Retargeting

The most competitive industry just went up a notch. On top of what is already the most dynamic industry in terms of competition and fluctuating consumer tastes, you now have heightened geopolitical turbulence that is rocking supply chains and margins. This equates to more pressure than ever put on digital fashion marketers to implement the latest technology and strategies to accelerate stock flow and revenue. This article highlights a range of tips to optimize inventory and orchestrate increased conversions.

Retargeting is a marketing tactic that lets brands show ads to potential customers who visited a website but left without buying. By reconnecting with people who have already shown interest in a product or service, retargeting helps businesses encourage shoppers to finalize sales and lift return on ad spend. Consider this your guide to retargeting. It covers how the tactic works, the main types of campaigns, and how Deep Learning provides a clear advantage in personalization.

Choosing a retargeting company is a major decision in digital advertising, yet many businesses still judge performance by the metric least connected to revenue. In this article, we explain what retargeting companies actually do, why clicks are a misleading measure of success, and how to compare retargeting platforms so that campaigns are evaluated on real marketing ROI, not vanity metrics.

Ask ten marketers whether you should run two retargeting vendors simultaneously and you'll get ten different answers. We think the data settles it—but we'll let you decide.

Core takeaway

Multiple retargeting means running two or more retargeting vendors simultaneously against the same pool of site visitors. Because each vendor uses different algorithms to evaluate user intent, they identify different high-value opportunities within the same audience. The result: more conversions, without proportionally increasing your budget. The biggest objections—overlap, bid inflation, added complexity—don't hold up under scrutiny. The data consistently favors a stack approach.

Online purchases now account for approximately 20% of all fashion sales, and potential customers can engage with your brand across multiple channels. This constant communication has transformed the way fashion ads are delivered to customers and greatly expanded the potential for personalization.

From the printing press to Deep Learning, the history of marketing shadows all our great leaps forward in communications technology. It is the marketer’s job to identify how these novel technologies can be used to reach potential customers, and educate them about products and services that enrich their lives.

The printing press let us create posters, radio and television enabled us to speak to people in their homes, and the internet gave us new ways to sell to people. Today, we’d like to take a moment to dive into how marketers can take advantage of the next big leap forward in technology: Deep Learning.