Todd argues that analysts too quickly blame predictive models when the real fault lies upstream. Inconsistent definitions, broken processes, stale data and weak governance compound over time, so fixing the surrounding data system should come before replacing the model.
Todd argues that impressions and attention are not rival metrics. Impressions create the opportunity for engagement and attention raises the odds of action, so both should sit in one predictive framework judged by whether spend produces incremental growth.
Todd points to Netflix's 16% ad revenue rise as evidence that brands are investing in digital advertising innovation. He warns that leaning only on algorithms risks losing the human touch, and says AI should enhance strategy rather than replace it.
Joel argues that marketers who rely on clicks, views and impressions are falling behind. He says the advantage lies in predictive analytics and personalization at scale, backed by strategy and frameworks that turn data into actionable insight rather than noise.