Absence Makes the Brand Grow Stronger: CaJu 2.0
New CaJu Offers and methods for 2026
In this article…
Allow us to reintroduce ourselves
Data analysis in the core offer
Audience modeling improvements
Scientific content production
Two-pronged KPI-targeting
Our new, formal Paid Media structure
New Profit-Share ad pricing model
Employee-Generated Content program
Our “Content Blitz” package
CaJu-U + Consulting
Well, well, well.
It’s been a while. Consider this a mea culpa for the radio silence, but if it’s any consolation, you’ve been on my mind.
It’s been almost a year-to-date since I sent out an update, but I promise I’ve had good reason.
2025 was a whirlwind year for CaJu. We began this journey in 2024 with the mission of becoming a marketing agency for “the little guy.” That mission came with its own set of challenges, and a lot of lessons you only learn by doing.
Truly, if it were easy, everyone would do it.
Rather than walk you through every false start and every experiment we ran this past year, I’m going to use this edition of the newsletter/blog to update you on CaJu’s 2026 operations and the specific problems each change was meant to address.
A lot of our growing pains are probably the same ones you’ve felt as a business owner. Here’s how we worked through them and why.
Data analysis for all
First off, we’re rolling our data analysis work into our main offer. Originally, it lived as an add-on. In practice, we found that many teams that are not trained in analytics have no clear way to see what they are leaving on the table by not modeling their sales data, customer behavior, or website traffic.
By including data analysis in the core offer (at no additional charge), we do two things at once. We raise the value of our work, and we make the onboarding and research phase sharper. Keeping this service as an add-on was effectively tying our own hands when it wasn’t opted for. Especially when considering that data analysis is not a typical marketing agency offer.
If you’ve got it, flaunt it.
Research goes Psycho… graphic.
On the research side, we’ve expanded our ability to develop a more complete audience picture. That includes the existing basics (who the customer is), i.e., demographics, and now the addition of a more useful layer (why they buy, what they’re trying to become, and what story they’re telling themselves when they choose one brand over another), i.e., psychographics.
We’ve expanded the sources we pull from and our modeling ability, such that our persona research contains entire data-backed sections now devoted to how these personas think, not just who they are, where they live, and what they buy.
If you’ve ever tried running ads and felt like you were sort of guessing when it came to targeting the right people – struggling to really speak their language – this is usually the missing piece. By reviewing open source psychographic surveys joined on existing demographic data, we can develop a better idea of a persona’s self-conception, priorities, interests an behaviors. That allows for much more personal creative and targeting.
Better audience insights make for better messaging. Better messaging makes for better performance. Better performance makes for cheaper campaigns. Cheaper campaigns keep money in our clients’ pockets. Saving our clients money makes us happy.
Scientific Content Marketing
This is a cool one.
Internally, we’ve experimented with several workflows for content production, and have now arrived at a repeatable, testable, scientific approach to content creation and optimization that still leaves room for creativity and taste.
Here’s the version I can share without giving away the recipe: we don’t treat content as pure “guesstimation” based on the assumed characteristics of top assets. That is to say, we’ve found a way to quantify our qualitative approach to the content of content.
Using this system, we can study what reliably resonates with followers, translate those patterns into a practical creative process, and make well-performing content that leaves very little to algorithmic chance.
For our clients, externally, this looks like more consistent posting, clearer brand voice, stronger hooks, and more predictable movement toward the KPI that actually matters to their individual business goals. For us internally, this looks like a major streamlining in operations; better output for far less labor input.
Dual-State KPI Targeting
That’s a fancy way of saying “we’re aiming at two things at once with our content.”
The “CaJu Method” now includes a deliberate two-pronged approach to content strategy.
During a client’s onboarding phase, we define principle KPI that best fits their intended business outcome. The content we create for them is then only informed by that target KPI, but to that end, we further develop it into two subtypes:
A high-reach variation designed to get in front of new audiences, increase discovery, and make potential followers (cold leads) problem-aware.
A high-retention variation designed to build trust, demonstrate competence, and make existing followers (warm leads) solution-aware.
We noticed that many brands attempt only one of these two kinds of content, which assumes the pros as well as the cons of that particular approach. Trend-driven content can grow an audience fast, but at the cost of high churn. “High value” content raises retention, but typically remains trapped inside a small audience bubble.
Our solution is simply not to split the difference. By mixing the two modes consistently, we procure the pros and combat the cons.
The real success criterion under all this is goodwill. When you give value for free, consistently, to the right audience, you increase the perceived value of the brand. That makes future offers feel more reasonable, even if the prices do not change.
A Two-Phase Paid Media Approach
Our approach to paid media has always been test-driven, but now that process itself has been tested, matured, and formalized. First, we run controlled tests, reallocate resources, and then scale what proves itself.
This approach seems obvious on face value, but is often complex to apply practically due to small sample sizes in the testing phase. It’s these specifics that we’ve worked the kinks out of.
Unstrategic ad campaigns are prone to either scaling too early and plateauing quickly or continuing to test indefinitely or being abandoned due to unrealized potential, wasting both the money invested in testing and any potential scaling returns.
This past year, we put more emphasis on measurement discipline. We developed new proprietary mathematical models, which I call “Near-Conversion” Indicators, that allow us to standardize and rank the potential of ads against themselves and all available metrics, rather than comparing campaign performance to competitors’, measured solely by conversions (which can be sparse when testing budgets are intentionally low).
Ad sets that cross our internal performance baseline now do so with much more obvious signals. This lets us redirect resources towards maximizing returns on top-performing assets through micro-optimization, minimizing the time and resources we spend in the targeting and creative A/B testing phase.
Our system, overall, remains largely unchanged; it’s just more concrete now, which makes progress more obvious to our clients.
We still perform research, which still informs our content, which still informs our ad testing, which still informs our ad scaling, and so on. We’ve just standardized each piece of the process so the outcomes are more predictable and therefore more scalable.
Our Brand-New Profit-Share Pricing Model
This evolution forced us to innovate our pricing structure, too. I think we’ve truly developed a win-win scenario here.
Traditionally, agencies formulate their paid media fee as a retainer or a percentage of total ad spend. For our legacy clients, we signed them on a similar model. A singular retainer fee covered our content marketing and our paid media strategy work. But there are incentive downsides to this that never sat right with me.
If you think about it, flat fees via retainers and percentages of the pre-run budget don’t actually incentivize good ad performance. They incentivize contract extensions and bloated budgets.
Spending more is categorically not the same thing as making ads more successful, so going forward, our paid media offer is structured around a profit-share model.
That means we take our fee as a percentage of post-run profit, not a percentage of pre-run ad spend. More specifically, we only participate in the upside after a mutually agreed-upon “baseline” is cleared.
That baseline is a dollar amount tied to a client’s unit economics (price points, margins, and what counts as a meaningful result for the business). The purpose is simple: you should not be paying a performance fee until the ads are clearly producing surplus value, and until there is enough headroom for the campaign to scale without stressing cash flow.
Here’s what this looks like in a simplified example. For clarity, I am going to use “ad profit” as a shorthand for revenue minus ad spend.
Let’s say your monthly testing budget is $100. Beginning in our Testing phase (which I previously outlined), we split the budget into two experiments at $50 each.
One experiment performs poorly. The other produces an ROAS of 2. That means on a $50 spend, it generates $100 in revenue. A good indicator, but we don’t stop testing there.
In the next cycle, we allocate the full $100 budget to the winning ad set. If ROAS holds at 2, that $100 produces $200 in revenue. That is $100 of ad profit.
Now we apply the baseline. Let’s say we agree the baseline profit is $100. That means the first $100 of profit is reserved for you. Our fee would not apply yet, because the campaign has not produced surplus profit above the baseline.
This is the key point: you are not paying us out of pocket for “management,” and you are not paying us simply because money was spent. You are paying only when the ads are producing a clear upside.
Continuing our example, at this point, the client would have a strategic choice. If they wanted aggressive ad scaling, they could reinvest most or all of that $100 profit into the next cycle’s budget. If they wanted to be more conservative, they could pocket a portion and increase the budget more gradually. Either way, they are not being asked to keep funding bigger budgets out of pocket just to keep the experiment alive.
Let’s follow the aggressive version for one more cycle.
They reinvest the entire $100 profit, bringing the next cycle’s budget to $200. If the ROAS of 2 holds, the ad generates $400 in revenue, which is $200 of ad profit.
We would then look at profit above the baseline. With a $100 baseline profit, there is now $100 of surplus profit. Our fee is a pre-agreed percentage of that surplus, not a percentage of the spend.
In all cases, the client always keeps the majority of the returns, and because the baseline is protected, the campaign can keep scaling without putting the business in a position where the agency is the only party benefiting.
This is the real mechanism behind what people call “exponential” ad returns.
The returns on any single dollar of spend can look linear on paper, e.g., invest $1, get $2 back; invest $1,000, get $2,000 back. You still have to come up with the cash to invest initially. From that perspective, marketing does not appear all that lucrative because the returns are linear.
However, that is an error of perspective. The returns compound when a new cycle’s budget can be funded by the previous cycle’s profit.
If a $100 ad returns $200, that ad can be rerun for $200 to gain $400, which can be rerun to gain $800. Taken as a holistic process, each cycle has not paid for itself; the first cycle has paid for every following cycle. In this example, $100 has become $800 across 3 cycles, not $200 across 1.
The first round is the only true out-of-pocket risk. After that, scaling can be self-funded, as long as the economics hold. The trick is to test to find as lucrative a first cycle as possible. That sustains further and faster scaling.
Of course, ads do not scale indefinitely. Creative fatigues, audiences saturate, competition shifts, and ROAS eventually plateaus. The nice thing about a reinvestment-led scaling model is that you can respond without panic. If ROAS declines, you simply reduce the reinvestment rate to match the new reality, keep pocketing profit, and begin a fresh round of tests. By the time a campaign runs its course, it has usually funded the next set of experiments.
In plain terms, this new model ensures we win only when the client wins, no matter the size of the budget.
Our new EGC Program
We’ve made major logistics improvements on the production side. This year, we authored and instituted Employee-Generated Content programs for our clients.
Employee Generated Content is content shot by (and usually edited by) “front-line” employees within a business. It’s warehouse workers racing forklifts or a cashier telling the story of the craziest cash-alternative a customer ever tried to pay with. It’s interesting because it’s real and revealing.
EGC is all the rage right now because authenticity works, and most businesses already have the raw material for authentic content within their existing teams. The main obstacles standing between companies and having their existing employees are systemic (thus, solvable): employees lack proper training or incentives to do additional creative labor in addition to their regular jobs, and most businesses can’t afford editors, let alone a content strategy to follow.
Our EGC problem minimizes these systemic obstacles.
We help clients build a culture of content from the ground up, with training, structure, and a low-friction capture and upload flow so that employees don’t feel like capturing content is an additional task for no additional pay.
We work with management to develop an incentive program where participation is rewarded. We provide regular pre-recorded or live seminars on various themes so employees can develop their soft skills, like communications, and hard skills like camera work and editing, on a timeline that is convenient for them. We give regular prompts informed by our research so employees don’t feel like they need to come up with ideas from scratch and always have strategy-aligned suggestions they can follow.
Critically, we handle the editing and the marketing of the EGC assets, so employees can “shoot it and forget it" until it shows up on the company timeline.
This solves a real problem for small business marketing and hybrid remote digital marketing agencies. Traditional production can be expensive, slow, and sometimes too polished to feel real on social platforms. The CaJu EGC Program fills the volume and authenticity gaps without sacrificing brand coherence or paying creative labor premiums.
The “Content Blitz” is still our golden child
The new CaJu EGC Program pairs nicely with our existing “big-value, fast” Content Blitz offer.
For prospective clients who want to try our high-production content without a contract, our Content Blitz includes deep research and strategy, as well as a detailed plan to capture several months’ worth of content in one or two production days. It’s a perfect way to sample the CaJu approach: strategy, content production, and editing, all in one concentrated sprint.
For our retainer clients, Content Blitzes are *included for every two months a contract covers, so high-value production is built into the process.
* This is dependent on physical proximity and is not always feasible for every client.
CaJu: Coming to a virtual classroom near you
Lastly, in 2025, we spoke with a lot of prospective clients who helped us realize that partnering with a marketing agency (no matter what size) is not always the right move for every business, at every moment.
And that’s okay. But we’d still like to help.
Over the course of 2026, we’ll be developing “CaJu-U” (CaJu University), an educational program designed to teach what we know about research, strategy, content marketing, paid media, production, and analytics.
The goal is to give small business owners and teams enough knowledge to run a serious digital marketing operation themselves, with structured lessons, practical assignments, downloadable resources, and regular live Q&A sessions.
And for those who would like even more hands-on help but are also not yet ready to sign on with an agency, we’ll also be offering consulting. This wouldn’t be your typical “one Zoom call a month” type of consulting. This would be research, strategy, presentations, and paid media tracking/optimization walkthroughs tailored specifically for you and your unique business situation.
If anything I’ve said here today sounds interesting to you, please don’t hesitate to respond directly to this email, and I’ll be more than happy to get you any additional information you need.
If you’re getting this in your inbox, thank you for subscribing to CaJu’s Fresh Picks, even during the sabbatical. I’m back on the horse, and new content will be rolling out weekly again.
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Until next time (and I really missed saying this), stay fresh.
- Casey