How Do I Know Which Marketing Channel Works Best?

A logistics company launches their new delivery tracking app and spends £15,000 across Facebook ads, Google search, and influencer partnerships in the first month. Downloads look decent—about 3,000 installs. But here's where it gets messy; the CEO wants to know which channel is actually working so they can double down on whats driving results. The marketing team looks at the data and... well, Facebook shows the most clicks, Google claims the most conversions, and the influencers are pointing to their promo codes. Everyone's taking credit but nobody actually knows the truth. Sound familiar?

This is the problem that keeps app developers and marketers stuck in this endless cycle of guessing and hoping. You throw money at different channels—social media, paid search, content marketing, maybe some PR if you've got the budget—and you cross your fingers that something sticks. Its exhausting and honestly, its expensive.

The thing is, most apps fail not because they're poorly built or because the idea was rubbish. They fail because nobody could figure out which marketing channel was actually bringing in valuable users. And I mean users who stick around, not just people who download once and never open the app again.

Marketing attribution isn't about finding a winner—it's about understanding how different channels work together to bring users through your door.

Over the years I've watched clients waste tens of thousands on channels that looked good on paper but delivered nothing meaningful. I've also seen tiny budgets produce incredible results when they were focused on the right places. The difference? Proper channel performance tracking and actually understanding user acquisition channels beyond surface-level metrics. But here's the thing—you don't need a massive budget or complicated tools to start figuring this out. You just need to ask better questions and track the right things.

Understanding Marketing Attribution Basics

Right, so marketing attribution sounds complicated but its actually pretty straightforward once you understand what it is. Basically, attribution is just figuring out which marketing channel deserves credit for bringing you a user. Did they find your app through an Instagram ad? A Google search? Maybe they heard about it from a friend who shared a link on WhatsApp. Attribution tells you that story.

Here's the thing though—it's never as simple as "user saw ad, user downloaded app." The reality is messier. Most people interact with your app multiple times before they actually download it. They might see a Facebook ad on Monday, ignore it. Then see your app mentioned in a tweet on Wednesday. Finally search for it directly on Friday and download it. So which channel gets the credit? This is where things get interesting.

When you first start tracking your marketing channels, you'll probably use something called "last-click attribution." This just means whoever the user interacted with last before downloading gets all the credit. In our example above, that would be the search. It's simple to track and easy to understand, which is why most people start here. But here's what I've learned over the years—last-click attribution can be really misleading because it ignores everything that happened before that final action.

The truth is, every touchpoint played a role in that user's decision. The Facebook ad introduced them to your brand. The tweet built credibility. The search was just the final step. Understanding this journey is what proper attribution is all about, and it'll completely change how you think about your marketing spend. You can't optimise what you don't measure properly, right?

Setting Up Proper Tracking Systems

Right, lets talk about tracking—because honestly, this is where most apps get it completely wrong from day one. I've seen clients spend thousands on marketing campaigns only to realise they cant actually tell which channels brought them users. It's a bit mad really, but it happens more often than you'd think.

The foundation of any good attribution system starts with your tracking URLs. You need UTM parameters on every single link you share, whether its a Facebook ad, an email campaign, or a tweet. These little tags (utm_source, utm_medium, utm_campaign) tell you exactly where each user came from. Simple stuff, but you'd be surprised how many teams forget to add them consistently. And here's the thing—if you're not consistent with your naming conventions, you'll end up with a mess of data that's basically useless; one campaign labelled "Facebook" and another "facebook" and suddenly your analytics thinks they're different channels.

You'll also need proper SDK integration for both iOS and Android. I usually recommend tools like Firebase Analytics or Adjust (there are others too, like AppsFlyer or Branch) because they track the full user journey from ad click to app install to in-app actions. But whatever you choose, make sure its set up before you launch any campaigns. Installing tracking after the fact means you've already lost valuable data.

Deep Links Are Your Friend

Deep linking lets you send users to specific screens within your app, not just the homepage. This is incredibly useful for conversion tracking because you can see exactly which campaign led to which action. A user clicks your Instagram ad about a specific product? Send them directly to that product page in your app, and you'll see much better conversion rates.

Test your tracking setup with small test campaigns before spending big money. Send yourself through the entire funnel from each channel to make sure everything fires correctly—you don't want to discover tracking issues after you've spent your budget.

Event Tracking Matters More Than Installs

Don't just track installs. Track what users actually do in your app. Did they complete registration? Make a purchase? Reach level 5? These events tell you which channels bring quality users, not just numbers. I mean, 1,000 installs from a channel that never converts is worth less than 100 installs from a channel where 20% become paying customers, right? Set up event tracking for every meaningful action in your app, and make sure those events are being sent back to your attribution platform so you can see the full picture of channel performance.

Testing Different User Acquisition Channels

Right, so you've got your tracking sorted and now its time to actually test where your users are coming from—this is where things get interesting. I've seen apps waste thousands of pounds testing every channel at once, which is basically just lighting money on fire and hoping something works. Don't do that.

The smart approach? Start with three to five channels maximum and give each one a proper chance to prove itself. I'm talking at least two weeks of consistent spend (longer if your conversion cycle is slow) because one day of data tells you precisely nothing. Facebook Ads, Google App Campaigns, TikTok, Apple Search Ads, partnership marketing with other apps—each of these behaves completely differently and attracts different user types.

Channels Worth Testing First

Here's what I usually recommend clients test based on their app type and budget. Social media ads work brilliantly for consumer apps where visual appeal matters;Google App Campaigns are solid for apps solving specific problems people search for;Apple Search Ads have stupidly high intent because people are literally searching for apps like yours already. Influencer marketing can work wonders if you find the right person whose audience actually matches your target user—but honestly, its harder to track and you'll need to set up promo codes or unique links for each one.

The mistake most people make is judging a channel purely on install cost. Sure, if Channel A gives you installs at £3 and Channel B costs £8, Channel A looks better right? Wrong. I've seen £8 installs turn into paying customers whilst the £3 ones delete the app within hours. You need to track what happens after the install—do they complete onboarding, do they stick around, do they actually use the core features?

What Your Test Results Should Tell You

After your testing period, you should know which channels give you the best quality users, not just the cheapest ones. Quality means different things for different apps but generally you're looking at Day 7 retention, cost per engaged user, and ultimately cost per conversion (whatever that means for your app—could be a purchase, subscription, or specific action).

Keep detailed notes on what creative worked where because—and this is important—the same ad that crushes it on Instagram might completely flop on TikTok. Different platforms have different user behaviours and expectations, which means your messaging needs to adapt too.

• Test 3-5 channels maximum to start with proper budget allocation
• Run tests for at least 2 weeks to gather meaningful data
• Track beyond install cost—look at retention and actual user behaviour
• Match your app type to appropriate channels (social for consumer, search for utility)
• Document what creative works on each platform
• Focus on quality users over cheap installs every single time

One more thing—don't abandon a channel too quickly just because the first week looks rough. Sometimes it takes a bit of creative testing and audience refinement before you find what works. But equally, know when to cut your losses if something genuinely isn't working after a proper test period.

Measuring What Actually Matters

Here's where most people get it wrong—they track everything and understand nothing. I've seen clients obsessing over vanity metrics like download numbers while their actual revenue per user sits at basically zero. It's a bit mad really, but I get why it happens; downloads feel important because they're easy to measure and they look good in presentations.

The truth is, downloads mean almost nothing on their own. What matters is what happens after someone installs your app. Do they actually open it? Do they complete the onboarding flow? Do they come back the next day, or even better, do they become regular users who stick around for months? These are the metrics that tell you whether your marketing channels are bringing in quality users or just numbers.

When I'm setting up conversion tracking for clients, I focus on three main things: activation rate (did they complete a key action like creating an account), retention (are they still using the app after 7, 30, 90 days), and lifetime value (how much revenue do they generate). These metrics tell you the real story about channel performance. A channel that brings in fewer users but higher retention? That's usually more valuable than one dumping thousands of installs that vanish within a week.

The best marketing channel isn't the one that brings the most users—its the one that brings users who stay, engage, and actually use what you've built.

You also need to track events within your app, not just installs. Set up proper event tracking for key actions like purchases, subscriptions, content creation, or whatever matters for your specific app. This lets you see which channels bring users who actually do the things that make your app successful. And honestly? Most channels will surprise you—the one you thought would perform best often doesn't, and some random channel you tested on a whim ends up being your biggest winner.

Multi-Touch Attribution Models

Right, so you've got your tracking in place and you're starting to see where your downloads are coming from—but here's where it gets tricky. Most users don't just see one advert and immediately download your app. They might see an Instagram ad, then search for you on Google, then click through from an email before finally installing. So which channel gets the credit? This is where multi-touch attribution comes in, and honestly, its one of the more complicated bits of app marketing to get right.

Multi-touch attribution models try to assign value to each touchpoint in a users journey. There are several models you can use, and each one tells a slightly different story about whats working. The most common ones are:

• Last-click attribution: Gives all the credit to the final touchpoint before download. Simple but ignores everything that happened before.
• First-click attribution: Credits the first interaction. Good for understanding awareness channels but doesn't account for what convinced them to actually install.
• Linear attribution: Splits credit equally across all touchpoints. Fair but maybe too generous to channels that barely influenced the decision.
• Time-decay attribution: Gives more credit to touchpoints closer to the conversion. Makes sense because recent interactions probably had more impact.
• Position-based attribution: Typically gives 40% to first touch, 40% to last touch, and splits the remaining 20% among middle interactions. A bit of a compromise really.

I'll be honest with you—there isnt a perfect model. Each business needs to choose based on their customer journey length and how people actually discover and download their app. For apps with short consideration periods, last-click might be fine; for ones with longer journeys, time-decay or position-based often gives better insights into what's genuinely driving installs.

Running Effective Channel Tests

Right then—so you've got your tracking set up and you know what metrics matter. Now comes the fun bit where we actually test which channels bring you the users who stick around and, you know, actually use your app. I'll be honest, this is where most people get a bit impatient and make decisions way too early. They'll spend £500 on Facebook ads, get mediocre results after three days, and declare the whole channel dead. Its not how testing works, I'm afraid.

Here's what I do when testing new user acquisition channels: I give each channel at least two weeks and a minimum of 100 conversions before making any real judgements. Why? Because mobile attribution isn't instant—people might see your ad on Tuesday, think about it, and then download on Friday. Some channels like content marketing or ASO can take even longer to show their true value. You need time for the data to settle and for user behaviour patterns to emerge properly.

Setting Your Test Parameters

Before you spend a single pound, decide what success looks like for each channel. And I mean specific numbers, not vague hopes. Set a target CPI (cost per install) that works with your unit economics, define what a "quality user" looks like (maybe someone who completes onboarding or makes it to day 7), and establish how much you're willing to spend to find out if the channel works. I usually recommend starting with £1,000-2,000 per channel if your budget allows it—anything less and the data gets too noisy to trust.

Running Tests in Parallel

Don't test channels one at a time unless you've got unlimited patience. Run them simultaneously so you can compare performance in the same market conditions. What works in January might flop in July, and you need that context. But here's the thing—make sure each test is isolated enough that you can see which channel actually drove each install. If someone sees your Facebook ad and your Google ad on the same day, your attribution system needs to handle that properly.

Start with three channels maximum when testing. Any more than that and you'll spread your budget too thin to get meaningful data from any single source.

Track these metrics for each channel as your test runs:

• Cost per install (CPI) and how it trends over time
• Day 1, day 7, and day 30 retention rates—this tells you if users actually like what they downloaded
• Time to first key action (completing onboarding, making a purchase, whatever matters for your app)
• Click-to-install conversion rate, which shows if your messaging resonates
• User lifetime value by channel, though you'll need to wait a bit for this one

One mistake I see constantly is people optimising for installs when they should optimise for retained users. A channel that gives you 1,000 installs at £2 each sounds better than one delivering 300 installs at £4 each, right? Wrong—if that second channel brings users who stick around three times longer, they're worth way more. Always look at channel performance beyond just the install; track how users from each source behave once they're actually in your app.

Stop your test early if a channel is bleeding money with zero quality installs after spending half your budget. But dont stop just because the first few days look rough—conversion tracking can take 24-48 hours to fully attribute installs, and user quality takes even longer to assess. Give it time, let the data build up, and make decisions based on patterns rather than individual bad days.

Common Attribution Mistakes to Avoid

Right then, let's talk about the mistakes I see people make over and over again—and trust me, I've made plenty of these myself over the years so I'm not judging! The first big one? Giving all the credit to the last channel a user touched before installing your app. It's called last-click attribution and honestly, its a terrible way to understand whats actually driving your installs. I mean, someone might see your Facebook ad three times, read a review on a blog, search for your app by name on Google, and then finally download it. If you only credit that final Google search, you're completely missing the full story of how that user found you.

Another massive mistake is not accounting for the time delay between seeing your marketing and actually installing. Some people need to see your app five or six times before they commit to downloading it—this is completely normal behaviour but if your attribution window is set to just 24 hours, you'll miss loads of conversions that your marketing actually caused. I usually recommend at least a 7-day window for most app categories, sometimes longer for big-ticket decisions like finance apps.

Here's something that catches people out constantly: forgetting to track iOS users properly after the whole App Tracking Transparency thing changed the game. If you haven't set up SKAdNetwork correctly, you're basically flying blind for a huge chunk of your potential users. And finally—and this one drives me a bit mad—people forget to exclude their own team from the data. Your internal testing shouldnt be counted as real installs; it skews everything and makes your cost per install look artificially low. Set up proper filters or you'll be making decisions based on rubbish data.

Building Your Attribution Framework

Right then—lets actually build something you can use. I mean, we've talked about all the theory and the different models and the tracking systems, but now its time to put it all together into a framework that works for your specific app. And honestly? It doesn't need to be complicated.

Start with your core metrics. What actually matters to your business? If you're a subscription app, its probably trial-to-paid conversion and lifetime value. If you're ad-supported, you need active users and session length. Write these down—I'm serious, physically write them down—because these are what you'll measure everything against. Every marketing channel you test needs to be judged on how well it delivers these specific outcomes, not just vanity metrics like installs or impressions.

Next, map out your customer journey touchpoints. Where do people first hear about your app? How do they move from awareness to install? What happens after they download? Your attribution framework needs to track users across these stages, which means connecting your pre-install data (ads, social posts, referrals) with your post-install behaviour (onboarding completion, first purchase, retention). This is where tools like Adjust or AppsFlyer come in—they bridge that gap between marketing spend and user actions.

The best attribution framework is the one you'll actually use and maintain, not the most sophisticated one you can build

Set up regular review cycles. Weekly for active tests, monthly for overall channel performance. Look at your data, adjust your spending, kill what's not working. And here's the thing—your framework will evolve. As you learn more about your users and as privacy regulations change, you'll need to adapt. Build flexibility into your system from day one so you can pivot without starting from scratch.

Conclusion

Look, I'll be honest with you—figuring out which marketing channel works best for your app isn't something you do once and then forget about. Its an ongoing process that requires constant attention and adjustment. What works brilliantly for six months can suddenly stop delivering results, and a channel that seemed useless at first might become your best performer after a few tweaks.

The biggest mistake I see app developers make is thinking theres some magic formula that'll tell them exactly where to spend their marketing budget. There isn't. Every app is different, every audience behaves differently, and what works for a fitness app might be completely wrong for a fintech product. You've got to test, measure, and adapt based on your own data—not what some marketing guru says worked for them.

But heres the thing—once you've got your tracking set up properly and you're actually measuring the right metrics (retention and lifetime value, not just installs), the answers start becoming clearer. You'll begin to see patterns in your data. You'll notice that users from certain channels stick around longer or spend more money. And that's when you can start making confident decisions about where to invest your time and budget.

Start small, test properly, and dont be afraid to kill channels that aren't working. I mean, I've shut down campaigns that looked promising on paper but just didn't deliver real users who actually used the app. That's perfectly normal. The goal isnt to make every channel work—its to find the ones that do work for your specific app and double down on those. Keep testing new things, but always come back to what your data is telling you.

Frequently Asked Questions