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Artificial intelligence (AI) and connected TV (CTV) have a perfect synergy that’s revolutionizing how advertisers connect with their audiences. CTV serves as a medium for streaming content, while AI acts as a sophisticated technology that improves the performance of CTV advertising campaigns. The integration of these two technologies has paved the way for advertisers to reach their target audience more effectively, making CTV advertising a powerful and efficient tool.
In this blog post, we’ll dive into how these technologies work together — and why you should jump on board with AI for CTV advertising if you haven’t already.
Why AI and CTV are a great match
CTV and AI are transforming how advertisers connect with their audiences and improving the performance of their advertising campaigns in the CTV space. They work together to make advertising smarter and more enjoyable for everyone involved. AI uses sophisticated computer programs to analyze and understand data, while CTV refers to the streaming services that consumers use at home. But what makes them a great match in advertising?
AI uses data to determine which TV ads are most exciting and relevant to certain people, and it can even adjust ads in real time to ensure viewers are always getting the most personalized experience. AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next. To sum it up, AI allows for:
- Precise targeting: AI uses data to determine which TV ads are most exciting and relevant to certain people.
- Personalization: AI can adjust ads in real time to ensure viewers are always getting the most personalized experience.
- Effective ad insertion: AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next.
CTV facilitates these AI-driven strategies for enhanced user engagement and satisfaction.
The rising popularity of CTV
CTV has become increasingly popular as people change the way they watch TV. Instead of the traditional approach, more viewers are now choosing CTV platforms for their entertainment. One of the main reasons for this shift is that CTV offers greater flexibility and lets viewers watch content at their convenience. The ability to skip ads on many CTV platforms also improves the experience.
CTV offers a great opportunity to interact with your target audience in a more engaging way. CTV allows for highly targeted advertising capabilities so you can reach specific demographics and households with tailored messages. Additionally, CTV provides valuable data insights that enable you to measure campaign effectiveness accurately.
If you haven’t embraced this advertising channel yet, you may be missing out on a growing and engaged audience. Here are three reasons you should add CTV to your advertising strategy.
Global video ad impressions
As a global platform, CTV has the unique ability to reach audiences worldwide. Unlike traditional TV, CTV transcends geographical boundaries and brings marketers a global audience, which makes it an ideal channel for global ad campaigns. No matter your target audience, they’re consuming content on CTV. In fact, a recent study showed that 51% of global video ad impressions came from CTV in 2022.
This abundance of global video ad impressions generates vast amounts of data, which AI can process in real time to help you make data-driven decisions and optimize your campaigns for diverse international audiences. AI can analyze viewer data from various regions, identify audience preferences and behaviors across borders, and tailor ad content accordingly. These data analysis capabilities ensure your ads get in front of the right viewers.
Viewers prefer ad-supported CTV
In 2020, the viewing time of ad-supported CTV surged by 55% while subscription video on demand decreased by 30%, according to TVision Insights. Viewers have a well-established preference for ad-supported CTV due, in part, to cost-effective access to premium content. Viewers are more engaged and less resistant to ads, as AI tailors ad content to viewer preferences and behavior to enhance ad relevance.
AI-powered insights can also aid in viewer retention and help you optimize your CTV campaigns. By accommodating viewers’ preference for ad-supported CTV and harnessing AI to improve the ad experience, you’re more likely to be successful in your marketing efforts.
CTV outpaces mobile and desktop for digital video viewing
eMarketer recently reported that U.S. adults spend 7.5+ hours each day on CTV — more than half of their digital video viewing time. Comparatively, they only spend 37.5% of their viewing time on mobile and 10% on desktops and laptops. These statistics demonstrate that CTV has become the preferred platform for digital video consumption, as viewers enjoy larger screens with superior quality for an immersive experience.
It’s important to note that AI is an essential CTV marketing tool, as it allows for precise targeting and content optimization. By utilizing AI on CTV, you can take advantage of this trend and deliver more engaging and effective campaigns to a growing and engaged audience.
How is AI already being used in CTV?
CTV has been integrated with AI across various facets and has revolutionized the television landscape. Here’s a look at how AI is already shaping the CTV experience:
Generative AI ads
Generative AI ads are taking CTV personalization to a whole new level. These innovative ads are customized versions of the same CTV ad to suit individual viewers. Some AI tools can generate several versions of the same CTV ad — swapping the actor’s clothing and voiceover elements like store locations, local deals, promo codes, and more — and can create up to thousands of personalized iterations in just a few seconds. Such capabilities are a game-changing approach to connecting with your audience.
Next, we dive into the advantages and impact of generative AI ads, and explore their transformative role in CTV advertising.
Contextual ads vs personal data
Generative AI ads use personal data, such as viewing history and demographics, to create highly personalized ad experiences. This sets them apart from contextual ads, which rely solely on the content being viewed. Using AI to harness this data, you can move beyond traditional contextual targeting and ensure your ads connect with viewers on a more individualized level.
Generative AI ads can be used to A/B test
Generative AI ads are not just about personalization; they also open the door to A/B testing. Being able to create several versions of one ad quickly allows you to experiment with various ad elements, such as messaging, visuals, and calls to action, to identify what works best for different segments of your audience and drives the best performance. This flexibility is especially valuable for refining ad campaigns and maximizing their impact.
What’s next for AI-generated ads like this?
The potential of AI-generated ads is exciting. As AI technologies constantly advance, we can expect even more personalized and automated CTV advertising. It’s a good idea to keep up with the latest AI-driven innovations to create more effective ad campaigns in the fast-evolving CTV space. The possibilities are endless, and you’ll likely find the most success when you embrace AI in CTV advertising.
Optimize streaming quality
AI helps viewers enjoy more seamless CTV experiences. By assessing network speed and user preferences, AI optimizes video quality in real time to reduce buffering interruptions. For instance, streaming platforms use AI to adjust video settings based on a user’s connection speed. This guarantees an uninterrupted and enjoyable viewing experience.
Review content for compliance
AI also has a part to play in quality assurance and compliance management. It assesses content alignment with technical parameters and moderates compliance with local age restrictions and privacy regulations. This means AI can identify and filter out unsuitable content to provide a safer and more enjoyable viewing environment for audiences while safeguarding brands from association with undesirable material.
Voice command
AI-powered voice command technology is increasingly used to control CTV viewing. This technology is embedded in streaming devices and smart TVs and allows viewers to interact with their CTV content through voice-activated commands. This personalizes the viewing experience and improves convenience, as it eliminates the need for remote controls.
CTV-integrated voice assistants like Google Assistant, Amazon Alexa, Apple Siri, and Samsung Bixby offer a more human-like interaction with the television, allowing users to give commands and receive tailored responses.
Content recommendations
AI can offer content recommendations that provide viewers a more personalized and engaging experience. Major over-the-top (OTT) services like Netflix, Hulu, and Amazon Prime use AI-driven data analysis to deliver tailored content suggestions to their audiences. By analyzing user habits in detail, AI can recommend content based on factors such as actors, genres, reviews, and countries of origin. This personalized approach helps viewers discover content that matches their preferences and enhances their viewing experience.
Advertising
Programmatic ad buying, driven by AI, automatically matches ad placements to specific audience segments based on behavioral patterns. It improves ad delivery by moving away from gross rating points (GRP) to more intelligent and targeted placements. This benefits marketers by ensuring ads are seen by the right people at the right time. It’s also cost-effective for publishers, as it maximizes the sale of ad spots to suitable buyers.
Automatic content recognition (ACR) technology, which AI powers, is integrated into smart TVs and streaming devices to improve ad relevance. It provides contextual targeting and extends the reach of ads across multiple devices. For example, platforms like Roku use ACR data to display ads to viewers who haven’t seen them on traditional TV. Similarly, Samba TV retargets mobile users based on IP address and aligns their viewing habits with their smart TVs.
Demand-side platforms
CTV advertising relies heavily on demand-side platforms (DSPs) to efficiently manage and optimize ad campaigns. These platforms use machine learning and AI in several important ways:
Using machine learning and AI to address data fragmentation
Data is abundant but fragmented when it comes to CTV advertising. DSPs are flooded with a massive amount of data, including information about households, viewer behavior, and viewing patterns. This data is far too much for manual analysis to handle effectively, which is where AI comes in.
By integrating machine learning algorithms into DSPs, AI can harmonize this fragmented data and provide valuable insights and a holistic view of your audience. AI can process zettabytes of data in real time, which streamlines the decision-making process and empowers you to compete quickly for limited CTV impression opportunities.
Predicting advertising outcomes with AI
AI is quickly changing the way we predict and optimize advertising outcomes. TV buying and optimization platforms are now using AI to improve ad performance. With machine learning, these platforms can anticipate which ad creatives will produce the best results based on various non-creative factors. These include the context of the ad, the audience’s profiles, the time of day it is displayed, and the frequency of the ad display.
By relying on AI to make these predictions, you can make sure your campaigns are highly optimized for success and deliver more relevant, compelling ads to viewers.
Optimizing generative ads
AI is also driving optimization in generative ads. These personalized versions of the same CTV ad can be tailored to suit individual viewers. By utilizing AI-driven analytics, DSPs can process extensive amounts of data in real time and optimize generative ads to ensure they align with viewers’ preferences and behaviors. This level of personalization is a game-changer in CTV advertising that boosts engagement and delivers content that truly resonates with the audience.
Add AI to your CTV strategy today
Integrating AI into your CTV strategy can help you stay competitive and ensure your ad campaigns are effective and engaging.
At Experian, we’re ready to help you elevate your CTV advertising and implement AI as part of your strategy. Our solutions, such as Consumer View and Consumer Sync, provide valuable audience insights, enhance targeting capabilities, and optimize engagement on TV. Plus, our partnerships with leading media marketing solutions can help you achieve greater success through effective advanced television advertising.
As you incorporate AI into your CTV strategy, you’ll be able to make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Explore Experian’s TV solutions and empower your CTV advertising with AI today.
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The cookieless future is here, and it's time to start thinking about how you will adapt your strategies to this new reality. In a cookieless world, you will need to find new ways to identify and track users across devices. This will require reliance on first-party data, contextual advertising, and alternative identifiers that respect user privacy. To shed light on this topic, we hosted a panel discussion at Cannes, featuring industry leaders from Cint, Direct Digital Holdings, the IAB, MiQ, Tatari, and Experian. In this blog post, we'll explore the future of identity in cookieless advertising. We'll discuss the challenges and opportunities that this new era presents, and we'll offer our tips for how to stay ahead of the curve. How cookieless advertising is evolving Programmatic advertising is experiencing multiple changes. Let's dive into three key things you should know. Cookie deprecation One significant change is cookie deprecation, which has implications for tracking and targeting. Additionally, understanding the concept of Return on Advertising Spend (ROAS) is becoming increasingly crucial. The demand and supply-side are coming closer together Demand-side platforms (DSPs) and supply-side platforms (SSPs) have traditionally been seen as two separate entities. DSPs are used by advertisers to buy ad space, while SSPs are used by publishers to sell ad space. However, in recent years, there has been a trend toward the two sides coming closer together. This is due to three key factors: The rise of header bidding Header bidding is a process where publishers sell their ad space to multiple buyers in a single auction. This allows publishers to get the best possible price for their ad space, and it also allows advertisers to target their ads more effectively. Cookie deprecation As third-party cookies are phased out, advertisers need to find new ways to track users, and they are turning to SSPs for help. SSPs can provide advertisers with data about users, such as their demographics and interests. This data can be used to target ads more effectively. The increasing importance of data Advertisers are increasingly looking for ways to target their ads more effectively, and they need data to do this. SSPs have access to a wealth of user data, and they're willing to share this data with advertisers. This is helping to bridge the gap between the two sides. The trend toward the demand-side and supply-side coming closer together is good news for advertisers and publishers. It means that they can work together to deliver more relevant ads to their users. Measuring and tracking diverse types of media The media measurement landscape is rapidly evolving to accommodate new types of media, such as digital out-of-home (DOOH). With ad inventory expanding comes the challenge of establishing identities and connecting them with what advertisers and agencies want to track. Measurement providers are now being asked to accurately capture instances when individuals are exposed to advertisements at a bus stop in New York City, for example, and tracking their journey and purchase decisions, such as buying a Pepsi. To navigate cookieless advertising and measurement, we must prioritize building a strong foundational identity framework. What you should focus on in a cookieless advertising era In a cookieless advertising era, you will need to focus on two key things: frequency capping and authentic identity. Frequency capping Frequency capping is a practice of limiting the number of times an ad is shown to a user. This is important in cookieless advertising because it helps to prevent users from being bombarded with ads. It also helps to ensure that ads are more effective, as users are less likely to ignore or click on ads that they have seen too many times. Frequency capping is often overhyped and yet overlooked. Instead of solely focusing on frequency, consider approaching it from an identity perspective. One solution could be to achieve a perfect balance between reaching a wider audience and avoiding excessive repetition. By increasing reach in every programmatic buy, you naturally mitigate frequency control concerns. Authentic identity The need for authentic identities in a digital and programmatic ecosystem is undeniable. While we explore ways to connect cookies, mobile ads, and other elements, it's crucial to remember who we are as real individuals. By using anonymized personal identifying information (PII) as a foundation, we can derive insights about households and individuals and set effective frequency caps across different channels. Don't solely focus on devices and behaviors in your cookieless advertising strategy and remember the true value of people and their identities. What’s next for cookieless advertising? The deprecation of third-party cookies is a major challenge for the digital advertising industry. Advertisers will need to find new ways to track users and target their ads. Here are three specific trends that we can expect to see in cookieless advertising. First-party data is moving in-house Many major media companies, equipped with valuable identifier and first-party data, are choosing to bring it in-house. They are focused on using their data internally rather than sharing it externally. "Many larger media companies are opting to bring their identifier and first-party data in-house, creating more walled gardens. It seems that companies are prioritizing data control within their own walls instead of sharing it externally."laura manning, svp, measurement, cint Fragmentation will continue The number of identifiers used to track people online is growing rapidly. In an average household, over a 60-day period, there are 22 different identifiers present. This number is only going to increase as we move away from cookies and toward other identifiers. This fragmentation makes it difficult to track people accurately and deliver targeted advertising. This means that we need new identity solutions that can help make sense of these new identifiers and provide a more accurate view of people. A portfolio of solutions will address signal loss Advertisers are taking a variety of approaches to cookieless advertising. A few of the solutions include: Working with alternative IDs. This refers to using alternative identifiers to cookies, such as mobile device IDs or email addresses. These identifiers can be used to track people across different websites and devices, even without cookies. Working with data index at a geo level. This refers to using data from a third-party provider to get a better understanding of people's location. This information can be used to target ads more effectively. Working with publisher first-party data that's been aggregated to a cohort level. This refers to using data that is collected directly from publishers, such as website traffic data or purchase history. This data can be used to create more personalized ads. Working with contextual solutions. This refers to using contextual data, such as the content of a website or the weather, to target ads. This can help to ensure that ads are relevant to the user's interests. "Cookie deprecation is often exaggerated, and alternate solutions are already emerging. As data moves closer to publishers and first-party data gains prominence, the industry will adapt to the changes."mark walker, ceo, direct digital holdings There is no one-size-fits-all solution for cookies, and you will need to be flexible and adopt a variety of different approaches. How will these solutions work together? You can take a waterfall approach to cookieless advertising. A waterfall approach is a process where advertisers bid on ad impressions in sequential order. The first advertiser to meet the minimum bid price wins the impression. In the context of cookieless advertising, a waterfall approach can be used to prioritize different targeting signals. For example, you might start by bidding on impressions that have a Ramp ID, then move on to impressions that have a geo-contextual signal, and finally bid on impressions that have no signal at all. This is a flexible approach that can be adapted to different needs and budgets. Watch our Cannes panel for more on cookieless advertising We hosted a panel in Cannes that covered the future of identity in cookieless advertising. Check out the full recording below to hear what leaders from Cint, Direct Digital Holdings, the IAB, MiQ, Tatari, and Experian had to say. Watch now Check out more Cannes content: Our key takeaways from Cannes Lions 2023 Insights from a first-time attendee Four new marketing strategies for 2023 Exploring the opportunities in streaming TV advertising Maximize ad targeting with supply-side advertising Follow us on LinkedIn or sign up for our email newsletter for more informative content on the latest industry insights and data-driven marketing. Latest posts

The rise of streaming TV advertising is revolutionizing the marketing landscape, bringing together the best of traditional television's broad audience reach and digital's precise targeting capabilities. Marketers now have a new platform to explore, but it comes with its own set of challenges and opportunities. To shed light on this topic, we hosted a panel discussion at Cannes, featuring industry leaders from AMC Networks, Disney, OMG, Paramount, Roku, and Experian. In this blog post, we'll explore the effectiveness of TV as a performance channel and audience targeting. TV as a performance channel Television has come a long way over the years. The evolution of linear TV to connected TV (CTV) is opening new possibilities for targeting and performance measurement, like what we're accustomed to in search and display. However, there's still a way to go. What's preventing us from fully realizing the potential of CTV? Let's explore what's holding us back. Three challenges Advertisers are captivated by CTV, a media platform that combines the best features of TV and digital advertising. With its unparalleled data and identity capabilities, alongside the immersive TV experience, it has the potential to be a powerful performance channel. However, we still face three challenges as performance dollars take center stage. "CTV is a valuable household device that provides direct audience insights. However, to gain a comprehensive understanding of the household and the individuals in the household, we need different techniques. The implementation of such methodologies from user level profiles to algorithmic inferences are still evolving across different companies." Louqman parampath, vp, product, roku Client education Performance marketers and agencies are still primarily focused on social and search. It's important to reassure them that CTV aligns with their established standards. Optimize KPIs We need to address the challenges around attribution and incrementality. We should optimize for the KPIs that performance marketers desire, which are different from the metrics commonly used in social media and search marketing. Results-driven interactions You should invest in interactive ad formats and novel experiences to give users clickable options that deliver the instant impact of performance marketing. While conversions and purchases can happen after seeing an ad thanks to view-through attribution, your goal should be to make video ad experiences feel like performance-based engagements. This transition is crucial to building trust and familiarity among performance marketers and agencies. Strategies to effectively reach audiences across different mediums There are various mediums to connect with consumers — TV, digital, and mobile offer multiple avenues. Which strategies should you prioritize? Data interoperability When it comes to buying unified audiences, programmatically is the easiest route. By prioritizing data interoperability, you can ensure a seamless buying experience across all screens. "At Disney, we focus on data interoperability with industry solutions such as The Trade Desk/UID2, Google PAIR, and Experian and the LUID, making it effortless to buy unified audiences programmatically across all screens. With an identity graph as the foundation of our tech stack, we help our clients reach their target audience across linear, digital, and streaming properties."jamie power, SVP, addressable sales, disney Advanced targeting capabilities in linear TV Don't limit your perspective on television consumption to traditional streaming platforms alone. While streaming is popular, it's equally exciting to see advanced targeting capabilities integrated into linear television. Viewer habits are shifting, with appointment TV becoming a thing of the past. Today, viewers have more options to watch a variety of programming, regardless of its age. "Streaming has become another platform for viewers to consume programming, and it's exciting to see digital targeting capabilities being applied to linear TV. Viewer behavior has changed, with more opportunities to consume programs at different times, so it's important to use targeting capabilities like linear addressable to effectively reach the audience across multiple channels."evan adlman, Evp, commercial sales & revenue operations, amc networks While live premieres still attract a substantial audience, utilize linear addressable targeting to reach viewers across channels. By doing so, you can ensure your message reaches the right viewers at the right time. The viewership landscape has diversified – it's time to adjust our strategies. Make TV viewing patterns predictable To bring predictability to the unpredictable and fragmented landscape of TV, advertisers can create products that simplify and unify the viewing experience. This allows users to effortlessly transition between episodes, resulting in a cohesive and engaging viewing journey. Watch our Cannes panel for more on the future of streaming TV advertising We hosted a panel in Cannes that covered the future of streaming TV advertising. Check out the full recording below to hear what leaders from AMC Networks, Disney, OMG, Paramount, Roku, and Experian had to say. Watch now Check out more Cannes content: Our key takeaways from Cannes Lions 2023 Insights from a first-time attendee Four new marketing strategies for 2023 The future of identity in cookieless advertising Maximize ad targeting with supply-side advertising Follow us on LinkedIn or sign up for our email newsletter for more informative content on the latest industry insights and data-driven marketing. 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As a marketer, you know that the digital landscape is always changing. That's why it's important to make sure you're equipped with the right tools every step of the way – no matter how rapidly things change. You want to ensure your strategies and tactics stay ahead of any changes in technology or consumer behavior, so what new marketing strategies should be in your toolbox in 2023? Discover what industry leaders from Experian, Adweek, FreeWheel, Tubi, and Instacart had to say about what should be in every marketer's toolbox in 2023 at Cannes. Keep reading to learn the top four new marketing strategies you need in your marketing toolbox for 2023 and beyond. 1. A plan for signal loss The first item you should have in your marketing toolbox is a plan for signal loss. The phasing out of third-party cookies presents both a challenge and an opportunity. This shift not only poses challenges but also opens up opportunities for alternative strategies. On the one hand, it makes it more difficult to track users across channels and measure the effectiveness of marketing campaigns. On the other hand, it forces marketers to focus on building relationships with their customers and collecting first-party data. Consumer behavior is changing When we consider signal loss in a traditional sense, we think of the implementation of iOS 14, where we couldn't track click-based data from campaigns. It's important to reflect on the fact that the paid media ecosystem needed to adapt to new consumer realities. Younger demographics are less likely to click on ads and instead engage in video environments. They discover brands through platforms like TikTok or Instagram. It's crucial to understand how people behave, where they discover products, and where influence takes place. This understanding becomes even more vital when targeting a young audience demographic. Four things to consider when planning for signal loss There are four things you should consider when building out a plan to address signal loss and fragmentation. Channel diversification You need to reach your customers on the channels where they are already spending time, such as social media, email, and your own website. You should work with platforms that have first-party data to understand how your customers interact with your brand. Data privacy You need to be transparent about how you are collecting and using customer data. You should also anonymize data whenever possible. First-party data First-party data is now more crucial than ever, awakening its importance in shaping our actions. The combination of channel diversification and first-party data will be essential in the years to come. By focusing on these two areas, you can build stronger customer relationships and create more effective marketing campaigns. Contextual targeting Contextual targeting is emerging as a viable method to deliver more relevant content to your intended audience. By embracing signal loss, the alternative new marketing strategies that are emerging as a result, and adopting a privacy-centric mindset, you can navigate cookie deprecation. 2. Collaboration The second item you should have in your marketing toolbox is collaboration within the AdTech ecosystem. To address signal loss and changes in privacy, moving toward a more collaborative, holistic marketing ecosystem is key. Two ways we can achieve better collaboration Here are two ways we can create better collaboration in the AdTech ecosystem. Enable interoperability We should aim to create an ecosystem that fosters collaboration between marketers, publishers, advertisers, ad tech companies, and more. When we enable seamless interoperability, everyone can use the best data available. Use clean rooms We are witnessing a growing trend of collaboration between parties, where buyers and sellers share data in these secure environments. Clean rooms can help us develop data strategies in a controlled manner. 3. Generative artificial intelligence (AI) The third tool you should have in your marketing toolbox is generative AI. Benefits of implementing AI There are three main benefits to implementing AI within your marketing strategy. Enables creativity Although AI and machine learning have long been part of our toolbox, this moment marks an extraordinary acceleration that expands our capabilities. Copywriters can now create visuals, and art directors can write compelling copy. It's an extension of what we're capable of, potentially alleviating the burden of repetitive tasks and enabling more time for collaboration, creativity, and strategic thinking. By embracing generative AI, we can preserve valuable talent, prevent burnout, and invigorate the advertising industry. Enables more personalization The rise of personalization with AI has significantly increased the demand for tailored experiences. People now willingly allow AI agents to read their emails, hoping for quicker and easier responses. This shift signifies a change in the previous emphasis on privacy and consumer preferences. Consumers now see the value in exchanging personal information for more targeted services. E-commerce has already witnessed this transformation with customized ads based on individual preferences and behaviors. For instance, if a CPG brand notices you're not purchasing meat, they won't serve you ads for meat products. However, it's crucial to strike the right balance between being useful and intrusive. Users want relevant information that aligns with their needs without feeling intruded upon. As we navigate this path, we must ensure that personalization remains beneficial and respectful of user preferences. Helps drive impactful results and customer satisfaction The tool is a perfect analogy for improving your job performance and business operations. Having the right data input to feed the machine is crucial, just like using the right ingredients to cook a perfect meal. Keeping the consumer in mind throughout the process is key. You can ensure customer satisfaction by putting the right ingredients in and allowing the machine to work its magic. Scaling up, repeating, and refining the process will drive impactful results. 4. First-party data The fourth item you should have in your marketing toolbox is first-party data. Benefits of implementing a first-party data strategy Moving from a third-party cookie world to a first-party cookie world brings about significant transformation. Here are two benefits of implementing a first-party data strategy. Greater accuracy The shift to first-party cookies ensures greater accuracy, enabling us to establish critical mass through secure partnerships. This empowers us to strengthen and refine our personalization capabilities, much like Amazon's ability to anticipate customer needs before they arise. When you can predict and understand customer behaviors with remarkable precision, you can reach your customers with tailored and creative ads. "Building a robust first-party data strategy should be a central discussion for marketers, involving key stakeholders such as CEOs and CMOs. Quality and precise data are paramount, and while first-party relationships with consumers form the foundation, even established brands benefit from strategic partnerships. Together, we can unlock the potential of accurate and meaningful data-driven marketing."jeremy hlavacek, cco, experian Identify high-growth audiences First-party data can help you identify audiences with the greatest growth potential, ultimately optimizing marketing dollars for greater efficiency. Watch our Cannes panel for more new marketing strategies for 2023 We hosted a panel with Adweek in Cannes that covered what should be in every marketer's toolbox this year. Check out the full recording below to hear from leaders at Tubi, Freewheel, Instacart, Adweek, and Experian. Watch now Check out more Cannes content: Our key takeaways from Cannes Lions 2023 Insights from a first-time attendee Exploring the opportunities in streaming TV advertising The future of identity in cookieless advertising Maximize ad targeting with supply-side advertising Follow us on LinkedIn or sign up for our email newsletter for more informative content on the latest industry insights and data-driven marketing. Latest posts