Which Growth Plays Are Actually Moving the Needle in 2026
By Roey Granot · September 12, 2026
Category: growth-playbooks
Key takeaways
The problem Founders often mistake high-revenue channels for healthy ones, without seeing which growth plays are actually profitable at the unit level.
Core insight A repeatable four-step loop - mapping channel economics, testing at 10% spend, calculating payback period, then scaling or killing - lets you make growth decisions from data rather than gut feel.
Practical outcome You can run this loop in 90 minutes using a Google Sheet and your existing CRM or billing data, then keep it current in 30 minutes every two weeks.
Most founders think they already know which growth plays are working. They look at what's generating revenue and assume the channel is healthy. The problem is revenue isn't the same as profitability, and a loud channel isn't the same as an efficient one. The loop below gives you a way to find out which growth plays are actually worth your time and money - and which ones are quietly burning cash you can't see yet.
This is built for a founder running the business personally, with no dedicated marketing headcount. It takes about 90 minutes to run the first time. After that, it's 30 minutes every two weeks.
Step 1: Map Your Current Growth Levers
Before you test anything, you need to know what you're actually running. Not what you think you're running - what the numbers say.
Take a B2B SaaS company running paid search, organic content, and a referral program. On the surface, paid search is driving the most new customers. But once you pull the actual unit economics, organic content has a customer acquisition cost (CAC) of $80 versus $220 for paid. The referral program has the best lifetime value (LTV) but almost no volume. That picture changes every decision about where to spend next.
The input: pull your last 90 days of revenue by channel from your payment processor or CRM. The exact fields you need are: source (how the customer found you), MRR (monthly recurring revenue per customer), customer count, churn rate (percentage of customers who cancelled in the same period), and CAC (total spend on that channel divided by customers acquired). If you don't have CAC tracked by channel, use your ad platform spend plus any agency or tool costs for that channel.
Copy this into a Google Sheet:
Channel | Monthly Revenue | Customer Count | CAC | LTV | Payback Period (months) | Trend Paid Search | $4,200 | 14 | $220 | $1,100 | 5.0 | Flat [Your Channel 2] | | | | | | [Your Channel 3] | | | | | |
What you get back:
Which channels are profitable on a unit basis, not just in gross revenue
Where your payback period sits relative to your cash position
Which channels are growing, flat, or declining over the 90-day window
What to do with it:
Flag any channel where CAC exceeds LTV - those are burning cash at scale
Identify the one channel with the lowest CAC or highest LTV - that's your Step 2 candidate
If a channel is flat despite consistent spend, treat it as a test candidate, not a safe bet
If you can't find source data in your CRM, add a one-question intake field to your sign-up flow: "How did you hear about us?" - it's not perfect but it's faster than nothing
What this step won't tell you: why a channel is declining, whether a flat trend is seasonal, or what a competitor just changed. That context lives outside your spreadsheet.
Step 2: Test One Lever at 10% Spend
Pick the channel that's either your most efficient or the one that's flatlined and deserves a new hypothesis. Don't try to test two things at once. The signal gets messy fast.
A concrete scenario: a founder running $5,000 per month in paid search notices CAC has been flat for three months at $220. The hypothesis is that a tighter audience - companies with 10-50 employees in the SaaS vertical - will convert at a higher rate and bring CAC below $150. The test budget is $500 (10% of monthly spend), run over two weeks.
The exact input you need before you run anything: the channel, the current monthly spend, the hypothesis written as a single sentence, the success metric as a number, and the timeline. If you can't write all five in two sentences, the test isn't ready.
Test [audience/creative/message] in [channel] at [10% of current monthly spend = $[amount]] for [2 weeks]. Hypothesis: [specific claim, e.g. 'SaaS companies 10-50 employees will convert at 2x rate']. Success = [metric] reaches [target, e.g. 'CAC below $150']. If it hits, scale to 25% spend for 2 more weeks. If it doesn't, kill and pick the next hypothesis.
What you get back:
Cost per acquisition for the test audience or creative
Conversion rate compared to your baseline
Click-through or engagement data that tells you whether the message is landing before someone converts
What to do with it:
Compare test CAC to your baseline CAC from Step 1 - not to your target, to your current reality
If the test hit the success metric, move to Step 3 before scaling
If it missed by less than 20%, adjust the creative or audience and run a second two-week test before killing it
If it missed by more than 20%, kill it and pick the next hypothesis from your Step 1 map
Log the result in your growth sheet regardless of outcome - failed tests are inputs, not failures
What this step won't tell you: whether the result holds at full spend, or whether the audience saturates after two weeks. That's what Step 3 and 4 are for.
Step 3: Measure the Payback Window
A test that lowers CAC doesn't automatically mean you should scale. You need to know how long it takes to recoup that acquisition cost given your actual unit economics.
The scenario from above: you spent $500 on the test and acquired 3 new customers at $167 CAC. Each customer pays $89 per month. Your current churn rate from Step 1 is 4% monthly. Now you calculate the payback period.
The exact input: CAC from the test, monthly revenue per customer (MRR), and your churn rate. Find churn in your billing system - most payment processors like Stripe show it under "Revenue Retention" or in cohort reports. If you don't have a billing dashboard that tracks this, pull cancelled customers from the last 90 days and divide by your starting customer count for that period.
Copy this formula into a spreadsheet cell:
Payback Period = CAC / (Monthly Revenue per Customer × (1 − Churn Rate))
Worked example:
CAC = $167
Monthly Revenue per Customer = $89
Churn Rate = 0.04 (4%)
Payback Period = 167 / (89 × (1 − 0.04))
= 167 / (89 × 0.96)
= 167 / 85.44
= 1.95 months
What you get back:
A single number that tells you how fast you're recovering acquisition spend
A baseline to compare future tests against - if payback stretches as you scale, you'll see it early
A cleaner view of whether your current cash position can support scaling this channel
What to do with it:
If payback is under 6 months, move to Step 4 and consider scaling
If payback is 6-12 months, scale only if your runway supports it - this is a judgment call based on your cash position, not a formula
If payback exceeds 12 months, don't scale regardless of how good the CAC looks - the unit economics aren't there yet
If payback is under 3 months and CAC is stable, this is the lever you prioritise for the next quarter
What this step won't tell you: whether payback will hold as you scale spend, or whether new customers from this audience churn faster than your existing base. You'll only know that after 60-90 days of cohort data on the new customers.
Step 4: Scale or Kill, Then Repeat
The decision here is mechanical. You're not making a judgment call based on gut feel - you're reading the outputs from Steps 2 and 3 and following the decision tree.
If payback is under 6 months and CAC held stable during the test: increase spend by 50% and re-measure in 2 weeks. If payback stretches beyond 12 months or CAC climbs more than 20% as you scale: pause the channel, return to your Step 1 map, and pick the next lever to test.
A real outcome: the test hit 1.95-month payback, so you move from $500 to $750 per week. After two weeks, CAC is still $167 and payback holds. You scale again to $1,500 per week. At that point, CAC starts climbing - it's now $210. You hold spend flat, check whether it's a temporary signal or a trend, and after one more week decide whether to pull back or hold.
The exact input: payback result from Step 3, current weekly spend, and the new spend level. Track this in the same Google Sheet you built in Step 1, with columns added for the test period:
Week | Spend | Customers Acquired | CAC | Payback Period | Decision Week 1 | $500 | 3 | $167 | 1.95 months | Scale to $750 Week 3 | $750 | 4 | $168 | 1.96 months | Scale to $1,500 Week 5 | $1,500 | 6 | $210 | 2.42 months | Hold and watch [Next week] | | | | |
What you get back:
A clear signal on whether the channel can scale or whether it hits a ceiling at a specific spend level
A documented history of CAC and payback at each spend level - useful when you revisit a paused channel
A rhythm that forces a decision every two weeks instead of letting underperforming channels run on autopilot
What to do with it:
If CAC is stable and payback is under 6 months at the new spend level, scale again in 2 weeks
If CAC climbs more than 20%, hold spend flat for one more cycle before deciding to pull back
If you kill a channel, immediately identify the next lever from your Step 1 map and run Step 2 on it
Log every paused channel with the date, spend level, and CAC at the point you paused - you'll want this when you revisit in 90 days
Keep your Step 1 map current - update it every time you start or stop a channel
What this step won't tell you: whether a paused lever will work again in 3 months if conditions change, or what's happening on channels you're not currently running. That's why you review the full map quarterly.
The Whole Loop on One Page
Four steps. Run them in order. Don't skip Step 3 when a test looks promising.
Step 1 - Map: Input: 90-day revenue by channel from your CRM or payment processor. Tool: Google Sheets. Output: CAC, LTV, payback by channel. Decision: which channel to test.
Step 2 - Test: Input: chosen channel, current spend, one-sentence hypothesis, success metric. Tool: ad platform or outreach tool. Output: test CAC and conversion rate. Decision: hit or miss?
Step 3 - Measure: Input: test CAC, MRR per customer, churn rate from billing system. Tool: spreadsheet formula. Output: payback period in months. Decision: scale, hold, or kill?
Step 4 - Scale or Kill: Input: payback result, current spend, new spend level. Tool: same Google Sheet. Output: updated CAC and payback at new spend. Decision: scale again or pick next lever.
Cadence: run this loop every 2 weeks. Test a new lever every month. Review your full channel map and payback on every active channel every quarter.
Sample
Frequently Asked Questions
How do I know which growth channels are actually profitable and not just generating revenue?
Pull your last 90 days of revenue by channel from your CRM or payment processor and calculate CAC (total channel spend divided by customers acquired) and LTV for each one. A channel driving high revenue can still be burning cash if CAC exceeds LTV. For example, paid search might bring in the most customers while organic content has a CAC of $80 versus $220 for paid - a difference that completely changes where you should spend next.
How much should I spend when testing a new growth hypothesis?
Start at 10% of your current monthly spend on that channel, run the test for two weeks, and define your success metric as a specific number before you launch. For instance, if you spend $5,000 per month on paid search, your test budget is $500. If the test hits your target, scale to 25% spend for two more weeks. If it misses by more than 20%, kill it and move to your next hypothesis.
What is the payback period formula and how do I calculate it for a growth channel?
Use this formula: Payback Period = CAC divided by (Monthly Revenue per Customer multiplied by (1 minus Churn Rate)). For example, a CAC of $167, monthly revenue of $89 per customer, and a 4% monthly churn rate gives a payback period of roughly 1.95 months. You can find your churn rate in your billing system - Stripe shows it under Revenue Retention - or by dividing cancelled customers in the last 90 days by your starting customer count for that period.
When should I scale a growth channel versus pause or kill it?
If payback is under 6 months and CAC stayed stable during your test, increase spend by 50% and re-measure in 2 weeks. If payback is between 6 and 12 months, only scale if your cash runway supports it. If payback exceeds 12 months, do not scale regardless of how attractive the CAC looks. If CAC climbs more than 20% as you increase spend, hold flat for one more cycle before deciding to pull back.
How often should I run this growth review process and how long does it take?
Run the full four-step loop every two weeks, which takes about 30 minutes once you have the Google Sheet set up. The first time through takes roughly 90 minutes. Test a new lever every month, and review your complete channel map - including CAC and payback on every active channel - once per quarter. Keeping this cadence forces a decision on every channel every two weeks instead of letting underperforming ones run on autopilot.