Information researcher passionate about audience intelligence methodologies. Concentrates on comparing firmographic versus demographic targeting for B2B, understanding psychographic frameworks like VALS, tracking behavioral signals in social analytics, and adapting to contextual targeting as cookies disappear. The aim: equip marketers with the data strategies that improve lead quality by 60% and targeting accuracy by 90%.
Driven by curiosity about why some targeting approaches predict buying behavior while others fail completely. Investigates the eight essential firmographic data points that define B2B targeting, whether ZoomInfo or Clearbit better serves UK market needs, and the common mistake that shrinks total addressable markets to just 200 companies. Research process combines platform testing, database comparison, and analysis of when stated psychographic values don't match actual purchasing behavior. Particularly focused on the post-cookie landscape, documenting how semantic contextual targeting in Google Ads can be set up in 90 minutes and achieve 90% of previous behavioral accuracy. Examines the five key behavioral signals that should appear in every social analytics dashboard and how long teams must test new content formats before judging response. Maintains objectivity when evaluating native platform insights versus dedicated behavioral analytics tools, rules-based versus AI personalisation engines, and whether to enrich leads at capture or qualification stage. Believes audience intelligence is the most underutilised marketing capability, and that understanding who you're targeting matters as much as what you say. Committed to helping readers avoid the personalisation mistake that makes 65% of users feel surveilled rather than served.