Last week, I broke down the Results-Forward model we use at Zmist & Copy to write the best case studies in the industry. This week, we're diving into part 5 of our Context Engine: How to zmistify your content.
I'm writing a 5-part series on this topic. Here's where we're at:
In today's newsletter:
Creating content used to be hard. Now it's easy. Everyone has access to the same AI tools.
Doing SEO used to be costly. Now it's much costlier. Your competitors have been building domain authority for years. Catching up requires a big SEO budget.
And if you do have strong authority, you’ve probably seen your highest-performing pages lose traffic anyway. That’s because users no longer click. They get their answers from AI.
If you're still in the 2020 mindset, you need to face the reality:
Modern search is multi-dimensional, AI-native, and changing fast.
How exactly is it changing? After reading every playbook on GEO I could find, I added my own spin to make it even easier to digest.
Here are the 3 biggest shifts you need to know about.
If the way people find information has changed, that means your strategy has to change as well.
Ryan Law, Director of Content Marketing at Ahrefs, recently posted something that echoes exactly what I’ve been saying all along:
"create brand demand. publish more studies, frameworks, and "coined concepts" - 'The Ahrefs Framework for X', 'The Ahrefs Study on Y'. get people searching for your brand, everywhere.
That's exactly what the Context Engine does.
It helps you create a system that makes your brand the reference point for your category.
If you've been reading my previous 4 newsletters in this series, you know that the Context Engine has 3 models. Here's how they work together as a funnel strategy to make your brand top of mind in your industry:
Purpose: Establish your unique perspective on industry concepts
What it looks like:
"Checkbox marketing" by Brendan Hufford
Read about the Teach & Tilt model.
Purpose: Show exactly how you solve customer problems, illustrating your methodology with mini case studies
What it looks like:
How The HubSpot Blog Is Combatting SERP Volatility
Read about the See It Solved model.
Purpose: Prove your claims and convert your prospects
What it looks like:
"Frotcom Ships Mobile Features at Scale: 70% Fewer Bugs, 99.94% Crash-Free Sessions"
Read about the Results-Forward case study model.
Your Teach & Tilt content serves as Attention in AIDA. It generates awareness by establishing your unique POV on industry challenges.
Interest: Prospects intrigued by your perspective want to understand how you actually solve problems. Your See It Solved content demonstrates your methodology in action so the prospects can evaluate whether you can deliver.
Desire: When prospects are considering you, they check out your Results-Forward case studies that show the exact outcomes you've achieved for others. That builds confidence in their decision.
Action: By the time prospects reach out, they've already been educated by your frameworks, impressed by your methodology, and convinced by your results. The sales conversation becomes about your capacity and timeline. You don't have to prove anything to them. They arrive pre-educated, pre-qualified, and pre-sold on your approach.
This is how you compress sales cycles.
Our Context Engine is a perfect content funnel that allows you to focus your content efforts on what matters.
Now, let me show you how we did this for one of our clients.
Flyaps needed to stand out in a crowded software development market by showcasing their unique AI and data engineering expertise.
TOFU: Teach & Tilt content: Big Data Engineering: It’s No Longer Just About “Big”
MOFU: See It Solved content: Why We've Used Python for Data Engineering for 12 Years (And Still Do)
BOFU: Results-Forward content: Bavovna AI’s RNN AI Model Achieves 99,98% Accuracy to Help Drones Navigate Without GPS
Flyaps became the reference point for Python data engineering.
Based in Ukraine with an office in New York, they specialize in custom AI solutions and Python development. When you ask ChatGPT to “list Python development companies with data engineering expertise in New York,” here’s what comes up:
"Flyaps (NY & Dnipro, Ukraine) - Delivers custom AI-driven and cloud-native development in NYC. Offers Python development along with big data and BI services."
That AI-generated description nails their positioning.
Our content strategy worked.
When AI references Flyaps, it mentions exactly what they want to be known for: AI development, Python expertise, big data, and cloud-native solutions.
Here is the Lovable version of it.
Before you publish anything, ask:
✅ Does this establish our POV? (Teach & Tilt)
✅ Does this show our methodology? (See It Solved)
✅ Does this prove our impact? (Results-Forward)
You want AI to cite you as a reference and make people remember our brand.
The Context Engine is a way to create demand for your brand.
That's how you zmistify your content. And win in the AI era.
This is the final newsletter in The Context Engine series. Next week, I'm diving into something completely different. Don't miss it.
Kate
P.S. Want our help zmistifying your content strategy? Contact us here.
P.P.S. If you missed any part of this series, here are all 5 newsletters:
Statistics make your arguments more persuasive, but only if used correctly. Learn more about how to use numbers to give your arguments a firm foundation.
Persuasiveness is one of the main principles of quality content. It’s the superpower you need to turn the readers into leads. But how do you make a persuasive piece of writing? This problem was solved two thousand years ago by a Greek philosopher. Curious to learn how? Read this article to find out!
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