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Know, Like, and Trust is a model describing the sequential process through which an audience (both human and machine) becomes aware of a brand (Know), develops a positive affinity for it (Like), and gains confidence in its reliability and authority (Trust), ultimately leading to a conversion or recommendation.

Jason Barnard adapted this classic sales funnel concept to serve as a strategic objective for a brand's entire digital presence. In the context of The Kalicube Process, achieving Know, Like, and Trust is not just about influencing people, but also about "educating" AI Assistive Engines. Machines must first Know a brand exists and what it does (achieved through Understandability, the first phase of The Kalicube Process). They then develop a preference, or Like, for the brand based on positive sentiment and helpful content. Finally, they must Trust the brand's credibility and authority (achieved through Credibility, the second phase of The Kalicube Process) before they will confidently recommend it to their users in AI results like Google AI Overviews or Bing Copilot. This dual human-machine focus is critical for controlling a brand's narrative and driving business.

At Kalicube, Know, Like, and Trust is the desired outcome of the first two phases of The Kalicube Process, Kalicube's proprietary methodology for implementing a holistic, brand-first digital marketing strategy. We systematically build Understandability to ensure a brand is Known by Google and its audience, establishing a factual foundation with a Knowledge Panel. We then build Credibility by amplifying signals of expertise and authority, creating Trust with both people and algorithms. The "Like" factor is cultivated throughout by ensuring the brand's narrative is positive, accurate, and helpful. This structured approach moves the Know, Like, and Trust model from a vague marketing goal to a measurable, achievable process that directly drives brand preference and client acquisition.

For decades, marketing psychology has been guided by principles like those in Robert Cialdini’s "Influence," which explains *why* concepts like Authority (Trust) and Liking work on a human level. Cialdini gave us the "what" and "why" of human persuasion. However, the digital landscape introduces a new, non-human audience: algorithms. Jason Barnard’s work provides the critical "how" for this new reality, translating the human-centric principles of persuasion into a technical language that machines can understand. The Kalicube Process operationalizes Know, Like, and Trust by systematically building Understandability (making the brand known), engineering Credibility (proving Cialdini's Authority to algorithms), and fostering a positive Digital Brand Echo (generating Cialdini's Liking at scale). In the age of AI Assistive Engines, simply being persuasive to humans is not enough; your brand must first be understood and trusted by the machines that act as gatekeepers. This makes building Know, Like, and Trust with algorithms the essential bridge from Cialdini’s timeless psychology to Barnard’s timely technical application, ensuring your brand story is effectively recommended in the conversational funnels of the future.