7 Behavioral Marketing Examples From Brands Doing It Right

A shopper adds a rain jacket to their cart, gets pulled into a meeting, and closes the tab. That evening an email arrives showing the same jacket. Two days later an ad for it appears in their social feed. Whether that sequence feels helpful or intrusive depends on how well the brand read the original signal and how quickly it responded.

Behavioral marketing uses what people do to decide what they see next. That includes the pages they view, the items they save, the emails they open, and the places they visit. When a brand misreads those signals, it spends budget chasing people who were never close to buying, or it keeps advertising to a customer who already purchased.

Below are seven behavioral marketing examples from well-known brands. Each one covers the signal behind the tactic, how a business your size can apply it, and what we check in the data before recommending a similar campaign.

1. Abandoned Cart Emails

A shopper who reaches checkout and stops has shown strong purchase intent. It happens constantly: Baymard Institute, which averages dozens of published studies, puts the average documented online cart abandonment rate at roughly 70 percent.

Shopify, for example, gives merchants a built-in abandoned checkout email that goes to shoppers who entered their contact details at checkout but left without paying. Many retailers build on that idea with a short sequence: a reminder within a few hours, a follow-up a day later, and sometimes an incentive at the end.

The reason a shopper left should shape the message. In Baymard's survey of US shoppers who abandoned an order, extra costs such as shipping, taxes, and fees were the most frequently cited reason, named by close to half of respondents. If surprise shipping costs drive your exits, a free-shipping threshold message may recover more orders than a discount code.

Signal to check first: When we plan these flows as part of our email marketing services, we start with the checkout step where exits cluster. Exits at the shipping step point to cost. Exits at account creation point to friction that an email cannot fix.

2. Browse Abandonment Retargeting

A visitor who views the same product category three times in a week has not added anything to a cart, but they have told you what they are considering. Retargeting keyed to that browsing behavior reaches them while the interest is still fresh.

Meta's catalog-based dynamic ads can automatically show people the items they viewed or added to a cart on a retailer's website, and Google Ads offers dynamic remarketing that works in a similar way. A sporting goods retailer can show hiking boots to the person who browsed hiking boots instead of running a banner for its entire catalog.

Product-level targeting like this keeps PPC advertising budgets focused on people who have already shown interest.

Signal to check first: repeat visits and time spent on product pages. A visitor who left after five seconds is usually a poor retargeting candidate. For visitors who did engage, a frequency cap stops the same ad from following them dozens of times.

3. Personalized Product Recommendations

Amazon is the example most people picture. Its product pages show sections such as 'Customers who bought this item also bought,' along with suggestions based on each shopper's browsing history.

Shoppers increasingly expect this. McKinsey's 2021 personalization research found that 71 percent of consumers expect companies to deliver personalized interactions, and 76 percent get frustrated when that does not happen. A smaller ecommerce brand does not need Amazon's scale to respond; a short list of 'frequently bought together' pairings pulled from its own order history is a practical start.

Signal to check first: order data showing which products customers buy together. Products that shoppers often view side by side can be substitutes, and recommending a substitute after a purchase rarely adds anything to the order.

4. Personalized Content Feeds

Netflix builds each member's home screen from viewing history, ranking rows and titles differently for different people. The company has also written on its technology blog about personalizing the artwork shown for a title, so two viewers with different tastes may see different images for the same film.

A B2B software company can apply the same idea on its resource page. Visitors who arrive from the pricing page might see case studies first, while first-time visitors see introductory guides. That kind of logic depends on a site built to swap content by audience, which makes it a web development question as much as a marketing one.

Signal to check first: whether you have enough content to personalize. Start with the two groups whose behavior differs most, such as new and returning visitors, before building more segments.

5. App-Based Offers Tied to Purchase History

Starbucks Rewards members receive personalized offers and challenges in the Starbucks app, shaped in part by what they have bought before. A customer who usually orders a morning latte might see a bonus-star challenge aimed at an afternoon visit.

A regional restaurant group or franchise can borrow the pattern through a loyalty program, text messaging, or email. The requirement is purchase data tied to an individual customer, which usually means a loyalty sign-up or account.

Signal to check first: purchase frequency and timing for each customer. An offer aimed at an existing habit gives away margin on a sale that would have happened anyway. Offers that target a new time of day or a new product line are the ones that earn their cost.

6. Streak and Re-Engagement Reminders

Duolingo counts the consecutive days a learner practices as a streak and sends reminders, through push notifications and email, when a learner has not practiced that day. The streak gives users a reason to return, and the reminder arrives at the moment the habit is at risk.

Subscription businesses, SaaS products, and membership organizations can watch for the same drop-off. A customer who logged in daily and then disappears for a week is at risk long before they cancel, and a well-timed message can reach them while they still care about the product.

Signal to check first: each customer's normal activity pattern. A gap only means something against that customer's baseline; a weekly user who skips three days has not lapsed.

7. Geoconquesting Based on Physical Visits

Burger King's Whopper Detour campaign in 2018 is one of the best-known uses of location behavior. The Burger King app unlocked a Whopper for one cent when customers were within 600 feet of a McDonald's, then directed them to a nearby Burger King to collect it.

Most brands work at a smaller scale. Through geoconquesting, a business can serve mobile ads to people who were recently near a competitor's location or inside a defined area tied to a buying occasion.

Signal to check first: how close the visit sits to a buying decision. A visit to a competing car dealership or furniture showroom suggests an active purchase. A visit to a busy shopping center that happens to include a competitor may not.

How We Decide Which Signals Deserve a Campaign

Every example above started with one signal worth acting on. Most businesses collect far more signals than they can use, and acting on all of them produces noise and wasted spend.

Our certified and trained digital analysts review behavior across platforms before recommending a campaign. With access to more than 20 marketing platforms, we can compare what a visitor did on the website with what they did in email, paid search, and social, instead of judging each channel on its own. That review is the core of our marketing analytics work, and it comes down to three questions:

• Predictive value: Does the behavior come before purchases, or is it just activity?
• Audience size: Do enough people show the behavior to justify building a campaign around it?
• Response speed: Can the systems react while the signal still matters?

Where Behavioral Programs Break Down

Even brands with good data run into the same problems:

• Channels running on separate data: The email platform stops messaging a buyer, but retargeting keeps showing them the product they already bought.
• Slow triggers: A cart email arrives three days late because customer data only syncs once a night.
• Over-frequency: A visitor who glanced at one page gets a week of ads and emails, and starts ignoring the brand.
• Consent gaps: Privacy and consent rules vary by channel and region, especially for email and text messaging, so confirm your requirements with legal counsel before launching.

Fixing these issues usually means treating email, paid media, social, and the website as one connected system, which is how we approach our digital marketing services.

Put Your Behavioral Data to Work with Purplegator

If your email platform, ad accounts, and website each run on their own data, or every visitor still gets the same homepage and the same follow-up, the signals in these examples are probably going unused. Purplegator is a growth-focused marketing partner whose certified analysts, creative team, and technologists turn customer behavior into campaigns across email, PPC, social, web, and geoconquesting. We start by understanding your business goals, then build a plan around the behaviors that matter most to your customers. Talk to an expert about which signals in your data are worth acting on first.