People ask me all the time what makes Vysta different. Why do we keep helping clients scale so fast, even when the space is so brutally competitive?
Well, the answer may shock you because it’s not a secret tactic. It’s not a new campaign type, either. It’s not even some AI bidding trick everyone’s going to be using in six months.
It’s a system. A defined sequence of steps that every account moves through, built from managing $200M+ in annual Google and YouTube ad spend across 150+ ecommerce brands.
Most agencies? They just optimize campaigns. We build acquisition systems.
Here are the 7 steps, in the exact order we follow them.
Before we touch a single bid or move a dollar of budget, we do one thing first. We separate every campaign into branded and non-branded performance.
This one step exposes the truth about an account faster than anything else we do.
And the pattern we see is remarkably consistent. An agency reports a 4-6x blended ROAS. Sounds great, right? But when you split it out, branded is running at 10-15x and non-branded is sitting at 1.5-2.5x. The agency has been padding results with traffic that was going to convert anyway, traffic you already owned and didn’t need to pay for.
Here’s a real example from a recent audit: a brand spending $2.2M annually showed a 2.28x blended ROAS, which looks decent on paper but tells a very different story once you dig in. A full $494K of that spend, nearly 23% of the total budget, was just cannibalizing branded demand.
Branded queries were flowing through Performance Max without exclusions, Brand Search campaigns, and a branded Shopping campaign simultaneously. They were paying for the same customer three times across three different surfaces.
We cap branded spend at 5-10% of total budget. Every dollar above that is money wasted on demand you already own. We take those savings and redeploy them into non-branded campaigns that actually drive new customer acquisition.
We rebuild every account around buyer intent, not campaign type. Every campaign gets tagged as top-of-funnel (awareness and discovery), mid-funnel (consideration and comparison), or bottom-of-funnel (conversion and brand capture).
This matters because each stage has completely different KPIs. Top-of-funnel campaigns are measured on cost per new visitor and search lift. Mid-funnel campaigns are measured on engagement and assisted conversions. Bottom-of-funnel campaigns are measured on direct ROAS.
When you measure every campaign against the same ROAS target, you end up killing top-of-funnel campaigns that are actually feeding the entire funnel below them. You’re cutting off your own growth without even realizing it.
We also separate Search, Shopping, and Performance Max within each funnel stage. PMax prospecting lives in the top-of-funnel. PMax remarketing lives in the bottom-of-funnel. When you run them together in one campaign without segmentation, Google defaults to the easiest conversions every single time, and the easiest conversions are always the people who were already going to buy from you anyway.
Here’s something a lot of ecommerce brands never think about: the product feed is where Google learns what you sell. If that information is incomplete or poorly structured, it doesn’t matter how much budget you throw at it because Google simply cannot match your products with the right shoppers at any spend level.
So we go in and rebuild it from scratch. We restructure feeds with separate branded and non-branded product titles and images. Non-branded titles lead with the primary keyword, meaning what someone would actually type into Google, not the brand name.
We test multiple image styles — lifestyle vs white background — and run 7-8 variations per top SKU. We fill every available Google Merchant Center attribute, add promotional sale badges, and duplicate the top 20% of SKUs with different titles to increase ad coverage. For brands selling in Europe, we activate our in-house Shopping CSS, which gives a 20% discount on every single click.
Most brands treat the feed as a one-time setup task and never touch it again. We treat it as an ongoing performance lever, because that’s exactly what it is.
I’ll be blunt. Bad data produces bad decisions. And bad decisions at scale are extremely expensive.
Before we scale anything, we verify that the account is tracking the right conversions with accurate values. For Shopify stores, this means properly configuring the Google and YouTube apps, linking GA4 for behavioral data, and installing enhanced conversions to improve signal accuracy. We also set up new customer tracking to distinguish first-time buyers from returning customers in every report.
And here’s why this step is so critical. We have seen accounts where 30-40% of reported conversions were completely inaccurate. Think about what that means. Every optimization decision the previous agency made, every budget call, every bid adjustment, every campaign they paused or scaled, all of it was based on wrong data.
If you notice, Steps 1 through 4 focus on building the infrastructure. The foundation. Step 5 is where things get really exciting because we actually start driving results.
We focus first on the campaigns with the highest conversion intent: non-branded Search, non-branded Shopping, and structured Performance Max. But here’s what most people get wrong at this stage. The goal is not to scale yet. The goal is to establish a profitable, stable baseline.
We need to know the account’s true non-branded CPA, the daily conversion volume Google needs to optimize effectively, and the spend level where efficiency starts to decline.
Going back to that same audit I mentioned in Step 1, the most incremental Search campaigns were budget-limited at just $70 per day, while brand campaigns were absorbing the majority of the budget. The campaigns doing the harder job, creating new customers rather than converting people who were already looking for the brand, were being completely starved of budget. We fix that immediately.
Once Search and Shopping are stable and profitable, this is where the real scaling begins. We introduce YouTube and Demand Gen campaigns, and we go big.
We take the best-performing creative the brand already has, usually from Meta, TikTok, or UGC, and adapt it for YouTube. We pair those creatives with high-intent keyword themes from Google Search data so the targeting is anchored to real buyer behavior.
And instead of launching generic campaign batches without a clear hypothesis, we organize every test around explicit audience narratives. What specific pain point does this creative address? What objection does it overcome? What action does it drive?
Now here’s something a lot of brands don’t understand about YouTube. Viewers rarely click and buy immediately. They watch, they get interested, and then they go search for the brand on Google later. That’s exactly why Step 1 matters so much. If your branded Search and Shopping campaigns aren’t ready to capture that interest, your YouTube spend looks wasted when it’s actually working perfectly.
Real result: One account went from $0 in YouTube spend to $43,000 per day, with over 80% of their total Google spend allocated to YouTube. The business grew 30x. Another went from $6K/day to $53K/day in just 18 days — from $500K/month to over $3M/month in Google revenue.
This is the step that separates agencies managing $50K per month from agencies managing $500K per month. When YouTube and Google traffic are flowing at volume, the bottleneck shifts away from media buying and moves straight to conversion.
Our internal landing page team builds advertorials, comparison pages, and presell funnels designed specifically for Google and YouTube traffic. And these aren’t generic pages. They’re built from real campaign data, showing which hooks hold attention on YouTube, which keyword themes drive higher-intent traffic on Google, and where users are actually dropping off on the site.
We even set up separate custom domains for some of these funnels, running them through independent ad accounts to isolate new customer revenue. We produce 50+ landing pages per week using our internal system. That volume of testing creates a compounding advantage where every week we learn what converts, and every subsequent page performs better than the last.
Real result: One brand went from $0 to $1M/month in 30 days using only comparison page prelanders on a separate domain. No traffic sent to the product page at all — strictly listicles and comparison pages. The market size was massive, and the brand was not converting well on standard PDPs, so we built an entirely separate funnel that worked.
Look, I want to be really clear about something. This is not a menu where you pick the steps that sound interesting and skip the ones that feel like work. The sequence matters because every single step depends on the one before it.
YouTube fails without demand capture, ready to convert the traffic it creates. Demand capture fails without a clean measurement to tell you what is actually working. Measurement fails without proper segmentation to separate real growth from inflated numbers.
Most agencies jump straight to tactics. Launch a YouTube campaign, test some new bidding strategies, and redesign the feed.
And honestly, that can work on a small scale. But it falls apart the moment you try to push past $50K, $100K, or $200K per day. The brands that reach those levels are the ones that build the system first. Every single time.
By Nate Schneider | CEO, Vysta Paid Media Group
If you want to see exactly where your account stands, book a free audit call with us. We’ll walk you through the entire system and show you what it’ll take to scale.
To know if your branded spend is too high, pull your campaign performance and separate every branded campaign from every non-branded campaign. If branded keywords, branded Shopping, and Performance Max without brand exclusions are absorbing more than 10% of your total budget, you are over-investing in demand you already own. Split those two out to see exactly where your budget is actually going.
You need to stabilize demand capture before introducing YouTube because YouTube creates interest that shows up later as branded searches and Shopping clicks. If your Search and Shopping campaigns are not properly set up to capture that traffic, your YouTube spend will look like it is not working when it actually is. Stabilizing demand capture first ensures that every dollar YouTube spends has somewhere to land.
To start seeing results from YouTube and Demand Gen, your Search and Shopping campaigns need to be stable and profitable first. On budget, Google recommends a minimum of $100 per day per Demand Gen campaign, or 20x your target CPA, to give the algorithm enough data to optimize effectively. Below that threshold, campaigns may struggle to exit the learning phase, and results can be inconsistent.
You can know your account is ready to scale budget when non-branded CPA has been stable and below your break-even threshold for at least 7 consecutive days and your new customer percentage is holding steady. Those two signals together confirm that the account is converting efficiently and that increased spend will drive real new customer acquisition rather than recycling existing demand.
If you skip the feed rebuild and go straight to scaling, you are giving Google incomplete information about what you sell. The algorithm will widen targeting, pull in lower-intent traffic, and spend faster without spending smarter. No amount of budget or bidding strategy can compensate for a feed that Google cannot properly read. The result is wasted spend before scaling even has a chance to work.
Landing pages become the primary bottleneck once YouTube and Google traffic are flowing at volume. At lower spend levels, a decent product page is enough. At higher spend levels, a generic product page simply cannot convert YouTube and Google traffic the way a purpose-built presell funnel can. The creative that wins on YouTube and the keywords that drive intent on Google need landing pages built specifically around that traffic to convert effectively.
Book a call with Nate Schneider to explore how Google and YouTube ads can drive scalable, measurable growth.
