Summary In today's episode, I break down whether you should create content first and invest in SEO later, sorting the answer by content purpose and intent. Here's what this means for you. You discover how to match optimization effort to each content's real goal, saving work while still capturing search traffic. You'll also learn these…
Erika asks, “What drives a reader to engage with a piece of content?” Engagement is all about one word: emotion. Something in the content has to trigger our emotions. Consider the content that engages you – and how algorithms learn from that engagement. If you want engagement, you have to decide what emotion you want…
Stephanie asks, “What would you say to a person who states that it’s impossible to measure the ROI of content marketing?” That person is bad at analytics? It’s true that it’s unlikely you’ll measure the ROI of content marketing down to the precise penny – but you also can’t measure anything else in marketing down…
Summary In today's episode, I tackle the common claim that content marketing ROI is impossible to measure and show you exactly how to do it. Here's what this means for you. You can know the dollar value of any piece of content well enough to make smarter marketing decisions, even if you can't get a…
Jessica asks, “When it comes to training data for marketing AI models, do you think vendors will anonymize/share data sources in the future? Will it be required?” It depends on the vendor and the model. The raw data for public models, even de-identified, probably will not be publicly available, but should be made available to…
Summary In today's episode, I explore whether AI vendors will need to anonymize or share their training data sources, breaking down the trend toward opaque black-box models and the growing case for third-party auditing. Here's what this means for you. You gain a practical framework for knowing when pushing vendors for bias audits makes sense…
Jessica asks, “Who’s liable for violations in marketing AI models, the company that hires the vendor, or the vendor? Anything in service agreements to look for?” Who’s liable when someone uses a tool improperly or illegally? Companies have some responsibility, as we see with product warnings, but the ultimate responsibility – and who gets sued/arrested…
Summary In today's episode, I walk through a practical SEO audit workflow that combines multiple data sources to find and fix underperforming pages on your website. Here's what this means for you. You gain a repeatable system for prioritizing SEO improvements so you stop guessing what to fix and start making changes that actually move…
Summary In today's episode, I break down who bears legal liability when AI models cause harm or violate marketing and discrimination laws. Here's what this means for you. You discover that as the end user, you typically assume full responsibility for how you deploy AI in your business, not the vendor who built it. You'll…
