developed for small and medium businesses, Alavi is a martech application that performs predicative analytics on your customers’ behavioural data. By combining AI, machine learning and automation, it gives digital marketers the cohorts and workflows they need to quickly target their most profitable audiences and boost campaign performance.
Alavi has a proven record of helping brands in a variety industries grow their revenue online. It has a very short time to value and is easy to setup and simple to use.