Maximizing advertising effectiveness with data-driven learning

Why marketers need a test-and-learn approach in ad measurement

Not long ago, advertisers relied on broad strokes and generalizations to reach their target audience. TV, print, and radio commercials were crafted based on demographic profiles, with advertising effectiveness measured by ratings and viewership.

However, digital advertising ushered in a new standard for precision and accountability. The advent of online platforms and social media networks armed advertisers with a wealth of new data. From clicks and impressions to conversion rates and engagement metrics, every online interaction offers valuable insights into consumer behavior and preferences that help to optimize brand experiences.

Today, as sands shift again and privacy controls limit Adland’s access to consumer data collected online (for example, popular browsers eliminating support for third-party cookies), marketers must again retool how they execute and evaluate campaigns. Here, we explore the value of data-driven learning programs in maximizing advertising effectiveness.

 

Why leverage data-driven learning for ad measurement?

Improve your targeting to increase ROI.

Reaching the right audience is paramount. In the past, advertisers cast wide nets, hoping to capture the attention of potential customers within broad demographic categories. Using granular consumer insights from a source like DISQO, along with data analytics and audience segmentation techniques allow you to pinpoint your target audiences with greater accuracy – and to target lookalike audiences. This ensures that your advertising efforts are directed toward those most likely to engage with them and ultimately buy your products or services.

Deliver more personalized brand experiences.

Consumers are inundated with advertising messages at every turn. To cut through the noise, you must deliver content that speaks to individual needs and preferences. This can come to life through dynamic ad creatives that adapt in real-time based on user interactions or personalized product recommendations that reflect past purchase history. Data-driven learning allows advertisers to tailor content to their target audience, increasing conversions and long-term loyalty.

Get more value our of your advertising dollars.

Tightened budgets and increased competition mean you need to ensure that every advertising dollar invested is worthwhile. Whether adjusting bid strategies in pay-per-click advertising or refining audience targeting in social media campaigns, data-driven optimizations ensure resources are allocated to channels and tactics that deliver the highest returns. This agile approach also allows advertisers to adapt to changing market conditions and consumer preferences. 

However, as you make these calculations, don’t forget about the long-term value of brand building for growth. Exclusive focus on performance metrics over lifts in brand metrics like awareness and preference is too short-term a view of campaign impact.

 

Building a data-driven learning program that delivers value

Not all data is created equal. Data from old campaigns, siloed data insights, and the resulting invalidated assumptions can impede a marketer’s efforts to continuously improve.  Below, we outline key characteristics defining a high quality dataset  for valuable campaign optimizations.

1. Single-source. Leveraging data from a hodgepodge of sources offers a disconnected view of the path-to-purchase. Consistency of source helps ensure each study is conducted with a similar audience, eliminating the risk of comparing apples in some studies to oranges in another.

2. Full-funnel. Ad measurement programs are often constrained by their overall breadth. Most legacy vendors rely solely on top-funnel attitudinal metrics to assess impact. Brand lift is critical, but a lack of unified visibility into behavioral impacts limits confidence in overall ROI. Combining Brand Lift with Outcomes Lift with DISQO gives you the most complete view of campaign value.

3. Cross-media. Most campaigns today are heavily focused on a cross-channel approach: social, digital, TV, and OOH. Identifying a partner that can measure the value of exposure in a fragmented digital environment provides a competitive edge.

 

How DISQO's clients use data-driven learning to drive ad effectiveness

With full-funnel, cross-channel data insights, DISQO clients have transformed their ad measurement programs into continuous learning opportunities.

 

Overall, we leverage DISQO’s findings for both in-flight optimization and post-campaign strategic work. And, our partnership expands beyond individual campaign measurement. We take a lot of the DISQO findings and incorporate them into measurement frameworks, test-and-learn agendas, and the meta analyses we do for big portfolio clients.

Teodora Scutelnicu Havas Media Network

 

Cross-platform analysis allows us to understand how different platforms work together in totality, but it’s also the only way that we can continue to help our clients optimize their campaigns. That’s where we can get better as an industry. We need a holistic view of the impact, and DISQO has been a big part of bringing those insights front and center.

David ShiffmaniHeartMedia

 

Data-driven learning with normative benchmarks

DISQO’s ad measurement benchmarks are setting a new standard for data-driven learning. Designed to help marketers discover what “good” looks like within a modern ad campaign, brands can test themselves against this standard and deliver increasingly impactful ad campaigns. Our 2024 Brand Lift & Outcomes Lift Industry Benchmarks just launched, click below to download!

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