Human touch vs. algorithmic precision: Rethinking shopper marketing in a digital era

Shopper marketing once relied on shelf space and clever design. Now, algorithms play a major role. 

Design and visibility still matter. Yet, competitive brands add real-time data, predictive personalization and AI that anticipates our needs before we do. For instance, today: 

• Predictive personalization now powers revenue engines at Amazon, Target and beyond

• Great campaigns speak to people and platforms

• Transparency and trust are non-negotiable

• Tomorrow’s shoppers include AI agents

So, what does this new era of shopper marketing mean for your brand? 

Shopper marketing has moved from endcap battles to everywhere-all-at-once digital engagement. Today’s 24/7 shopping experience is always-on and omnichannel. 

McKinsey reports that 75% of U.S. consumers tried new shopping behaviors during the pandemic, and those habits stuck. Think: curbside pickup or grocery delivery options offering convenience and low-friction shopping.

Now, AI shines at convenience and personalization. Predictive personalization goes beyond traditional AI rule-based targeting. It learns, adapts and tailors offers to customers based on data signals. The results speak for themselves. Amazon drives over 35% of its revenue through AI-powered recommendations. Walmart uses its brand affinity tool to tailor promotions based on individual behavior. 

But it’s not all technology. This shopper marketing shift is an artful blend of psychology and technology.

“Even in AI-enhanced campaigns, human emotion remains the heartbeat of shopper marketing.”

- Andre Oentoro, CEO of Breadnbeyond

Still, personalization needs boundaries. Fergal Glynn, the Chief Marketing Officer and AI Security Advocate of Mindgard, says, “Users trust brands that comply with regulations such as GDPR, allowing the brands to still provide tailored experience.”

So what does this look like in practice?

Timing is everything in marketing. AI excels at helping brands get it right. By automating, predicting and personalizing each interaction, brands can meet shoppers where they are in real-time. 

But first, a quick rewind. 

Shopper marketing used to mean shelf displays and coupon cutouts. Then came endcap wars and in-store radio. 

In the 2000s, digital entered the mix. Retailers began experimenting with online promos and loyalty data, but the real shift came when mobile phones and e-commerce collided. The lines between digital and in-store shopping began to blur, forcing marketers to adapt.

The past decade has moved fast. Advances in machine learning and predictive analytics let brands track behavior across devices, decode buying signals and deliver the right message at the right time. It’s no longer simply about targeting. It’s about the timing, tone and context. 

Take Kroger, for example. Its partnership with NVIDIA uses AI to simulate store layouts and optimize shelf arrangements for real-world impact so customers shop faster and buy more efficiently.

Or consider Sephora, which uses AI tools to personalize makeup and skincare recommendations. From smart diagnostics to chatbot consultations, customers get data-driven product matches in seconds. 

Innovative brands are using AI to win consumers’ trust and build brand loyalty. Let’s break down why predictive personalization is so powerful. 

Predictive personalization means knowing what a shopper wants before they do. You’ve experienced this with Netflix and Amazon, but they’re not the only ones using it. 

What powers this approach? Behavioral analytics + purchase history. 

Brands pull from four main data types:

• Browsing behavior: Clicks, time spent, exit points 

• Purchase history: Repeat buys, frequency, recency

• Device context: Location, platform, time of access 

• Loyalty signals: CRM inputs, preferences, coupon usage

These signals feed into:

• Real-time recommendation engines 

• Personalized email sequences 

• Dynamic offers across channels 

These signals fuel real-time recommendation engines, email sequencing and personalized offers.

Here’s how it works:

1. A shopper views sneakers but doesn’t buy them

2. The algorithm notes past purchases, preferred price points and time-of-day activity

3. Later, the shopper sees a promo for a new sneaker drop, right before they typically browse, ultimately enticing them to reconsider

It feels seamless to the shopper. That’s the goal.

There are two brands setting the success metrics for this method: Amazon and Target.  

• Amazon’s powerful recommendation engine, which accounts for 35% of its overall revenue, serves as a benchmark.  

• Target has famously predicted pregnancies, sometimes before the mother-to-be even shares this news with her family. How? Through shifts in buying behavior, in particular, newly pregnant women bought large quantities of calcium, magnesium and zinc. Based on purchases of about 25 different products, Target’s data scientist could assign a “pregnancy prediction” score to consumers. 

Of course, predictive personalization can go too far. When recommendations are a little accurate or frequent, it can cross into “creepy” territory. 

As CEO Andre Oentoro puts it: 

“Brands are walking a fine line between personalization and respecting privacy. The key is transparency and control. That means letting users know how their data is used and offering opt-in choices.”

Transparency and control are non-negotiable. Consumers want relevance, but not at the cost of trust. So, how do you strike a balance? 

Today’s shopper marketing needs to resonate emotionally and perform technically.

Two audiences. One message. 

You’re speaking to: 

• A human who wants timing, value and emotion

• A machine that tracks scrolls, clicks and conversions

Modern marketing strategies are built for both. 

You’re aiming for: 

• Emotional hooks: Stories, visuals, language 

• Technical signals: Structure, metadata, engagement loops 

When done well, both boost performance and reinforce one another. 

Here’s two campaigns that nailed both: 

1. 💄Sephora Turkey + TikTok Smart+ (Black Friday 2024)

Used AI-powered optimization to boost performance across the funnel, which resulted in:

• +53% return on ad spend (ROAS)

• +44% improvement in average revenue per user (ARPU)

• +14% lift in conversion rate

2. 🏃 Adidas Originals + Ready Player Me (Ozworld Collection)

Created a personalized avatar experience powered by AI, which resulted in:

• 10 million possible AI-generated avatars

• 428,000 avatars created in the first 10 days

• 18,000+ avatars used across virtual platforms

Why they worked 

Both campaigns delivered on two fronts: They made people feel something and gave platforms the signals they crave. 

Sephora paired creator-led storytelling with real-time optimization. Adidas fused self-expression with shareable, AI-generated avatars. 

In both cases, the emotional hook fueled engagement, while the technical design made it easy for algorithms to amplify.

But as personalization gets smarter, the stakes get higher. How do you stay relevant without crossing the line? Let’s talk about what happens when personalization goes too far—and how smart brands are keeping it ethical.

The right blend of emotion and precision makes for high performance. Yet, it’s essential to remain ethical and keep trust intact.

Personalization vs privacy 

Every click leaves a digital trail. While that trial powers smarter targeting, it can also raise concerns. 

According to Pew Research, 77% of Americans “have little or no trust in leaders of social media companies to publicly admit mistakes and take responsibility for data misuse.”

A Gartner study found that 55% of respondents say they’d stop shopping for a brand if they find its communications invasive. 

It’s a fine line between gathering data for better targeting. 

Ethics is the new UX 

Privacy isn’t just a compliance issue; it’s a brand experience. When customers feel they’re being watched or manipulated, even subtle friction (like a mistimed retargeting ad) can damage the relationship. 

Consumers are pushing back in the following ways, which we can see with: 

• Rising use of ad blockers

• Stricter opt-in preferences

• Growing backlash against third-party cookies and data brokers

Regulatory shifts include: 

• GDPR

• CCPA

• AI transparency guidelines 

What experts say: Lead with transparency

Here’s a few stances from business leaders on the matter.  

Fergal Glynn, CMO of Mindgard, notes:

“Brands are being open about how users' data is used, and complying with strict privacy regulations, to balance personalized experiences with user privacy.”

Similarly, Andre Oentoro, founder of Breadnbeyond says:

“We prioritize ethical data use by anonymizing insights and focusing on contextual engagement rather than personal identifiers.”

The most effective brands now bake privacy into the experience, offering clear opt-ins, simple controls and personalized content that feels earned and not extracted.

AI isn’t replacing marketers. It’s redefining the role. Humans bring the big idea and AI helps you test it, optimize it and deliver it in real time. 

Expect to see more:

• Hourly content and pricing updates based on local conditions, inventory, or user mood

• Micro-targeted creative variations at scale

• Personalized post purchase moments (think: Thanks [First name]! Here’s 10% off your favorite cereal.”

Human creativity stays in the loop

AI can write headlines and product descriptions. But it can’t craft a brand voice. It can test ideas. But it can’t feel them.  

In fact, the rise of AI makes human creativity more valuable—not less.

As Andre Oentoro notes: 

“AI can tell you when and where to deliver a message, but it’s emotional storytelling that drives action.”

However, tomorrow’s shoppers aren’t always humans. 

What’s coming next: Expert signals

90% of consumers are omnichannel shoppers. They expect a coordinated experience across platforms. Circana VP of global consumer solutions, Anne Zybowski says, ”They’re not choosing between browsing online or shopping in stores; they’re doing both and often simultaneously. Now, they also expect seamless experiences across all brand and retailer touchpoints…as consumers seek to shop on their terms.” 

In addition to an omnichannel world, the future also has AI shoppers in store for brands. 

AI shopping agents 

Walmart for example is preparing for a future where AI agents shop on behalf of the consumer. Why? Customers are already using tools like ChatGPT to help them build shopping lists and decide what to buy. 

Walmart’s Chief Technology Officer, Suresh Kumar, stated that Walmart is developing APIs and infrastructure to support AI agents, enabling them to access inventory, pricing and personalized promotions directly.

Consumers can set up preferences like price ranges, delivery windows and preferred brands and the AI monitors your needs, habits and inventory via connected apps or devices. 

For example, when you run low on your favorite coffee, the AI agent can order for you or notify you, depending on your settings. 

Brand takeaway for the future: You’re not just selling to people anymore. You’re selling to systems that act on behalf of people. If your product data isn’t machine-readable, your brand won’t show up.

Emerging trends to watch:

• Privacy-first personalization: First-party data and consent-based design will become standard

• Voice + visual search: As behaviors shift, shopper marketing will need to adapt to non-text-based discovery

• Emotional AI: Tools that detect sentiment, tone, and stress in real time will shape how offers are delivered

• Creative intelligence platforms: AI won’t just optimize what works, it will help teams discover new ideas worth testing

Shopper marketing is a series of duets. 

• Human + machine

• Emotional + algorithmic

• Digital + physical

The brands that thrive will be those that treat AI not as a shortcut, but as a strategic partner.

Build responsibly. Track what matters. Speak to people and platforms. That’s what winning looks like in today’s shopper marketing world.