Kynship

We started this because we saw the transactional nature of influencer marketing today as just scratching the surface. No agency was providing anything deeper other than money exchanged or received, nor a desire to do anything more. This was dissatisfying and out of it, a desire grew to create a "kyn" between brands and influencers. A table where both exist to create a culture of trust and empowerment. Our approach is simple: we build your community of influencers on giving, not asking and sales will be the outcome of that.

Co-Chief Executive Officer

Launched a Shopify App to help brands seed influencers easily through our all-in-one seeding app. Send your products to any influencer within your store.

Founder; The Influencer Seeding App

QALO Inc.

Prior to starting Kynship, I began my journey at QALO, the brand that created the silicone wedding ring for the active lifestyle. There, I grew the ambassador and influencer roster from the ground up - to 500+ people including names such as Lebron James, Mike Trout, and Dale Earnhardt Jr. As QALO grew, the influencer roster became as wide-ranging as the product offering: to mommy bloggers, firefighters, outdoors, and even pet influencers.

Influencer Marketing

Helping 8-9 figure DTC brands drive growth + reduce CAC with performance marketing

If you’re involved in an 8-9 figure ecommerce brand, you’re in the right place.

I'm Cody Wittick, Co-Founder and Co-CEO of Kynship, an ecommerce growth agency that helps 8-9 figure e-commerce brands scale new customer revenue (efficiently).

Over the past 5 years, our agency driven over $150M in attributable revenue, analyzed 100+ P&L's over the past 18 months, and produced 200k+ ad creatives  for our DTC clients. 

How do we do it? Not through a set of services, but proven system where each stage is designed to make sure every part of your business drives financial success.

A few brands we’ve worked with:

- Purdy & Figg (increased new customer rev. 772%, reduced CAC by 61%)
- Supergut (increased new customer rev. 799.53%, reduced CAC by 24.96%)
- Saltyface (244% increase in NC revenue, 512% increase in ad spend)
- Wildbird (hit a 5 aMER, 30% Contribution Margin (CM)%, and 17.5% Profit%—Kynship has been within 1-5% of those goals throughout our 2+ year partnership.)


On LinkedIn, I share everyday insights into the work we do as an agency to help ecommerce brands operate profitably while driving growth:

- Financial forecasting
- Influencer marketing
- Product seeding
- Meta ad account audits
- Cost control ad strategy
- Industry case studies
- DTC observations

If you’re interested in this type of content, make sure you’re following along — any questions related to influencers, paid strategy, or if you just want to talk, my messages are open.

Okay seriously, I just audited an account where ads had been reset 27 times in the last month.

TWENTY SEVEN TIMES… 

There were changes made almost every single day for the entire month:

- campaigns turned on and off
- budgets changed
- ads killed and relaunched

Unsurprisingly, the results over the last 6+ months have been a disaster.

I’m not sure if folks genuinely believe they can out-manage Meta’s algorithm, or if they are just trying look useful through constant activity in the absence of tangible results.

Please don’t do this.

Meta does not work this way. The system is built on learning. Every reset wipes out data, social proof, and optimization history.

When we manage accounts, each ad gets a minimum of two weeks to prove itself. We give Meta the time it needs to optimize placements, identify high-intent buyers, and allocate spend efficiently. 

We let the algorithm cook.

And that’s why we’ve become so good at helping DTC brands bust through growth plateaus, most recently growing WildBird’s revenue by 10x while maintaining 5 aMER, 30% CM, and 17.5% profit.

1. Align top and bottom line goals.
2. Scale creative.
3. Structure ads around cost controls

Let it cook.

Cody Wittick

I help ecomm brands grow new customer revenue.

What people think our media buyers do all day:

- wake up
- upload creative
- adjust cost controls up and down
- sleep

What are media buyers actually do: 

- Adjust that “suggested” profit target to one that will actually achieve the brand’s goals

- Calculate if the competitor's "4.0 ROAS" would bankrupt the business in 30 days

- Evaluate how that 1am “TEST BILLBOARDS!!!!!!!!!!!” email might fit into the client’s ad budget

- Set ONE perfect cost control and pray to the algorithm gods we never have to touch it again

- Build forecasting models based on cost centers and LTV instead of that one podcast story

- Explain why your beautiful new creative isn't getting spend (and why that's a win)

- Constantly feed Meta diverse creatives

- Convince the creative dept. that exclusively “on-brand” creatives are a fast-track to insolvency

- Pretend you didn’t hear “Let’s just duplicate the ad, it worked last year”

- Test a brilliant new creative… only to watch Meta spend $3 on it over 7 days

- Convince everyone that Meta's algorithm is smarter than any of our brilliant new ideas

We do actually sleep though, so we have that going for us, which is nice.

If you want to work with media buyers who help DTC brands between $2M–$50M break through growth plateaus by reverse engineering from both top and bottom line goals, building scalable creative systems, and driving new customer growth profitably… let’s talk.

Last week, I audited a DTC account spending $50K/month and found something that made my stomach drop. Unfortunately, it’s not the first time I’ve seen this EXPENSIVE mistake…

When I opened the audience breakdown, 35% of the total spend ($17,500 a month) was going toward existing customers. 

In other words, they were paying Meta to convince people who already loved their brand… to buy again.

The founder was sharp. He’d clearly done his homework: “We already set up customer exclusions,” he said, pointing to the campaign settings.

And he was right. 

But here’s what Meta doesn’t make clear: exclusions defined at the campaign level don’t automatically carry down to your ad sets.

So while the campaign knew who to ignore, the ad sets, where targeting actually happens, did not.

It’s like telling your bouncer not to let VIPs pay for drinks but forgetting to tell the bartender. The system breaks down right where the transaction happens.

Here’s how to fix it:

1️⃣ Define your existing customers at the campaign level: pixel purchasers, Shopify customer uploads, Klaviyo email subscribers, recent purchasers.

2️⃣ Then apply those same exclusions manually to every ad set. The campaign definition won’t trickle down automatically.

3️⃣ Finally, check your audience breakdown in Meta. If you see spend against existing customers, you’ve got a leak.

If you’re spending $20K/month or more on Meta and want a second pair of eyes to make sure your ad dollars are going where they should, use the link in my bio to book a free audit with our team at Kynship. We’ll help you find the leaks before they drain your growth.

There’s a 90% chance your DTC brand is running a Meta strategy that hasn’t worked since 2019.

Having recently grown a CPG brand by 10,900% (between 2021 and 2024), here’s what actually works TODAY.

Back in 2019, detailed targeting made sense. Meta needed help figuring out who to show your ads to. But that’s not the world we live in anymore.

Today, Meta literally tells you inside Ads Manager: “We may ignore your targeting to improve performance.”

And it means it.

Every time you create that “perfect” 1% lookalike, you’re putting blinders on the algorithm. You force Meta to ignore profitable audiences outside your definition, and if you’re even slightly wrong about your assumptions, you’ve just shrunk its ability to explore and optimize.

As a result, you pay the price in higher CPMs, weaker performance, and money left on the table.

And the same goes for interests. Meta doesn’t treat them as hard rules. It treats them as suggestions. If the system can find better results outside that audience, it will, and it usually does.

Let’s say you ask Meta to target ‘yoga moms interested in wellness.’ On paper, it feels smart and hyper-relevant. But in reality, you’re blocking Meta from reaching profitable buyers who don’t happen to be tagged with those exact signals.

Maybe they’re yoga moms who never clicked “interested in wellness.” Maybe they just buy yoga mats every six months without fitting Meta’s definition of ‘interested’. Either way, you’ve cut them out, and cut your own growth with them.

That’s why Meta doesn’t care about the interests you type in. It cares about signals. Who stops scrolling? Who clicks? Who buys? That’s what the algorithm is trained on, and that’s what drives performance.

Which is why the cliché is true: creative is the new targeting. If you want yoga moms, don’t waste time selecting “Yoga Moms” in Ads Manager. Feature a yoga mom in the ad. Show her unrolling her mat or blending a smoothie. Meta will find the audience that engages with that creative faster and more efficiently than you ever could.

So instead of spending hours building fragile audiences, go broad. When you do that:

- Meta has maximum flexibility to discover your best customers
- You don’t choke your audience size with arbitrary filters
- The algorithm optimizes against real-world behavior instead of your assumptions

Interests and lookalikes are suggestions at best, and roadblocks at worst. Don’t waste time building those out. 

Your job is to feed the system with enough creatives. Meta’s job is targeting. Stop trying to do both.

At Kynship, we’ve helped DTC brands like Purdy & Figg and WildBird scale profitably by doing exactly this, aligning Meta strategy to P&L and contribution margin goals, not outdated targeting tricks.

If you want your Meta performance tied directly to your bottom line, drop me a line or click the link in my bio to schedule a call.

If 70% of your pixels are the same across “different” ads, Meta treats them as near-duplicates. That’s why you’ll often hear people say, “We uploaded 10 new variations,” and see… absolutely nothing happen.

What most advertisers call “creative testing” is usually just minor tweaks to a winning ad—changing the color, adding a text overlay, or swapping a background. 

It looks different to you, but Meta sees it as the same ad. 

Imagine there are 50 similar ads in an an ad set. Out of those 50, 1 has the most historical data because it’s been running the longest and already generated the most conversions. 

It’s obvious that Meta will pour most of the budget into that single old creative. 

The rest of your creative rots in the learning phase. Your “new” ads never get a chance to prove themselves, and your account can stagnate.

So the only way to get Meta to push new creatives to truly diversify them. Here’s how you can do that:

Build diversity across five dimensions:

1. Formats: Video, static, carousel, UGC, professional shoots
2. Angles: Problem-focused, social proof, product benefits, lifestyle
3. Personas: Different customer types and demographics
4. Styles: Professional studio, raw UGC, animations, testimonials
5. Context: Seasonal content, trending topics, evergreen messaging

When you do that, Meta finally has distinct options to test, spend distributes across multiple winners, and your new creatives get the chance to prove themselves.

Everyone thinks Meta rewards yesterday’s clicks. THEY ARE WRONG! 

If you don’t understand the second half of the equation, your DTC brand WILL NOT SCALE!

My team scaled Purdy & Figg from $500K to $50M over the last 3 years and literally 10x’d WildBird’s revenue over the last 2 years while maintaining 5 aMER, 30% CM, and 17.5% profit.

We know that Meta can figure out click-through rate almost instantly. Impressions are cheap, so within minutes it can test your ad across thousands of people and see exactly who clicks.

But clicks are just the starting point. 

The real lever is expected conversion rate, the share of clicks that Meta predicts will actually turn into purchases.

Most people assume Meta waits for real purchase data before it learns. If 100 people click and 3 buy, they think Meta now knows the ad converts at 3%.

But that isn’t how it works. 

Meta doesn't wait for conversion data. It analyzes micro-signals — watch time, scroll stops, shares, bounce rates — and maps them against trillions of past interactions.

It already knows someone who watches 75% of your video is far more likely to buy than someone who scrolls past in two seconds.

So when your ad goes live, Meta immediately compares its engagement signals to patterns it has seen millions of times before and predicts whether the ad will drive conversions.

If the signals are strong, Meta spends aggressively. If not, it simply won’t spend.

Meta doesn’t reward ads that look good. It rewards ads that act like winners. If your engagement signals don’t match the patterns it knows will convert, it will bury your ad no matter how high the CTR is.

The solution here is to set up your account structure the right way and then invest your time in ad creative and offer testing rather than micro-managing Meta.

I can't tell you how many audits I've done where the highest-spending, most profitable ads are sitting there... turned off. It is a complete mistake from brands’ previous agencies. 

Because if this is the case., the algorithm is literally screaming at you that this ad works. If it's spending, it's performing. Meta's probabilistic forecasting has vastly more data points than your gut feeling about creative fatigue.

But when you (or someone you put in charge of your account) turns off high-spending ads, you take an ad that the system has identified as a winner and remove it from the auction.

Unless an ad is expired (sale ended, product out of stock, seasonal offer no longer relevant), you have zero reason to turn it off. Let Meta suppress losers and amplify winners. That’s the entire point of the system.

Besides, every time you kill a winning ad, you also reset optimization, disrupt performance, and force Meta to go find a new winner from scratch. You’re just wasting your budget and fixing something that doesn’t need fixing. 

If there’s one takeaway here, it’s this: trust the machine. If it’s spending, it’s working. Don’t get in the way.

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