3 CEOs Transforming Big Data in Retail Now : Fancy’s Joe Einhorn + More

There are over 7 billion shoppers worldwide, and it may be surprising to some, but core family values and religious values influence our shopping.  Though there are many similarities in shoppers all over the globe, there are still some factors that affect our decision on how and where we shop, not to mention regional influences. It’s unlikely for someone in the tropics to purchase a pair of knee-high snow boots.

A recent Nielsen study, which included more than 29,000 online respondents in 58 countries, reports that “more respondents in Asia-Pacific shopped impulsively and were attracted to designer brands than in any other region. Latin Americans were intensely brand-loyal and well-informed shoppers. North American and European shoppers were largely driven by price, and Middle East/Africa respondents were environmentally savvy and influenced by professionals.”

With Big Data growing up and now being adopted by more industries such as retail, it is expected that brands better able to understand what defines a consumer’s preference, all in an effort to deliver better products and services.

3 Companies Transforming Big Data in Retail



What’s important to an individual can depend on the time of day, their age and position in life, what type of mood they’re in or their current activities.  We all wear a variety of hats, acting as a team leader one moment, and the family chef the next.  “When you think of online communities, there’s ways to treat them as a collective whole,” says MetraTech CEO Scott Swartz.  His company helps businesses use data to predict customer behavior, empowering a B2B exchange network amongst online retailers.

“When you look at an individual, you need to look at them from a different mode. You need to go below the individual,” Swartz says.  “Individual-based filtering rather than finding individuals that are similar–it’s too expensive to compute.

“You start building these self-organized communities that display behavior that may be contrary to another community.  There’s similarities amongst populations, and if you set that dynamic affinity group to sell me, you develop loyalty,” explains Swartz.

Piqora (formerly known as Pinfluencer)

Though it changed its name from Pinfluencer to Piqora, the company is not moving away from the Pinterest ecosystem, as it still considers itself the complete marketing suite for the popular pinning site.

Piqora CEO Sharad Verma sees the name change as  appropriate since  it sounds like “pick” and suites  the web which is becoming more visual.

When it comes to Big Data, Piqora focuses on two things, analytics and content management.

“What we found is that in general, people are afraid of analytics — of what the data can tell you. And so as a company, you’re always challenged with bridging the gap between analytics and action. If you package your analytics around action, it must be more digestible and usable.  We want to be able to do predictive analytics and tell [a retailer] which products are beginning to trend and might go out of stock in two weeks.

Another direction is content management. We’re looking at building a content management suite that would allow users to select what products to promote on different platforms and manage that from a certain location. We’re making analytics an integral part of actions in merchandising and content management,” Verma explains.

The Fancy

The Fancy founder Joe Einhorn may have pinned the ultimate goal of Big Data and analytics  in two sentences:

“If you’ve seen the movie Minority Report, we want to be the pre-crime of shopping. We are going to get that pair of black boots in front of you a month before you search for it or respond to traditional marketing.”

It’s quite unnerving thinking how brands or companies would know what you want even before you think about it, but that’s the reality.  All these predictive analytics will be useless if one brand cannot tell what consumers would want next month or the following month or next year.  In order for them to stay ahead of competitors, they need to find a way to predict what people would want even before they want it.  Or if that’s not possible, make something that people would want and the people can set it into a trend.