Omnichannel, Consumers, and Privacy Concerns

Brands and retailers (especially those that can afford to) are more than ever interested in consumer behavior as a ticker for predicting sales, product successes, and revenue baseline. This drive, or push, didn’t start in the last decade. It gave rise to omnichannel marketing, a move to unify consumer data across online and offline channels.

With omnichannel marketing, these businesses bring all customers, whether paying or non-paying, under one ecosystem, allowing them to further understand the behaviors that differentiate paying and non-paying customers, short- and long-term customers (to effectively predict lifetime value), as well as customers who are likely to purchase more than others (per customer buying/revenue potential). These datapoints have also helped to guide product pricing structure (which could sometimes be purely based on human instinct).

So, why did I decide to write something about this topic?

Last week, I came across a viral video of a man who had received an email survey from Walmart after walking into the store without his mobile device and paying in cash. Immediately, the viral video cast my mind back to 2012; a story about a father who had confronted a Target store manager for sending pregnancy-related coupons to his daughter. In that story, the father would later get a call from the store manager, who he apologized and admitted that his teenage daughter was indeed pregnant.

As big brands and corporations, understanding consumer behavior in relation to their buying preferences means being able to predict which products are more likely to become successful among specific demographics. It could also be the make-or-break decision between a colossal failure and an earth-shattering revenue zenith. On the other hand, consumers do not like to be watched/tracked, at least, to their knowledge. This puts both sides of the market at a standstill. Should businesses and brands be tracking customers and consumer behavior? Where does it stop?

An anecdote from Forbes’ publication on Target’s reported Andrew Pole, Target’s statistician at the time, as saying: “If we send someone a catalog and say, ‘Congratulations on your first child!’ and they’ve never told us they’re pregnant, that’s going to make some people uncomfortable. We are very conservative about compliance with all privacy laws. But even if you’re following the law, you can do things where people get queasy.” Queasy customers are no good for revenue projections.

On the other hand, brands and businesses can argue that such tracking and datapoints are essential towards delivering a robust and improved customer experience; after all, customers admit they save a lot more time when they get tailored advertisement or coupons based on the products they’re more likely to purchase.

But what does a win-win situation look like?

In Target’s case (and as with many other big brands), the key remains to not let consumers know the extent of data you’ve got on them. Sneaky right? Not quite.

As humans, we like to feel an air of mystery around ourselves.

The solution was simple: Target started mixing targeted ads with fluff while testing targeted coupon positioning. What this does to the human mind is to effectively remove the apprehension that you’ve been studied, analyzed, and classed into buckets based on the likelihood you’ve shown over the past buying and non-buying decisions.

“Then we started mixing in all these ads for things we knew pregnant women would never buy, so the baby ads looked random. We’d put an ad for a lawn mower next to diapers. We’d put a coupon for wineglasses next to infant clothes. That way, it looked like all the products were chosen by chance.

“And we found out that as long as a pregnant woman thinks she hasn’t been spied on, she’ll use the coupons. She just assumes that everyone else on her block got the same mailer for diapers and cribs. As long as we don’t spook her, it works.”

Consumer Data & Protection

Interest in consumer data protection has risen in the last decade. In 2021, Apple launched iOS 14.5, which effectively spelled doom for consumer tracking. In addition, consumers are now more likely not to share their data or accept cookies as part of their web experience.

In a 2016 study published by Periscope by McKinsey, consumers (online: 27% U.S., 29% U.K.; in-store: 22% U.S., 18% U.K.) admitted to wanting relevant personalization information for their online shopping experiences, yet an overwhelming proportion of these respondents (61% U.S., 62% U.K.) won’t share their personal data with retailers.

All these points to the fact that although consumers enjoy targeted ads and personalized recommendations, they want to retain control over what is shared and the extent of their information that is available out there. Talk about eating your cake and having it.

So, What Does an Effective Omnichannel Marketing Setup Look Like?

An effective omnichannel setup should deliver a unified, consistent, and personalized experience to individual customers across all platforms, online and offline.

Breaking it down into 4 phases:

This is the foundation and brain behind the entire Omnichannel system. This system networks Customer Relationship Management (CRM), Customer Data Platform (CDP), Analytics, and Attribution.

The entire setup combines ads, email, SMS, website tracking and experience, social media, and offline store experience (Wi-Fi, email signups, and memberships).

At this stage, you understand who your customers are, where they’ve come from, what they’ve viewed, their buying decisions and by extension, what they’re likely to buy next.

Brand messaging and creating a consistent experience across the board help to gently lull customers into relaxing into your brand messaging. An effective brand message establishes a core brand identity, pushes the same value proposition, and ensures that creatives are targeted to different channels.

This body builds heavily on the foundations you’ve created. It marries and tracks user behavior across online channels like social media, SEO and organic content interaction, email engagement and automation flows, SMS, website and blog, and mobile app experiences, as well as offline channels like retail stores, pop-ups, physical events, and print materials like flyers and physical coupons.

With data collection and integration in place, data analysis becomes easier to better understand consumer insights and track propensity to make certain buying decisions. This also means a better approach to automating customer experiences, from triggering abandoned cart emails and SMS to establishing a retargeting sequence via ads.