Marketing Investments in Search
Facing the meteoric growth of online sales, the challenge for today’s fashion companies is not just to offer on trend and desirable products, but to efficiently, and consistently, engage customers with the brand. Sites that excel in understanding what their customers want dedicate enormous resources, both human and financial, to making sense of search data.
The recognised leader of the pack is Amazon who in 2015 spent $2.8 Billion on digital marketing, according PR Newswire against online sales of $71.84 billion. According to Internet Retailer, HSN Inc. and Wayfair.com were next in line with the most spend.
Almost 91% of Amazon’s digital advertising spend was on search marketing, according to Fortune. Other online giants such as Etsy spent 94% of their budget on search with Apple spending 85%. In comparison, Target, Best Buy, Home Depot and Kohl’s all spent less than 20% for search.
The fashion e-commerce platform Farfetch has commited $4 Million in their marketing technology platform with a team of 130 creatives, data scientists, editors, artificial intelligence specialists all working under Chief Marketing Officer, John Veichmanis. In this Glossy article he states that “Data is the new marketer’s currency. Our job is to build meaning around the data to serve our customer more appropriately. That goes back to the basics of what marketing is: understanding consumer preferences. But rather them telling us in words and in surveys, we use our own gathered data to make decisions in real time. Ten years from now, any marketing team at any level will have those capabilities.” The company is relying heavily on its successful marketing strategy to generate profitability as it approaches an IPO, expected to be valued anywhere from $1.5 billion to $5 billion.
For most fashion companies without the revenue or marketing budget of Amazon or Farfetch, prudent marketing investments in search are needed. One such option is with the company Similar.ai. According to company founder and CEO, Robin Allenson, “Similar.ai builds meaning around data for our fashion customers. Our software understands consumer preferences from their actions on the site. People experience ‘added meaning’ by us not treating fashion items as being the same, but instead our software understands the subtle nuances that people have about clothes.” By tapping into Similar.ai’s artificial intelligence, enormous datasets, and visual imagery, your customers’ searches will be more efficient. Knowing your customers’ preferences better will allow you to serve them more appropriately and engage them longer.