More ads
More spend cannot rescue a weak promise or the wrong audience.
Strategy
Google was step one. Today, LLMs are recommending your competitors before buyers ever hit your homepage. Our hub-and-spoke model turns your website into the definitive source AI engines cite—with live monitoring on every channel that matters. Ready in 2 weeks.

Quick strategy check
What we would test first
Your channels are active, but the journey is not built around a clear buying question.
Your first move
Match each high-intent question to one page, one proof point and one next step.
Most teams stuck in ‘traffic, not pipeline’ are quietly losing an estimated 20-30% of marketing spend to activity that never converts to revenue (industry estimate — confirm with your own funnel data).
How we work
Ten years building growth marketing systems for Fortune 1000 enterprises and the same five-stage process behind every one of them.
Where the real demand is, and where it's moving. We size the opportunity and map who else is chasing it before we write a single word of copy.
Not 'everyone who could buy' — the specific buyer whose problem you solve better than anyone else, and who's worth building the entire system around.
The activity theatre trap
When pipeline slows, teams add activity. The real job is to understand the buyer, make a clear choice and connect every action to the same commercial goal.
More spend cannot rescue a weak promise or the wrong audience.
Publishing faster does not help when every competitor sounds the same.
A larger list creates more noise when the timing and message are wrong.
Reports do not create growth unless they lead to a clear decision.
Three tools. Three distinct jobs.
Real Markiverse work
Since 2015, we’ve run this exact process for enterprise brands including Tata Communications Transformation Services, TCS, Tech Mahindra, and NTT Data.
15X ROI
$2.4M+ qualified pipeline
One recent 6-month engagement (results vary by starting point and market).
Client sector: Digital infrastructure
Target buyer question
What Markiverse changed
We used AI Marketing Radar to find the demand gap, then rebuilt the journey for technical and commercial buyers.
The Eugene Schwartz model
Any market — not just yours — breaks down into the same five stages of buyer awareness. Over the last 10 years, Markiverse has applied this exact lens to solve some of the most intricate marketing challenges for Fortune 1000 enterprises. The frameworks below aren’t theory — they’re the same diagnostic we run before any strategy engagement.
Choose a stage to see what the buyer needs from you next.
Buyer asks
“Why should I care?”
Your job
Show the hidden cost of doing nothing.
Check your positioning
Enter a keyword, headline or public page URL. See the awareness stage your message most likely addresses.
The Hub-and-Spoke model
Stop treating every content piece as a fresh start. Build one strong point of view, then turn it into the answers buyers need across the journey.
The DeSiRE decision model
Protect what already brings trust, demand and revenue.
Move quickly where a competitor is weak or buyer intent is rising.
Fix the pages, messages and journeys that are leaking buyers.
Take a proven offer into a new audience, market or channel.
Questions we get on the first call
You do not get a large deck and a vague recommendation. Every finding becomes a page, campaign, message or sales action your team can use.
The AI Marketing Audit comes first to reveal current gaps. AI Marketing Radar then helps build the AI marketing system. BIRD is a separate sentiment-analysis tool for strengthening reputation and mitigating negative sentiment.
Usually two to four weeks. By the end, you have a clear audience, sharper positioning and a 90-day plan your team can start using.
Almost never. DeSiRE starts by protecting what works. We rebuild only where the evidence shows buyers or revenue are leaking.
Start here
In 30 minutes, we’ll look at your market, message and buyer journey — then show you three practical moves worth making next.
Every quarter you wait, competitors are being cited in AI search results where you’re absent — the gap gets harder to close the longer it’s left unaddressed (illustrative — confirm with your own AI-search visibility data).