Kacyn Goranson

Exceptional Marketing & Consulting

Fractional marketing consultant and strategic lead providing assistance to multiple businesses at different stages, encompassing activities such as account-based marketing, operational process design, technical setup, and go-to-market strategy. 

Contracts span across various industries including real estate, recruiting, technology and marketing.

➥ Plan, execute, and optimize account-based marketing campaigns, resulting in increased target engagement and conversion.
➥ Direct all aspects of product marketing and positioning, including content development and in-depth persona research, to enhance market presence.
➥ Orchestrate successful product launches by conducting thorough market research, crafting strategic positioning, and developing effective go-to-market strategies.
➥ Develop and implement data-driven marketing strategies, utilizing analytics and market research to make informed decisions and drive growth.
➥Build, launch and optimize digital marketing efforts across various channels, including SEO, SEM, social media, email marketing, and content marketing, significantly boosting customer acquisition and engagement.

Vice President of Marketing | Demand Generation | Product Marketing

Worksuite

Developed and executed a comprehensive marketing strategy to increase brand awareness and generate revenue growth, including rebuilding the MarTech stack, creating a public relations plan and establishing formalized customer and internal communications strategies. 

➥ Drove a 52% increase in ARR value of opportunity creation in Q2 by boosting MQLs from Trials by 33% QoQ and MQLs from Demos by 86% QoQ through UX/UI enhancements and targeted paid search and social ads within our ICP.
➥ Collaborated with SDRs to develop weekly persona-focused messaging cadences, increasing MQL to SQL conversion rates from 10% to 30% over four months.
➥ Partnered with Finance to establish a 'Proxy' for best-fit customers and prospects, optimizing marketing and sales spend and efforts.
➥ Shifted from a lead-based to an account-based sales motion, targeting high-value accounts with higher annual revenues, and trained Marketing, BDRs, and Account Executives in this approach.
➥ Integrated the MarTech stack and developed executive-level dashboards and reporting systems for KPI visibility.
➥ Implemented internal communication strategies in partnership with People Success, enhancing employee engagement.

Vice President Marketing | Revenue-Driven Strategy | Demand Generation 

RevSure AI

Owned all go-to-market strategy planning, execution and implementation for this seed-stage start-up using AI to forecast pipeline and accelerate revenue, I drove tangible results in a short period of time. Partnering with Sales to achieve goals targeting $1M in revenue. 

➥ Achieved a 203% month-over-month increase in qualified lead creation through the implementation of a research-based marketing and content strategy.
➥ Secured executive-level alignment on the RevSure brand and value proposition, defining target personas, ideal customer profiles, and product messaging.
➥ Enhanced website SEO and user experience, driving demand among key audiences and accounts.
➥ Led and optimized all demand-generation activities, including PR, events, content marketing, SEO, and paid search, ensuring alignment with budget efficiency and revenue goals.

Head of Marketing, Marketing Operations & Demand Generation | Brand Development | Lead Generation

Knak

Part of the executive leadership team in a contract role for this Series-A MarTech codeless campaign creation platform built for enterprise marketing teams, I drove strategic initiatives to position the company for long-term success and scaled the brand across the SaaS industry and to key accounts. 

➥Aligned marketing operations and demand generation teams to create a cohesive and effective go-to-market strategy, achieving a $3M revenue target and generating 28% of new opportunities from the target ICP.
➥ Launched an Account-Based strategy with BDR and Sales teams, including a 6sense advertising campaign, delivering a 44x return on program investment to revenue created.
➥ Directed the prioritization of marketing initiatives, establishing scalable processes for future growth and efficiency.

Vice President of Growth Marketing | Series-A MarTech | SaaS Marketing | Strategic Initiatives

CM Group

I came on board this global pioneer in relationship marketing (now rebranded as Marigold), providing tailored, industry-specific martech solutions to a growing portfolio of thousands of businesses, and was promoted to Vice President of Marketing within 3 years, managing a team of 20. I played a key role in shaping the marketing organization's design and infrastructure, overseeing a full marketing budget across 10 brands, and partnering with C-Suite leadership to strategize, integrate acquisitions, and drive growth.

➥ Strategized and implemented organization design, infrastructure, and strategic plans, managing the budget and collaborating with FP&A to convert data into precise financial forecasts, creating actionable roadmaps.

➥ Developed and managed a sophisticated marketing technology stack, seamlessly integrating tools and systems across a rapidly expanding portfolio to ensure optimal data privacy and comprehensive reporting.

➥ Brands included Campaign Monitor, CM Commerce, Delivra (ended 2021), Emma, Sailthru, Liveclicker, Selligent, Cheetah Digital (beginning 2021), CM Group, Vuture

As Head of Marketing Strategy (2019 - 2021), I headed a team executing end-to-end brand and campaign management for three of the portfolio’s brands, Emma, Delivra and Vuture. Responsible for go-to-market campaigns, and brand management with a 20% YoY revenue growth.

Vice President of Marketing | Strategic Planning | Relationship Marketing | Operational Design

I was responsible for a $20M budget, collaborating with the FP&A team to create forecast models and maintain the financial viability of all key marketing initiatives. This included partnering with the legal team around marketing compliance, aligning with regulatory standards and practices to empower ongoing success.

➥ Engineered and implemented platform-specific automation and data-automation systems, driving significant efficiency improvements and elevating the marketing automation capabilities to a world-class standard.

➥ Led the expansion of marketing and campaign initiatives by overseeing MarTech stack operations, which resulted in enhanced capabilities and notable performance achievements.

➥ Created custom dashboards and reports that provided real-time visibility into key marketing metrics and KPIs, empowering executive leadership to make informed, data-driven decisions.

Director of Marketing Operations | Marketing Automation | Driving Growth & Performance Results

Computer Services, Inc.

As Digital Marketing Manager with CSI, I directed digital marketing initiatives, leading dynamic implementations to propel ongoing improvement and growth. 

• Integrated advanced marketing automation and web personalization tools, leading pilot personalization activities that significantly increased conversion rates and optimized customer reach.
• Conceptualized and implemented a unique multi-stage lead nurturing program, collaborating with leadership to expand the marketing qualified leads (MQL) strategy and drive higher quality leads.
• Overhauled the customer engagement strategy by launching comprehensive persona development processes and shaping automation workflows, effectively guiding leads through the buyer journey.
• Developed and executed tailored ABM strategies and campaigns, resulting in more targeted and successful marketing efforts.
• Advised leadership on best practices for marketing automation and email strategy, ensuring adherence to CAN-SPAM and GDPR compliance standards. 
• Partnered with the business intelligence team to maintain the integrity of customer relationship management software, enhancing data management processes.

Digital Marketing Manager

In this first role with CSI, I governed social media strategy, building creative engagement initiatives and a comprehensive brand guidebook to optimize digital engagement. 

• Spearheaded the creation and execution of a dynamic social media strategy, leading to a 30% increase in total website traffic by leveraging social media and pay-per-click campaigns.
• Created innovative engagement initiatives and a comprehensive brand guidebook, significantly enhancing digital engagement and brand consistency across all platforms.
• Established and standardized key performance metrics and measurement protocols, leading to the identification of critical improvement areas and the design of high-impact remediation strategies.
• Conducted detailed analyses of email marketing campaigns, utilizing insights from marketing automation platforms to inform strategic planning and optimize campaign performance.

Social Media Manager

Cyber Sytes, Inc.

Social Networking & Marketing Strategist

Tennessee Technological University Department of Athletics

Marketing Intern

MMA Creative

VP of Marketing | Growth Strategist | Revenue Optimization | Marketing Automation ➥ Building High-Performing Teams, Leveraging Innovative Strategies to Drive Growth & Impact

With over 14 years of experience as a marketing strategist and growth leader, my approach centers around achieving concrete results and real-world impact. I excel in highly competitive landscapes by implementing ahead-of-the-curve strategies. Passionate about uncovering the 'why' and 'how' behind business challenges, I guide teams to prioritize revenue results instead of vanity metrics and take a full-funnel view of the pipeline. I also understand the importance of leading with a healthy work-life balance and a sense of fulfillment, both for myself and for my teams. By keeping both outcomes and people at the forefront, I'm able to create a culture of success for my organizations.

I thrive in change management and high-growth environments focused on mergers and acquisition and operational challenges. 

Data-Backed Results
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➥ Researched, launched, and optimized an Account-Based Marketing Program aimed at moving more up-market, with initial results showing a 44x return on program investment to revenue generated

Change Champion
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➥ Collaborated with internal and newly-acquired stakeholders to establish culture, organizational and initiative alignment 7 times in a 3 year period

I have successfully leveraged budget, operations, and technology management to optimize results within revenue ranges from seed-stage start-ups and Series A companies to those with over $340M in revenue. I am adept at using data and analytics to pinpoint areas requiring optimization for increased marketing efficiency and building high-performing teams that deliver on ambitious revenue targets. 

My ability to understand and harness the power of technology is a key asset in creating a culture of innovation and continuous improvement. I possess a strong technical acumen that enables me to effectively leverage a wide range of marketing automation, CRM, PPC, ABM, analytics, and social media tools to drive business.

I am committed to catalyzing growth and reach through out-of-the-box marketing strategy. With my background in social media marketing, I’m always open to connect with other professionals and deliver value to my network here on LinkedIn. Let's connect and help each other.


CORE COMPETENCIES:
► Marketing Operations 
► Marketing Automation 
► Digital Marketing Strategy & Execution 
► Campaign Execution
► Revenue Growth 
► Sales Enablement 
► Account Based Marketing (ABM) 
► Marketing Analytics
► Marketing Compliance 
► Marketing Budget Management

Head of Marketing, Marketing Operations & Demand Generation | Revenue-Driven Strategy

Owning all go-to-market strategy planning, execution and implementation for this seed-stage start-up using AI to forecast pipeline and accelerate revenue, I have driven tangible results in a short period of time. Partnering with Sales to achieve goals targeting $1M in revenue, I spearheaded the development of research-based marketing and content strategies that have led to a remarkable 203% increase in contact creation MoM.

I have also been responsible for building and managing the RevSure.AI brand, ensuring that it resonates effectively with our target ICPs and personas. I have designed and implemented a scalable go-to-market tech stack process and systems, consistent with industry standards, to optimize our website for SEO and user experience, while creating demand within key audiences and accounts.

As a strategic marketing leader, I excel in highly competitive landscapes and thrive in change management and high-growth environments, having worked with both seed-stage start-ups and Series A companies.

Stella | Growth Intelligence

Chief Marketing Officer

Neighbor

Growth Marketing Contractor

CourseCareers

Digital Marketing Course Instructor

Growth Marketing Machines

Strategically acquire new clients through high-caliber networking, laying the foundation for each client of transformative marketing programs built from scratch.

Architect compelling websites on versatile CMS platforms like WordPress, Squarespace, and DreamWeaver, serving as the cornerstone for each client's robust digital brand.

Implement cutting-edge SEO techniques to elevate newly constructed websites, turning them into strong organic traffic hubs and revenue drivers.

Execute technical Paid Media campaigns across platforms such as Google, Meta, and LinkedIn, laser-focused on Conversion Rate Optimization, to supercharge client growth and profitability.

Consistently achieve a flawless 100% client satisfaction and on-time project completion, while generating a robust $10,000+ monthly net profit, solidifying a benchmark in freelance marketing excellence.

Founder

Dysrupt

Senior Paid Media Strategist

American Marketing Association

Mentor

Half Past Nine

Orchestrate comprehensive performance media strategies for 7 high-profile client campaigns across a spectrum of platforms, raising the bar in brand prominence while optimizing Return on Media Spend (ROMS) and Media Efficiency Ratio (MER).

Skillfully deploy $500,000+ in monthly media budgets, consistently hitting the mark with a 98% attainment rate toward all quarterly client objectives.

Master sophisticated analytics tools like GA4 and Measured to infuse campaigns with data-driven precision, elevating effectiveness through nuanced incrementality insights.

Pioneer groundbreaking media-buying efficiencies via custom Google scripts and APIs, rewriting the playbook for agency-level performance standards.

Lead a specialized, outsourced team to conduct weekly account audits and optimizations, ensuring campaigns continually operate at peak performance.

Act as the linchpin account manager for 5 of the 7 high-stakes client accounts, consolidating relationships and streamlining communication channels for optimal results.

Udemy

B2B Google Ads Masterclass: B2B Lead Generation

Course Instructor

Cordelia Labs

Lead a diverse portfolio of over 20 client accounts across multiple platforms, while mentoring an Assistant Media Buyer to excel in cross-platform strategies.

Serve as a key marketing consultant to internal teams and account managers, translating complex media trends into actionable insights for strategic planning.

Masterfully negotiate and manage advertising inventories, ensuring optimized ad exposure and cost-effectiveness, while achieving unparalleled ROI for clients.

Oversee creative teams to align graphic design and copywriting with customer journeys, driving a seamless and high-converting user experience.

Cultivate lasting client relationships through meticulous reporting and strategic advisement, contributing significantly to the agency's long-term growth.

Digital Media Planner

Big Sea

Digital Media Buyer 

CMO at Stella

For the past 8 years, I've immersed myself in the world of digital advertising and performance media. I've had the privilege of managing $38 million in ad spend, which has translated into $100 million in revenue for the clients I've worked with. My expertise spans all performance media channels—whether it's Paid Search, Paid Social, Account-Based Marketing, or the intricacies of CRO and A/B testing, I've been there, driving results.

I've been fortunate to play a part in some significant growth stories, helping companies scale from $10k to $100k in monthly revenue or $1 million to $5 million in monthly revenue. I’ve worked across various platforms like Google Ads, Microsoft, LinkedIn, Meta, and have also dived into programmatic display, CTV, and audio advertising.

In 2022, my work on innovative campaigns for a leading online pharmaceutical company earned me a spot on Performance Marketing World’s 30 Under 30 list—a milestone that I’m incredibly proud of.

Now, I've taken on a new challenge as the founder of Stella, a marketing measurement startup. My focus is on all things advertising, and I’m committed to helping brands navigate the ever-changing landscape of performance media to achieve exceptional results.

Brenden Delarua

LinkedIn sometimes bums me out. 

It’s like the most insane highlight reel of everyone stroking each others ego. 

So here’s a story of a time I failed (and learned from) to show I’m human and not everything is perfect all the time. 


One of the early holdout studies I ran (as a consultant) we measured YouTube for a large ecom brand. 

iROAS came back at a 9x which is high. 

Like suspiciously high. 

Like, “no way this is accurate” high. 


So, like a good consultant, I recommended a retest. 

We did. 

The 2nd study came back at about an 8x. 

We did it properly too, confounders, multiple models, weighted controls, etc.


Holy cow, 2 different studies validating ~8.5x iROAS on YouTube. 

The client loved this. And scaled hard. 

Tripled investment in YouTube the next month. 

Going from about $2k per day in YouTube to $6k.


So at 8.5x iROAS from $6k in spend should be $51k per day in incremental revenue. 

Thats not what happened. 


I think for the month, they drove $1.5m in total DTC revenue. Which was down like 7% MoM. 

In other words, the iROAS didn’t hold. 

This was a huge failure on my part. 

I was stumped as to why the data didn’t hold up. 


Here was the learning lesson: incrementality is a snapshot in time. 

YouTube WAS 8.5x incremental at $2k in spend per day. We proved it twice. 

But what we didn’t see is if YouTube was already maxed out or at a point of saturation. 

Meaning if we spend another dollar on YouTube we begin to see diminishing returns. 

Let alone tripling spend on YouTube. 

iROAS might have dropped down to 1-2x. 


The proper way to measure this is a scale test to see your marginal growth curve.

To know exactly how far you can scale each channel. 

So now at Stella we always recommend testing channels in 3 phases: 

1. Holdout study to find baseline iROAS
2. Scale test to find how far you can scale before hitting diminishing returns
3. Validating with an iROAS-calibrated MMM and reviewing the response curves. 


The clients we’ve done this for, have been able to trust and scale with that marginal growth curve. 

It was the piece we were missing. 

It’s a piece most brands doing incrementality are still missing. 


So there it is. A real failure. A real learning. No highlight reel bs.

Learn from my mistakes. I know I have.

Co-Founder @ Stella | Accessible Incrementality Testing & MMM for Mid Market DTC Brands

Black Friday tends to turn every marketer into a temporary genius.

CPAs drop. Blended numbers look clean. Incremental revenue climbs like it’s on steroids.
 
And every Slack channel is full of victory laps and screenshots.

Then January shows up and reminds you that math exists. 

Most of what’s happening in your ad account right now has nothing to do with strategy.

It’s the season picking you up and carrying you whether you deserve it or not.

Q4 doesn’t care how good your media plan is. Most times, it lifts everything.

The strong channels, the mediocre channels, and the ones you should’ve killed months ago.

They all get a free pass for a few weeks.

And that’s exactly how teams get blindsided when they should be gathering the most valuable dataset of their entire fiscal year.

They might scale spend assuming the lift is coming from their choices instead of the calendar.

Then the moment demand cools, the whole thing falls apart and everyone panics.

If you want to know what’s working right now, you need an MMM running during Q4.

Not after the fact or "when things calm down". 

Q4 rewards everyone.

But only the teams who understand their numbers get to keep the gains once the music's over.

Black Friday can be like pulling an all-nighter at the bar with your best friends...

But the January hangover can be extremely brutal. 

Measure early or learn the hard way later.

Some agency owners feel the need to preface consulting calls with their resume.

“I’ve been doing this 15 years.”
“I run a team of 30.”
“I’ve managed millions in spend.”

Then they show me an account they “can’t crack”.

And in 10 minutes we uncover five things they’ve never even considered.

Don't get me wrong. They’re not bad marketers.

But every marketer, no matter how senior, has blind spots.

The funniest part is how relieved they look. You can almost see the weight fall off their shoulders.

15 years in the game and still learning is exactly how it works.

The minute you think you’ve seen it all, you start getting complacent and your business just gets worse.

Expertise doesn't mean never needing help.

It’s knowing when you’ve stared at the same account so long that your brain stops seeing obvious things.

That’s why I love those calls.

People think they’re paying for 30 minutes of my time.

They’re actually paying to borrow a fresh brain, a second set of eyes, and a different angle.

If you’ve been stuck on the same problem for a month, bring someone else in.

It doesn't mean you’re inexperienced. It just means you're a human being.

I made a TikTok about DTC growth once and to answer some comments, I asked ChatGPT a simple question:

If a DTC brand is doing X revenue, growing at Y percent per year, what's the revenue in 3 years?

The answer looked pretty good and to be honest I took it as correct for a second...

But it was horribly off, by like 50%. And this was extremely basic math, all things considered. 

If ChatGPT can't handle 6th grade math, what happens when you ask it about:

- Correlation coefficients between test and control regions
- Statistical significance with proper confidence intervals
- Weighting control markets to build synthetic matches
- Accounting for promotional calendars and competitive pressure

These aren't just formulas you can pattern-match from a few docs of training data.

They require understanding what the numbers actually represent...AND extreme accuracy with the actual math. 

But since ChatGPT generates text that resembles statistical analysis, you have companies making massive budget allocation decisions based on pure AI slop. 

Insanity.

When we run actual incrementality tests - with proper power analysis, cooldown periods, market validation - we know the constraints of our data and we run statistical systems that actual 9-figure software behemoths are trying to snake from under us constantly.

When you ask ChatGPT, you get a ridiculously confident answer with nice formatting made from horribly wrong information. 

Very simple choice considering our main complaint at Stella is "the price feels too low to be real".

A lot of brands talk about incrementality like it’s a Yes or No quiz:

“Is Meta incremental?”
“Is Google incremental?”
“Is CTV incremental?”

You can hear the hope in their voice. They want a single clean answer so they can move on with their day.

But incrementality is not, in fact, a light switch. It’s a thermostat. 

You turn it and the whole house shifts. Slowly.

And the actual truth tends to be uncomfortable:

Even when a channel is incremental, it will never be equally incremental at every spend level, every season, or every promo cycle.

And the second you change how hard you’re pushing it, the return profile changes too.

It's why most “incrementality programs” fall apart. They treat the whole thing like a pass or fail test.

Meta is “good”.
Google is “good”.
CTV is “bad”.

But since any given channel can be incremental today and tank next quarter, you end up hedging huge amounts of spend on extremely bad data. 

The channel you "proved wasn't incremental" might be unprofitable at 60k a month but profitable at 30k.

Or, it can be a lightweight in May and a heavyweight in August.

That’s literally the entire point of running holdouts, MMMs and saturation curves.

You’re not answering “is this channel incremental”.

You’re answering “what actual strategy gives me the most new business per dollar”.

Marketers who think in binaries get binary results.

The ones who think in gradients end up with more profit and fewer “oh shit” meetings.

Treat incrementality like a thermostat instead of a switch, and you’ll stop guessing and start steering the thing in real time.

At Stella, we have 3 new features/tools that will be released within the next 30 days. They are f***ing game-changers. 

Our users talk about not liking to format data sheets for the final analysis. They want easy data ingestion. 

The problem with ingestion is that it trades accuracy for convenience. It’s best to use data with confounding variables unique to your business. 

But we figured out the best solution to this to have the convenience AND accuracy utilizing Stella’s AI. 

Just download all your data individually. Upload it to Stella. 
Stella matches and combines all rows automatically. 
Revenue, orders, spend, confounders, everything.
No need to make sure everything is formatted correctly. Stella takes care of all of that now.

It’s in QA right now (live for some accounts) but will be fully rolled out soon. 


The other thing is 2 new tools will be released. That actually closes the gap from insight -> action. 

I’m noticing a lot of marketers use incrementality studies as “one-offs” or temperature checks. 

“Was it incremental? Yes or no?” - this is the wrong way of using this methodology. 

We need to constantly be testing to find the answers to: 
how incremental is this channel? 
At what point of spend does this channel become non-incremental? 
What campaign settings are most incremental for my company?

Then updating budgets, settings, ads, strategies, and conversion tracking to better align with more incremental outcomes. 


That’s been the missing piece. 

No player in this space has cracked this. 

We believe we have. 

The tool already works internally. Just not released yet. When it comes out, im looking forward to the response. 


2026 is going to be the year Stella “grows up”.

It’s amazing how fast someone can become a “data expert” when there’s a meeting in the morning.

A few filters, a quick export, a pivot table for style points; and then the budget recommendation in the deck says, “shift 150k from Meta to Google.”

And leadership nods along like this makes perfect sense.

It doesn’t. It’s literally just rolling dice but with nicer formatting.

I’m not saying the people doing this aren’t smart. They are. 

They’re working fast, under pressure, trying to make decisions with whatever time they’ve got. 

But the minute a 6 figure move is based on half-baked ChatGPT "math", you have to start questioning what's really going on.

A spreadsheet doesn’t understand seasonality.
It doesn’t know when creative fatigued.
ChatGPT doesn't account for promos, stockouts, attribution delays, or the weird things that happen when you scale a channel too fast.

So when massive monetary decisions are made on this basis and it DOESN'T work out? 

The media plan wanders off-course anyway while everyone argues about who misread what because no one wants to end up fired for leaning on AI and in-platform metrics.

If the analysis driving a six- or seven-figure budget change took a half hour to build at a coffee shop with ChatGPT, you're gonna have a bad time. 

It won’t show up in the P&L immediately. 

It’ll show up in three months, when the CFO starts asking why nothing is behaving the way you projected.

Using AI to generate new ad concepts?

Then testing them in a single ad set, broad audience Meta campaign?

What if you could generate 100 creative concepts and show them to 1000 synthetic personas to predict performance at every funnel stage?

All before putting a single dollar into market.

Well, you can now. 
and it’s completely free.

Here’s how it works: 
> Provide your URL and 2 competitor URLs. 
> Add optional creative assets 
> Refine your audience insights 
> Generate synthetic personas 
> Generate synthetic ads
> Run simulation 
> Export winning ad concepts


The team at Stella has been building this for a while, and with Nano Banana Pro we’ve taken it from 80% to 100% finished.


Comment “AI ads” on this post 
and connect with me.

I’ll send you the link.


Bookmark it and scale winning creative generation.

Send the winning concepts to your designers. Whatever you want. We live in the future.

No alternative text description for this image

I lost the argument to charge for this.. 

.. so I guess it’s free. INSANE.

CEO @ Stella | Claude code for marketing measurement

We're opening up our internal ad generation tool that uses synthetic audience simulation to find winning ad creatives.

At Stella, we're a marketing measurement platform. Incrementality testing. Marketing mix modeling. Statistical rigor.

But measurement only works if you have winning ads to measure.

Among many internal tools we built and use regularly is AdPilot:

- Generates hundreds of ad concepts in minutes
- Simulates them against synthetic audiences
- Predicts which will perform before you spend
- Renders only the winners as ready-to-use creatives

We've used it to generate thousands of ads. Headlines, body copy, and images - all matched to brand guidelines and audience psychology.

Now we're making it available publicly.

If you're a D2C brand struggling with high-quality creative volume, this is for you.

No more guessing which ads will work.
No more rendering hundreds of images you'll never use.
No more burning budget on concepts that were dead on arrival.

🟢 Connect with me and comment "AdPilot" to try this Synthetic Audience Approved Ads tool.

#D2C #MetaAds #CreativeStrategy #PerformanceMarketing #AdTech
#syntheticaudience

My favorite line on sales calls is “we already do incrementality testing”

Then they show me a google sheet where they turned off ads in two random states and called it a day.

Cool.

But...how did you pick those two states? 

Did you check if their sales patterns actually correlate historically?

What was your correlation coefficient between regions? Was it above 0.8 for at least 12 months?

Did you account for seasonality differences between regions? What about regional promotions or competitive activity?

How did you handle spillover effects from bordering states? 

What about other marketing channels -- were they also turned off? Or did you pump more budget into paid social while cutting paid search?

Did you run a power analysis first? How did you know your test would even detect a real difference?

Where's your synthetic control? How did you weight your control regions to mirror the test region?

Did you include a cooldown period? How long did you wait for the market to stabilize before measuring?

The scariest part of the whole thing is that your flawed test will still give you a number.

A confident-looking 2.3x ROAS, clean lift percentage, etc. And you can arrange pretty charts that feel bulletproof.

But here's what actually happened:

- Your "control" region was already declining (seasonal pattern)
- Your test region got hit with a competitor's store closure 
- Your "40% lift" had nothing to do with your marketing budget whatsoever

Now you're doubling down on channels that don't work and cutting the ones that do.

The worst incrementality test is the one that makes you confident in the wrong direction.

You can literally burn 7 figures by running a "quick geo test" in Q4 without realizing your control regions don't have the same holiday shopping patterns.

Real incrementality testing is like surgery -- better to not do it at all than to do it badly with dirty tools.

The companies that win understand this isn't about "having an answer".

It's about having an ACCURATE answer.

And if you can't commit to doing it properly you're probably better off avoiding it altogether.

At least then you know what you don't know.

Even the best marketing measurement tool is only as good as the information you feed it.

If you dump sloppy data into a tool, the tool won’t magically clean it.

It’ll just give you sloppy conclusions in a nice-looking format.

This is why marketing teams get confused when their lift number looks off.

When the results look strange, it’s almost never the model. It’s the setup. 

I’ve been on calls where a team insists the tool “missed something,” and once we walk through the inputs, the issue shows up immediately. 

→ The timing didn’t match the business cycle
→ Promo periods weren’t marked
→ Regions that behaved nothing alike were compared as if they were
→ A product launch is sitting right in the middle of the data with no context at all

Stack a few of these blunders, and you're going to get a dataset that might feel ok, but is functionally useless. 

Add to that the real-world challenges of running any business:

Campaign timelines shift. Inventory isn’t always there when you expect it. A creative update lands the same day a sale goes live. 

If the model isn’t told any of that, it’ll still give you an answer. It just won’t be the right one.

The reason Stella works so well is we spend as much effort preparing the inputs as we do interpreting the outputs. 

The unglamorous work of data hygiene can seriously make or break your experience with a serious measurement tool. 

This is what gives us a big leg up on the behemoths in the space -- we actually spend an inordinate amount of energy making sure our users are equipped to get a good result without wasting a bunch of time running useless tests.

"Is this channel incremental?"

Wrong question. The right question:

"How incremental is this channel?"

Incrementality is not pregnancy. You aren't either "incremental or not". 

iROAS moves with spend, competitive pressure, and market conditions.

To prove this out, just think about what actually happens when you scale a channel:

You start off spending $10k, Meta's dashboard shows 5x ROAS. Looks great, so you scale spend. 

Next month at $30k, your dashboard still shows 2x. Excellent, there's some room to keep spending.

Month three at $50k, you're still seeing 2x in-platform.

But Meta's attribution is counting every person who clicked an ad and bought within 7 days. 

It doesn't know they had your product in their cart for two weeks. Or that they're on your email list. Or that they would've bought anyway because their friend recommended you.

If you run an actual geo holdout test at those different spend levels, you tend to get dramatically different information:

- At $10k: 3.5x incremental return
- At $20k: 1.8x incremental return
- At $30k: 0.8x incremental return

You went from a SUPER incremental channel to literally wasting money -- but it happened gradually, like turning a dial rather than flipping a switch off. 

Because platforms report on correlation, not causation. They count touches, not actual influence.

The problem is most teams run one quick holdout at whatever they're currently spending and call it done.

(this isn't even mentioning the problems with designing the holdout in the first place)

Then they jump into a meeting and claim "our Meta iROAS is 2.2x!"

At $10k/month? What about at $20k? 30k?

You tested one point on a curve without any nuance whatsoever and you are now generalizing that information out to your entire business and allowing it to dictate where you allocate huge amounts of capital. 

Incrementality really isn't about getting a single answer and that's why it makes people uncomfortable.

It's about mapping where the money actually works versus where you're just subsidizing demand that already existed.

And that line moves based on competition, promotions, seasonality, and a million other little factors that we've spent years accounting for inside our platform.

But you'll never see it in the ad account because their ONLY incentive is to keep you spending.

I keep seeing brands make 6-figure budget decisions using spreadsheets that look like they were built during a layover.

Someone downloads three columns from Shopify, adds a pivot table, divides something by something else, and suddenly they’re moving 100k from Meta to Google like it’s a crossword puzzle.

Look, you can feel productive inside a spreadsheet while also being completely wrong.

The spreadsheet doesn’t know seasonality.

It doesn’t know promo windows.

It doesn’t know creative fatigue, saturation, stockouts, attribution delays or the weird black hole that happens every time you launch a new product.

It just knows whatever you typed into it at 11pm.

This is extremely terrifying if you think about it from a brand owner perspective:

Marketing leaders are walking into board meetings showing “analysis” that was basically 12 minutes of Excel plus some ChatGPT plus some unearned confidence.

Then the leadership is expected to approve 6 or even 7-figure budget moves based on math that wouldn’t pass a freshman stats quiz.

Back-of-napkin math is fine for splitting the lunch bill.

It sucks when you’re reallocating lifeblood cashflow of your business.

Incrementality isn’t a "vibe check".

It’s not “test minus control and fingers crossed”.

It’s statistics, causality, confounders, synthetic controls and calibration.

If the goal is to run a real business, not a spreadsheet role-play game, then the bar has to be higher than “my Excel said so”.

Nothing will feel worse than having to explain to the board why the numbers tanked because your “analysis” was more arts and crafts busywork than data science.

A founder recently told me “you’d be shocked how much we’ve spent on tools that might give us even a small advantage”

Top operators (especially in ecom) aren’t emotional about tools.

They’re disciplined. And they’ll try anything that gives them the slightest edge over their competition.

They don’t care whether something is trendy or uncool.

They care about gaining an advantage. Plain and simple.

On the other hand, there are still a lot of brands out there who think accurate measurement and attribution is optional.

At the end of the day, the teams who are going full-bore on data right now are going to have a massive leg up on everyone else in 2 or 3 years. The insights you collect tend to compound, especially if you're in a market that's sophisticating or growing at a decent pace. 

You don’t have to like marketing influencers or agree with their posts.

But if you think the biggest companies in this space got where they are without real measurement, you’re living in a dreamworld.

Marketing leaders won’t want to hear this, but BFCM is actually the perfect time to run granular holdout tests.

Almost every brand is making huge, high-impact decisions going into this weekend hoping it does well enough to carry the entire year.

But if it doesn’t, they’re stuck playing a blame-game.

Because they don’t have the data to figure out WHY the numbers look the way they do.

Here’s the thing: Q4 is the only time when every channel looks better than it really is.

CPAs look friendlier. Revenue jumps. Lift appears where it doesn’t exist.

It’s easy to think everything is “working” when people are shopping no matter what you do.

If you don’t understand how your channels behave in this environment, you’re not really in control of anything.

So here’s what the smart brands are doing:

Turn off Meta in ~2 DMAs. Google in ~2 other DMAs. TikTok in ~2 others. (Don’t pick this randomly)

Each DMA still has coverage, just one channel goes dark.

(Yes, this sounds terrifying. Yes, it’s worth it.)

Because here’s what you learn:

• Which channels actually create new demand vs just capture it
• Which ones only look strong because the entire market is caffeinated
• How much revenue you’d keep if you cut spend by 30%
• Where you’re burning money that could go straight to contribution margin
• What actually works when customers are already looking to buy

For brands that make 70% of their revenue in November, this isn’t nice-to-have information.

This is the difference between guessing and knowing.

The holdout data you collect this weekend tells you exactly how to structure your spend for next BFCM.

And the one after that.

And what to do in January when the demand cliff hits and every channel suddenly looks terrible.

You can’t get this from in-platform reporting. Meta’s dashboard will never tell you that Meta isn’t working.

And you definitely can’t get it from a spreadsheet analysis done two weeks after the fact.

The brands that win Q4 are the ones who know exactly what each dollar is doing in the middle of the chaos.

Black Friday isn’t the time to guess. It’s the time to verify.

There’s always this strange outrage whenever someone in eComm talks about a measurement tool.

People jump into the comments accusing them of being “paid to promote something” or “pushing an agenda.”

As if the brands scaling to hundreds of millions are doing it with intuition and a whiteboard.

People seem to forget that the biggest operators will use ANYTHING that helps them understand their numbers, or become even just a tiny bit more efficient.

Attribution platforms. Lift tools. MMM. Custom reporting setups.

If it gives them clarity, they WILL test it.

If it actually helps them scale, they keep it.

The people screaming the loudest are usually the ones relying on last-click reports and three spreadsheets that barely line up.

Don't get so caught up scrutinizing tools that you spend time arguing online instead of uncovering tangible advantages for your business.

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