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Attribution. It’s a big challenge for e-commerce marketers. Most of these pros use a bevy of technologies and methodologies to concoct their attribution approach. They assign weights to actions across ad channels, and monitor their analytics to determine which of the channels are contributing to sales and how to allocate spend. If the attribution model reveals that email is the highest contributing channel, marketers will likely pump more dollars there. Display ads are not helping convert customers? Remove or shift budget.

But a problem with current attribution methods is that they look at how channels are related rather than how consumers are related. These models fail to consider the ways in which people, specifically families, influence one another’s purchasing decisions. Think, for example, about how much a teenager can influence a parent’s purchases.

What if marketers could see the domino effect that one consumer’s browsing behavior has on another consumer’s buying behavior? What if marketers could create an attribution model that understands a consumer’s interests or actions based on his or her relationships to others and to their online activity and transactions? Let’s unpack it.

The family attribution gap, defined

Going back to the teenager-parent example: Mom and Dad are not scouring the web to learn about the hottest new sneakers and counting down the days until their release date. That’s their son, Tim, who’s searching on Google, swiping online review sites, and ultimately clicking on a Facebook Ad for 123Sneakers.com (to use a hypothetical example) to see if his size is in stock for the latest Nike LeBrons.

But Tim is only 14 years old and isn’t approved for plastic. That’s when he goes to Mom, promises to get all A’s on his report card and do all his chores, and begs her to buy the sneakers.

Two weeks later when Tim hands over a stellar report card, Mom grabs her tablet, goes directly to 123Sneakers.com, and buys the kicks. The problem, of course, is that the retailer has no data on the attribution path that led to Mom’s purchase. To the retailer, it looks like Mom came directly to the site without being influenced by any ads or emails. There’s no credit to Tim’s search or clicks on the Facebook Ad.

That is the essence of the family attribution gap.

Enter Facebook

Facebook is in the position of understanding relationships between people. Parents, children, siblings, husbands, wives, aunts, uncles, and so on. Facebook knows because we tell it. At the same time, kids are doing a ton of product research online. All that data around who the true customer is (Tim) gets lost because a new user (Mom or Dad) buys the product.

The marketer’s attribution system would show that the investment to attract Tim did not pay off because he did not buy. In reality, the investment did pay off. Mom bought the sneakers. When the family attribution gap is open, marketers would likely pull back spend where they should fuel the fire.

So the question becomes: Can — and should — Facebook invest in the capability to connect Tim to Mom and provide that data to e-commerce marketers to help them more wisely spend their budgets?

How it could work

A retailer adds a tracking code to its site. Consumer #1 is logged into Facebook and then visits the retail site. The code tracks his behavior. Meanwhile, Consumer #2 is logged into Facebook on her own computer. She visits the same retail site and the tracking code again logs her behavior.

The technology then looks at the connection between Consumers #1 and #2 and assigns the pair a weight — let’s say 1, 2, or 3 — based on how their behaviors are related.

Category 1 = No connection on Facebook.

Category 2 = The consumers are friends on Facebook. Their online behaviors do not suggest that there is a relationship between their browsing and purchasing activity.

Category 3 = The consumers have indicated a relationship on Facebook (married, dating, related, etc.). Their online behaviors show a relationship between their browsing and purchasing activity.

The system could constantly pair users and assign them to a category. Once two users pass a certain threshold of correlated activities, the system would determine that there is a relationship between Consumer #1’s behavior and Consumer #2’s purchases.

Mom and Tim, for instance, would be in category 3. Armed with this data, marketers could accurately give credit to the channel that truly spurred the purchase — such as the ad in Tim’s Facebook feed.

Marketers could then target consumers with more relevant ads. Ads to Mom could be structured to provide recommendations for products her son might like. Ads to Tim would directly influence his choice of footwear. This “family attribution model” would let marketers hone their target market and avoid wasting spend on pushing the wrong ads to the wrong consumers. A blind spot would be illuminated.

Caveats? Yes. But the potential is immense

Certainly some conditions need to exist for this system to work. Consumers would have to be logged into Facebook — which is often the case. Seventy-one percent of online American adults use Facebook, according to Pew Research, with 70 percent of Facebook users logging in daily. Consumers would also need Facebook accounts, of course, so retailers would be able to gain data around those who are 13 and older. While this system probably would not replace other attribution systems, it could certainly supplement them.

The family attribution gap really gets interesting when you think about how far it could reach. It could close gaps beyond just parents and children. For example, connections could show a woman browsing sweaters online and then her husband buying one for her birthday. An executive might research new computers, and then her assistant purchases them.

Then there are groups and communities where one consumer can influence multiple people’s purchases — say a professor or several teacher assistants who influence college students to buy certain books or lab supplies. You can start to see how the family attribution gap can then adapt to become the “academic attribution gap.” Among co-workers, it could be the “co-worker attribution gap.” And so on.

Attribution gaps pervade our daily lives. But Facebook could be a bridge. The data surrounding the online behaviors and purchases of connected consumers could be used to understand how marketing spend flows between families, friends, and colleagues — and ultimately leads to a transaction.

Andre Golsorkhi is the founder and CEO of Sidecar. Previously, Andre was the CEO and Founder of Snipi, a patented system for people to save their interests while browsing anywhere online.

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