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Meet John and Alex. John is a budding founder of a contract management platform, and Alex is his newly hired CMO—a seasoned marketer with years of experience. They are both excited about taking their product to the next level. They sit in a small, brightly lit conference room, discussing their next big move: running ads.
“Should we start running ads?” asks John, with a hint of anxiety in his voice.
Alex sighs, “I’ve seen too many startups burn their budgets on ads without results. Ads can be powerful, but I’m unsure if they’re the first step. They can be expensive and tricky to get right. Without a clear strategy, it’s easy to burn through a budget with little to show for it.”
This dilemma is common for many B2B SaaS companies. This confusion leads us to our first question – Should you run ads?
Here’s your “Before You Run Ads” checklist. Avoid ads if you check any of these:
Without product-market fit, you likely don’t have message-market fit. Your product might not solve a real problem for your audience, making conversions from ads unlikely. You’d be spending money driving traffic to a product that doesn’t resonate.
Even if ads work by chance, you’re getting leads for a flawed business model. This usually means pivoting, and the insights from your ads won’t be valuable for the new market, wasting your investment.
Focus on refining your product and achieving a strong market fit before scaling with ads.
Don’t start ads if you haven’t tested your messaging. Explore less expensive channels like en-mass cold emails. These can help you identify the right message-market fit for your audience.
Once you have this fit, starting ads means only testing targeting, copywriting, and funnels. This significantly reduces variables and allows for better experiments.
Note: Referrals, founder networks, and investor introductions don’t count—they rely on trust, not your messaging.
Running ads is pricey. B2B SaaS companies can face costs from $8 to $25 per click. For a decent test, you’d need around 200 clicks. At $20 per click, that’s $4,000 per experiment. Multiple experiments can quickly escalate to tens of thousands of dollars.
Don’t start ads if your budget is tight. Testing a few variables won’t give you the full picture. Remember, a penny saved is a penny earned—don’t waste it on incomplete experiments!
In the next section, I’ll help you estimate the amount of budget you’ll need to run ads.
Ads aren’t a casual DIY project. With thousands of dollars at stake, each experiment must be run carefully and strategically.
Expecting ad results in two months? Think again! Effective campaigns need time for data gathering, optimization, and refinement. Commit to a longer period—typically at least six months—for proper testing and optimization.
Even if ads generate leads, an inefficient sales process can waste these opportunities. Ensure your sales process is optimized to handle leads effectively and avoid wasting your ad budget.
🧾 Clarifying Key Concepts |
PMF (Product market fit): Here’s how I define PMF: The confusion: Most founders follow the YCombinator definition of PMF: “The customers are buying the product just as fast as you can make it — or usage is growing just as fast as you can add more servers. Money from customers is piling up in your company checking account. You’re hiring sales and customer support staff as fast as you can.”– Michael Seibel The problem with this is that a lot of founders feel they’ve reached it before they truly have. So, we needed a definition that wasn’t subjective. The clarity: A B2B SaaS company that has hit PMF has achieved stage 3: Stage 1: Get ten customers who pay you, refer you, AND give you feedback. (Not ten each, but ten who do all 3.) Stage 2: Know exactly who they are. Firmographics, Psychographics, Demographics, and Product usage data. Stage 3: Have a repeatable process to get more such clients. This process is usually not scalable. |
Before diving into ads, calculate the minimum budget required to run enough experiments.
Here’s how you can do it:
You need data from at least 4 experiments (usually closer to ~7-8) to see if ads are right for your company. Insufficient data leads to inconclusive results, wasting time and money.
Identify all viable ad experiments you could run. For instance, creating different ad copies, targeting different audience segments, using various images or videos, leveraging different channels, and experimenting with different ad placements. We will discuss this in detail in the upcoming chapters.
Identify the leading and lagging metrics per experiment. For each experiment, determine the minimum volume of leading indicators you’ll need. E.g.: 200 clicks for Demand capture via Google ads. Or 10 conversations for Demand generation via LinkedIn ads.
Add the budget needed for all experiments to find the minimum amount required to test whether ads will work for you.
Let’s say you plan to test:
This totals to
4 x 2 = 8 experiments on Google.
And
2 x 2 = 4 experiments on LinkedIn
Assuming an experiment costs $4000 on Google and $3000 on LinkedIn, you require a total budget of:
8 x $4000 + 4 x $3000 = $44,000
Add a buffer of ~20% for optimizations.
i.e. $52,800.
If you spend this over three months, your monthly ad spend budget will be
$52,800 / 3 = $17,600.
Determining the minimum budget helps you plan and ensure that you have enough data to make calculated decisions—which is the cornerstone of a well-executed ad strategy.
💡Core Idea |
The worst thing isn’t spending money on ads that didn’t work. The real problem is running ads for 6-12 months and still not knowing if it’s an ideal channel for you. |
So, if you’re not ready for ads yet, close the book and come back when you are.
If ads are for you, let’s discuss the best way to approach them in the following chapters!