
Centralized data access is emerging as a key strategy for advertisers. In our next Ask the Expert segment, we explore this topic further and discuss the importance of data ownership and the concept of audience as an asset.
We’re joined by industry leaders, Andy Fisher, Head of Merkury Advanced TV at Merkle, and Chris Feo, Experian’s SVP of Sales & Partnerships who spotlight Merkle’s commitment to centralized data access and how advertisers can use our combined solutions to navigate industry shifts while ensuring consumer privacy. Watch our Q&A to learn more about these topics and gain insights on how to stay ahead of industry changes.

The concept of audience as an asset
In order to gain actionable marketing insights about your audience, you need to identify consumers who are actively engaged with your brand and compare them against non-engaged consumers, or consumers engaged with rival brands.
Audience ownership
Audience ownership is a fundamental marketing concept where marketers build, define, create, and own their audience. This approach allows you to use your audiences as an asset and deliver a customized journey to the most promising prospects across multiple channels. With this strategy, you enhance marketing effectiveness and ensure ownership over your audience, no matter the platform or channel used.
Merkle enables marketers to own and deploy said asset (audience) so that marketers can have direct control over their audience. With audience strategy, you can tie all elements together – amplify your marketing reach, while maintaining control of your audience. Merkle connects customer experiences with business results.
Data ownership
Data ownership refers to the control organizations have over data they generate, including marketing, sales, product, and customer data. This data is often scattered across multiple platforms, making it difficult to evaluate their effectiveness. Alternatively, owning this data, which is typically housed in a data warehouse, allows the creation of historical overviews, forecasting of customer trends, and cross-channel comparisons. With advertisers and publishers both claiming ownership over their respective data and wanting to control its access, there has been a growing interest in data clean rooms.
Data clean rooms
The growing interest in data clean rooms is largely due to marketers increasing preference to maintain ownership over their audience data. They provide a secure environment for controlled collaboration between advertisers and publishers while preserving the privacy of valuable data. Data clean rooms allow all parties to define their usage terms – who can access it, how it is used, and when it is used. The rise in the use of data clean rooms strengthens data privacy and creates opportunities for deeper customer insights, which leads to enhanced customer targeting. Data clean rooms unlock new data sets, aiding brands, publishers, and data providers in adapting to rapidly changing privacy requirements.
Why is centralized data access important?
Centralized data access is crucial for the effective organization and optimization of your advertising campaigns. It involves consolidating your data in one place, allowing for the identification of inconsistencies.
Merkle’s Merkury platform
The concept of centralized data is a key component of Merkle’s Merkury platform, an enterprise identity platform that empowers brands to own and control first-party identity at an individual level. A common use case involves marketers combining their first-party data with Merkury’s data assets and marketplace data assets to build prospecting audiences. These are later published to various endpoints for activation.
The Merkury platform covers three classes of data:
- Proprietary data set – Permissioned data set covering the entire United States, compiled from about 40 different vendors
- Marketplace data – Includes contributions from various vendors like Experian
- First-party data from marketers – Allows marketers to bring in their own data
Merkury’s identity platform empowers brands to own and control first-party identity at an individual level, unifying known and unknown customer and prospect records, site and app visits, and consumer data to a single, person ID. This makes Merkury the only enterprise identity platform that combines the accuracy and sustainability of client first-party data, quality personally identifiable information (PII) data, third-party data, cookie-less media, and technology platform connections in the market.
End-to-end management of data
Data ownership and management enables you to enhance the quality of your data, facilitate the exchange of information, and ensure privacy compliance.
The Merkury platform provides a comprehensive, end-to-end solution for managing first-party data, all rooted in identity. Unlike data management platforms (DMPs) that are primarily built on cookies, the Merkury platform is constructed on a person ID, allowing it to operate effectively in a cookie-free environment.
A broader perspective with people-based views
The Merkury platform is unique because it contains data from almost every individual in the United States, providing a broader perspective compared to customer data platforms (CDPs) which only contain consumer data. The platform provides a view of the world in a people-based manner, but also offers the flexibility to toggle between person and household views. This enables you to turn data into actionable insights and makes it possible to target specific individuals within a household or consider the household as a whole.
How Experian and Merkle work together
Experian and Merkle have established a strong partnership that magnifies the capabilities of Merkle’s Merkury platform. With Experian’s robust integration capabilities and extensive connectivity opportunities, customers can use this technology for seamless direct integrations, resulting in more effective onboarding to various channels, like digital and TV.
“Experian’s role in Merkury’s data marketplace is essential as they are considered the gold standard for data. It significantly contributes to our connectivity through direct integrations and partnerships. Experian’s presence in various platforms and technologies ensures easy connections and high match rates. Our partnership is very important to us.”
andy fisher, head of merkury advanced tv
Through this partnership, Merkle can deliver unique, personalized digital customer experiences across multiple platforms and devices, highlighting their commitment to data-driven performance marketing.
Watch the full Q&A
Visit our Ask the Expert content hub to watch Andy and Chris’s full conversation about data ownership, innovative strategies to empower you to overcome identity challenges, and navigating industry shifts while protecting consumer privacy.
Tune into the full recording to gain insights into the captivating topics of artificial intelligence (AI), understanding how retail networks can amplify the value of media, and the growing influence of connected TV (CTV). Dive into the Q&A to gain rich insights that could greatly influence your strategies.
About our experts

Andy Fisher, Head of Merkury Advanced TV
As the Head of Merkury Advanced TV, Andy’s primary responsibility is driving person-based marketing and big data adoption in all areas of Television including Linear, Addressable, Connected, Programmatic, and X-channel planning and Measurement. Andy has held several positions at Merkle including Chief Analytics Officer and he ran the Merkle data business. Prior to joining Merkle, Andy was the EVP, Global Data & Analytics Director at Starcom MediaVest Group where he led the SMG global analytics practice. In this role, he built and managed a team of 150 analytics professionals across 17 countries servicing many of the world’s largest advertisers. Prior to that role, Andy was Vice President and National Lead, Analytics at Razorfish, where he led the digital analytics practice and managed a team of modeling, survey, media data, and business intelligence experts. He and his team were responsible for some of the first innovations in multi-touchpoint attribution and joining online/offline data for many of the Fortune 100. Andy has also held leadership positions at Personify and IRI. Andy holds a BA in mathematics from UC Berkeley and an MA in statistics from Stanford.

Chris Feo, SVP, Sales & Partnerships, Experian
As SVP of Sales & Partnerships, Chris has over a decade of experience across identity, data, and programmatic. Chris joined Experian during the Tapad acquisition in November 2020. He joined Tapad with less than 10 employees and has been part of the executive team through both the Telenor and Experian acquisitions. He’s an active advisor, board member, and investor within the AdTech ecosystem. Outside of work, he’s a die-hard golfer, frequent traveler, and husband to his wife, two dogs, and two goats!
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Study reveals that brands with more mature identity programs were significantly more likely to be successful in achieving their key objectives Tapad, a part of Experian, a global leader in cross-device digital identity resolution and a part of Experian, has commissioned Forrester Consulting, part of a leading research and advisory firm, to conduct a new study that evaluates the current state of customer data-driven marketing and explores how marketers can use identity solutions to deliver privacy safe and engaging experiences, in an evolving data landscape. The study highlights the changing ground rules for digital marketing and the threat that poses to marketers’ ability to deliver against long standing KPIs and campaign goals. Nearly two-thirds (62%) of respondents said that the forces of data deprecation will have a significant (40%) or critical (21%) impact on their marketing strategies over the next two years. Among those surveyed, identity resolution strategies have surfaced as an opportunity to create more powerful customer experiences, with 66% aiming to have it help improve customer trust and implement more ethical data collection and use practices, while nearly 60% believe it will point the way to more effective personalization and data management practices. Although organizations are eager to implement identity resolution strategies, a complex web of solutions and partners makes execution a challenge. For example, respondents report using at least eight identity solutions on average, across nearly six vendor partners, and they expect that fragmentation to persist in the ‘cookieless’ future. Additionally, brands’ identity resolution technologies typically represent a patchwork of homegrown and commercial solutions. Eighty-one percent of respondents use both in-house and commercial identity resolution tools today, and 47% use a near-equal blend of the two. Despite the challenges, many brands have the foundation for a strong identity resolution strategy in place, and they are thriving as a result. Specifically, more mature brands were 79% more successful at improving privacy safeguards to reduce regulatory and compliance risk, 247% more successful at improving marketing ROI, and over four times more effective at improving customer trust compared to their low-maturity peers. Additional insights include: Marketers Are Increasingly Playing a Key Strategic Role Within the Organization, But There is a Mandate to Demonstrate Value. Nearly three-quarters of respondents in our study agree the marketing function is more strategically important to their organization than it used to be, while almost two-thirds agree there’s more pressure than ever to prove the ROI or business performance of their activities. Consumers Expect Brands to Deliver Engaging Experiences Across Highly Fragmented Journeys: Tapad, a part of Experian found that 72% of respondents agree that customers demand more relevant, personalized experiences at the time and place of their choosing. At the same time, 67% of respondents recognize that customer purchase journeys take place over more touchpoints and channels than ever, and 59% of respondents agree that those journeys are less predictable and linear than they once were. Marketing Runs on Data, But the Rules Governing Customer Data Usage are Ever-Evolving: According to the study, 70% of decision-makers agree that consumer data is the lifeblood of their marketing strategies – fueling the personalized, omnichannel experiences customers demand. At the same time, 69% of respondents recognize that customers are increasingly aware of how their data is being used. At least two-thirds agree that data deprecation, including tighter restrictions on data use (66%), as well as operating system and browser changes impacting third-party cookies (68%) means that legacy marketing strategies are unlikely to remain viable in the long-term.“ Our latest survey findings give us a better understanding of how our customers and other companies around the world are trying to master the relationship between people, their data and their devices,” said Mark Connon, General Manager at Tapad, a part of Experian. “This research shows why it's fundamental for the industry to continuously work to develop solutions that are agnostic. Tapad, a part of Experian has worked tirelessly to deliver on this with our Tapad Graph, and by introducing solutions like Switchboard to help the evolving ecosystem and in turn helping customers reap the benefits of better identity in both short and long-term.” The study is founded on an online survey of over 300 decision-makers at global brands and agencies, which was fielded from March to April, 2021. Data deprecation and identity are fast-developing, moving targets, so this study delivers targeted insights and recommendations for how to prepare for coming shifts in customer data strategies – whether they manifest tomorrow or a year from now. Get started with The Tapad Graph For personalized consultation on the value and benefits of The Tapad Graph for your business, email Sales@tapad.com today!

Marketers are always challenged to expand sales beyond “business as usual,” while being good stewards of company resources spent on marketing. Every additional dollar spent on marketing is expected to yield incremental earnings—or else that dollar is better spent elsewhere. You must be able to determine return on advertising spend (ROAS) for any campaign or platform you add to your marketing mix. A key driver of positive ROAS is incremental customer actions produced by ad exposure. Confident, accurate measurement of incremental actions is the goal of an effective testing program. Why do we test campaign performance? Because demonstrating incremental actions from a campaign is a victory. You can keep winning by doing more of the same. Not finding sufficient incremental actions is an opportunity to reallocate resources and consider new tactics. Uncertainty whether the campaign produced incremental actions is frustrating. Ending a profitable marketing program because incremental actions were not effectively measured is tragic. Test for success When you apply rigorous methods to test the performance of campaigns, you can learn to make incremental improvements in campaign performance. The design of a marketing test requires the following: Customer Action to be measured during the test. This action indicates a recognizable step on the path to purchase: awareness, evaluation, inquiry, comparison of offers or products, or a purchase. Treatment, i.e., exposure to a brand’s ad during a campaign. Prediction regarding the relationship between action and treatment (e.g., Ad exposure produces an increase in purchase likelihood). Experimental design is the structure you will create within your marketing campaign to carry out the test. Review of results and insights. Selecting a customer action to measure Make sure that the customer action you measure in your test is: Meaningful to the campaign’s goal. What is the primary goal of the campaign? Is it brand awareness? Web site visits? Inquiries? Completed sales? An engagement by the customer. Your measurement should capture meaningful, deliberate interaction of consumers with the brand. Attributable to advertising. There should be a reasonable expectation that ad exposure should increase, or perhaps influence the nature of customer actions. Abundant in the data. Customer action should be a) plentiful and b) have a high probability of being recorded during the ad campaign (in other words, a high match rate between actions and the audience members). Selecting campaign treatments It is best for treatments to be as specific as possible. Ad exposures should be comparable with respect to: brand and offer, messaging, call to action, and format. Making a prediction This is the “hypothesis.” Generally, you assume that exposure to advertising will influence customer actions. To do this, you need to reject the conclusion that exposure does NOT affect actions (the “null hypothesis”). Elements of an experimental design An attribution method that links each audience to their purchase action during the test. This consists of a unique identifier of the prospect which can be recognized both in records of the audience and records of the measured action during the measurement period. A target audience that receives ad exposure. A control audience that does not receive ad exposure. It provides a crucial baseline measurement of action against which the target audience is compared. Time boundaries for measurement, related to the treatment: Pre-campaign Campaign Post-campaign Randomly selected audiences (recommended) Some audience platforms, such as direct mail and addressable television operators, feature the ability to select distinct audience members in advance. Randomly selected audiences can generally be assumed to be similar in all respects except ad exposure. The lift of the action rate is simple to calculate: Campaign Lift = (Action Rate (target) / Action Rate (control)) -1 Non-randomly selected audiences are more difficult, but still possible, to measure effectively. There may be inherent biases between them that may or may not be obvious. To measure campaign performance, we must first account for any pre-existing differences in customer actions, and then adjust for these when measuring the effect of ad exposure. Typically, the pre-campaign period (and possibly the post-campaign period as well) are used to obtain a baseline comparison of actions between the two audiences. This is a “difference of differences” measurement: Baseline lift = (Action Rate (target) / Action Rate (control)) -1 Campaign Lift = (Action Rate (target) / Action Rate (control)) -1 Net campaign lift (advertising effect) = Campaign Lift – Baseline Lift Analyzing results and insights How large is the lift? This is generally expressed as a percentage increase in action rate for the target audience vs. the control audience. Are we confident that the lift is real, and not just random noise in the data? This question is answered with the “confidence level.”. 95% confidence means the probability of a “true positive” result is 95%; and the probability of a “false positive” due to random error is 5%. What was the campaign cost per incremental action? If you also know the expected revenue from each incremental action, you can project out incremental revenue, from which you can calculate return on ad spend. Other insights: Do the results make directional sense (we would hope that ad exposure will cause an increase in customer actions, not a decrease)? Does action rate generally increase with the number of ad exposures? Summary Well-designed testing and measurement practices allow you to learn from individual advertising campaigns to improve decision-making. The ability to draw confident conclusions from campaigns will allow experimentation with different strategies, tactics, and communication channels to maximize performance. These test-and-learn strategies also enhance your ability to adjust to marketplace trends by monitoring campaign performance. To learn how Experian’s solutions can help you measure the success of your marketing campaigns, watch our short video, or explore our measurement solutions.

It’s almost that time of the year again, the time to put away fourth of July merchandise and replace it with this year's favorite superhero backpacks. It’s almost back-to-school season, and parents and kids from kindergarten to college are preparing for school's "new normal." To navigate the challenge of 2021, Experian’s Marketing Analytics team is sharing Back-to-School shopping season insights with you. Download the eBook to learn more. Our outlook about this year's Back-to-School shopping season can help you better plan and improve your marketing effectiveness. The report covers who's actively shopping for school supplies, whether they're shopping in-person or online, and what they're buying this year. Here's a summary of what you'll learn in the report: Who (specifically) is shopping for back-to-school supplies this year? More than half of online searches related to Back-to-School were made by a small set of consumer segments. We’ve identified 4 Mosaic® groups as being in-market for back-to-school merchandise. To find these types of consumers, we used online behavioral data and filtered for households with school-age children between 5 and 15 years old. Each group, such as Flourishing Families, share similar shopping behaviors and needs. While each group of consumers has a need for Back-to-School merchandise, they have different circumstances that require more personalized marketing. Let's break down each Mosaic® group to better understand their size and key features so that you can build more personalized messaging. Contact us for segments and insights specific to your brand. Power Elite As you can see in our Mosaic® product brochure, Power Elite is categorized as Group A. This is the largest group analyzed in the report, accounting for 4.5 million U.S. households. Here are the Power Elite consumer types actively shopping for back-to-school merchandise this year: A01: American Royalty A03: Kids and Cabernet A04: Picture Perfect Families Key Features: Wealthy Highly Educated Politically conservative Purchase housewares and electronics in store Vacation and fitness retail influencers Luxury lease cars Flourishing Families Also called Group B in this report, Flourishing Families is comprised of 3.7 million U.S. households. Active consumer types: B07: Across the Ages B08: Babies and Bliss B09: Family Fun-tastic Key Features: Affluent Charitable contributors Athletic activities High-priced children’s clothing Home products & furnishings Sporting good Suburban Style Suburban Style, also Group D, is made up of 2.9 million U.S. households. Active consumer types: D15: Sport Utility Families D16: Settled in Suburbia Key Features: Comfortable lifestyle Ethnically diverse Politically diverse Instagrammers Children’s games Wholesale members Family Union The Family Union group, Group I, is the smallest of those analyzed in this report, but still a respectable size: 1.2 million U.S. households. Active consumer types: I31: Hard Working Values Key Features: Bilingual Married with kids Large households Hunting clothing Automotive tools Will they shop online or in stores? Prepare for a return to in-store shopping as the US moves post-pandemic. These consumers have shopped in-store for Back-to-School and have trended toward in-store shopping as the vaccine was distributed. Mobile location data shows these consumers actively shopped in-person during the 2019 Back-to-School season, and are shopping in-person again post-pandemic. Experian analyzed consumer mobile location data for big box retailers, department stores, malls and apparel-accessory stores since June 2019. The aggregated number of visits was indexed each month against 12-month average of that respective year. An index higher than 100 indicates shopping behavior that month was higher than the average of that year. An index less than 100 indicates shopping behavior that month was less than the average of that year. Planning store layouts and inventory will be more important this year for marketers as consumers return to the stores for Back-to-School shopping needs. What will they buy? Plan for Back-to-School product composition to be like pre-pandemic while you plan your inventory. Keep an eye on local outbreak risk which dictates whether school districts will pivot to remote learning. Product composition during the 2020 Back-to-School season was skewed away from apparel and towards virtual learning materials, such as home office supplies and technology, but should revert to pre-pandemic behaviors. Using ConsumerViewTM Transactional data, we compared consumer product composition during the 2019 and 2020 back-to-school shopping seasons. Children’s Apparel and Accessories: share was smaller in 2020, and was a more dramatic impact for Groups A, B, and D. Books: Groups B and D saw an increased share in 2020, but Groups A and I saw little change. Home Office: share was greater in 2020 for all groups, particularly Group A. Computers: share was greater in 2020 for all segments, particularly Group I Want to learn more? Improve your marketing ROI and grow your business during back-to-school season using Experian’s new Discovery Platform. No sign-up required: watch the demo to learn how retailers like you can use The Discovery Platform™ to track online versus in-store shopping and safely navigate evolving back-to-school consumer behaviors.