Considering that users rely on Google to provide them with information about virtually any topic, it should come as no surprise that Google continues to expand the reach and promise of its predictive analytics. A recent option seems like a perfect match, because of its rapidly changing markets. That is, these days, Google is predicting fashion.

In a recently released report for example, Google noted that no one is into string bikinis anymore, and skinny jeans are on their way out. But palazzo pants and tulle skirts are starting to be the focus of more shoppers’ searches, suggesting they are the next big things.

The reports go into more depth than just citing what’s hot and what’s not though. In line with its ambition to transform into an e-commerce site, rather than just a search engine, Google offers insights into which trends suggest sustained growth (e.g., tulle skirts, jogger pants), which ones are temporary trends (e.g., emoji shirts), which ones exhibit seasonal growth each year (e.g., white jumpsuits), and which fashions are just plain done (e.g., peplum jackets, scarf vests).

In addition to biannual summary reports, which it will issue for free to retailers, Google sells its analytics capabilities to fashion firms, providing them with real-time insights into search trends. These firms in turn can forecast demand, predict required inventory levels, and enhance their supply chain operations. For example, fast fashion retailers might note a recently emerging trend in Google searches, then make sure to have those items in stores within weeks to get ahead of the trend and maintain their image as fashion destinations.

Google’s approach also can break down the trends by geographical region, thus alerting smaller retailers about what their local clientele want. In one example, Google showed that searches for white jumpsuits increased in the area around Jackson, Mississippi, in May, soon after a local stylist had held a big fashion show touting the items as functional alternatives to dresses. Then Solange Knowles wore a jumpsuit as she rode a bicycle to her wedding in New Orleans, prompting even more searches among southern fashionistas. Only thereafter did the trend spread throughout the United States.

The current round of analytics focus on clothing fashion, but they certainly are not limited to that market. Thus, in addition to selling the services to interested companies, Google can promote itself as a premier advertising channel. Imagine if Google can identify the newest trends in dining room furniture, based on the searches it receives. Then it can turn to furniture manufacturers and retailers, offering evidence that their latest styles are already of interest (or not) to shoppers who are looking for those items. Such an appeal makes it nearly impossible for the advertiser to miss the value of advertising on Google.

Other companies have attempted similar analytical approaches; IBM predicted the emergence of the steampunk movement several months before hipsters wearing top hats and corsets were a common sight. In addition, Spotify’s essential business model helps musicians track the popularity of their songs in virtually real time.

But Google has an advantage in this market, because of its ubiquity in consumers’ searches for information. It gathers more data than virtually any other company, which implies that it knows more about consumers too. However, some observers argue that this ubiquity might be a detriment to the accuracy of Google’s predictions. People might search for “palazzo pants” because they want to investigate and buy the fashion—or they could simply be confused about what palazzo pants are and run a search to figure out what the term means, with no intentions of ever wearing them.

Discussion Question:

How can retailers use Google to predict new fashion trends?

 

Source: Hiroko Tabuchi, The New York Times, April 26, 2015