After planning their budgets and having a relaxing weekend, John and Alex were ready to dive into their new ad campaign. Both are feeling the weight of launching their first big push.

John: “We’re about to drop serious cash on these ads, Alex. What’s the game plan? Should we expect leads to start rolling in from day one?”
Alex: “Not so fast, John. The first few weeks are all about projections. We’ll be testing the waters—tweaking messaging, refining targeting, and experimenting with formats. Only then can we start seeing the real results.

Before we start the chapter, here’s a friendly warning: This isn’t a “read and forget” kind of chapter. It’s not going to work if you just try to read and not implement it. If you’re not at a stage where you’d make projections, skip this chapter and return when you do.

If you can create projections every quarter and the numbers that you hit actually are close to what you projected—you’ve reached the state of predictability, and that is honestly the Holy Grail of running ads.

Can Projections Even Be Accurate?

The short answer is yes—but only when you have data from previous experiments. We’ll dive deeper into experiments in one of the upcoming chapters, but for now, understand that every campaign you run is essentially testing a hypothesis.

You’re basically saying, “Hey, if I show this message to these people, they’ll probably take this action, and it’ll cost me about that much.”

Creating projections means making some assumptions. You’ll need to estimate conversion rates, click-through rates, and lead-to-revenue ratios. Even data from tools like Google Ads Planner tends to be unreliable at this early stage. But once you’ve run enough ads and collected baseline data, these assumptions start turning into concrete data you can rely on.

This leads to our next question.

Why Bother With Projections if You Don’t Have Data Yet?

At Spear Growth, we create projections for every client. Why? Because after running thousands of campaigns, we’ve learned that our educated guesses usually aren’t too far off the mark.

We break our projections into two parts:

1. Top-Down Approach

This is where we check if there are any gaps in data, potential misalignments with leadership, or are there any expectations that might need adjustment? This helps us set realistic goals from the start.

2. Bottom-Up Approach

This is our reality check. Doing this helps us understand what are the success levers in each of the experiments, how well-positioned we are to win, and take a better decision on which experiments to begin with.

Now, let’s talk about how to actually create these projections.

Creating Projections

To help you understand projections, we’ll use the template below. But this isn’t a simple fill-in-the-blanks kind of template. Instead, it’s meant to inspire you. Use it as a guide, add the KPIs that matter most to your business, and build projections tailored to your company’s specific goals and needs.

Ads projection sample | Spear Growth – Google Sheets

Before you open this, here’s a quick walkthrough of the key terms and metrics you need to know:

ARR: Annual Recurring Revenue (your business’s yearly income)
MQL: Marketing Qualified Lead (leads that marketing believes are ready)
SQL: Sales Qualified Lead (leads sales thinks are worth pursuing)
ACV: Annual Contract Value (average yearly revenue per customer)
Payback period: How long it takes to make back what you spent to acquire a customer
CAC/LTV ratio: The relationship between customer acquisition cost (CAC) and their lifetime value (LTV)
Lead to Revenue ratio: Out of everyone who filled out the form, how much revenue did you generate (most companies break it down into multiple parts like MQL, SQL, SAL, pipeline amount, etc.)

Now, let’s get to the steps of making projections.

Steps to Create Projections

You can create projections following these 4 steps. We will be discussing these in detail with the help of our template in the next section.

1. Top-Down Projections: What’s Needed

Start with a top-down projection. Determine what you need to achieve without considering what’s possible. It helps you outline the goals, like the number of leads, cost per MQL, or revenue targets, based solely on business needs or financial objectives. However, at this stage, you’re not worrying about whether those numbers are realistic.

2. Bottom-Up Projections: What’s Achievable

Next, move on to bottom-up projections. Here, you’re looking at what’s actually achievable based on real-world data and market conditions. This could involve factors like conversion rates, cost-per-click, or demo booking rates from previous campaigns. The goal is to figure out what’s possible, given the resources and market dynamics you’re working with.

3. Align the Numbers

Once you have both top-down (needed) and bottom-up (achievable) projections, it’s time to align the two. More often than not, these numbers won’t match up initially. You might find that the cost per demo needed is much lower than what’s achievable, or vice versa. In this step, you’ll iteratively tweak both projections—adjusting goals or refining strategies—until they meet in a realistic and manageable way.

Note: Start your ads with the projections you have till step 3, then move onto step 4.

4. Refine Projections with Real Data

Two weeks into running your campaigns, real data will start coming in. At this point, you need to revisit your bottom-up projections and refine them based on actual performance. The original numbers you get from tools like Google Ads Planner or LinkedIn Ads Planner are rarely accurate, so this step ensures you have the most up-to-date, actionable projections. But make sure everyone involved understands this process—management needs to know that initial projections are not final, and adjustments will be necessary once real data is available.

Step 1: Top-Down Projections: What’s Needed

Re: Open the Gsheet template shared above.

Sections A and B

To understand this, let’s look at Sections A and B from the template.

First, you need to set a target. Your target could be revenue-based or any other meaningful metric, like customer acquisition numbers, market share, or even specific product adoption rates. While ARR is a common target, it’s not the only possible choice.

When starting out, one thing to remember is not to blindly accept the cost targets handed to you. Even if management gives you a cost per MQL target or a volume of MQL target, always double-check it.

Why?

Because they might not have the full picture. Even if it comes from your CMO, redo the maths. And if your recalculations don’t match the original numbers, start a discussion to understand WHY, but don’t assume management’s target is perfect.

You should work with realistic metrics based on your specific goals, not just management’s assumptions.

Here are a few shitty examples of how these targets get set:

“At my last company, the cost per MQL was X.”
This ignores all the differences between companies—industry, audience, funnel quality—yet, management wants to replicate a target that worked elsewhere.
“I read in a benchmark report that the cost should be Y.”
Benchmarks are useful, but they can be misleading if taken at face value. Every business has unique variables.
“The cost has to be Z for my top-down projection to work.”
This one’s a classic. Management picks a number to make their maths work without considering what’s actually possible or realistic.

You’re setting yourself up for failure when the funnel isn’t optimized or the target is impossible. Why even start ads if the best-case scenario still leaves everyone unhappy?

In our template, we use an ARR target for a specific timeframe.

A	Duration
	Start	February 2025
	End	January 2026
	Months	11

B	Business Goals
	Target ARR	$900,000
	Current ARR (MRR x 12)	$300,000
	Additional ARR	$600,000

Section C

Next, we need to determine how much of our target will come from ads. Section C in our template provides this breakdown:

C	Performance Marketing Goals
	% Sales Sourced	50%
	% Marketing Sourced	50%
	% Performance Marketing (from Marketing Sourced)	20%
	ARR from Performance Marketing	$60,000

Sections D and E

Next, you need to figure out how many customers you need to hit that goal. To do this, we’ll use the ACV. By dividing our ARR goal from ads ($60,000) by the ACV ($6,000), we determine that we need to acquire 10 new customers through our ad campaigns.

Factor in your sales cycle length to convert these into a monthly number.

D	Total Customers needed
	ACV	$6,000
	Customers Needed in the Pipeline	10

E	Monthly Customers Needed
	Time(Months) to Close	3
	Total Months	8
	Customers (Pipeline) /Month	1

Section F

Now that we know how many customers we need to acquire, we need to determine how much we can afford to spend to acquire them profitably. There are two main methods for this calculation:

1. CAC/LTV Ratio: This method is more popular, but it has several drawbacks. After budgeting for over 100 companies, we’ve found that many businesses aren’t sure of their actual LTV. Additionally, this approach completely disregards cash flow, making it unsustainable for most companies.

For example, if you have a YoY churn rate of 5%, having a 1:2 CAC/LTV would mean you’re spending about 10 years of revenue to acquire a single customer. That is clearly unsustainable.

2. Payback Period: The Payback Period method is simpler and often more reliable.

In B2B SaaS:

The average payback period is around 16 months
If you can achieve a payback period of 8-9 months, you’re doing exceptionally well
This payback period is for acquiring a customer—not just a lead, not a demo, not an MQL, not a pipeline—but a CUSTOMER.

Important: Ensure your average customer lifetime is longer than your payback period. If your payback period is 16 months, make sure customers stay with you for at least that long. Otherwise, you’ll be acquiring customers at a loss.

If the budget seems high or the numbers seem unlikely, don’t worry. We’ll address this in Step 3 of our overall process (Iterative Alignment).

F	Monthly Budget
	Payback Period	16
	Total Budget	$80,000
	Avg Monthly Budget	$10,000

In our template, this budget is based on a 16-month payback period. It means we’re willing to spend up to 16 months of a customer’s revenue to acquire them. Our total budget for the campaign is $80,000, or about $10,000 per month.

Section G

Next, map out your conversion funnel. In this template, we’re using an example of a funnel of a sales-assisted company. You could have a different type or a more complex funnel than the one in our template.

G	Monthly Funnel (Content)
	Win (that close some day)	1
	Cost / Win	$8,000
	% Win rate	15%
	SQL	8
	Cost / SQL	$1,200
	% Qualification	40%
	MQL	21
	Cost / MQL	$480
	% Qualification	60%
	Demo	35
	Cost / Demo	$288

This funnel shows:

Demo Stage: We need to generate 35 demos per month
MQL (Marketing Qualified Lead) Stage: We expect 60% of demos to qualify as MQLs
SQL (Sales Qualified Lead) Stage: 40% of MQLs are expected to become SQLs
Win Stage: We anticipate a 15% win rate from SQLs to customers

The funnel also provides target costs for each stage, which are important for budgeting and performance evaluation.

Look for places where you can reduce drop-offs anywhere in the funnel. Very often, this includes conversations with Sales, Product Marketing, or MarkOps teams.

Step 2: Bottom-Up Approach

1. Bottom-Up Approach for Demand Capture Ads

This is what the bottom-up approach to demand-capture ads looks like. To make the template simpler, we’ve grouped these quite a bit. In a real client scenario, seeing over 15 campaigns is very common. I suggest you go into detail, list every competitor and every category, and do this separately for each one.

Keyword Category	General Category	Brand	Competitor	TOTAL
Search Volume	590	12150	70450	83190
Search Impression Share	12%	42%	28%
Impressions	72	5103	19726	24901
CTR (hist.)	4%	14%	3%	5.26%
Clicks	3	714	592	1309
Avg CPC	$7	$7	$15	$11
Cost	$20	$5,001	$8,877	$13,898
Traffic to Demo %	2%	2%	2%
Demos	0	13	10	23
Cost/Demos	$400	$400	$857	$606.65
Demo to MQL %	26%	30%	20%
MQLs	0	4	2	7
Cost/MQL	$1,538	$1,000	$4,286	$1,962

2. Bottom-up approach for Demand Gen

Demand generation projections vary too much based on the funnel you’ve created. Here, what matters is that no matter what your goal is through demand gen ads, ensure there’s some value in it. If the amount you’re spending is lower than the value you’re generating, it’s not sustainable.

P.S.: We will talk about demand gen funnels in upcoming chapters.

Here are the three main strategies to keep in mind when creating projections for demand gen ads:

Direct Conversion Campaigns: If your product is already a strong offer, you can run direct conversion campaigns. This means your ads directly lead to purchases or sign-ups. Only a small percentage of products (maybe 1 in 100) can successfully pull this off because the product itself is appealing enough to convert users without extensive nurturing.

Influenced Conversions: For many companies, an indirect path works better. This strategy focuses on influencing potential customers over time. For example, tracking how many times a user engages with your ads (say, 30 times) before they convert can give insight into how your ads contribute to their decision-making process. While ads alone may not drive the conversion, they certainly influence it.

Lift Reports: Another effective approach is using lift reports. These reports show how consuming specific content increases the likelihood of conversion. If a company engages with your content (articles, videos, etc.) and then becomes more likely to buy, you’re seeing an increase in conversion rate, thanks to the value your content provides.

Whatever way you’re generating value, just ensure that it’s profitable.

Step 3 – Iterative process

Once you have both top-down (needed) and bottom-up (achievable) projections, it’s time to align the two. This means you’ll have to constantly adjust both your top-down and bottom-up strategies to find the sweet spot. You may need to change something in the top-down approach based on insights from the bottom-up initiatives and vice versa. This back-and-forth process continues until both align.

Some examples of this step are:

If you have multiple initiatives (for example, seven), you might discover that only three of them fall within a profitable cost range. In this case, dropping the other four initiatives makes sense. It’s not worth the effort to pursue campaigns that can’t deliver a satisfactory ROI.

Another example involves optimizing the funnel. Let’s say there’s a significant drop-off after a form fills in your funnel. You’ll need to figure out how to reduce this drop-off, as it could make your cost per demo unrealistic. Optimizing the funnel at this stage will help ensure that the cost per demo stays within a reasonable range, making your overall campaign more efficient and profitable.

Step 4 – Refine Projections with Real Data

The last step is crucial: two weeks into running your campaigns, real data will start coming in. At this point, you need to revisit your bottom-up projections and refine them based on actual performance.

Here’s why this step is so important:

Inaccurate initial data: No tool can give you exact data on metrics like CPC, conversion rates, or search volume before you start running ads. The data from tools like Google Ads Planner or LinkedIn Ads Planner is often inaccurate.
Strategy adjustment: With this new information, you might find that some initiatives you initially ruled out are actually worth trying, or vice versa. Someone with experience in ad management can use this data to suggest new strategies or optimize existing ones.
Expectation setting: Everyone involved, especially management, should understand that the initial projections are not final. Make it clear from the start that adjustments will be necessary once real data is available.

P.S.: We will discuss ads optimization in detail in the upcoming chapters.

Advanced Considerations in Projections

While we’ve covered the core process of creating and refining projections, there are a few advanced considerations that can significantly impact your results:

Seasonality and market trends
Product updates and new feature releases
Impact of competitor activities
Customer retention and expansion

I’ll not dig deep into each of these now, but if you think any of these may impact your projections a lot and have questions about how I’d solve this, reach out to me on LinkedIn.

TL;DR

NO… No TL;DR here.

Sorry, not sorry.

Some things are worth the time investment, and this is definitely one of them.

Chapter 5 – Projections