5 Ways Predictive Audiences Improves Performance

Look at five ways that predictive audiences can enhance performance

The ability to drive better performance in advertising campaigns has never been more vital for success. Particularly as brands hit the point of audience saturation within relied-upon social channels, they need new and reliable ways of finding new and relevant audiences likely to be interested in their products and services. 

As privacy regulations tighten and third-party cookies disappear, marketers must adopt new methods and technology to find their audiences online. One of the most promising solutions in this regard is the use of predictive audiences.

Predictive audiences employ advanced analytics and machine learning to forecast the behavior of potential customers based on accumulated data. This approach not only adheres to new privacy standards but also provides a more nuanced understanding of customer behaviors and preferences. 

Let’s look at five ways that predictive audiences can enhance performance in advertising campaigns.

Targeting Efficiency

Predictive audiences help marketers to pinpoint the segments of the market that are most likely to respond positively to their campaigns. This improved targeting efficiency ensures that marketing efforts are not wasted on uninterested parties, thereby increasing the overall ROI of advertising campaigns.

For example, a luxury car brand might use predictive modeling to analyze online behaviors of past car purchasers and then identify potential buyers most likely to buy, perhaps based on factors like recent high-value purchases, interest in luxury goods, and financial demographic data. By focusing their digital ads on the select group of people deemed most likely to buy, rather than a broader, less targeted audience, the brand can achieve higher engagement rates and a better conversion ratio.

Budget Optimization

With predictive audiences, marketers can more accurately predict which campaigns are likely to yield the best returns, allowing for smarter allocation of budgets. This optimization of spending not only saves money but also boosts the effectiveness of campaigns.

For example, a software company could use predictive analytics to determine which users are most likely to upgrade to a premium account based on usage patterns and engagement with the product. By targeting these users with specific upgrade promotions, the company can allocate its advertising budget more effectively, focusing on high-potential customers rather than a general audience.

Improved Customer Retention

Predictive audiences can also help improve customer retention rates by identifying at-risk customers before they churn. Proactive engagement with these customers can prevent them from leaving and thus maintain the revenue stream they represent.

For example, a mobile phone service provider could use predictive analytics to identify customers who may be at risk of switching to a different carrier. By analyzing data points such as call drop rates, complaint history, changes in usage patterns, and billing issues, the provider can predict dissatisfaction before customers cancel their service. To address concerns and retain these at-risk customers, the provider might reach out to these targeted audiences with personalized communications offering tailored solutions, such as a better suited plan with more data or improved call quality, exclusive discounts, or one-on-one customer service calls to resolve any ongoing issues. By proactively addressing the factors contributing to customer dissatisfaction, the company can significantly reduce churn and enhance overall customer loyalty.

Measuring Campaign Effectiveness

Finally, predictive audiences can contribute to a more accurate measurement of campaign effectiveness. By understanding which audience segments are most responsive, marketers can continuously refine their strategies and improve their future campaigns to replicate this responsiveness.

For example, a cosmetics brand launching a new skincare line might use predictive analytics to target its campaign toward audiences that the data suggest are more likely to be interested in similar products. By analyzing the engagement levels and purchase rates within these predictive segments, the brand can measure the impact of its campaign more precisely and adjust its approach for future launches.

Bridging the Gap Left by Third-Party Cookie Deprecation

Finally, let’s talk about how important predictive audiences are becoming in the wake of Google’s deprecation of third-party cookies in Chrome. As this traditional means of targeting audiences and evaluating cross-channel campaign performance disappears from the landscape, predictive audiences are proving to be far more effective at driving campaign performance than other third-party targeting tactics. 

For example, Nativo's proprietary solution, SPARC, powered by Nativo Predictive Audiences, consistently outperforms contextual and third-party targeting. The solution achieves 2x greater click-through rate (CTR), 2x greater click-through conversions (CTC), and up to 50 percent lower cost-per-acquisition (CPA). With SPARC—a proprietary, privacy-compliant cookieless technology—brands can leverage off-the-shelf predictive audiences or build a custom predictive audience using seed data derived solely from their campaign data.

Recently, a leading pharmaceutical brand sought to provide education to heart failure patients and their caregivers about their condition and how their pharmaceutical brand could help. Pharmaceutical campaigns must typically rely on expensive third-party segments, which use cookie-based targeting and are hard to scale. Knowing it’s hard to make real-time adjustments to reach the target audience during the campaign, Nativo incorporated SPARC to scale the pharmaceutical brand’s content to non-cookied environments in a privacy-compliant way to reach and expand the audience. As a result, custom-built predictive audiences—built from seed data derived solely from the pharmaceutical brand’s historical campaign data—increased CTR by 104 percent and decreased CPC by 73 percent compared to the leading third-party data providers.

As the marketing world adapts to a future without third-party cookies, predictive audiences offer a powerful tool for enhancing performance. By enabling more precise targeting, budget optimization, and effective retention strategies, predictive audiences allow marketers to not only survive but thrive in this new environment.


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