How do I decide which ad channel deserves more of my budget?

This page may contain affiliate links from which Blur Studio earns commissions.

Every business running paid ads on more than one platform eventually faces this question: Google or Facebook, Microsoft or LinkedIn, where should the next incremental dollar actually go? The honest answer is almost never a general industry rule. It's whatever your own data says about your own specific product, audience and current performance on each channel, which means the real work is building a fair comparison, not finding someone else's answer.

Why general advice about channels is mostly useless here

You'll find plenty of content online claiming Google Ads is better for high-intent search traffic, Facebook is better for broader reach and visual products, LinkedIn is better for B2B. There's a kernel of truth in each of those generalizations, but they're nowhere near specific enough to make a real budget decision. A B2B software company might get genuinely strong results on Facebook if its audience happens to be active and targetable there; a consumer brand might find Google Search surprisingly cheap in its specific category. The generalizations describe tendencies across thousands of businesses, not your business.

The only data that actually matters for your decision is your own: what's your cost per acquisition on each channel right now, what's your return on ad spend, and how has that trended as you've adjusted budget up or down on each one. That requires looking at your real numbers side by side, not reading someone else's case study.

How do I actually build that comparison?

Diginius's Advertising Insights connects to Google Ads, Microsoft Advertising, Facebook, LinkedIn and TikTok (the last via a partner integration), and puts spend, performance and ROI side by side across whichever of those you run. That removes the manual work of logging into each platform separately and reconciling different reporting formats into one comparable view, which is usually the actual barrier that stops people from doing this comparison properly in the first place. The reporting side is covered in reporting Google and Facebook ads in one place.

But the tool only speeds up the comparison, it doesn't create the data you need to compare. If you've only spent $200 on LinkedIn ever, against $5,000 on Google, any side-by-side comparison between those two channels right now is comparing a real trend against statistical noise. The tool makes a fair comparison easier to see once you have one; it can't manufacture a fair comparison out of lopsided spend history.

Step by step: making a real budget decision

1. Connect every channel you're running, even small ones. You can't compare a channel you haven't connected, and small-spend channels are exactly the ones people forget to include.
2. Look at cost per acquisition and ROAS over a comparable time window, not total spend or total conversions, since a bigger channel will naturally have bigger raw numbers regardless of efficiency.
3. Check whether each channel has had enough spend to be statistically meaningful. A rough rule many media buyers use: you need at least 15-20 conversions on a channel before drawing real conclusions from its performance data.
4. Look at the trend, not just the current snapshot. A channel that's been improving steadily as you've learned to target it better is a different story from one that peaked early and is now declining.
5. Shift budget incrementally, not all at once. Moving 10-20% of spend toward a channel that's outperforming, then reassessing after another comparable time window, avoids overcommitting based on a single good month.
6. Re-run the whole comparison on a fixed schedule, monthly or quarterly depending on your spend level, since channel performance shifts over time as platforms change algorithms and competition changes.

What I'm watching out for in this comparison

The biggest trap is comparing channels using different attribution windows without realizing it. Google Ads, Facebook and LinkedIn each have their own default windows for how long after a click or view they'll credit a conversion to that ad, and those defaults aren't the same across platforms. A side-by-side ROAS comparison that doesn't account for this can make one channel look artificially stronger simply because it's claiming credit for conversions over a longer window than another platform is configured to claim. Check each platform's attribution settings, or rely on the cross-channel tool's own normalized view if it offers one, before trusting a raw side-by-side number.

The second trap is ignoring channel interaction effects. Someone might see your Facebook ad, not click, then later search for your brand on Google and convert through a search ad. A simplistic last-click comparison credits that conversion entirely to Google and makes Facebook look like it did nothing, when in reality it likely helped create the demand Google then captured. This is a genuinely hard problem that even large, sophisticated marketing teams struggle with, and no single tool fully solves it. Treat your comparison as directionally useful, not perfectly precise, and be especially cautious about completely cutting a channel's budget to zero based on last-click data alone.

A third, quieter trap is seasonality. Comparing a channel's October performance against another channel's July performance, or comparing this year's holiday-season numbers against last year's non-holiday baseline, can produce a difference that has nothing to do with which platform is actually better and everything to do with when the data happened to be collected. Always compare like-for-like time windows across channels, and if you're drawing year-over-year conclusions, compare the same calendar period, not just the same length of time.

A worked example

Say a business splits $5,000 a month between Google Search ($3,000) and Facebook ($2,000). After three months with both channels connected in one dashboard, Google shows a $45 cost per acquisition with a steady trend, while Facebook shows $38 but with volume too thin (under 15 conversions a month) to be fully confident in that number yet. The instinct might be to shift budget hard toward Facebook immediately based on the lower cost per acquisition. The more disciplined move is a smaller shift, perhaps $500 from Google to Facebook, giving Facebook enough additional spend to cross that 15-20 conversion threshold within another month or two before deciding whether the early signal holds up at larger volume. Overreacting to an early, thin-data signal is one of the most common and most expensive mistakes in budget allocation.

What I'd actually tell you

For most small businesses running ads on two or three platforms, the practical answer is rarely "abandon a channel entirely," it's "shift the margin." Keep a baseline presence on every channel that's shown any real signal of working, and direct new incremental budget toward whichever one currently shows the best trend, reassessing regularly rather than making one big irreversible call. Completely pulling budget from a channel is a decision that's hard to reverse cheaply, since rebuilding audience data and algorithm learning on a platform you've abandoned takes real time once you decide to go back.

I'd also flag a common bias worth naming directly: whoever manages a given channel day to day tends to unconsciously favor the data that makes their channel look good, and discount the data that doesn't, simply because they're closer to it and understand its context better. If one person manages your Google account and a different person or agency manages Facebook, build the comparison process to be genuinely neutral between them, ideally with someone outside either channel reviewing the combined numbers before budget decisions get made, rather than letting each channel's advocate make the case for their own platform. Agencies in that spot can read managing ads for several clients in one place. This is exactly where a shared, vendor-neutral dashboard genuinely helps beyond just saving time: when everyone involved is looking at the same consolidated numbers rather than exporting their own channel's data independently, it removes a lot of the room for a channel owner to present their own results more favorably than the full picture supports.

How I'd approach this

I'd set up a cross-channel dashboard as the baseline comparison tool, then build a simple, consistent monthly review process around it rather than making ad-hoc budget decisions whenever someone glances at the numbers. If attribution and channel-interaction effects are genuinely muddying your decisions at a meaningful spend level, a custom analysis layer that models this more carefully than a standard dashboard can be worth building, but that's a step up from what most small businesses need day to day. Start simple: get every channel connected in one place, run it for a full comparable quarter before making any big call, and resist the urge to act on the first month of data alone.