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đ No More Guesswork: How to Track, Test, and Win Big
Plus, unlocking growth with relentless optimization
Most marketing teams think theyâre data-driven, but how many actually prove what works, cut what doesnât, and optimize relentlessly?
Leon Tang, Senior Performance Marketer at QA Wolf, doesnât believe in gut feelings when it comes to marketing spend. He takes a rigorous, experiment-driven approach to make every dollar contribute real revenue.
Leon and his team have built a marketing engine that delivers results, not just impressions.
Letâs take a peek at his playbook.
The Art of Granular Tracking and Experimentation
For Leon and the QA Wolf crew, marketing isnât set-it-and-forget-it. Every element is tested and optimized. Everything from ad copy and CTA placement to background colors and buyer journey touchpoints. They test and optimize it all.
"It's a lot of granular tracking and experimentation. Weâre really getting down to the nitty-gritty and breaking things down to a very minuscule level. Things like text copy within the creatives, backgrounds within creatives, what CTAs people are clicking on, what body text people are clicking on, and how that converts further down-funnel, and whether thatâs the first or second interaction."
Thatâs how each experiment feeds into QA Wolfâs performance strategy. The lesson is: donât just guess what works, prove it with the data.
âWe set pass/fail metrics for almost everything that we do. So if it doesnât necessarily reach those pass metrics that we set, we have to cut it off⌠Either we have to say, âwe think it didnât work because of this,â and then letâs iterate on it or weâll have to move on.â
Think About Reverse-Engineering Your Growth Targets
Instead of setting vague growth goals, QA Wolfâs structured approach is to work backward from revenue targets.
âWe have targets that we set for ourselves. And most of the time we use a backwards calculationâŚTake the average value, divide that by how many leads weâll eventually need to get [in order] to get to those closed ones, and from that point forward, dedicate how much money we need to spend in order to get those leads.â
That level of precision means that every dollar spent at QA Wolf is tied to tangible outcomes, not just vanity metrics.
Bonus: you get to make real-time adjustments based on performance.
âA success metric for us would be whether we can say we hit that target⌠for example reaching 2000 leads. If we say we hit those 2000 leads, fantastic. Another thing we could say [as a success metric] is efficiency metrics⌠So if from our historical calculations to hit those 2000 leads, we knew we needed to spend X dollars, then we found out that we were more efficient with that, we can say thatâs a success metric as well.â
Using Data to Drive Smart Decisions
Data is at the core of QA Wolfâs marketing decisions. Leon emphasizes the importance of understanding every data point and how it influences their funnel.
Their ability to track movement within an account also gives them an edge.
âItâs not necessarily even just ad platforms, but weâre even looking at the CRM level⌠Understanding what different objects within Salesforce are telling you. Whether that actually meant success from the sales side⌠and why they actually closed. We have tools that tell us which accounts are visiting what pages of our site, how long they spend⌠sometimes it tells us the seniority behind it.â
Meeting Decision-Makers Where They Are
We know that marketing to a senior-level or highly technical audience isnât just about getting in front of the right people.
Itâs about speaking their language in a way that resonates. For Leon, that means targeting engineering leaders like Directors, VPs, and CTOs with precision. They use highly specific platforms and tailored messaging to get maximum engagement.
âAlmost everybody in the tech startup world wants to go after those heads of engineering, product leaders, and decision makers, obviously. Itâs also more expensive to bid against.â
Reaching engineering decision-makers is competitive and expensive. To avoid wasteful spending and maximize efficiency, QA Wolf focuses on highly targeted platforms like LinkedIn, demand-side platforms (DSPs), and niche industry newsletters.
âWeâre really leveraging any platforms that allows us to target [job titles] specifically. So the no-brainers are LinkedIn and the specific DSPs that offer those services.â
Talk the talk
Donât make one of the biggest mistakes in B2B marketing: failing to tailor messaging for different levels of an organization.
QA Wolf takes a deliberate approach to make their content appeal to high-level decision-makers instead of individual contributors.
âA big example would be things like a sponsored newsletter. We obviously canât control who we talk to within the newsletterâs audience, but what we may be able to do is speak to thingsâŚthat call out people who are a little bit more senior in that [engineering] role. So if the message is something like âWhen you have to QA your code yourselfâ obviously that speaks to an individual contributor⌠But if itâs something like âWhen your team doesnât have to wait two hours to deploy anymoreâ thatâs obviously more engineering-leader messaging. â
Noted: refine your messaging to align with the priorities of your target audience.
Do what works
Success in B2B marketing isnât about doing more⌠itâs about doing what works, smarter. And Leonâs approach at QA Wolf proves it.
If you need to make your marketing dollars work harder, start thinking like a (QA) wolf.
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