The Strategic Application of Data Analytics and Intent Data in Political Campaigning

Introduction: The Data Revolution in Political Campaigning

The landscape of political campaigns has undergone a significant transformation in recent years, marked by an increasing reliance on data analytics to inform and drive strategic decision-making.1 Traditional methods of campaigning, which often involved broad outreach strategies such as mass mailings, yard signs, and rallies, are now being complemented, and in many cases, superseded by more sophisticated, data-driven approaches.2 This evolution signifies a fundamental shift from relying on intuition and anecdotal evidence to adopting evidence-based strategies grounded in the analysis of vast quantities of voter data.3 Political campaigns now operate in an environment where election data analysis is considered a critical battlefield, necessitating a deep understanding of voter behavior and preferences.2

This paradigm shift has led to what some observers have termed an “arms race” among political parties and campaigns, each striving to leverage ever-growing volumes of data to gain a competitive edge in the electoral arena.4 The increasing accessibility and decreasing cost of data, coupled with advancements in analytical tools and technologies, have democratized access to sophisticated campaign strategies. This means that data-driven campaigning is no longer the exclusive domain of well-funded national campaigns but is increasingly being adopted by campaigns of all sizes to enhance their effectiveness and efficiency.4 Currently, a significant majority of political campaigns utilize data analytics for voter targeting and outreach, highlighting the pervasive nature of this transformation.1

At the heart of this data revolution lies the concept of data-driven campaigning, a mode of operation that seeks to use data to develop and deliver targeted campaign interventions aimed at producing specific behavioral or attitudinal changes among voters.3 This approach is characterized by four key components: data itself, the analytics used to interpret that data, the technology that enables the collection and processing of data, and the personnel with the expertise to manage and utilize these resources effectively.3 Within this framework, intent data has emerged as a crucial element, providing valuable insights into what voters are actively searching for, researching, or studying online. This behavioral data offers a deeper understanding of voter motivations and concerns, going beyond traditional demographic or polling data.5

This report aims to provide a comprehensive analysis of the strategic application of data analytics and intent data in political campaigning, with a particular focus on the methods and potential impact of Link Media Partners’ approach. It will delve into the definition and sources of intent data, the techniques used to analyze voter interests and concerns, the role of data visualization in voter segmentation, the hyper-focusing of audiences through demographic information, strategies for optimizing fundraising efforts, case studies of successful data-driven campaigns, and the inherent benefits and challenges of this approach. Ultimately, this report seeks to synthesize the gathered information into a comprehensive overview relevant to the services and objectives of Link Media Partners.

Understanding Intent Data and Its Role in Voter Targeting

In the context of political campaigns, intent data can be defined as behavioral data that reveals what voters are actively searching for, researching, or studying online.5 This type of data provides valuable insights into the potential future actions and motivations of voters, offering a significant advantage over traditional forms of data collection.6 Unlike traditional demographic data, which focuses on static characteristics such as age, gender, and location, or polling data, which captures a snapshot of current opinions, intent data focuses on the dynamic and evolving interests of voters as demonstrated through their online behavior. Understanding intent data allows campaigns to gain insight into the “why” behind voter actions, not just the “what,” enabling a more nuanced and effective approach to targeting and messaging.6

Intent data snapshots are collected through a variety of online sources and methods. One primary source is online search queries conducted on search engines. These queries provide direct insights into the topics and issues that are of immediate concern to voters.2 For example, a surge in searches related to “healthcare costs” might indicate a growing voter interest in this particular issue. Website browsing history also serves as a rich source of intent data, revealing the types of content and information voters are actively consuming online.2 This can include visits to news websites, political blogs, candidate websites, and policy research pages, offering clues about their political leanings and priorities. Engagement with online content, such as the amount of time spent on a particular page, the downloading of resources like policy papers, and interactions with videos or infographics, further indicates the level of interest in specific topics.2

Social media activity represents another crucial source of intent data. Voters often express their opinions, share articles, and engage in discussions about political topics, candidates, and issues on platforms like X (formerly Twitter), Facebook, and others.7 Analyzing these interactions, including posts, shares, likes, and comments, can provide valuable insights into public sentiment and the intensity of engagement with different political narratives. Furthermore, there are data brokers who specialize in collecting and analyzing intent data specifically for political campaigns.11 These brokers aggregate online behavior from various sources to create detailed voter profiles, often incorporating browsing history, social media activity, and other digital footprints. Finally, campaigns themselves collect first-party intent data through their own online platforms and interactions.12 This can include sign-ups for email newsletters, registrations for online or in-person events, and responses to online surveys, providing direct insights into the expressed interests and levels of engagement of their supporters and potential voters.

The combination of online and offline data sources offers a more comprehensive understanding of voter intent. Campaigns often purchase voter records from states, which include information such as voting history and party affiliation (offline data), and then enhance these records with online behavioral data obtained from brokers.11 Additionally, methods like face-to-face canvassing and social media interaction bridge the gap between the online and offline worlds, allowing campaigns to connect real-world actions and stated preferences with digital behavior.9 This integrated approach provides a richer and more actionable understanding of voters. Moreover, the recency and quality of intent data are paramount for effective targeting. Voter values, behaviors, and media consumption evolve rapidly, especially during an election cycle.6 Campaigns now have the capability to adjust their messaging and outreach strategies almost instantaneously in response to shifts in public sentiment, underscoring the importance of real-time or near real-time intent data analysis to ensure that targeting remains accurate and impactful.2

Analyzing Voter Interests and Concerns Through Data Analytics

The raw intent data collected from various sources must undergo rigorous processing and interpretation to yield actionable insights for political campaigns. Several techniques are employed to achieve this, enabling campaigns to understand the nuances of voter interests and concerns. Sentiment analysis is a key technique that utilizes natural language processing to gauge public opinion and emotional tone associated with specific issues, candidates, or political events mentioned in online text data.13 By analyzing social media posts, news articles, and online forums, campaigns can understand whether the prevailing sentiment towards a particular topic is positive, negative, or neutral.

Predictive modeling is another crucial analytical technique. It involves employing historical data, such as past voting patterns and demographic information, along with current intent data, to forecast voter behavior and preferences.2 These models can predict the likelihood of a voter supporting a particular candidate or issue, as well as their propensity to turn out to vote. Machine learning algorithms play an increasingly significant role in processing complex datasets to identify subtle patterns in voter behavior that might be overlooked by human analysts.15 These algorithms can segment the electorate into highly specific micro-categories based on a wide range of data points, allowing for more precise targeting. Statistical analysis, including techniques like regression analysis and logistic models, is used to uncover correlations between online behavior, demographic data, and political leanings.14 This helps campaigns understand which online activities or demographic characteristics are most strongly associated with support for certain political positions.

Through the application of these analytical techniques, campaigns can effectively identify the key issues and priorities that are driving voters. Analyzing trending topics and keywords related to political discourse on social media and search engines reveals what is currently top-of-mind for the electorate.10 For instance, a campaign might observe a significant increase in online discussions about economic inequality, signaling this as a key concern for voters. Mapping voter concerns based on their online research patterns across various platforms provides a deeper understanding of the specific aspects of these issues that are of most interest to different voter segments.6 Furthermore, by analyzing the depth and frequency of voter engagement with online content related to different issues, campaigns can gauge the intensity of voter interest. This allows for a strategic prioritization of messaging, ensuring that the campaign focuses on the issues that resonate most strongly with the target audience.6

Advanced analytics enables campaigns to move beyond simply identifying topics of interest to understanding the emotional intensity and underlying motivations driving voter behavior. Sentiment analysis, for example, can reveal not just that voters are discussing healthcare, but also the specific anxieties or priorities they have related to this issue, such as concerns about affordability or access.6 This allows campaigns to craft more empathetic and persuasive messaging that directly addresses these underlying motivations. Moreover, real-time data analysis provides campaigns with the agility to respond quickly to evolving voter sentiment and emerging issues.2 By continuously monitoring online conversations and search trends, campaigns can detect shifts in public opinion almost instantaneously and adjust their messaging and strategies accordingly. This responsiveness is a key advantage of data-driven campaigning, allowing campaigns to capitalize on timely events and address immediate voter concerns in a relevant and impactful manner.

Voter Segmentation Using Analytics and Data Visualization

Voter segmentation is a cornerstone of modern political campaigning, allowing campaigns to divide the electorate into distinct groups based on shared characteristics, beliefs, or behaviors.7 This process enables the creation of highly personalized messaging and targeted outreach strategies, maximizing the efficiency and impact of campaign resources.6 Online behavior and research patterns, as revealed through intent data, play a crucial role in this segmentation process. By analyzing the types of content voters consume, the issues they research, and their engagement on social media, campaigns can create granular segments of the electorate with shared interests and priorities. This allows for the identification of persuadable voters who may be open to the campaign’s message, as well as likely supporters who can be mobilized to vote and contribute.2 Furthermore, social media data enables psychographic profiling, going beyond basic demographics to understand voters’ attitudes, values, and lifestyles, leading to even more refined segmentation.18

Data visualization tools are indispensable for transforming complex analytical findings into easily understandable formats, facilitating a deeper understanding of voter segments and their characteristics.19 Mapping voter data geographically allows campaigns to identify regional trends and concentrations of specific voter segments.21 This can reveal areas with high concentrations of undecided voters or specific demographic groups, enabling targeted allocation of resources for canvassing, events, and advertising. Creating charts and graphs provides a visual representation of voter preferences and issue priorities across different segments.19 For example, a bar chart might illustrate the varying levels of support for a particular policy among different age groups, while a pie chart could show the distribution of voters’ primary concerns. Interactive dashboards offer a dynamic way to monitor voter sentiment and campaign performance in real-time.19 These dashboards can display key metrics, such as engagement rates with online content, shifts in sentiment towards the candidate, and the effectiveness of different campaign messages across various voter segments. This allows campaign teams to explore data dynamically, identify emerging trends, and make informed adjustments to their strategies on the fly.

Effective segmentation allows for highly personalized messaging, significantly increasing the relevance and impact of campaign communications.6 By tailoring outreach to address the specific concerns and motivations of each voter segment, campaigns can craft messages that are more likely to resonate and drive action. For instance, a campaign might send messages about clean energy policies to a segment identified as “environmentally conscious millennials,” while delivering information about tax plans to a segment of “fiscal conservatives nearing retirement”.7 This level of personalization makes every voter touchpoint more impactful and potentially more persuasive.2 Data visualization plays a critical role in this process by enabling campaign teams to quickly understand the nuances of each segment and tailor their communication strategies accordingly. The ability to see clear visual representations of voter preferences and behaviors empowers campaigns to make smarter decisions about how to engage with different parts of the electorate, ultimately leading to more efficient and effective campaign outcomes.

Examples of Voter Segments Based on Online Behavior and Research Patterns

Segment Name

Key Online Behaviors/Research Patterns

Potential Issue Priorities

Example Messaging Themes

Environmentally Conscious Millennials

Searches for “renewable energy policies,” browsing articles on climate change, engaging with environmental organizations on social media, researching sustainable products.

Climate change, environmental protection, clean energy, social justice.

“Join our campaign to fight climate change and build a sustainable future for generations to come.” “Learn about our candidate’s commitment to clean energy initiatives.”

Fiscal Conservatives Nearing Retirement

Browsing articles on “tax cuts for retirees,” researching information on social security and Medicare, engaging with conservative financial news websites, searching for information on government spending and national debt.

Tax cuts, social security, Medicare, government spending, national debt, fiscal responsibility.

“Our candidate will protect your retirement savings and ensure fiscal responsibility in government.” “Learn about our plan to lower taxes for retirees.”

Suburban Families with Young Children

Searching for information on school quality, researching affordable childcare options, engaging with parenting blogs and social media groups, browsing articles on family-friendly policies and local community events.

Education, childcare, family leave, community safety, local infrastructure.

“Investing in our children’s future: Our candidate’s plan for better schools and affordable childcare.” “Ensuring safe communities and quality education for your family.”

Rural Voters Concerned About Jobs

Browsing articles on local job markets and unemployment rates, engaging with news related to manufacturing and agriculture, searching for information on economic development initiatives in rural areas, following local business news.

Job creation, economic development in rural areas, trade policies, support for local businesses, infrastructure.

“Our candidate will bring good-paying jobs back to our rural communities.” “Supporting our farmers and manufacturers: A plan for economic growth in our region.”

Urban Progressives Focused on Social Justice

Engaging with social justice organizations on social media, researching articles on racial equality, LGBTQ+ rights, and criminal justice reform, participating in online discussions about progressive political issues.

Racial equality, LGBTQ+ rights, criminal justice reform, affordable housing, healthcare access.

“Standing up for social justice: Our candidate’s commitment to equality and opportunity for all.” “Learn about our platform for a more just and equitable society.”

Hyper-Focusing Audiences with Demographic Data

Demographic data, encompassing characteristics such as marital status, homeowner status, approximate annual income, and approximate net worth, provides another critical layer for hyper-focusing audiences in political campaigning.2 These factors can often correlate with specific political views, issue priorities, and voting behaviors.23 For instance, research suggests that unmarried women are more likely to lean towards the Democratic Party and prioritize social programs, while homeowners may be more inclined to support Republican candidates and focus on issues like property taxes and local governance.24 Income and net worth can also be indicative of political leanings and can influence support for certain economic policies, as well as a voter’s capacity to contribute to political campaigns.25

By leveraging these demographic insights, campaigns can tailor their messaging to address the unique concerns and motivations of specific voter groups.7 For example, a campaign might highlight opportunities for first-time homeownership in communications targeted towards young adults, or emphasize plans for lowering property taxes when reaching out to homeowners.35 Similarly, messaging around economic policies might be tailored differently to high-income earners versus lower-income households.36 Demographic data also plays a crucial role in refining voter segmentation strategies, allowing campaigns to narrow down their target audience to individuals sharing common characteristics and likely holding similar views on key issues.7

However, the use of demographic data in political targeting also raises significant ethical considerations.38 It is crucial for campaigns to avoid discriminatory or manipulative targeting based on sensitive demographic information such as race, ethnicity, or religion.38 Transparency and respect for voter privacy are paramount when collecting and using demographic data, which often comes from various sources and may be shared with other political entities.42 Campaigns must also be mindful of balancing personalization with the risk of creating echo chambers, where voters are primarily exposed to information that aligns with their demographic profile, potentially hindering exposure to diverse perspectives and a shared understanding of the political landscape.1 While demographic data offers valuable parameters for targeting, relying solely on these factors can lead to oversimplification and stereotyping of voters. A more nuanced and accurate approach involves combining demographic data with intent data and behavioral analysis to gain a more holistic understanding of individual voters.2

Correlation Between Demographic Factors and Political Leanings (Based on Research Snippets)

Demographic Factor

Potential Political Leanings

Associated Issue Priorities

Marital Status

Unmarried women lean Democratic; Married individuals tend to be more Republican.

Social programs, women’s rights, family policies; traditional values, fiscal conservatism.

Homeowner Status

Homeowners tend to be more Republican than renters.

Property taxes, local governance, community development, housing policies.

Income Level

Lower-income voters often lean Democratic; Higher income without a college degree tends to lean Republican.

Economic inequality, social safety nets, minimum wage; tax policies, business regulation.

Net Worth

Higher net worth individuals may be more inclined to support candidates favoring lower taxes and business-friendly policies.

Investment income, capital gains taxes, estate taxes, financial markets regulation.

Optimizing Fundraising Efforts Through Data-Driven Strategies

Data-driven strategies have revolutionized how political campaigns approach fundraising, enabling a shift from broad appeals to highly personalized and effective outreach.46 By analyzing various data points, campaigns can identify potential donors, tailor their fundraising messages, and ultimately maximize their financial resources.47 One key aspect of this process is the ability to identify high-potential donors by analyzing their donor history, past giving patterns, and demographic information, including income and net worth.7 Campaigns can also segment their existing and potential donors based on their specific interests, past contributions (e.g., one-time versus recurring donors, amounts given), and levels of engagement with the campaign.46 This segmentation allows for the crafting of targeted fundraising messages that resonate with each donor segment’s motivations for giving, whether it’s a particular issue, the candidate’s values, or a sense of civic duty.50 These personalized appeals, which may include specific donation amounts or highlight the impact of their contribution on a particular campaign goal, are significantly more effective than generic fundraising emails or mailers.51

Leveraging voter data is also crucial for enhancing fundraising outcomes. Campaigns can use this data to identify potential small-dollar donors and build a broad donor base by understanding who is likely to support the campaign’s values and message, even with modest contributions.49 Furthermore, data analytics allows campaigns to optimize their fundraising channels based on the preferences and engagement patterns of different donor segments.46 For example, younger donors might be more responsive to online appeals via email or social media, while older donors may prefer direct mail. By tracking the performance of various fundraising channels, campaigns can allocate their resources more effectively, focusing on the channels that yield the best return on investment. Moreover, employing data analytics to track fundraising campaign performance in real-time enables campaigns to monitor key metrics such as conversion rates, average donation amounts, and the overall return on investment.46 This allows for timely adjustments to fundraising strategies and messaging, ensuring that campaigns can adapt quickly to changing circumstances and maximize their fundraising potential. Engaging with past donors and understanding their motivations for giving is also essential for sustained fundraising success, as retaining existing donors and re-engaging lapsed donors can significantly boost political contributions.5

Case Studies of Successful Data-Driven Political Campaigns

Several political campaigns have successfully leveraged data analytics and intent data to connect with voters and optimize their fundraising efforts. Barack Obama’s 2008 and 2012 presidential campaigns are often cited as pioneering examples of data-driven campaigning.2 These campaigns effectively used data for voter segmentation, microtargeting, and predicting voter behavior, allowing for highly personalized messaging and efficient resource allocation. The integration of digital, field, and financial data into a unified database, like the “Narwhal” system used in 2012, provided an unprecedented level of insight into the electorate.56

Donald Trump’s 2016 campaign also demonstrated the power of data-driven strategies, particularly in its targeted advertising on social media platforms.58 By leveraging psychographic profiling and analyzing voter data, the campaign was able to reach specific demographics in key swing states with tailored messages that resonated with their concerns and motivations. This targeted approach is credited with playing a significant role in the campaign’s success. Other campaigns, such as Ed Markey’s 2020 Senate race, have also effectively utilized data analytics to identify and engage specific voter clusters based on their interests and turnout history, demonstrating the continued evolution and application of these techniques.62

The impact of demographic targeting on campaign success is evident in numerous instances where specific voter groups have been effectively reached with tailored messaging. For example, campaigns have targeted suburban women with messages focused on issues like education and healthcare, while reaching out to working-class voters with appeals centered on job creation and economic opportunity.25 These targeted approaches, when implemented effectively, have often resulted in increased voter turnout among the desired demographics and ultimately contributed to favorable election outcomes.2 These case studies highlight that successful data-driven campaigns often involve a sophisticated integration of various data sources and analytical techniques, demonstrating the power of a holistic understanding of the electorate. However, the specific strategies and their effectiveness can vary significantly depending on the context, candidate, and target audience, underscoring the need for customized approaches rather than generic solutions.57

Key Data-Driven Strategies Employed by Successful Campaigns

Campaign Name

Key Data Sources Used

Primary Analytical Techniques

Notable Outcomes/Impact

Obama 2008 & 2012

Voter files, social media, online engagement, field data, financial data

Predictive modeling, microtargeting, data integration

Increased voter turnout, effective mobilization of specific demographics, optimized resource allocation

Trump 2016

Voter files, social media data, consumer data, psychographic profiles

Microtargeting, targeted advertising on social media, sentiment analysis

Reached specific demographics in swing states with tailored messages, influenced voter preferences

Markey 2020

Voter files, environmental interest data, turnout history, online engagement

Voter segmentation, targeted outreach via email, social media, and SMS

Reached environmentally minded voters in areas with low turnout, optimized canvassing efforts

Benefits and Challenges of Using Intent Data and Demographic Information

The strategic application of intent data and demographic information in political campaigning offers numerous benefits across various aspects of campaign operations. One of the primary advantages is the increased efficiency and effectiveness of campaign outreach.1 By focusing resources on voters who have demonstrated an interest in the campaign’s issues or candidate, campaigns can avoid wasting valuable time and money on less receptive audiences. This targeted approach also leads to enhanced personalization of messaging, resulting in higher engagement rates and a greater likelihood of resonating with voters’ specific concerns and motivations.6 When voters feel that a campaign understands their individual needs and priorities, they are more likely to pay attention and consider the message. Furthermore, data-driven strategies enable optimized allocation of campaign resources, ensuring that time, money, and manpower are concentrated on areas and voter segments where they are most likely to influence election results.1 This allows for a more strategic and impactful use of limited campaign resources.

Intent data and demographic information also significantly improve a campaign’s ability to identify and mobilize key voter segments.7 By analyzing online behavior and demographic characteristics, campaigns can pinpoint likely supporters who need encouragement to vote, undecided voters who might be persuaded, and even potential volunteers. This precise targeting allows for tailored get-out-the-vote efforts and volunteer recruitment strategies. Moreover, data-driven insights lead to more effective fundraising through targeted appeals to potential donors.7 By understanding donors’ giving history, interests, and demographics, campaigns can craft personalized messages that resonate with their motivations for contributing, ultimately increasing donor engagement and contributions.

Despite these significant benefits, the use of intent data and demographic information in political campaigning also presents several limitations, ethical concerns, and potential pitfalls. One major challenge revolves around data privacy, security, and the need to obtain informed consent for data collection and use.1 The collection and analysis of vast amounts of personal data raise concerns about potential privacy violations and the need for stringent security measures to protect this sensitive information. Ensuring that voters are aware of how their data is being used and have given their consent is crucial for maintaining trust and complying with regulations. Another significant challenge is the risk of data inaccuracies and biases in algorithms.39 If the data used for targeting is inaccurate or if the algorithms employed are biased, it can lead to misinformed targeting and potentially reinforce existing societal inequalities.

The potential for voter manipulation and the creation of echo chambers are also major ethical concerns associated with data-driven campaigning.1 Highly tailored and emotive messaging, while effective in persuasion, can also be manipulative if it exploits voters’ vulnerabilities or biases. Furthermore, the use of microtargeting can lead to the creation of echo chambers, where voters are primarily exposed to information that confirms their existing beliefs, limiting their exposure to diverse perspectives and potentially increasing political polarization. The “creep factor,” or negative voter reactions to highly personalized targeting that feels intrusive, is another potential pitfall.44 When voters feel that campaigns know too much about them or are using their personal information in an unwelcome way, it can lead to resentment and disengagement. Finally, the digital divide presents a limitation, as certain segments of the population may not have the same level of online presence or engagement as others.74 Relying too heavily on intent data derived from online behavior could lead to overlooking or under-engaging with these segments, potentially resulting in unequal democratic engagement.

Conclusion: The Future of Data-Driven Political Campaigning

The analysis presented in this report underscores the transformative role of data analytics and intent data in the contemporary political landscape. Modern political campaigns are increasingly embracing data-driven strategies to enhance their efficiency, effectiveness, and overall impact. By leveraging intent data, campaigns gain invaluable insights into the active interests and concerns of voters, allowing for a level of personalization and precision targeting that was previously unattainable. Advanced analytical techniques enable the processing and interpretation of this vast amount of data, facilitating accurate voter segmentation and the identification of key issue priorities. Data visualization tools further empower campaign teams to understand complex information and make informed strategic decisions. The ability to hyper-focus audiences based on demographic factors, when combined ethically with intent data, allows for highly tailored messaging that resonates with specific voter groups. Moreover, data-driven strategies are proving instrumental in optimizing fundraising efforts, enabling campaigns to identify potential donors and craft personalized appeals that maximize contributions.

The case studies examined in this report highlight the success of campaigns that have effectively integrated data analytics and intent data into their operations. From the pioneering efforts of the Obama campaigns to the targeted strategies employed by the Trump campaign, the evidence suggests that a sophisticated and ethical use of data can provide a significant competitive advantage. The ongoing evolution of data analytics, coupled with the increasing sophistication of artificial intelligence and the pervasive influence of digital platforms, indicates that data-driven political campaigning will continue to shape the future of elections. However, as this report has also emphasized, the benefits of these powerful tools must be carefully balanced against the inherent challenges and ethical considerations. Issues related to data privacy, security, potential for manipulation, and the risk of creating a fragmented public discourse remain critical concerns that must be addressed proactively.

Moving forward, it is imperative that political campaigns, and the organizations that support them, prioritize ethical considerations and responsible data practices. Transparency in data collection and usage, a commitment to data accuracy, and a mindful approach to personalization are essential for building trust with voters and ensuring the integrity of democratic processes. Link Media Partners, with its expertise in data analytics, intent data, and data visualization, has a significant role to play in helping political campaigns navigate this evolving landscape effectively and ethically. By championing responsible data practices and providing sophisticated analytical tools, Link Media Partners can empower campaigns to connect with voters in meaningful ways while upholding the fundamental principles of transparency, privacy, and democratic engagement.

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