More than ever, digital privacy is top of mind for many consumers. Headlines citing widespread data breaches on seemingly secure institutions have become so commonplace they’ve almost lost their shock value. Laws requiring greater transparency for digital data tracking give consumers the option to opt out immediately. Digital privacy is important, but this behavioral and structural change also takes away a valuable marketing tool: cookies. 

Without cookies, marketers can’t easily track user activity across websites, thus reducing opportunities to personalize and promote relevant offers. While a digital landscape without cookies might seem bleak, remember that refined customer data hasn’t always been so readily available. Before cookies, mainstream advertising cast a wide net to acquire new customers, but in a post-cookie era, you can do better. Learn today’s techniques, strategies, and analytics that allow marketers to identify and target their ideal customers — no cookies needed.

1. Predictive Analytics 

While your customers are certainly unique, there are common behaviors, life stages, and trends that can inform your marketing tactics. Most businesses already have buyer personas that help determine messaging and campaigns. Predictive analytics takes personas to the next level by analyzing historical data and identifying patterns and trends. The results of this analysis help predict user behaviors and preferences, which then support personalized experiences at scale.  

Customer actions are at the core of this approach, which helps inform marketing messages so they are relevant and useful. We’ve all received tone-deaf, mass emails that are so generic they feel almost offensive. Instead, build predictive audiences to tailor messaging to people most likely to make a purchase. This way, marketers can be proactive with messaging that anticipates customer needs and presents a solution and option to buy.

Use consumer behavior to assign a score to determine what kind of messaging to deliver and when. A higher engagement score means they’re more likely to buy and warrant additional messaging and calls to action. After your messaging campaign has been completed, review the results to determine efficacy and make improvements. With each interaction, your predictive model improves and you can further refine new audiences.

2. Consent-Based Marketing Using First-Party Data

It’s always polite to ask permission, and today it’s almost baffling that requesting access to data wasn’t always the norm. Enhance your current data collection process to incorporate as many opportunities for customers to provide explicit consent. When ingesting new customer information, add an opt-in checkbox for marketing messaging for each contact type. Give customers autonomy to choose email, text, or both, while setting expectations for frequency.

Leverage the data you collect from your website, app, and specific interactions to gain insights into user behavior and preferences. Use a customer relationship management platform to track interactions, including chat and abandoned cart data to refine messaging. Sync owned data to customer journeys and automations that present unique offers like discount codes for abandoned carts. Owned data can even help present upselling opportunities during checkout by offering can’t-miss deals on relevant products.

Craft your request with your customers’ aims in mind to improve the odds of agreeing to marketing messaging. A pet food retailer might request permission to provide customized product suggestions that your pet might love. Skincare retailers might facilitate reorder reminders for prior purchases, which can help ensure customers never run out of their favorites. Be transparent in how you collect and use customer data to build trust and long-term relationships with your audience.

3. Contextual Targeting

Some generalizations are reasonable to make, especially when grouping audience types and preferences. People visiting a site about training for a marathon are likely to be interested in the best shoes for long-distance running. This approach, called contextual targeting, involves aligning ads with site content versus user behavior or data. As one of the oldest strategies in the marketing book, it still has a place in your toolkit. As sites niche down and individual influencers refine their audiences, half of the work is already done for you.

Leverage site-provided data and statistics to determine which presents the right audience for your offer. Analyze the context of the content on the page to align messaging with individual posts and categories. Readers of a do-it-yourself site might respond well to marketing from a custom-blend paint retailer, especially if there’s a tutorial. Link your offer to color guides, videos, and examples that resonate with readers already engaged in DIY. 

By syncing up your offer alongside content users visit independently, you’re coexisting with their digital space. This way, your offer is relevant and has an increased likelihood of resulting in a sale and long-term relationship. Brands that do this will also convey respect for users’ privacy while effectively targeting customers by interest.

Embrace Alternative Tracking Methods and Respect Customer Privacy

The less reliant your strategies are on cookies, the more agile and effective your marketing efforts will be. By reducing your reliance on cookies, you’re building an owned knowledge base. Use alternative tracking methods like predictive analytics that you can refine and improve over time. Align strategies with industry data and forecasts, and invest in first-party data capabilities. 

Facilitate test groups to see which tools and approaches yield the greatest reward while respecting your customers’ digital privacy. Focus on delivering value to your customers, adjusting your messaging based on first-party data and customer feedback. When you do, you’ll reach and engage your customers authentically, maintain data privacy, and grow your business.