AUGUST9MedI aNMENTEvaluating Generative AI Content Performance in B2BMany core metrics like engagement rates, time on page, conversions, and SEO remain key. But with AI-generated content, you need to add a few important layers.The biggest shift is focusing on quality and brand alignment. It's not just about performance, but whether the content truly reflects your brand's tone, messaging, and expertise. Metrics like tone consistency, factual accuracy, and brand voice alignment--often assessed through editorial reviews or stakeholder feedback--become critical.AI also introduces new efficiency metrics: time-to-publish, content velocity, and cost per asset. These show how AI speeds up workflows and cuts production costs--vital for fast-moving B2B teams aiming to reduce time to market. However, marketers can fall into the trap of celebrating scale and speed while overlooking quality and brand alignment, which are crucial to long-term success.So, while traditional KPIs remain essential, evaluating AI-generated content means assessing both results and process: how well the content performs, how efficiently it's created, and how faithfully it represents your brand.Personalizing B2B Content at Scale Using Generative AIPersonalization in B2B marketing starts with a deep understanding of the buying committee personas, since decisions are made by groups with varied needs and priorities. A strong generative AI strategy leverages tools to ensure research-driven insights into these personas, which are validated and refined by experts.Generative AI helps by aggregating research, understanding, and mapping the needs and benefits for each buying committee persona--whether it's the economic buyer focused on ROI and cost-efficiency, the technical buyer assessing integration with sales tools, or the process buyer prioritizing operational alignment. This drives differentiation by enabling tailored messaging that truly resonates.
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