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    You are at:Home»Technology»Why traditional monetization tactics are costing publishers revenue
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    Why traditional monetization tactics are costing publishers revenue

    TechAiVerseBy TechAiVerseJuly 19, 2025No Comments8 Mins Read2 Views
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    Why traditional monetization tactics are costing publishers revenue
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    Why traditional monetization tactics are costing publishers revenue

    Traditional ad models may no longer deliver the revenue publishers need, but better audience strategies can. With privacy regulations tightening, the role of third-party cookies evolving and digital platforms capturing a greater share of advertiser spend, it’s harder than ever for resource-strapped publishers to monetize through legacy channels. With a digital landscape as complex and fragmented as it is today, many publishers are unaware of how much revenue they lose due to stagnant or inefficient ad strategies. 

    “Traditional advertising models are increasingly misaligned with how audiences engage today,” said Georgia Gkolfinopoulou, senior marketing strategist at Marigold. “Static ad formats, untargeted messaging and siloed monetization efforts limit publishers’ ability to create meaningful, revenue-driving experiences.”

    Publishers can find a path forward by rethinking how they use owned channels like email, mobile and on-site experiences not just as communication tools, but as engagement and data-collection vehicles. Hearst UK, for example, recently modernized its email marketing strategy with real-time personalization and embedded dynamic content to improve consumer engagement and maximize revenue. 

    Publishers who take a similar modernization approach will be able to deliver more relevant reader experiences, gain a clearer picture of their audience and move beyond traditional ad tactics like banner ads.

    “Ultimately, what’s holding many publishers back isn’t lack of opportunity; it’s the persistence of legacy thinking in a landscape that now demands personalization, responsiveness and long-term user value,” Gkolfinopoulou said.

    The logic is simple, but powerful: Publishers with an engaged readership benefit from higher conversion rates and brand loyalty, and publishers who deliver those high-value audiences to marketers command higher ad rates. This makes it essential that publishers use smarter data-capture techniques to provide more personalized experiences for readers and to build audience profiles for advertisers. 

    While most publishers gather user data at subscription sign-up or when readers take surveys, some have begun incorporating strategic data-capture techniques throughout the consumer experience to build databases of highly engaged users. These techniques range from interactive quizzes and polls, which also drive engagement, to gated content and premium user experiences that encourage readers to opt in.

    “Gamification plays a crucial role in audience engagement and data collection for two key reasons,” Gkolfinopoulou said. “First, it makes the overall user experience more enjoyable and interactive, increasing dwell time and the likelihood of content sharing and virality. Second, it enables data collection in a way that feels less intrusive, especially when paired with a clear and compelling value exchange that highlights what users receive in return for sharing their information.”

    Publishers can then use the resulting data to train AI tools on lookalike models that provide accurate content recommendations and dynamic user experiences. As user engagement improves, so do behavioral signals which can be used to refine product offerings and drive long-term strategic innovation. With a deeper understanding of audience behaviors, preferences and motivations, publishers can offer advertisers expanded reach and improved targeting across platforms.

    However, AI models are only as effective as the data they’re trained on. Publishers need to invest in robust data enrichment strategies, from interactive experiences to declared preferences, to ensure their AI-driven outputs are contextually accurate and commercially viable.

    “Ultimately, AI should be viewed not just as a tool for efficiency, but as a partner in creating smarter, more profitable relationships with audiences,” Gkolfinopoulou said. “Its success, however, depends on how intelligently it is integrated with human insight, ethical data use and meaningful value exchange.”

    Using enhanced personalization to access new revenue streams

    By combining high-quality data with well-calibrated AI models, publishers can deliver more personalized, relevant and timely user experiences. This approach creates opportunities to unlock new revenue streams and improve existing ones across newsletters, affiliate marketing and cross-selling.

    Newsletters that leverage personalization to reflect user preferences not only create a more relevant brand experience, but also see significantly improved open rates, click-through rates and customer retention rates. In turn, newsletters become more attractive to premium sponsors and advertisers who value those direct, high-intent audiences.

    In the case of affiliate marketing, enriched user profiles allow publishers to insert personalized product recommendations into editorial content with greater relevance and conversion potential — increasing the value of each touchpoint and enhancing the overall user experience by keeping offers aligned with genuine interest.

    Cross-selling and upselling opportunities also expand as publishers use first-party behavioral data to target audiences with product recommendations, content bundles or membership tiers most suited to their tastes and behaviors. Automated placements can enable this at scale, without overwhelming editorial or marketing teams.

    Personalization is proving to be a powerful catalyst for increasing ad revenue, according to Gkolfinopoulou. “With more granular audience segmentation and real-time behavioral insights, publishers can offer higher-value ad placements, improve targeting precision and reduce wastage,” Gkolfinopoulou said. “This leads to increased CPMs, stronger partnerships and more sustainable monetization models, especially as third-party cookie support continues to decline.”

    How Hearst UK applied an efficient, targeted email strategy to increase revenue

    Recently, Hearst UK faced the challenge of modernizing its email marketing strategy to improve consumer engagement and increase revenue — and doing so with smaller marketing teams and fewer resources. To do this, the media company partnered with Marigold to streamline cross-channel targeting and embed personalized, real-time content across email campaigns and site content.

    By sending readers emails from the editorial brands they engaged with the most, rather than strictly the emails to which they were subscribed, Hearst UK saw between a 75% and 100% uplift in email conversion rates. The publisher also improved its newsletter open rate by 10% year-over-year and saved more than 50 hours per month previously spent on building newsletters.

    Hearst UK further maximized its revenue through cross-selling opportunities by recommending products to audiences based on their browsing behaviors, monetizing the company’s newsletters and launching premium subscription options.Hearst UK’s success demonstrates the value of this playbook for identifying and addressing revenue strategy gaps. One essential element for sustaining and improving those results over time is performance analytics.

    Measuring monetization efforts over time: A guide to key metrics

    While traditional marketing KPIs still apply, the way publishers use, interpret and act on the data is evolving, especially in a landscape increasingly shaped by personalization, AI and automation. Publishers should monitor the following key metrics and tactics closely to improve their digital monetization efforts. 

    Foundational metrics are essential, cross-industry KPIs that should form the backbone of any publisher’s monetization dashboard. Some baseline health indicators can be used in the following ways: 

    • Average basket size or spend per user shows upsell and cross-sell effectiveness. 
    • Retention over time identifies where drop-offs occur and where interventions are needed. 
    • Lifetime value assesses the average long-term impact of the average basket time and retention over time.
    • Time to churn identifies early warning signs and enables timely winback strategies.

    However, to truly capitalize on personalization and audience intelligence, publishers should look beyond static KPIs and analyze dynamic, behavior-driven measures like response metrics and predictive insights. 

    • Average response rate to personalized content allows publishers to A/B test results against generic, one-size-fits-all content. 
    • Segmentation engagement depth assesses how audiences respond to tailored experiences.
    • Content consumption velocity identifies how frequently users engage with content post-personalization.
    • Preference update frequency acts as a proxy for engagement and intent. 

    As AI and automation become deeper parts of publishers’ operational toolkits, it’s critical to also measure AI’s contribution to efficiency and speed with operational impact metrics.

    • Campaign time to market tracks how automation accelerates execution compared to manual workflows.
    • Labor hours saved quantifies gains from using AI tools for content generation, segmentation or personalization.
    • AI personalization accuracy over time monitors campaign precision and relevance to ensure ongoing value.

    Once publishers have tracked campaign performance within the tiered framework of foundational, response and operational metrics, additional steps are necessary to make those KPIs actionable. 

    Publishers should embed feedback loops by using data from interactive experiences like quizzes and polls to refine audience segments and retarget more effectively. Their editorial and marketing teams should also regularly review and amend models based on qualitative insights — after first allowing AI to surface patterns or anomalies. 

    Next, it is important to incorporate dashboard dynamism by avoiding static dashboards and instead building customized views that drill down by lifecycle stage, cohort or campaign type to uncover revenue opportunities. 

    Lastly, publishers should prioritize actionable insights, not simply volume, by identifying metrics that lead to actionable changes, including price adjustments, recommendation model changes and campaign pauses.

    Hearst UK’s successful modernization of its email strategy demonstrated the value of publishers using strategic data collection, AI tools and automation and audience segmentation and personalization to address revenue gaps, expand audience reach and improve outcomes. Publishers who lean into newer technologies like AI and follow Hearst UK’s lead with an innovative audience strategy will be best positioned to improve consumer engagement and maximize revenue for the foreseeable future.

    Sponsored by Marigold

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