My work
As a strategist and writer, it's my job to determine which stories to tell and how to tell them — then to measure their success. Curious about my work? Check out a few of my past projects.
How I shifted an SEO strategy to focus on quality traffic — not just any traffic
When I joined Commerce Cloud, the SEO strategy was built around broad awareness: long-form definitional content targeting generic, high-volume keywords. This approach successfully increased website visitors by 40% year over year, but much of that traffic was shallow. Most people who landed on our pages simply wanted basic definitions, but had no real intent to evaluate a commerce platform. When folks did convert, a large portion of them inevitably ended up as unqualified leads (which meant the sales team was very unhappy with the marketing team).
I recognized the need for a content strategy that prioritized differentiation over volume. Rather than competing for broad, commoditized search terms, I shifted our focus to helpful, specific "how-to" content that addressed real problems our audience couldn't easily solve elsewhere.
To achieve this, I audited our existing content library, keyword performance, and user behavior to identify where we were competing for attention versus where we could own a topic outright. I worked closely with sales, campaigns, and product marketing teams to replace generic definitional pages with in-depth guides, comparison charts, and interactive tools built around the specific questions high-value prospects were actually asking.
The results validated this approach: 90% of our targeted keywords ranked on page one, driving a 104% increase in organic traffic to our product pages. This shift proved that prioritizing differentiation and usefulness over sheer keyword volume is a more durable way to drive both visibility and conversion.
How I created account-based content strategies to achieve measurable impact
Attributing sales and revenue to specific content assets is one of the biggest challenges in content marketing. It’s a persistent pain point for marketers across industries. I approached this challenge head-on with account-based content strategies.
Recognizing that personalized content fosters stronger engagement, I introduced an account-based content strategy (ABCS) to target key enterprise accounts. I partnered with campaigns and product marketing teams to pinpoint high-value accounts and designed bespoke content journeys for each. These journeys included tailored whitepapers, articles, and interactive ROI calculators, all designed to tackle the unique challenges of each client and position our product as the ideal solution.
For top retail accounts, our customized funnel included a drip campaign full of content that addressed hyper-specific technology and scalability hurdles. By the end of the quarter, 40% of targeted accounts completed form fills for gated content and we secured a $1.2 million contract renewal.
By aligning content strategy with account-based principles, I’ve helped our team move beyond vanity metrics and focus on meaningful engagement that drives revenue.
How I use primary research to create
Original research is a goldmine for content marketers when leveraged effectively. A single, well-executed report can fuel an entire year’s worth of content—and that’s exactly what I achieved with our biennial State of Commerce Report.
To ensure our team maximized the value of this flagship piece, I developed a hub-and-spoke content strategy paired with a year-long content calendar. The strategy encompassed a wide array of formats, including blogs, short-form videos, and infographics, to engage diverse audiences. Beyond customer-facing assets, I created sales enablement materials—such as tailored decks and talking points—aligned to specific customer segments, ensuring alignment across teams.
This comprehensive approach not only amplified the reach and longevity of the report but also drove significant business results, generating $15 million in revenue. This success highlights the transformative potential of strategic planning in content marketing, proving that thoughtful execution can turn a single asset into a powerful revenue driver.
How I fueled revenue for an entire year with one well-executed research report
Original research is a goldmine for content marketers when leveraged effectively. A single, well-executed report can fuel an entire year’s worth of content. This is how I approached the project for our biennial State of Commerce Report.
To maximize the value of this flagship piece, I designed and implemented a hub-and-spoke content strategy paired with a year-long content calendar. The strategy encompassed a wide variety of formats, including blog posts, short-form videos, infographics, and even sessions at live events. This holistic plan ensured engagement across diverse audience segments. To further align efforts, I developed sales enablement materials, including tailored decks and detailed talking points, customized for specific customer segments and aligned to our most crucial sales initiatives.
This comprehensive approach amplified the reach and longevity of the report, driving significant business outcomes. Over the course of a year, the strategy directly generated $15 million in revenue, brought in valuable leads, earned more than 50 media mentions, and fueled citations in LLMs. This success underscores the transformative potential of strategic planning in content marketing. Thoughtful execution can turn a single asset into a powerful revenue driver.
How I use primary research to create
Original research is a goldmine for content marketers when leveraged effectively. A single, well-executed report can fuel an entire year’s worth of content—and that’s exactly what I achieved with our biennial State of Commerce Report.
To ensure our team maximized the value of this flagship piece, I developed a hub-and-spoke content strategy paired with a year-long content calendar. The strategy encompassed a wide array of formats, including blogs, short-form videos, and infographics, to engage diverse audiences. Beyond customer-facing assets, I created sales enablement materials—such as tailored decks and talking points—aligned to specific customer segments, ensuring alignment across teams.
This comprehensive approach not only amplified the reach and longevity of the report but also drove significant business results, generating $15 million in revenue. This success highlights the transformative potential of strategic planning in content marketing, proving that thoughtful execution can turn a single asset into a powerful revenue driver.
How I optimized content strategies to stay relevant in an AI-first market
As LLM platforms became the go-to source for information, I read the tea leaves and quickly realized that zero-click searches would erode two metrics I often used to define content success: organic traffic and funnel conversions.
My old approach assumed a person would type a question into Google, click a result, land on our site, and convert. But as more people used ChatGPT, Perplexity, and AI Overviews to get answers without ever clicking through, I knew it would be a mistake to bury my head in the sand and continue optimizing for the old funnel.
To get ahead, I rebuilt our content strategy around a new journey. My main question: If someone never visits our website, how do we still earn their trust, stay in the consideration set, and show up in the sources an AI model chooses to cite? The new goal was to become a source worth citing, and stay visible in the places AI already looks.
I focused the strategy on three pillars.
Original research to earn citations in LLM search
LLMs don't cite marketing copy. They cite data. If you want to show up in an AI-generated answer, you need to be the primary source behind a stat, not the twentieth site repeating it.
This is the thinking behind the State of Commerce research report. Instead of writing about commerce trends, we generated them by surveying thousands of commerce leaders and layering in behavioral data from 1.5B+ transactions. That combination made the data genuinely new, not an aggregation of what already existed.
The result was a strong lead generation asset (it contributed to $15M in influenced pipeline) and a strong reference point. Other publications, analysts, and even competitors began citing our numbers. Since the underlying data was proprietary, it persisted in AI-generated summaries long after the initial launch.
Expert bylines that give people a reason to leave the search platform
One thing an AI output can't give you is a genuine, human point of view from someone who has qualified, lived experience in a niche subject. So I shifted a meaningful share of our time and resources away from generic explainer content (the stuff most likely to get summarized and skipped) and into first-person opinion pieces, how-to guides, and thought leadership written under real names with real expertise.
This helped us build something AI summaries can't: a recognizable voice and a reason to trust the company behind it.
Publication on strategic third-party channels to attract the right audience
The hardest shift was actually mental, not strategic. We chose to publish articles on a platform we didn't own and couldn't fully control. That felt risky. Years of training and experience told me to drive everything back to owned properties. But the data told a different story. A large share of LLM platforms cite LinkedIn disproportionately for business and B2B queries. If that's where the models look for content, meeting the audience there matters more than preserving control over the destination.
So we treated LinkedIn as a distribution channel in its own right, not just a promotional afterthought. Weekly articles on product capabilities and innovation gave us consistent visibility with the exact audience evaluating competitive solutions, and it positioned us to be part of the answer when someone asked an AI tool to compare options in our category.
The results:
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Blogs bylined by internal product experts performed 3x higher than non-bylined, on average across page views, click-through rate, time on page, and referrals to product pages.
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Our flagship research report was cited as a source in 50+ external articles and multiple AI-generated search summaries.
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200% growth in AI referral traffic from platforms including ChatGPT, Claude, and Perplexity.
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150% year-over-year increase in AI Overviews
How I define (and report) content success
I firmly believe that it’s time for content marketers to move beyond vanity metrics like page views, rankings, and the number of content assets we create. These details are important, but the right KPIs will always tell a story about the demonstrable business value of content. Here’s what I mean.
Each quarter, I report on my content team’s page views and rankings, but the bulk of my presentations focus on monetary value, such as:
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Cost saved on PPC
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Organic form fills
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Organic referrals to product pages
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Marketing-driven pipeline from gated assets
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Leads and opportunities from gated assets
To get this data, I use Tableau and Looker Studio dashboards. I’ve also developed close working relationships with other teams that play a role in content success, like campaigns, SEO, field marketing, and social media. This gives me a holistic view of how my team’s content performs in the market across different channels and tactics. Here’s a glimpse at a few of my quarterly reporting slides, so you can get a feel for how I think about content success:
How I really feel about AI in content marketing
It’s time for content marketers to stop treating AI like the enemy. It’s okay to feel threatened by AI. (Honestly, if you’re a content marketer and you don’t feel at least a little threatened, you’re probably not paying attention.) Regardless of how you feel about the technology, it’s here. We still need to learn how to live and work with it.
Hint: If you’re spending three hours writing a lengthy prompt in hopes of getting an output that’s exactly what you want, you’re doing it wrong. Also, I don’t know who needs to hear this, but it’s time to stop talking about the em dash. There are more important things at stake when it comes to AI.
I don’t have a crystal ball and I don’t claim to know how all of this will shake out, but I’m trying to adapt in a way that feels authentic. This is what my path has looked like so far. If you want to have a friendly working relationship with AI, here’s what I suggest.
1. Get curious.
Even if you think AI is soulless, scary, and evil, learning more about the technology will only help. At the very least, it will ground your perspective in fact rather than fear. What do the experts say about AI’s effect on the economy and the job market? How do large language models actually work? What datasets are they trained on? (Spoiler alert: This part is scary.) Who are the powerful folks making the big decisions? Are there any adults in the room?
My curiosity has led me down lots of rabbit holes. I devour podcasts, articles, and books about generative AI, and what I’ve learned impacts the way I use it. For example, I learned through my extracurricular research that chatbots are prone to sycophancy because LLM training involves human beings rating responses. (So, if you’re using AI to affirm the quality or feasibility of your content marketing ideas, take the chatbot’s responses with a grain of salt.)
2. Learn to adapt.
Stories are fundamental to human nature; they shape what we believe and how we act. AI might change a lot of things, but the power of narrative won’t be one of them. (Even Steve Jobs said the most powerful person in the world is the storyteller.)
What will change? The channels where we tell our stories, the way we tell them, and the kinds of stories that will be perceived as most valuable. Here’s what I’m prioritizing:
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Original research: Unfortunately, misinformation and slop are byproducts of generative AI. Truth and data have never been more valuable. Lean into facts and original research. Get ridiculously good at telling and amplifying true stories. This is especially important when you consider that AI search tools primarily cite original data (if they cite anything at all).
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Customer stories: Case studies have always been the crown jewel of content marketing. They’re detailed accounts of actual people using (and hopefully loving) your product, and these stories are unique to your business. They require human sources, and they can’t be faked. At least not ethically.
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Deeply niche topics: Zero-click searches keep swallowing traffic for simple questions and definitional queries. Maybe the silver lining of all this will be the end of surface-level, generic content that none of us ever wanted to create in the first place. Now, we can focus more on assets that answer deeply important questions and guide consequential decisions. You know, the kinds of questions people don’t fully trust AI to answer.
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Bold opinions: AI is painfully vanilla; It flattens voices into a neutral average. Showing up with a strong (but authentic) point of view will be a signal through all the noise.
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Emotional resonance: Empathy has always been a content marketer’s superpower, and it’s the backbone of emotional resonance. As AI makes it easier and cheaper to generate content at scale, it will become increasingly difficult to capture and hold audience attention. But not for you. Content marketers, you’ve been training your whole career for this moment.
3. Tinker around.
Give yourself permission to play. Pro tip: Don’t treat AI like copywriting is its only function. In my humble opinion, drafting a simple blog post is a pretty unimaginative way to use such a powerful tool.