Ross Hudgens

SEO Manager

Siege Media

We drive organic growth with SEO, content marketing and PR. Past and current clients include Intuit, Zendesk, Casper, TripAdvisor, Shutterfly, Asana and more. 

Notable achievements: 
• Named to Inc. 5000 6x 
• Named to Inc's Best Workplaces 2x
• $100,000,000+ in Lifetime Revenue Generated
• Named a Fastest Growing Company in San Diego 6x
• Named Top 25 B2B Digital Marketing Influencer by Clutch
• Named Top 10 Most Influential Content Marketer by BuzzSumo

Founder / CEO

Member

Full Beaker, Inc.

•	Lead SEO initiatives for Full Beaker, developing web properties from initiation to generating thousands of search referrals monthly across several verticals, including but not limited to insurance and mortgage. Dictated keyword research, content strategy, and link building strategies for Full Beaker's portfolio of websites.
•	Integral part of a team that built Full Beaker from inception to a multi-million dollar, profitable company in under two years. 
•	Developed PPC campaigns in highly competitive mortgage industry.
•	Supported affiliate and business development strategy to rapidly scale the business in the course of two years, utilizing inbound marketing strategies to help improve profit-per-lead and overall lead supply-and-demand levers. 
•	Grew SEO traffic over 500% over the course of two years, leveraging scalable link building strategies to diversify efforts over many domains and still achieve results. 
•	Supplied recommendations for CRO strategies which improved site performance (cumulatively) over 500% across Full Beaker's portfolio of websites.

MediaBoost - Billy.com

•	Head of all SEO operations for MediaBoost. Leads the SEO development of MediaBoost’s multiple properties, from infancy into maturity.
•	Manages an SEO support team of two full-time content writers as well as two developers, half of which are located in Israel, in building out MB properties to match current SEO best-practices. 
•	In charge of all SEO processes as it comes to link building and SEO strategy, utilizing network contacts, creativity and experience to build links, implement best practices, and maintain competitive advantage.  
•	Oversees social media development, providing Facebook, Twitter and blog recommendations to provide growth and build community to meet long-term monetization goals.

Single Grain LLC

•	As Single Grain’s first employee, helped build the company from a base of three clients to a height of twenty. Developed all of Singlegrain’s internal SEO processes, including client reports, link building, scaling strategies, as well as all standard operating procedures. 
•	Analyzed search problems and formulated creative solutions to launch and build SEO campaigns. Performed link building, keyword research, on-site and off-site optimization, and other relevant tasks pertaining to an account’s SEO needs.
•	Managed other employees. Trained new hires on SEO and internal processes. Supervised new employees and nurtured growth and development in the workplace.
•	Wrote all content for the Single Grain blog and Twitter accounts, while managing a personal business-related account. Utilized these accounts to promote expertise and build the Single Grain brand.

Senior SEO Analyst

I’m the founder and CEO of Siege Media. We’re dedicated to helping great brands scale through AI and Google-first SEO, content marketing, and PR. 

Siege Media has been honored with inclusion in the Inc. 5000 list six times and recognized as one of Inc.'s Best Workplaces.

And we’re so proud to collaborate with some of the world's leading brands, including Adidas, Airbnb, Angi, Asana, Audible, Casper, Healthline, HubSpot, Instacart, Intuit QuickBooks, Intuit TurboTax, Norton, Quicken Loans, Shutterfly, The Zebra, TripAdvisor, Williams Sonoma, Y Combinator, Zendesk, and many more.

We grow great brands with SEO-focused content marketing. Past and current clients include Intuit, Zendesk, Casper, TripAdvisor, Shutterfly, Asana and more. 

Notable achievements: 
• Named to Inc. 5000 6x 
• Named to Inc's Best Workplaces 2x
• Named a Fastest Growing Company in San Diego 6x
• Named Top 10 Most Influential Content Marketer by BuzzSumo

Siege Media is excited to become an official partner of Women in Tech SEO!

For years, we've heard great things about their thriving community from Siege team members and also, direct members of the group.

As a company with a female-dominant team (leadership+company wide), it was a no brainer to support such a great group as we head into 2026 and beyond.

I'm a special fan of Areej AbuAli and Erin Simmons (they/them), two leaders behind the scenes who run the organization with class and polish.

We look forward to supporting their events and partnering on content initiatives (such as our upcoming trends report) as we head into the New Year. 

If you haven't heard of Women in TechSEO, highly suggest checking them out!

CEO, Siege Media | SEO for Google + AI, Content & PR

This is the exact process we use to prioritize content for LLM visibility:

First, input the core prompts we care about into a tracker, by creating “what is the best X” using our full set of products and solutions. 

For example, “what’s the best running shoe for wide feet”, or “best organic growth agency for fintech”.

Transactional terms are all that matters, and having those covered for our full product suite is the correct way of pushing visibility towards the things that convert.

From there, identify what URLs are sourced most often across that set of prompts. 

This set of URLs, and how often they’re sourced, is our prioritization scorecard.

We’re looking for “companies like us” in the list. If we see them, that means we can directly create content that has a chance of replacing (or adding to) what’s cited here.

Using this information, we can then weight the pipeline we’re seeing from LLMs so far against SEO data for these same topics. 

If a highly sourced URL – in an industry seeing significant LLM usage so far – is also in high demand on Google, it’s a no brainer to prioritize that content highly in our roadmaps.

“I've been there 10 years, have filed 1,000 JIRA tickets, and they’ve implemented maybe 5 of them.”

If you work in enterprise SEO, you’ve heard some version of that. Maybe you’ve said a version of it.

The thing is: that implementation rate isn’t destiny.

It’s usually a mix of misaligned strategy, weak business cases, and poor communication design. And sometimes, issues with company selection.

At Tech SEO Connect (Durham NC, Dec 4th-5th), I’m excited to be giving a talk on "The SEO Execution Gap: How to Get Recommendations Deployed in Complex Environments".

I'll be sharing a proven playbook from 13+ years of agency experience working with Fortune 500 companies and high growth startups.

See you in Durham in a few weeks?

Siege Media’s Digital PR department is growing fast!

We’ve been excited to bring on some talented, specialized resources around data journalism and PR in the last few months, with our VP, PR Carrie Van-Brunt Wiley leading the charge.

Some of the talented people we’ve brought on:

Lane Gillespie - Data Journalist 
Ryan Flanigan, CCC - Data Journalist
Taylor Lynch - Digital PR Specialist
Fontaine Gwynn - Digital PR Specialist
Abby Hartness - Senior Digital PR Specialist

… with more on the horizon! 

I’m excited to see how these specialists accelerate results for our clients in the days to come.

"Traffic is down for everyone."

This can be trumpeted as an excuse for a poorly performing SEO program in 2025.

Lots of AI-powered programs I see with a little less traffic than everyone else, but it feels good because publishing volume is up and there's a valid explanation.

If you check the metrics and you see:

- Organic sales are significantly down
- AI visibility is notably behind competition
- Rankings are declining (especially for BOFU terms)

Using that as an excuse is not a valid one.

Yes, it’s reasonable for traffic to be down, especially in B2B. 

But there are layers under that very worth digging into to verify your change is based on the macro, not your own strategy. 

And that's not a valid excuse for every business (or SEO) to make.

ChatGPT is the most popular LLM, but is it the best?

We analyzed more than 2.3 million user sessions across five leading LLMs to get a better sense of which LLM is most effective at sending high-quality traffic.

In our data, ChatGPT is actually the worst of the five, at least based on the engagement rate deriving from traffic it sent to websites we track.

ChatGPT notably had the highest sample size by far (~1.9M visits across our sample), but it's notable to see the other five heavyweights actually outperform from traditional user metrics.

This plays off something we've been seeing recently, as well -- ChatGPT's lead from a quality perspective seems to be shrinking, and this pairs with actual declines in traffic share as well.

It’s possible this engagement rate portends a slow shift to other LLMs. The way things are looking to me, I’d expect Gemini to take the lead.

From a business perspective, getting Pro access free for our entire team on G-Suite makes it a no-brainer choice, and the professional “feel” of the responses is something I personally prefer as well.

Do you need a content engineer? 

My take: no, but you do need content engineering.

What’s the difference? In content-driven workflows and SEO-driven workflows today, there are many opportunities for automation. 

But the name “content engineering” implies it directly (and significantly) flows through to the writing itself. 

A better definition, and one we have employed with our own version of this role, is a head of automation. 

This person can deploy leverage where it’s most impactful: communication, reporting, updates, competitive intelligence, and etc. But I’m not sure that is adequately summed up by the term “content engineer” in particular, which feels more precise to the writing workflow itself. 

Also, if that role were to exist in isolation, I’m not sure there’s enough work within that process to warrant that title in particular, *unless* it’s in aim of high volume, low quality writing.

This was the crux of the great podcast conversation I had with Josh Spilker of AirOps, which has a great tool that in many ways is building on that idea. 

Josh has been at the front of this “content engineer” movement, and like the GEO/AEO/AI for SEO debate, I think we’re all mostly caught in a naming convention back and forth here, while mostly agreeing on the same things.

Do you really need an SEO audit? Or did the market just move on without you?

We looked at a website recently with a market dominant position in a low price market selling information.

Their competition? A changing perception of expected cost and ChatGPT.

Their traffic (the blue line) has dwindled slowly over the past few years.

Their free SEO competition (the orange line) has slowly increased on the same timeline. And there's also ChatGPT.

Unseen, Reddit, a “frugal” disseminator of information, has only accelerated this discovery cycle as free competition has emerged around them. 

So they came to us wanting an audit. 

And like everybody, there’s generally room for improvement.

But when people want an audit, they are often trying to completely refill an empty bucket. Sometimes, only drops can be added back in rather than the original amount, as the competitive environment has been rewritten.

This situation is all the more common in the last two years, especially in markets where information is sold at low cost.

Part of being an SEO is reporting on and understanding the macro, not just a title tag or 404 that needs to be fixed. 

Good SEOs don’t just tell you what to change on the page.

They tell you when the game itself is now played differently.

Programmatic SEO is not a blog strategy.

Programmatic SEO successfully exists in a few forms:

1) Long-tail landing page use cases where the product brings the value, not the copy itself.

2) Situations where "the product" is the UX of the page, and that UX is world-class.

At least, those were the core points programmatic SEO expert Matt Bowers (ex-Zapier, Zillow) brought on our podcast discussing how this approach has evolved in the age of AI.

In short, AI (or programmatic), can do something useful when you give it something great. 

But it's not as useful supplying 1,500 words of copy on an undifferentiated blog design. That's not true programmatic. 

If we think about it correctly, programmatic is essentially the 80% in the equation -- product that took months if not years to build, that then has an extra 20% of value brought from secondary sources (AI, or third party data in situations like real estate) that fill out the equation. 

Even better when you bring this all together. 

A great product, great landing page UX, and a well-considered use of third party data or AI to scale up the operation. 

This was one of our most popular podcasts of the past few months, so the data suggests it might be worth checking out if you're considering a programmatic approach.

(There was a pie-in-the-face moment, too: we praised the AI-driven site Greg(dot)app and then shortly after realized it had gotten hit by a Google update.)

If you're nervous about employing "best X" strategies on your own site, "X alternatives" posts are a great place to start.

1 - You don't have to explicitly call yourself the best.

2 - The article doesn't have to be deeply adversarial, and can instead softly focus on the feature differences without being disparaging to the original site.

3 - There's little argument as to why these shouldn't exist on our sites beyond nervousness of controversy in mentioning competitors.

Given point two -- which can be lighter in tone than even "US vs THEM" posts, this is a great, high impact way for companies to wade their toes into a BOFU approach.

Once the company sees the potential impact (as well as additional lift on LLMs), that will likely open up the gates for scaling the strategy.

Deb Mukherjee

Founder, AI x Ecom • DTC AOV & CRO Consultant • Ex-Numeral (YC23), Wonderment

Hello there! Thanks for perusing my profile.

I'm Deb, a SaaS growth leader with ~10 years of experience working with 40+ orgs across the globe. 

Currently, I'm building Blync AI, the revenue acceleration platform for ecom stores around the globe.

A few of my humble brags:

- Consistently added $500k in pipeline revenue through organic channels every month at Numeral
- Grew Staytuned's revenue by 33% through organic marketing strategies
- Launched and scaled Wonderment's agency partner program to 10+ agencies in the first two months
- Accelerated DelightChat's launch and scaled the company to 50 paid customers in the first six months of operation

P.S.: Read the individual experiences to know more.

Besides that, I have managed FT team members, freelancers, and agencies to get stuff done while coordinating with different departments to launch campaigns and drive ROI. 

Want me to help you launch and scale your SaaS marketing ops? I also help Seed and Series A startups as a Fractional CMO. 

Drop a line at debgotwired@gmail.com or DM me here on LinkedIn.

Fractional Growth Marketer & Content Strategist - B2B SaaS Brands

I'm helping growth-stage startups like Triple Whale, Shopify Retail, DTC Newsletter, Prive, and a few others with content that's centered around search intent but also optimized to rank on the big G. 

- Increased site traffic by 120% with a handful of articles in just 3 months
- Helped several high-difficulty keywords to rank on #1 
- Wrote ad copies that created $10k in sales pipeline 

Want similar results for your ecomtech or B2B SaaS company? Connect with me for a free 30-min consultation.

Every PM I’ve talked to says the same thing: the dashboard is open all day, but the real thinking happens over coffee (metaphorically, of course).

Dashboards used to feel like control; you could see signups, retention, activation, everything in one place. 

"Used to" is the key phrase here. Nowadays, it's all noise. 

Every metric has five definitions, every team tracks them differently, and no one fully trusts what they’re seeing.

You know the biggest problem with dashboards? They assume your product and your definitions don’t change. 

But modern products evolve super fast - new funnels, new pricing, new cohorts, new everything, every other week. The moment those change, our dashboards start lying by omission.

So we rebuild them - new SQL, new filters, new dashboards that tell the same story with slightly different logic. The irony is that the more data visibility we get, the less clarity we have.

What we need is analytics that adapt to the change; systems that understand what you’re actually asking, interpret context, and explain the reasoning behind the numbers.

Dashboards can tell us what happened, but we need tools that tell us why in the same breath.

Founder, Stealth <​Data x Gen AI x Product​> • Product & Growth Advisor for AI Companies • Ex-Numeral (YC23), Wonderment

Your best user might be a state-sponsored hacker.




Last month, Anthropic caught a Chinese espionage campaign targeting 30 organizations. 

The attackers used AI to automate 80-90% of sophisticated cyberattacks, with only 4-6 human decision points per campaign.

Here's what caught my attention: Anthropic detected this through "suspicious activity" in their product usage data.

Not a security breach, but usage patterns that didn't look right.

Then they spent 10 days investigating before taking action. Ten days of active attacks while they figured out the scope, mapped targets, and built evidence.

Could your analytics do the same?

Most product teams can tell you:

- DAU/MAU ratios
- Feature adoption rates
- Funnel conversion metrics

But can you:

- Reconstruct what a specific user did 60 days ago?
- Detect when individual usage patterns shift?
- Identify coordinated activity across accounts?
- Answer "what is this user trying to accomplish?"

The gap between aggregate dashboards and investigation-ready analytics is massive.

I wrote about what the Anthropic case teaches product teams about building analytics that can actually detect misuse.

The attackers generated "thousands of requests per second." To your product analytics, this just looked like a power user.

The question isn't whether your AI product will be abused. It's whether you'll notice.

Read the entire article here >

Monday morning. Your inbox: "Why was my account banned? I've been using your API heavily for legitimate testing. I need access restored immediately fo

Open article: Your Best User Might be a State-Sponsored Hacker: A Product Analytics Wake-Up Call by Deb Mukherjee • 9 min read

Your Best User Might be a State-Sponsored Hacker: A Product Analytics Wake-Up Call

𝗠𝗼𝘀𝘁 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝘁𝗲𝗮𝗺𝘀 𝗮𝗿𝗲 𝘀𝘁𝗶𝗹𝗹 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗿𝗼𝘂𝗻𝗱 𝟮𝟬𝟮𝟯 𝗺𝗼𝗱𝗲𝗹 𝗮𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻𝘀. 𝗧𝗵𝗮𝘁 𝘄𝗶𝗻𝗱𝗼𝘄 𝗶𝘀 𝗰𝗹𝗼𝘀𝗶𝗻𝗴 𝗳𝗮𝘀𝘁.

Gemini 3's (by Google DeepMind) new benchmarks do not just improve scores. They cross reliability thresholds that change what product and data teams can actually automate.

𝐓𝐡𝐞 𝐬𝐡𝐢𝐟𝐭 𝐭𝐡𝐚𝐭 𝐦𝐚𝐭𝐭𝐞𝐫𝐬

Teams currently spend hours stitching together logs, session replays, and scattered screenshots when something breaks. Results on ScreenSpot, Video MMMU, and OmniDoc show that models can now interpret these inputs directly. 

The messy step of converting real-world evidence into structured data becomes something the model can finally do.

Example: 

Checkout conversion drops eight percent. Instead of waiting for an analyst to pull funnels, join tables, and review replays, a PM pastes a screenshot of the error state and asks what failed. The model reads the interface, matches it with logs, and traces the root issue. This is already possible.

𝐖𝐡𝐚𝐭 𝐣𝐮𝐬𝐭 𝐛𝐞𝐜𝐚𝐦𝐞 𝐯𝐢𝐚𝐛𝐥𝐞

1. Investigation tools that work on raw evidence

Performance on CharXiv and MMMU shows that models can read screenshots, PDFs, charts, and fragmented inputs without preprocessing. Tools no longer need everything piped into a dashboard. They can use whatever evidence the team already has.

2. Real root cause analysis through conversation

Better multistep reasoning lets models form hypotheses, test them, reject or validate, and continue deeper. PMs can now explore churn shifts, funnel breaks, or usage anomalies through natural language instead of SQL or tickets in a queue.

3. Agents that can run multistep workflows without constant supervision

T Bench and Terminal Bench show stable execution with memory. Workflows like RCA summaries, alert triage, experiment documentation, data quality checks, and internal knowledge upkeep can become agent-first rather than human-first.

4. Investigations that stay coherent over long horizons

Vending Bench proves that the model can hold context for extended tasks. Teams can now run multi-day investigations without losing the plot every session.

𝐓𝐡𝐞 𝐩𝐚𝐭𝐭𝐞𝐫𝐧 𝐭𝐡𝐚𝐭 𝐢𝐬 𝐞𝐦𝐞𝐫𝐠𝐢𝐧𝐠

Teams are now redesigning their entire incident loop from “human interprets, then queries” to “model interprets and queries, human validates.” 

The work shifts from slow, sequential steps to parallel investigation, where the model handles the grunt work across multiple data sources.

𝐖𝐡𝐚𝐭 𝐜𝐡𝐚𝐧𝐠𝐞𝐬 𝐧𝐞𝐱𝐭

The bottleneck is whether your workflows are designed for an AI native world: from batch to real-time, from reactive to proactive, from human in the loop to human on the loop.

Teams that redesign their systems around this shift will compound advantages over those who just plug AI into existing steps.

What workflow in your stack would look completely different if you rebuilt it with these capabilities in mind today?

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Ross Hudgens

Deb Mukherjee

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The Battle

Ross Hudgens

Deb Mukherjee

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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);}Ross Hudgens's LinkedIn Performance

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