The Insight
Aditya Sriram saw performance marketing changing rapidly due to evolving algorithms and AI capabilities. So he and his co-founders built an MCP server at GoMarble that turns LLMs into real-time performance marketing analysts.

How It Works
GoMarble's MCP (Model Context Protocol) server acts as an interpreter that enables LLMs like Claude to access live data from your ad accounts. You can:

• Pull real-time performance data from Google Ads, Meta Ads, and Google Analytics

• Generate detailed ad hoc performance reports in minutes instead of hours

• Conduct ad hoc analysis like time-bound root cause analysis of performance dips and spikes by asking natural language questions

The tool essentially makes Claude a data-connected analyst that can answer questions like "Why did my Meta spend spike yesterday?" or "Show me campaign performance trends for the last 30 days" with actual numbers, not hallucinated data.

What's Accurate vs. What Requires Human Judgment

The data recall is highly accurate because the LLM works with real numbers from APIs. However, ambiguities can arise if prompts are vague or metrics have multiple definitions.

For reasoning and recommendations, the tool provides powerful hypotheses based on data trends, but human expertise remains crucial. The LLM can spot patterns and suggest potential causes, but it can't replace the account context and strategic judgment that experienced marketers bring to decision-making.

What's Coming Next

Aditya says GoMarble will be rolling out its own platform, removing it’s current dependency on the Claude UI. They’re also adding more sophisticated capabilities and connectors to deepen creative analysis and streamline performance workflows including visual video/static ad analysis that allows the AI to break down what’s working and what could improve in your creative, along with competitor research tools to help you stay on top of the ad angles your peer brands are using. Expanded custom reporting features and support for new connectors like Shopify, TikTok Ads, LinkedIn Ads, and more are also on the way.

Business Model & Access

Basic connectors for Google Ads, Meta Ads, and Google Analytics will stay free. Advanced features like AI driven creative analysis, competitor research and more powerful reporting capabilities will be part of a paid tier with a dedicated interface optimized for growth marketers.

The Bottom Line

GoMarble represents a shift toward AI-powered performance marketing analysis that works with real data, not assumptions. The team serves 15 partners with full-stack performance marketing services while powering 2,000+ users with their MCP tool. They also have an active 600+ member Slack community for support and prompt sharing. If you or your team is spending significant time on manual reporting and analysis, visitwww.gomarble.ai/mcp to get started and let them know you heard about them on Growthish.

The Insight
Nate Yu hit this wall as a growth marketer. So he built Butter, an AI-native creative operating system designed for speed, quality, and control.

How It Works
Butter is the only video editor on the market that can reverse-engineer any ad from Facebook’s Ad Library into fully editable timelines. You can:

• Remix ads from top brands in seconds

• Swap out assets, motion, and copy with a single click

• Save reusable blocks (end cards, logos, captions, etc.)

• Animate with drag-and-drop effects that used to require After Effects

Traction

• 10,000+ users across brands like Netflix, Crocs, and top agencies

• $0 spent on paid ads — all word-of-mouth

• Built by a team of four

• $18/mo starting price, 7-day free trial

Make ads or need ads and feel underwhelmed by today's AI creation tools, Butter’s worth a look. Check out the full interview for more detail.

What is the AI Growth Stack Series?

I'm launching a new video series where I sit down with the most interesting AI-focused marketing companies I encounter. These will be real conversations & live demos with founders building tools that could genuinely impact how growth marketers work.

Each conversation will dig into what specific problem they're solving, how their approach differs from existing solutions, showcasing real performance data, who should use their tool and who shouldn't, pricing and implementation complexity.

What You Can Expect

Raw, unscripted conversations. I'll ask the questions you would ask: How does it work? What does this cost? How long does setup take? What happens when it breaks? How does it integrate with our existing stack? What results are you actually seeing?

Starting Tomorrow!

True to Growthish form, these videos will be published when there is value in sharing it, not on a predetermined schedule. Some weeks might have multiple conversations. Other weeks might have none if nothing crosses my desk that's worth your time.

Each video will be worth watching, or it won't be published.

The first conversation drops tomorrow.

Building an interesting AI tool for marketers? Have a favorite tool you'd like to see covered? Questions about specific use cases or problems you're trying to solve? As always, reach out at rob@growthish.com.

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text on the image”.

The gold standard in consumer sentiment data, as far as I can tell, is The University of Michigan Consumer Sentiment Index. Data is posted twice a month covering the trends in consumer purchasing sentiment. Once as a preliminary (mid-month) read and again as a final (end-of-month) number for each month. This makes it one of the earliest consumer-facing economic indicators available, beating most government data to the punch and giving you an early sense of which way the wind is blowing. It’s a well-established read on how consumers are feeling about the economy (jobs, inflation, income expectations) and it’s one of the fastest macro indicators available.

The index itself is built from a recurring national survey of U.S. households. Each month, about 500 people are asked five key questions designed to gauge how they feel about their personal finances and the broader economy. The questions cover both current conditions and expectations for the future including whether they’re better or worse off financially than a year ago, how they expect their situation to change in the year ahead, and how they view national business conditions over the next 12 months and five years. They’re also asked whether they think it’s a good or bad time to buy major household items, which is a useful signal for discretionary spending.

Respondents are selected using a combination of random-digit dialing and address-based sampling, which ensures the survey reaches a nationally representative mix of U.S. adults. Historically, the interviews have been conducted by live interview over the phone, with trained interviewers asking each participant the same five questions each month. In recent years, they’ve started incorporating online methods as well, but phone remains the backbone of the survey process.

Answers are categorized as positive, negative, or neutral, and then used to calculate three separate indices: current conditions, consumer expectations, and the headline consumer sentiment index. This consistency in who they ask and how they ask keeps the data clean and comparable over time. This is also why economists, investors, and business operators still pay close attention to the results, even decades after the index was first launched.

The result is one of the clearest, fastest signals you can get about what American consumers are feeling and how that might translate into sales.

If you’re running a consumer business, especially in discretionary categories, tracking this index over time can help you contextualize sales performance and spot early signals of headwinds or tailwinds.

I’ve used it to add a macro layer in weekly, monthly and quarterly sales dashboards as well as an input into forecasting. Correlation isn’t always perfect, but directional shifts in sentiment often show up in our topline a few weeks later. It’s become a regular part of several monthly readouts and planning cycles that I have been a part of. And like Google Trends, the data is public, free, and easy to access.

Let me know if you’ve used a better data source! I am all ears.

Thanks for reading growthish! Subscribe for free to receive new posts and support my work.

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text on the image”.

In a past life, a team I was part of spent a LOT of money with Google and our reps had access to an internal tool they called “Wildcat”. They used Wildcat to quantify changes in baseline demand in our category and used it to give us historical data to help us forecast future demand. It was powerful, but slow. Every data pull had to go through a rep, people went on vacation, calls were missed, timelines dragged, etc. As a result, it became difficult to regularly incorporate the data into our workflows and reporting.

Out of curiosity (and impatience), we back-tested Wildcat data against what’s available publicly via Google Trends. The results were nearly identical.

Seasonality patterns? Spot on. Weekly changes? Close enough.

And unlike Wildcat, Google Trends is always on, free, and self-serve.

Since then, I’ve used Trends to model consumer behavior, identify early shifts in interest, and confirm timing for campaigns. It’s not perfect, but it’s quite good - and for early & growth stage demand modeling, that’s often exactly what you need.

Bonus: no need to wait on anyone to pull it for you.

Marketing measurement has always been challenging. Since the dawn of time, marketers have tirelessly sought methodologies to measure and maximize returns on their marketing budgets. Traditional tools like Media Mix Models (MMM), pioneered over 60 years ago by companies like Procter & Gamble, and Multi-Touch Attribution models (MTA) from the 2000s, have seen their effectiveness fluctuate due to technological and privacy changes. Despite these shifts, marketers continue to hunt for a measurement edge to maximize ROI and elevate their brands.

So what’s next for marketing measurement? What’s coming in 2025 and beyond?

Long Live Cookies? And APIs.

Cookies have become integrated into nearly all marketing channels in some way over the last 25 years. They store information in customer browsers and pass information back to marketing tools that enable tracking, optimization, and more. Since 2020, marketers have been preparing for “the death of the cookie” as browsers have vowed to be more and more privacy and consumer-centric. There are lots of technical details around first-party cookies, third-party cookies, privacy controls, etc. that I won’t get into here. The punchline is that while Google was on track to follow Safari/Apple and kill third-party cookies entirely, they have since backed off that stance and canceled their cookie crackdown. In parallel, Google Chrome has maintained its position as the dominant browser by market share, so the end of cookies does not appear to be as near as it once was.

That said, while everyone was preparing for cookies to go away, advertising platforms like Google and Meta invested heavily in backend conversion APIs that allow advertisers to share data with the platforms without using cookies at all. The advertising platforms also got much more creative, and at times sneaky, in how and where they use modeled data to plug gaps left behind by cookies when representing results to advertisers, particularly when using longer click-and-view attribution windows. Marketing tool companies have also gotten very creative in using first-party cookies for internal analytics tools like MTAs, etc. More on walled gardens and MTAs below.

TLDR:

• Third-party Cookies are sticking around in Chrome, which is the largest browser by far

• Safari deletes first and third-party cookies by default but has a minority of the market

• Marketing tools that do need cookies, like MTAs, will continue to rely on first-party cookies to survive (more on this below)

Privacy Banners on Privacy Banners

Once new and scary to both consumers and advertisers alike, everyone is now swimming in a sea of privacy banners that are largely never read. Consumers have grown numb to the privacy banners driven by CCPA and GDPR and marketers have grown savvy to using conversion rate optimization strategies to elevate opt-in rates. Advertisers need to follow the rules, but they also need to not punch themselves in the face by accident with their privacy banner UI, because their privacy banner opt-in rates drive the amount of data they can share with their advertising platforms which drives their campaign success which drives their marketing spend ROI.

TLDR:

• Privacy banners are not going anywhere

• Advertisers looking to maximize ROI need to boost the opt-in rates on their privacy banners just like they try to boost the conversion rates of their checkout funnels

The Walled Gardens Are Growing

As mentioned above, the mega advertising platforms Google, Meta, and Bing have been heavily investing in conversion APIs that allow for backend communications between advertising platforms and advertisers. This has reduced their reliance on cookies (which have been under attack, see above) and allows them to enrich their data and target more new customers without privacy concerns (except for that pesky privacy banner opt-in, see above). These platforms don’t need anyone else to tell them who they showed an ad, or who clicked on an ad, and if advertisers tell them via API call who ended up purchasing, these platforms have everything they need to keep driving more new customers to advertiser websites and printing money for their shareholders. This is why advertising dollars continue to flow to these platforms and their flagship, macro, “AI-enabled” products like Google’s Performance Max, Meta’s Advantage+ Shopping Campaigns, and Microsoft/Bing’s…Performance Max. Yes, they named it that too. The challenge marketers will face going forward is to determine 1) how to feed these beasts with enough creative to maximize ROI and 2) how much to trust these tools. They will need to test and balance budgets across these campaign types and platforms as they are changing very, very fast.

TLDR:

• Conversion APIs are also not going anywhere and strengthen the walled gardens

• Marketers will need to focus on creative insights and creative velocity

• Marketers will need to test mega-platform tools, figure out how to maximize their results within them and determine what the optimal cross-channel mix should be on any given day

Platform Reporting: Stable Apples + Oranges

A constant within the marketing world is the general stability and usefulness of “platform reporting,” aka the things that the advertising platforms tell advertisers are true. The strength of the Meta and Google walled gardens continues to grow (see above) and the ad-serving algorithms used by the large advertising platforms are some of the largest deployments of machine learning and AI in the history of humankind. The only problem is that, while their reporting is generally stable and consistent, advertisers can only safely use today’s results to compare them on a relative basis to yesterday’s results or last month’s results on the same platform (e.g. is today higher or lower than yesterday). You can’t trust the actual number itself (e.g. a platform-reported $38 CPA is very likely not actually a $38 CPA), and you can’t compare numbers from one platform to the results from another unless you have run incrementality tests to create discount rates for each before doing so (see below). So platform reporting is an essential tool for managing a channel relative to itself, but it’s comparing apples to oranges if you try to use it to compare one channel to another.

TLDR:

• Platform reporting will continue to be essential for day-to-day optimization, but it is not an accurate depiction of reality

• Incrementality testing is essential to determine what platforms are delivering and how they compare to each other

MTAs: Living to Fight Another Day

Once a marketer's dream, the drawbacks of MTAs in a post-consumer privacy-based world have been widely documented. Since browser-based privacy changes started heating up in 2017, MTA efficacy has been on a steady decline. I have spent years of my life and millions of dollars on tools and teams to build internal MTAs, and I am very sure I’ll never build one internally again. There are, however, several 3rd party tools available like RockerBox, Northbeam, and TripleWhale. At their peak, these tools promised advertisers cross-site view-through (“impression level”) data that would in theory tell a clear story of the location and frequency of ad impressions (without clicks) that later drove on-site purchases. More recently, post-browser privacy revolution, these tools can only deliver a picture of where customers came from just prior to arriving on your site (via UTM), what the customer does while on-site (which is available via GA4 and other tools), and attempt to link users cross-session and tell a complete picture of the on-site customer journey. These tools rely on their cookies being placed as first-party cookies, while under attack and auto-deleted by Apple/Safari, Google has canceled their crackdown. This could mean that MTA efficacy has stabilized, at least temporarily, and paired with the generally disliked rollout of GA4, third-party MTA tools could see a resurgence. However, they are still pretty expensive, they are limited to click-based activity, they will use modeled data to fill Safari-sized holes in their data sets, and they require maniacal attention to detail to implement and maintain across a marketing team to be somewhat accurate.

Similar to the app advertising platforms, the companies that make these tools and the advertisers who use them are living in fear of the next browser privacy change that might knock their measurement approach out of commission. Some marketers love these tools. I am not one of them. But given Google backing off the death to cookies bandwagon, it looks like MTAs will live to fight another day.

TLDR:

• Since cookies are not dying, 3rd party MTA platforms will stick around but with a view limited to click-based activity with some creative modeling to fill in the gaps

• GA4’s weakness is an opportunity for MTA providers

Fast & Lean MMMs Continue to Emerge

MMMs are magical tools for the likes of the companies that invented them…mega CPG brands with deep historical sales and marketing data and massive distribution. Brands like Gatorade, Clorox, Cheerios, Pepsi, and Coke can get massive value out of MMMs and have done so for decades. The MMM market has historically been dominated by players like Neustar (now TransUnion) and Analytic Partners which generally require annual contracts, cost many hundreds of thousands of dollars, and take many months to deploy. These providers are generally too big and heavy for fast-moving growth-stage companies with lean teams. There is, however, a cohort of leaner, faster MMM providers like Recast, Prescient, and Paramark which cost $5k - $20k/month, deploy pretty quickly, and generally harness open-source models and SaaS playbooks & best practices. These providers make spinning up an MMM faster and cheaper…but they are still MMMs. Again they are great for generally stable businesses, but a major problem remains for the fast-growing cohort of companies: if you are relying on the organic fluctuations of your business and advertising spend to fuel an MMM, the result will be something that appears to be highly precise but might be a massive hallucination. These models rely on large historical datasets (12-24 months) and can easily confuse cause and effect, e.g. are the results from a Black Friday sales bump due to the uptick in spending on Meta during that period or the increased consumer proclivity to buy during that window? Additionally, the historicals of growth-stage businesses are often just too volatile and the advertising changes are not aggressive enough for MMMs to be useful by themselves. An MMM fueled by aggressive incrementality testing is another story, though. More on this below.

TLDR:

• Fast & lean MMM providers continue to emerge, but they don’t make MMMs alone any better at delivering marketing insights

The Rise of Incrementality Testing

The biggest trend in the last ~18 months in the marketing world that will certainly continue in 2025 and beyond is the explosion of incrementality testing. Platforms like Haus and Measured have created tools for advertisers that enable them to run lots and lots of geographic holdout tests in their campaigns. When these tests are run properly, they tell marketers very quickly what results their spend is delivering to their business without needing any support from analytics or data science teams. These tests don’t rely on cookies and are very privacy-friendly. They give marketers rare slivers of truth in a sea of apples and oranges (see above). Well-structured and analyzed incrementality tests tell marketers, at a moment in time, what results are actually coming from a campaign or platform. They do this by simply turning the tested marketing effort off in a variety of locations and seeing what happens. If you do this and no KPIs change, whatever you were testing wasn’t doing very much work for you. Some challenges with incrementality testing are that you can only run a couple of tests at any given time, and keeping track of test results gets pretty complicated. More on this below. Disclaimer: I am a Haus investor and advisor.

TLDR:

• Well-run incrementality tests deliver a rare snapshot of truth and allow for cross-platform comparison

• Only a couple of tests can be run at any given time

• Once you have run lots of tests, results can be hard to keep track of

On the Horizon: Incrementality-Driven MMMs

A new class of tools that is on the cusp of being brought to market and widely adopted is the incrementality-driven MMM (“iMMM”? You heard it here first?). First and foremost, the most valuable MMM is one with a massive amount of aggressive incrementality tests in the historical data that the model is ingesting. I am sure that I will never use an MMM again without a rich history of incrementality testing, and ongoing incrementality testing run in parallel to the MMM. Additionally, while the existing MMM tools can ingest incrementality tests into their datasets, advertisers need these tools to put the results of the incrementality tests as the hero within the MMM readouts. The incrementality tests are the strongest, and sometimes the only, “facts” in the data while everything else is based on modeled correlations. An MMM used in this manner can be a very helpful repository for housing and visualizing incrementality test results and surrounding modeled data over time as performance data and test results build up within a company’s historical data. I am sure that there will be several providers who bring this to market in 2025 and foresee them being the standard operating for marketers very quickly.

TLDR:

• Incrementality-driven MMMs are a new class of emerging tool

• 2025 will certainly see many new products emerging in this category

Conclusion

As we look toward 2025 and beyond, the landscape of marketing measurement is rapidly evolving. The challenges posed by privacy regulations, the uncertain future of cookies, and the expanding walled gardens of major advertising platforms necessitate a shift in how marketers approach measurement. Incrementality testing has emerged as a vital tool, offering rare snapshots of truth in an environment filled with inconsistent data. The likely rise of incrementality-driven MMMs promises to combine the strengths of traditional models with the actionable insights of rigorous testing. By focusing on accurate measurement and being adaptable to technological and regulatory changes, Marketers can maximize the ROI of their marketing dollars and elevate their brands to new heights. The future holds many uncertainties, but with the right tools and strategies, marketers can navigate the complexities and thrive.

TLDR:

• Marketing measurement is constantly evolving due to privacy regulations and technological changes

• In 2025 and beyond, incrementality testing will continue to take off

• Incrementality-driven MMMs will emerge as a new category of tool and become essential to marketing measurement

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text on the image”.

I hope this 2025 calendar might help some marketing folks out there plan their 2025 campaigns and promotions during this busy time.

I am also going to keep a copy on my desk and break it out next time I am working with a team and we are saying "how the heck can we justify running a promotion next month?!" because there just might be a holiday or celebrated occasion that is a perfect fit for the brand we didn’t remember.

And yes, Cyber Monday is in December again next year 🤦‍♂️

Let me know what important dates I missed as I am sure I didn't get them all.

Growthish 2025 Essential Marketing Dates & Planning Calendar

95KB ∙ PDF file

Download

Download

• Practical Approaches: We talk about methods that have helped me drive growth for various businesses.

• Current Trends: The video covers some of the latest developments in marketing measurement and how they might impact your strategies.

• Real-World Examples: I share experiences from my work with different companies, which might resonate with challenges you’re facing.

If these topics interest you, I invite you to watch the video and share your thoughts.

Feel free to leave a comment or reach out if you’d like to discuss any of the ideas further. Thanks to Zach and the Haus team for having me on!

I have found businesses with very strong weekend sales to be particularly tricky to manage on Meta. I have also witnessed firsthand that Meta finds these businesses particularly challenging as well.

Why are Strong Weekends Hard for Meta & Growth Marketers?

• A two day spike(the weekend) is not that long…

• A five day lull (the weekdays) is pretty long!

• Over-managing campaigns (“touching them too much”) is a great way to kill performance. 2x touches every week just for weekend management burns pretty much all the touches you should allow yourself in a given week.

• Increasing budgets significantly at any time triggers the dreaded “learning mode” which hurts performance.

I do think that the reverse scenario (strong weeks, softer weekends) is a much easier scenario to manage. With a five day strong period followed by a two day lull, the majority of your week is strong. However sometimes the challenge with these businesses can be when Monday is the strongest day of the week and campaigns need to “wake up” after a sleepy Sunday.

OK then what are our choices?

• Do nothing and pray to the Meta gods 🙏

• Adjust budgets up every Friday/Saturday AM and down every Sunday PM/Monday AM

• Stable budgets with high bid caps. Keep the budgets high throughout the week and weekend and give Meta evergreen CPA targets ideally with campaigns spending more on weekends than weekdays while hitting your CPA targets.

• Use “The Budget Tool”, the wonderfully named tool released in fall 2023 that allegedly avoided triggering learning mode with large budget swings.

• Launch Weekend-long “Lifetime Campaigns” overlaid on top of existing campaigns.

• Other options? Let me know!

Well, what is the best option?

• Do nothing and pray to the Meta gods: I have found this not effective particularly with businesses that have very strong weekends. Right now, Meta just cannot react fast enough to spiking demand. I am sure they will fix this someday. But it’s not fixed yet. If your weekends are only slightly stronger than your weekdays, this could work for you though! Remember, when in doubt, touch it less.

• Adjust budgets up every Friday/Saturday AM and down every Sunday PM/Monday AM: This is a lot of thrash in the campaign and we all know we need to touch our campaigns less. Plus you need to navigate with sending campaigns back into learning mode with +20% changes, although I believe any change causes some re-learning to occur. This could be OK with small changes but I would try to avoid it. This is very scary with big changes because you risk destroying your evergreen workhorse campaign performance.

• Stable budgets with high bid caps: While this in theory should work, in practice I have seen across multiple companies these campaigns work for a couple of weeks but then just wither and die. They don’t keep spending for mysterious unknown Meta reasons.

• Use “The Budget Tool”: When Meta launched this tool it sounded like weekend management would would be a perfect use case, but then after using it with mixed results this way, then heard that it should only be used once in a while like getting ready for Black Friday…which is a scary way to get ready for Black Friday…not adviseable.

• Weekend-long “Lifetime Campaigns” overlaid on top of existing campaigns: This I have found to be the best option! Overlaying weekend long Lifetime campaigns on top of your existing campaigns allows you to not touch your workhorse evergreen campaigns while also allowing you to spend more on weekends. However, its July 30, 2024, and this could be a horrible option next week because these things change so fast. But for now this is the best option I have found recently.

What other options are out there that I missed? As always, reach out to me at rob@growthish.com with any thoughts.

The Squid Head: Your Strategic Marketing Core

The head of the Marketing Squid is where your strategic elements converge and become the foundation where all of your marketing tactics and decisions grow from. You must first know who your customer is, then you can determine what the top benefits are that you can deliver to these customers with your product, and finally you can determine what words are best to communicate these benefits with your messaging. 

• Customer Definition: Who are you targeting? Understanding your audience is crucial. What is their age, job, location, gender, interests? An ideal customer definition should be concrete enough that you can identify people you have met in your life that match your customer profile. You can either research the customers you have or you can research the customers you want to target. You need data to tell you the insights into the needs, preferences, and pain points of your target audience, allowing you to tailor your marketing efforts effectively. You should also have one primary customer target. Focus is critical. If you have 8 different personas/ICPs/customers you are targeting, you have no focus!

• Benefits/Differentiators: What sets your product or service apart from the competition? While many offerings boast a multitude of features, it's crucial to leverage quantitative and qualitative research to help you focus on no more than three benefits. These key benefits will take center stage in your messaging and later in your marketing tactics. This research doesn’t have to cost a lot and you should be very wary of anyone internally saying “we know this already” who is not pointing towards some form of quantitative research. If you have to pick one place to spend research money, this is usually the best spot.

• Messaging: How do you communicate your value proposition in a way that resonates with your audience? Testing your messaging using both quantitative and qualitative methods is very helpful to ensure you're effectively communicating the benefits of your product. By iterating and refining your messaging based on data-driven insights, you can communicate your value proposition in a way that resonates deeply with your audience. 

These core elements form the strategic backbone of your marketing efforts. Without a clear and strong head, your squid’s tentacles will flail aimlessly.

The Squid Tentacles: Tactics, Briefs & Execution

While a real squid has eight tentacles and two arms, your marketing squid can have infinite tentacles! The point here is not the exact number, but the flexibility to adapt and grow from the same foundation (the head). These 'tentacles' represent specific marketing channels or tactics, each deriving its direction and strength from the clarity of the head. Tentacles can include:

• Email Onboarding: Effective email onboarding relies on the clarity of the squid head, ensuring that the messages resonate with the target audience's interests and preferences. Your benefit based messaging should be a punch list for the concepts and subject lines for your email onboarding. 

• How It Works Video: You can only get 3 or 4 concepts across in a “How it Works” video. The squid head should guide by identifying the most compelling features and benefits to showcase.

• Website Messaging: Again, the squid head should create a clear hierarchy for your website messaging. Above the fold? Your #1 benefit message for your target customer. Just below the fold? #2. Etc.

• PR Briefs: The squid head tells you who your customers are with enough clarity that you can then determine which publications you want to be in. The head also tells your PR agency what you should try to get writers to talk about in those amazing hits they get.

• Influencer Briefs: The head can also tell you who your influencers should be, on what channels they should be strongest and what they should be ideally talking about in their spots!

• Channel Selection: The head tells you who your customers are so you know what channels you use to find them. 

• And more…any marketing tactic/tentacle you might want to deploy can, and should, be heavily informed by your well defined squid head.

Embrace the Squid!

The Marketing Squid offers a structured approach to building a marketing strategy that is both comprehensive and adaptable. Start with the head, your foundation, before extending to the tentacles, the channels and tactics. This approach ensures that every piece of your marketing puzzle is aligned, purpose-driven and consistent. This makes your marketing more effective and ensures you are giving your brand the best chance of breaking through the minds of your target customers with the highest impact messages you have at your disposal. 

I hope you find the Marketing Squid helpful when thinking about how you can grow. As always, please reach out to me at rob@growthish.com with any thoughts or other marketing tools.

The most insightful form of user testing is moderated user testing, where there is a trained guide helping with individuals who are fresh to the process through the test. These "virgin" testers, who have never participated in such tests before and are unaware of the product or site they'll be evaluating, offer the most unbiased and authentic feedback.

One crucial aspect often overlooked is the element of surprise. If a tester knows in advance what product they'll be testing, they're likely to try to “do their homework” which can skew their natural reactions and first impressions. And it's these first impressions that are gold. Do they understand your offering? What questions arise immediately? How do they go about seeking answers?

Equally important is the avoidance of "professional" user testers. These are individuals who frequently participate in user testing for sites like usertesting.com, often as a side hustle for extra cash. The issue with these testers is their tendency to see themselves as UX experts, leading to generic advice that doesn't represent the thoughts and reactions of a genuine first-time user.

Another key factor is moderation. It's far simpler to conduct unmoderated user testing and just record the tester’s screen and audio, but having a moderator present to prompt the tester to articulate their thoughts, delve into areas of interest, and keep the session on track is crucial. This interaction helps capture authentic, valuable insights that unmoderated sessions often miss.

Despite its importance, moderated user testing is rare due to the logistics involved. Recruiting virgin testers, ensuring technology compatibility, having adept moderators, and processing the results effectively are all daunting tasks. Yet, it's arguably the most crucial step you can take to boost conversion rates, inform your product development pipeline, and more.

Businesses operating at scale should aim to conduct moderated user testing quarterly, testing any new product elements and revisiting existing to ensure continued comprehension and efficiency. I built our team internal testing capabilities at multiple companies, but as a consultant I don’t have this as an option. Fortunately I have found a great agency that specializes in moderated user testing as a service (MUTAAS?). Feel free to contact me for an introduction if you’d like to chat with them. If you want more detail or want to build this capability internally for your team, check out the classic, ultimate instruction manual for user testing: “Don’t Make Me Think, Revisited” by Steve Krug.

Remember, in the world of digital products, user testing isn't just a nice-to-have; it's a must-have. Don't be the business that overlooks this crucial step. I can guarantee that you will find multiple jaw-dropping issues with your product the first time you test your product the right way.

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text on the image”.

The matrix is a simple 2x2 with market growth rate (high vs low) on one axis and market share (high vs low) on another. The four categories companies can fall in are Dogs, Cash Cows, Question Marks and Stars. Dogs are small market growth rate, small market share. Cash Cows are high market share, low market growth rate. Question Marks are high market growth rate, low market share. And finally Stars are high market growth rate, high market share.

BCG, and later Bain, introduced the growth-share matrix to large conglomerate product manufacturing companies in the early 1970s and helped many of them improve performance by following a simple path...invest in the Stars. Divest the Dogs. Milk the Cash Cows. Be wary of the Question Marks.

For over half a century, both practitioners and academics have extensively scrutinized the BCG Growth Share Matrix and it has many flaws to be sure, but I find it to be frequently useful in my work. Many VCs certainly use a version of this in placing their bets as well. It is helpful for me in thinking about what companies I work with, and could be useful for full time employees looking at job opportunities.

Is the company you are looking at in a category that is growing? How fast is it growing? Several companies I have worked with over the years were great companies, but not in categories that were growing quickly.

Does the company you are looking at have a shot at being the market leader? Or are there multiple 800lb gorillas already there? In the software world there are booms and busts, and many are quick to jump into trends with companies where it is unlikely they will be able to be the market leader. The purveyors of the BCG Growth Share Matrix would argue to give yourself a shot! Work for a company that has a chance of being the market leader.

Take the generative AI market right now...there is one clear Star (OpenAI/ChatGPT), lots of gorillas lurking (Google, Amazon, etc.) and a whole lot of Question Mark companies trying to get in the mix. If you were to use the BCG Growth Share Matrix and apply it to generative AI, you would likely conclude if you were going to make a move, going to a smaller upstart generative AI company would be risky, and OpenAI/ChatGTP would be the safest bet.

Consider companies like Uber, Doordash, Zillow, Stripe, and Google; analyzing their trajectories through the lens of the BCG matrix reveals that they were always, or evolved into, 'Stars' - market leaders in rapidly growing categories.

Today I use the BCG Growth Scale Matrix to help me decide which companies I should work with. I wish I learned about it earlier! In hindsight I have spent a lot of time at potential Stars, but I have also put in significant time with Cash Cows, Question Marks and Dogs.

The brilliant Richard Koch, champion of the 80/20 principle, accredits a lot of his investing success to the Star principle. His ethos is to go all-in when you find a Star, and it has served him very well.

I hope it is useful for you as well and please let me know at rob@growthish.com how I could think about this in a better way. And as always if you know of other unique growth marketing tools or service providers I should investigate, please send them my way.

Given how much money flows through Marketing and Growth teams and campaigns, it’s essential to be fluent in not just marketing terminology but also in the languages of Finance and Product. Different GTM strategies focus on different metrics, companies always use slightly different definitions for the same metrics, and we all know that the business world is constantly creating and reinventing acronyms.

Finance & Marketing Cheat Sheet For Growth Marketers Growthish V02

4.43MB ∙ PDF file

Download

Download

I have been testing this out and found it to be useful, but I am sure I have missed some metrics and mangled some definitions. I hope it is useful for you as well and please let me know at rob@growthish.com how it can be better. I will share updated versions as material improvements are made. Huge thanks to my friends at Lasagna who nailed this design.

And as always if you know of other unique growth marketing tools or service providers I should investigate, please send them my way.

Here’s how the PR Whisperer works:

1. You send the PR Whisperer a note when you are looking for a PR firm with your target budget, contract duration and a brief overview of your priorities.

2. He analyzes your company and goes through his database of several hundred PR firms, asking the ones he thinks would be the best fit if they are 1) OK with your budget and duration 2) if they are conflict free 3) and for relevant clients and a brief text-based pitch. He introduces you to the top 3 or 4 firms that you agree are the best fit for your business.

3. You meet with the firms you want to meet and sign up with one if you like them.

4. For this incredibly useful service…you pay the PR Whisperer nothing.

5. He gets paid a commission from the winning agency, if there is one.

The PR Whisperer has helped +1500 companies find PR firms. At any given time he is helping ~10 companies find their next PR agency. I have successfully found several firms with him and highly recommend his work. He is a one stop (free!) shop for finding a PR firm and makes running the whole RFP process much more efficient and easy.

There is an interesting positive side effect when working with him. Similar to working with a contractor vs a sub-contractor when working on a house project … agencies want to stay on his good side and treat his referrals well so they keep getting deal flow from him. If any of you have ever tried to hire a tile or cabinet subcontractor directly you’ll understand what I am talking about. He deep context across the industry covering track records & reputations, as well as market rates for various services.

I’ve partnered with the PR Whisperer. If you have any questions or would like an introduction to them, hit me at rob@growthish.com.

If you know of other unique growth marketing tools or service providers I should investigate, please send them my way!

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text on the image”.

Lately I’ve been working with a company that has built an AI-driven tool that largely automates content marketing end-to-end. Over the years I’ve spent well over $100,000 and thousands of team hours doing what this tool does entirely with AI. Huge thanks to Nat Robinson @ Trustworthy for the introduction.

Here's what this company does:

1. Automated Content Analysis: You start by dropping a line of your code on their site so their platform can learn what is working on your site now. This generates a rich dashboard of content performance that updates in real time.

2. AI-Created Content Calendar: Their platform then uses AI to generate a content calendar for your business based on your existing content performance, fully automating the planning process. You can modify the calendar created as you wish.

2. AI-Generated Content Briefs: Each piece of content in the calendar has a brief, also generated by AI, which you can modify to adjust the output however you wish. You can also select which key statistics you would like to include in the piece, which are also collected for you by AI.

4. Automatic Content Creation: The platform then generates the content from the AI generated content calendar and AI generated briefs you could modify as you wish and includes whatever datapoints you selected.

5. AI-Driven Engagement Units & Image Generation: For each piece of content, the platform creates relevant images using AI, ensuring that visual elements are as engaging and tailored as the text content but also require no licensing contracts or fees. AI also populates engagement units driving traffic to engage more deeply with your site to boost conversion rate.

6. AI-Generated Podcasts for Each Post: Icing on the AI cake is an AI generated podcast about your AI generated post that is an actual discussion of the post, not just an audio recording of it.

The amount of time, effort and money this platform removes from content marketing is truly mind-blowing. Even if you just use it as a starting point for each step, its an exponential change in efficiency.

I’ve partnered with this company. If you have any questions or would like an introduction to them, hit me at rob@growthish.com.

And as always if you know of other unique growth marketing tools or service providers I should investigate, please send them my way.

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text on the image”.

I've been working with a company that has developed very clever automated bid management technology specifically for managing paid search bids when a company also has relevant organic search results. The result in the right situations is a very dramatic boost in ROAS. Huge thanks to Growth guru Steven Johnson for the kind introduction.

Here’s what this technology does:

1. Continual Monitoring of Your Bids, Your Organic Placements and Your Competitors: Every six minutes, the tool uses 3rd party data to monitor your Google paid search ads, your Google organic search rankings for those terms, and your competitors bidding on your paid search terms (if any).

2. Strategic Bid Adjustments: When your organic content is in the top organic spot for a paid search term with no active competitor bids, the system automatically lowers your bid to $0.01 CPC. This keeps your ad in play but at a $0.01 click and blocks PMAX from overbidding. In the event a competitor begins bidding on that term, the tool immediately adjusts your bid back upwards to block out your competitors attack.

This approach ensures minimal spend on terms you already dominate organically, improving ROAS by automatically reducing your "Google tax" payments when you don't need to pay them.

I’ve partnered with this company. If you have any questions or would like an introduction to them, hit me at rob@growthish.com.

If you know of other unique growth marketing tools or service providers I should investigate, please send them my way.

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text on the image”.

Consumer and prosumer software growth stage companies are my bread and butter. Currently I work with Prose, SPAN, MileIQ, RUX, Humane, and Halo among others. I was previously SVP of Growth at Tonal. You can learn more about me on LinkedIn.

I will only post when I have high-value content to share, so don’t be afraid to subscribe.

Image courtesy of ChatGTP, prompted with “Please give me the perfect image for this post in a modern minimal 1960s style in grayscale with no text or humans in the image”.