Elizabeth Greene

Co-Founder @ Junglr | Amazon Advertising

“I don’t know what I’m doing…I’m just leaving money on the table.”
“Weeks go by, I don’t look at it, and suddenly I’ve wasted $100 on something stupid.”

That’s what I hear from sellers all the time.

They’re frustrated.
Burned.
Unsure if ads are fueling growth or just bleeding cash.
...And when they do hand it off, it feels like a gamble

“Agencies never seemed to know it better than I did.”

Most agencies make it worse. They either zoom out so far they miss the real problems, or they bury you in data you don’t have time to sift through.

Suddenly you're the one catching mistakes.

That’s where things break.
Spend climbs
profits shrink
growth flatlines
...and nobody knows why.

Clients tell us the reason they trust Junglr is because we know when the details matter.
We’re in the weeds, ASIN by ASIN, but we don’t just drown you in noise.
We surface the things that actually move the needle...when they matter.

“You actually caught something in the audit I’d missed for three weeks.”

That’s the difference. Relief.

It’s more than just ‘keeping an eye on it.’ Anyone can do that.

The difference is surfacing the right things...before they cost you.

With us, you don’t have to micromanage or second-guess.

You get clarity on what matters.
Protection against waste
...and freedom to focus on scaling your brand.

Anyone can run ads.
We make sure nothing slips through the cracks.

Co-Founder

WE’RE HIRING: Our Next Amazon PPC Manager

Most “PPC Managers” push buttons and hope for the best.

That’s not how we operate.

At Junglr, we build growth machines for 7 and 8-figure brands.

We turn complexity into clarity and strategy into scale.

As we grow, our machine needs more power.

We’re looking for a strategy-driven Amazon PPC pro who’s done with the status quo.

The Role

• Solve complex problems that stop brands from scaling

• Own PPC strategy for established, growth-focused e-commerce brands

• Work alongside a high-performance team that brings its A-game every day

Why Junglr

• Precision and transparency over fluff
• Focus on results that actually move the business
• Be part of an agency that truly knows how to scale Amazon brands

Step 1: Review the requirements
Step 2: Submit your application
Step 3: Start building growth machines

👉 Apply here:
https://lnkd.in/e4t6vShC

P.S. Know a rockstar Amazon PPC pro? Tag them and do them a favor.

⚠️ Please use the official application form only. DMs will not be reviewed.

Ad strategy that grows your brand, not Amazon’s bottom line | Co-founder @ Junglr

3 mistakes you’re making with your Amazon budget

(you won’t believe the 3rd):

Here’s the truth.

If your budget says $30/day
but spend sometimes doubles…

Amazon isn’t broken.

It’s doing exactly
what the settings allow.

Here’s what’s really happening.

Mistake #1: The 100% Overdelivery Setting

If you’re using a daily budget cap,
Amazon can spend up to 100% more.
$30 budget
$25 spent yesterday

That unused $5 rolls forward.

Today, Amazon can spend $60.

Amazon calls this a win.

I don’t.

That’s why we cap it at
5% or 20%.


Mistake #2: Thinking One Budget Covers Everything

Look closely.

“Sponsored Products budget cap.”

That means it does NOT include:

→ Sponsored Brands
→ Sponsored Display

So spend keeps climbing
even when you think you’re capped.


Mistake #3: Portfolio Budget Sharing

This one surprises most sellers.

Amazon now allows campaigns
inside a portfolio
to share unused budget.

One campaign underspends.

Another one takes the money.

Same portfolio.
More spend.
No warning.

Average sellers set budgets.

Great sellers understand the rules behind them.

If your spend surprises you..

you don’t control your PPC yet.

If your Amazon PPC bids aren’t driving more sales..

the problem probably isn’t the bid itself.

Most sellers spend hours adjusting bids.

Up.
Down.
Tweaked daily.

And still see flat conversion.

Here’s the reality.

Bids don’t create sales.
Targeting and timing do.

If the product to keyword fit is wrong, no bid will fix it.
You’re just paying more to stay invisible.

Timing matters more than most sellers think.

Peak season is over.
Buyer urgency drops.
Traffic intent shifts.

Conversion tightening doesn’t mean your ads broke.
It means behavior changed.

That’s seasonality.

The step most sellers skip is simple.

Start with the keywords that already convert.
Then let those keywords dictate your bids.

Not guesses.
Not gut feelings.
Just data.

For efficiency, Dynamic Bids Down Only works well.
Controlled.
Predictable.
Margin safe.

For growth, testing Up and Down can unlock scale.

Yes, CPC increases.
But we’ve seen conversion jump from 15% to 25%.

That leverage is real.

One warning.

Without intent, costs spiral fast.
Metrics look good.
Profit disappears.

That’s why we built an Amazon PPC audit tool.

Upload your bulk file and instantly see what’s really happening inside your account.

It reveals wasted spend, highlights what’s driving conversions, and shows where your bidding strategy helps or hurts sales.

100% FREE.
No email required.

Comment AUDIT and I’ll send it over.
(Make sure we’re connected)

Repost this if you know a seller who needs to see it.

Lower ACoS is the ultimate lie
in Amazon advertising.

I’ve seen it break accounts.

Here’s a real example
pulled straight from an audit.

ACoS went
from 35% → 25%.

Looks amazing, right?

Sales dropped 40% YoY.

Profit?

Didn’t move.

Not even a little.

What went wrong?

They optimized ROAS
and forgot how Amazon actually works.

Here’s the part most people miss:

ROAS is driven by
cost per click control.

Yes, bids matter.

But not alone.

It’s bids placement adjustments

bidding strategy segmentation.

They focused on one metric

and down-bid everything.

Including:

→ Market share campaigns
→ Ranking campaigns
→ Defensive terms

That’s how you lose.

When you stop protecting territory,
competitors move in.

Organic rank slips.
Visibility drops.
Sales vanish.

All while ACoS looks “better”.

That’s the trap.

If you hyperfocus on ROAS,

you can absolutely hurt an account.

I’ve seen it too many times.

The rule:

ROAS needs protection.

Ranking and market share campaigns
should never be thrown
into aggressive down-bidding.

Different purpose.
Different rules.

If you segment correctly,
you can have both.

Affordable total ACoS
AND scale.

But only if you stop treating
every campaign the same.

Quick takeaway:

→ Control CPC, not just ROAS
→ Segment branded vs non-branded
→ Protect market share campaigns
→ Stop optimizing yourself into a corner

Otherwise?

You hit targets
and kill the business.

What if I told you
being “technically” perfect

is no longer enough
to scale on Amazon?

Yesterday, I reviewed an account
running 100% static ads.

On paper?

Everything looked right.

Bids were dialed in.

Keywords were relevant.

Structure was clean.

Yet performance was stalling.

Most sellers would do
what everyone does.

Optimize harder.
Tweak bids.
Harvest more keywords.

That wasn’t the problem.

The real issue?

The creative hadn’t evolved.

The 2026 creative shift

Amazon quietly moved the goalposts.

Creative is no longer just branding.

It is now a direct performance lever.

And this is where most brands fall behind.

Video is no longer optional..

It’s the filter between winners and losers.

The video gold rush

Sponsored Products Video is still early.

Low volume.
High leverage for anyone who moves now.
The quality gap

Most brands are bad at video.

Even big ones.

They upload lazy slideshows.

Call it video.

Then wonder why ROAS tanks.

Amazon is copying what works on social.

But with one unfair advantage.
Buyer intent.

If your creative is boring,
Amazon doesn’t save you.
It filters you out.

The takeaway:

Stop treating video like an add-on
Start treating it like a lever

Master creative now to win cheaper traffic later

Win the click before CPCs explode

It has to work.

Still not taking video seriously?

Joe Nilsen

Machine Learning Engineer 🤖 Revolutionizing E-Commerce with AI

The AI conversation in e-commerce has been hijacked.By people who've never shipped a product. By "experts" who discovered LLMs last year and now talk like they invented them. By creators recycling the same surface-level garbage with a fresh screenshot.They're loud. They're everywhere. And they're getting real operators burned.I've spent 15 years in the Amazon trenches. Built and exited two brands. Architected the systems behind TraceFuse, Seller Strategies, and Selletek.Now I deploy AI inside real operations while the influencers are still workshopping their next thread about it.I'm not here to add noise. I'm here to end it.What I share is the operational reality of AI that nobody else will show you. What to automate and what to never touch. Workflows that hold up under real volume. The mistakes that sink teams. What's working now versus what's already dead.No fluff. No theory. No "exciting updates coming soon."If it isn't deployed, it doesn't exist.

Founder

Our vision is to make the world a more connected place through the art of cooking and passion for food. The platform was launched in 2015 and was built upon challenging the status quo. Over the years, Culinary Connect evolved into a movement celebrating cooking, food, and love. These core principles are the cornerstone of what the modern-day brand is built upon.

The Rufus optimization advice you're about to hear at conferences is mostly garbage.

We know because we tested it.

300 real Rufus queries. Category browsing, product comparisons, buying prompts.

Here is the gap between the slides and the data.

"A+ Content is critical for visibility"

Reality: A+ was referenced in 43% of queries. Bullets appeared in 85%. Reviews in 92%.

Rufus is not an A+ reader. It is a bullet and review synthesizer.

"Optimize images for AI shopping"

Reality: Rufus contradicted packaging claims in 26% of tests. When image text conflicted with backend data, Rufus ignored the image.

Backend truth beats visual marketing.

"The Overall Pick badge helps recommendations"

Reality: In most "best option" queries, Rufus recommended products without the badge. It runs its own value math.

Badges are decorative. Rufus runs calculations.

"More reviews equals more visibility"

Reality: Volume plateaued fast. Content did not.

We watched Rufus recommend a lower-review challenger because users complained the market leader's container was hard to open.

Rufus read the complaints. Then used them as evidence.

The hierarchy after 300 queries:

→ Reviews are the primary evidence layer
→ Bullets define differentiation
→ Backend attributes must match claims exactly
→ Value per unit is calculated automatically
→ Images are secondary and overridden when conflicting

Sellers optimize for the PDP.

Rufus optimizes for accuracy.

Frameworks are opinions. Queries are evidence.

I don’t follow AI trends in e-commerce. I create them.

Infographic titled "Inside the AI Shopper’s Brain: How Rufus Really Decides." This visualization maps the actual data hierarchy Amazon’s Rufus AI uses to generate answers, based on research of 100 queries, debunking common Amazon SEO strategies. The central element is a glowing blue neural network brain labeled "RUFUS AI SYNTHESIS ENGINE," illustrating how the generative AI processes information.

On the far left, a section titled "THE 'TRUTH' FUEL (Source & Frequency)" ranks the inputs Rufus prioritizes. At the very top, the most critical source is "REVIEWS (95%+)," accompanied by chat bubble icons, indicating Rufus relies heavily on them for "Sentiment & Specific Quotes". Below that is "TITLE & BULLETS (85-90%+)," with a document icon, showing these are the primary source for "Key Claims & Specs" and backend attribute confirmation. The third tier is "PRICE (80%+)," with stacked coins, showing Rufus uses this data for "Per-Serving/Unit Value" calculations, ignoring decorative badges. 

Amazon gurus are teaching AI image shortcuts that don't work in real catalogs.

The prompt template pitch goes like this: Here's a prompt. Copy it. Paste it. Get professional images in minutes. Save $2000 on photography.

That's the fantasy. Here's the reality.

I've been generating AI images for e-commerce since the day each image model was released. The learning curve is steep. Don't let anybody tell you different.

What actually makes it work:

→ Context files. You need to tell the model what your brand looks like, what you've done before, and what your competitors are doing wrong.

→ Example libraries. The more reference images you feed it, the faster it understands what you want. This takes time to build.

→ Specification depth. "Make it look professional" gets you garbage. "White background, 45-degree angle, soft shadow, lifestyle context showing kitchen counter with morning light" gets you usable output.

The upfront investment is real. Hours of setup before you get anything worth posting.

But here's where it flips.

Once you've built the context, once the model knows your brand, iteration drops from hours to minutes. What used to take a photoshoot takes a prompt.

That $2000 in savings is real. But only after you've built the skills and context that make it possible. Not some 8-page SOP.

The shortcuts don't exist.

Illustrated image of a man at a conference podium wearing a t-shirt that says "AI expert" with an exaggerated surprised expression and gesturing hands. The image is intentionally AI-generated with visible artifacts, including slightly distorted hand proportions and an overly stylized cartoon appearance. A blurred presentation screen and audience members are visible in the background. The image satirizes self-proclaimed AI experts teaching e-commerce sellers shortcuts for AI image generation that require significant skill and context-building to actually execute well.

"Amazon AI Experts" are celebrating basic MCP connections as if they'd just split the atom.

Over the last three months, we've deployed 40 Claude automations across the brands we partner with.

33 are still running in production.

The 7 that failed taught us more than any $900 course or summit ever could.

Connecting two APIs isn't engineering. It's page one of the documentation. It's the tutorial. Not the product.

Amazon AI that wins engagement on LinkedIn and gets applause at keynotes rarely reflects reality.

Here is what applied AI actually looks like in the wild:

• The Compliance Warden: Flags suppression risks before Amazon's bots wake up.

• The Review Miner: Scrapes reviews to find (and inject) the exact language buyers use.

• The PPC Sniper: Audits spend daily and tells us exactly where to cut budget.

• The Watchdog: Alerts us the moment a competitor shifts strategy.

Not concepts. Production systems doing the dirty work.

The difference between a Guru and a Builder is simple: One looks good on a slide deck. The other prints time and money.

This is the work that doesn’t fit into a 45-minute talk.

Comment "RIPOFF" and I'll send you a link to my $5,000 Mastermind where I read this post out loud.

Satirical cartoon illustration showing 12 caricatures of stereotypical Amazon and AI influencer personas with titles like Dr. Chip Silicon Amazon AI Expert, Guru Gary Prime AI Strategist, Tech Bro Tony Image Generation Expert, and Nancy Neural Deep Learning Diva, each wearing branded merchandise and holding coffee mugs, representing the gap between LinkedIn AI gurus and actual practitioners who build production systems

Claude skills are the most underrated feature in AI right now.

Most people are still treating Claude like a chatbot. Ask a question, get an answer, move on.

That's not how you build systems.

Skills are different. You package context, examples, and instructions into something AI can call on when needed.

→ Context Retention: Your brand voice persists across every conversation
→ Task Velocity: Skip repetitive setup, jump straight into high-value work
→ Standardization: Your quality standards are enforced automatically

The fundamental concept here isn't going away. Models will get smarter. Interfaces will evolve. But the pattern of structured context packaged for AI to reference on demand is a permanent infrastructure.

Every organization serious about leveraging AI needs to invest time in building these.

Our team has been using a platform we built specifically for creating skills. Ten days in, the outputs are stunning.

I'm sharing access by the end of this week. Let me know if interested.

MajestIQ Claude Skills Builder platform interface displaying a no-code AI skill creation tool on dark background. Main headline reads Build Powerful AI Skills in Minutes with gold accent on Powerful AI Skills. Subheadline explains the process: Create custom AI Skills step by step, define the persona, upload your knowledge, set the rules, and export ready to use skill files. Three primary action buttons shown: Start from Scratch, AI Generate, and Use a Template. Below the buttons is a View Example Skills link. Three feature cards displayed at bottom highlighting core capabilities. First card Context Retention with brain icon explains Your AI remembers your brand voice SOPs and preferences across every conversation. Second card, Task Velocity, with a lightning bolt icon, states Skip repetitive setup and jump straight into high-value work with pre-configured expert.

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The Battle

Elizabeth Greene

Joe Nilsen

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The Battle

Elizabeth Greene

Joe Nilsen

Followers

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Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Elizabeth Greene's LinkedIn Performance

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Performance ScoreElizabeth Greene's LinkedIn Performance