How Marketers Make Better Decisions When Results Overlap

With overlapping channels, I work backwards from the sale and ask what would’ve happened if each channel disappeared. When you look at more than $100M in tracked client revenue across Google Ads and SEO, you see paid search getting credit at the end of journeys that started somewhere else. Quite often, it was just the final step.

Where the spend allows it, I’ll use a holdout, split regions or pause a channel at different times and compare relevant leads and revenue. If the result barely changes during a comparable test period, the platform may have recorded the conversion without adding much.

I move budget towards the channels that create extra leads or revenue relative to their cost. A dashboard claiming the last click isn’t enough.

Choose the business outcome before choosing which channel gets credit. If several dashboards count the same customer, adding their reported conversions together does not create additional customers.

My first agency clients included a cybersecurity company and an online auto dealership. That taught me to define a useful conversion in the context of the business before comparing traffic or lead counts across industries. The same discipline matters when comparing channels inside one business.

My practical framework is to keep three views separate: the deduplicated business outcome, the recorded customer journey, and each platform’s own attribution claim. For a lead business, start with one inquiry record and trace whether it became a qualified opportunity. For a store, start with the actual order. Preserve campaign identifiers and dates, but do not present them as proof of causation.

A hypothetical example: someone discovers a business in a paid social post, returns through search, and buys after an email. That is one order with several observed touches. I would record the touches and compare acquisition cost against the order economics, rather than let three platforms turn it into three purchases.

The lesson is to reconcile what happened before deciding why it happened. When the evidence cannot isolate a channel’s contribution, say so and test the next spending decision with a defined comparison and outcome. Do not manufacture precision to make the dashboard look complete.

A client in northern Virginia called to tell me he was cutting his ad budget. Done. He’d run the numbers and was already decided.

I asked him to give me three days first.

When I went into the session logs, the picture looked completely different from what his attribution report was showing.

Six of those eight cases had found the site through organic search first. Blog posts, mostly.

They’d read, left, come back. Two or three times. Then an ad showed up and they called.

The ad got credit for every single one. The blog didn’t show up anywhere.

Same budget, four more blog posts. Thirteen cases next quarter.

He called two weeks later to ask what changed. Nothing changed. The blog had been doing the work the whole time. His report just couldn’t see it.

One thing I’ve learned from running a business for more than 20 years is that customers rarely discover you through one channel and buy straight away. They might hear about your business on a podcast, see something on LinkedIn, search for you on Google and then request a quote a few weeks later.

The tricky part is working out which channel deserves the credit. At Cubic Promote, I place more weight on enquiries that turn into actual orders than on traffic or clicks alone. Getting 1,000 visitors from a campaign looks great in a report, although I’d rather have 50 visitors who are genuinely interested in buying.

A good example is our podcast appearances and media commentary. A few years ago, we focused heavily on SEO, paid search and our website. We’ve since spent more time building visibility through interviews and media contributions.

We’ve had customers contact us who already knew about the business before making an enquiry. They might eventually find us through Google, meaning search gets the credit, even though something they heard or read earlier helped build that trust.

That’s made me more careful about judging channels purely on last-click attribution. I look at whether we’re attracting relevant enquiries, whether those enquiries are converting into orders and what customers tell us about how they discovered the business.

I also wouldn’t claim that every podcast appearance generates a certain number of sales. We simply don’t have enough information to make that connection accurately, and I’d rather acknowledge that than put an impressive-looking number in a report.

The biggest lesson has been not to make marketing decisions based on one metric. If a channel brings in fewer direct enquiries but regularly puts our business in front of the right audience, I’m not going to dismiss it just because another channel gets the final click.

I’ve found that looking at the whole customer journey gives me a much better picture of where our marketing budget is actually helping.

Coming from a technical services background in passivation and precision cleaning, I’ve learned that attribution gets messy fast when you’re dealing with long B2B sales cycles. We started treating marketing measurement like we treat surface contamination testing: you need multiple data points to get the real picture.

The breakthrough for me was when we stopped obsessing over “which channel gets credit” and started tracking assisted conversions alongside last-click. A prospect might find us through organic search, download a technical guide from a LinkedIn ad, then convert after an email nurture sequence. All three mattered. We now prioritize channels based on their role in the journey, not just the final touch. For top-of-funnel awareness, we look at engagement and qualified traffic. For bottom-funnel, we track direct conversions.

The one lesson that changed everything: measure influence, not just conversion. When we mapped our actual customer paths, email and content consistently showed up as influencers even when paid search got the final click. We doubled down on nurture campaigns as a result, and our cost per qualified lead dropped 30%. You can’t optimize what you can’t see, so we measure the full stack now.

My rule when channels seem to claim the same customer: trust the customer’s own account over the dashboard. At a local business like Pickleland, our indoor pickleball club in Austin, last-click attribution flatters whatever someone touched right before booking, usually search or a direct visit. But a local decision is rarely one touch. Someone hears about the club from a friend, sees a post, gets a newsletter, then Googles the name and signs up for the free intro class. The last click gets the credit and the work that started the decision gets none.

The lesson that made me more confident: measure the decision, not the click. Ask new customers directly how they found you, count those direct responses per channel, and compare them to what analytics report. Where the two disagree, take the customer’s answer seriously for local, and keep funding the channels people actually name. Two imperfect signals that agree beat one clean-looking number.

When different channels all look like they’re influencing the same customer decision, we prioritize the channel that sits closest to the actual booking. In our world, a homeowner might see a Facebook ad showing a completed roof down the street, read a blog post about how to spot hail damage after a storm, and then finally type our name directly into Google to schedule an inspection. While every touchpoint matters, we give the heaviest weight to the direct search or the local map listing that drove the final phone call or form fill. We then treat those top-of-funnel channels, like social media or awareness ads, as critical support pieces that built the trust necessary to make that final conversion happen.

The biggest lesson that helped us make more confident measurement decisions was learning to stop looking at our marketing channels in silos. Early on, it’s easy to fall into the trap of double-counting conversions because both your paid ads manager and your organic tracking want to take 100% of the credit for the same storm-damage lead. Once we started looking at the whole customer journey through a single CRM dashboard, we realized that our marketing channels aren’t competing against each other, they’re passing the baton. Embracing that multi-touch view stopped us from accidentally cutting budgets for “low-performing” awareness channels that were actually feeding our highest-converting phone calls.

A blockchain founder came to us for reputation repair, and once the search results were cleaned up, his team handed over PR, content and most of the marketing. A few months in, someone asked the obvious question: which channel is actually bringing in deals?

Their analytics said branded search. Almost every converting session ended with someone typing the company name into Google. On paper the cheapest channel was winning, and the logical move was to cut everything sitting upstream of it.

We push sales call recordings and transcripts through an automated analysis step, mostly to catch the objections we keep losing on. Reading through those for something unrelated, the pattern was hard to miss. Prospects kept referencing an article, a podcast appearance, or a founder post on LinkedIn, then said they searched to confirm the company was real. The search was not the reason. It was the verification.

So we stopped treating it as a channel at all. For one quarter we tagged every inbound conversation with what the prospect said they saw first, in their own words, and put that beside the analytics. Two sources, deliberately not reconciled. Where they disagreed, the human answer almost always pointed to something earned: a placement, a comment thread, a piece of coverage with no clickable path back to us.

Budget moved upstream. Branded search volume climbed anyway, which was the point, since it was only ever reflecting demand created somewhere else.

The lesson I keep returning to is that some metrics are scoreboards rather than players. Branded search and direct traffic usually belong in that first group. Optimise a scoreboard and you get a better looking scoreboard, nothing more. Ask prospects what actually moved them, accept that the answer arrives messy and inconsistent, and let that rough qualitative signal override the clean dashboard number when the two point in different directions. The dashboard is measuring the end of a decision that started well before anyone clicked.

When Every Channel Claims the Sale, Follow the Customer, Not the Dashboard

By Dawn McGrath, Marketing Director, Keller-Heartt Oil Co.

Every platform we use is happy to take credit. Amazon says its ads drove the order. Google says search did. YouTube shows views. Our Shopify store, Walmart, eBay, and Fastenal each report their own version of the truth. Add them up and we’d have sold several times more oil than we actually did.

That’s the trap of multi-channel marketing. Each dashboard measures only what it can see, and none of them see the whole customer.

Our buyers are maintenance managers, plant operators, and shop owners. Their journey rarely happens in one place. A buyer might watch a video on hydraulic oil, search for the spec, compare options, and then order on whichever channel is most convenient. If I credit the channel where the order landed, I’ll overfund checkout and starve the content that earned the trust.

So I stopped asking which channel gets the credit. I ask what the customer needed to believe before buying, and which of our efforts helped them believe it.

That one question changed how I prioritize results:

Separate the roles. Educational video builds confidence. Marketplaces capture demand that already exists. Neither should be judged by the other’s metric.

Weigh the outcome, not the click. I favor results tied to real orders, repeat customers, and healthy margins over views, impressions, or platform-reported conversions.

Treat platform numbers as clues. When a dashboard tells a story that seems too good, I look for a second source that agrees, like our own HubSpot and Shopify data.

Test before shifting budget. If I want to move money, I change one thing, hold everything else steady, and see whether real sales move.

The lesson that gave me the most confidence is that a measurement decision doesn’t require perfect attribution. It requires knowing the question you’re answering. Once I stopped chasing a single winning channel and started measuring how each one contributes to the purchase decision, my choices got calmer and easier to defend.

In marketing, the loudest report isn’t the most accurate one. The best measurement is the one that helps you decide what to do next.

What I try to avoid in this situation is giving the most credit to the channel that happens to produce the final click. A client may see a LinkedIn post, read an article, receive an email from us then talk to one of our business development teams before deciding to engage us. Generally, I look toward the results closest to the business outcome. I still track channel-level metrics, but I look at these as contributing signals instead of treating each conversation like it belongs to one channel entirely.

One thing I’ve learned is that attribution is not the same thing as influence. Early in my career I put a lot of weight on last-touch attribution because it gave me a clean number. Over time, though, I’ve found that comparing the entire customer journey gives me a much better basis for decisions. If LinkedIn consistently introduces prospects who later convert through direct outreach, I wouldn’t want to cut LinkedIn simply because it rarely gets the final conversion credit. This shfit in thinking allows for more confident budget decisions because I’m measuring the role a channel plays in creating demand, not just where a customer happened to click last.

When several channels influence the same customer, I try not to focus only on which one gets credit for the final conversion. I want to understand what role each channel played in getting that person there.

For Beacon Nonprofit, that often means looking at organic search, email, and direct traffic together. Someone might first find us through organic search, come back through an email, and eventually return directly to the site before becoming a customer. If I only looked at the channel tied to the final conversion, I’d miss a big part of what actually brought that customer to us.

That’s taught me to look at the customer journey before deciding which results matter most. I still care about conversions, but I don’t expect every channel to contribute in the same way. Looking at how those touchpoints work together gives me a much clearer picture of what’s actually working and where to put our time and resources.

When evaluating marketing results by channel, its important to determine which metrics actually move the needle for your business. While there is a swath of valuable data for each digital marketing channel, the best practice is to identify a few core metrics to report on a continual basis to see what results arrive from ongoing efforts.

Start with the overarching business goal you are trying to work towards with your marketing efforts and determine which specific aspects of your marketing campaign contribute to it and work backwards from there. If your goal is more leads/sales, set up conversion tracking to get accurate counts of leads by platform. Then, you can get more granular and report on which tactics drove the most leads by channel.

For example, if the company website drove X number of leads in the given period, a certain percentage came from email marketing campaign traffic, some came from local search, some came from the wider scope content marketing. In this instance, it would be beneficial to create a repeatable stats report that lists all major areas contributing to lead generation and the result change compared to the previous period. That way, you can identify which channels, tactics, and campaigns were most effective for achieving your goals.

I’m Lars Nyman, a fractional CMO with two decades in tech growth.

I’d start with old-fashioned regression analysis. With enough history and variation, model weekly revenue against channel spend, accounting for seasonality, pricing, promotions, delayed effects and diminishing returns. That gives you a broad channel-by-channel baseline when click attribution gets tenuous.

It’s a fallback of sorts (rather than specific proof of causation), but it gives you an unbiased general stance when attribution gets to fluffy.

We look at the full customer journey rather than giving all the credit to the channel that receives the final conversion. When multiple channels influence the same decision, we compare metrics such as engagement, website traffic, lead quality, assisted conversions, and conversion activity to understand how each channel contributes. For Social Media Marketing Services, this can mean looking beyond likes and clicks and considering whether social content is helping people discover the brand, visit the website, engage with content, or eventually become leads or customers.

One lesson that has helped us make more confident measurement decisions is that no single metric tells the complete story. A social media campaign may not always generate the final conversion directly, but it can play an important role earlier in the customer journey. By comparing multiple data points and looking at performance over time, Sage Mind Marketing can make more informed decisions about where to focus efforts and how to improve overall marketing performance.

I think you have to understand how channels or campaigns work together. Someone could see an ad on Meta, but not be ready to take action. Two days later they are reminded of the product and possibly not even the brand and do a search on Google and buy. Or the other way around where they find you on Google and see you again on Meta and remember your product/service and make a purchase.

I would look at things as a combination. Are they bringing in more customers at a cost that makes sense to the business instead of which platform gets credit. What are they costing individually and maybe test a channel that I believe is truly not working by lowering the budget instead of completely stopping it.

A lesson learned was not assuming the platform getting the conversion is always doing all of the work. I try to understand what helped get the person there.

Arin Gharapetian

Founder, Brand House

I’m Mariia Grachova, Co-Founder & CEO of Loona Agency, a marketing agency that runs SEO and lead generation for US local businesses in construction and home improvement.

When several channels touch the same decision, I stop arguing about which one deserves the credit and go back to the money. Every channel is judged on the same chain: cost per lead, cost per sale, customer lifetime value and, finally, ROMI. A channel that brings cheap leads that never close loses budget, even if it looks great in a dashboard. A channel with an expensive CPL that closes $10k+ jobs keeps it.

Before scaling anything, we calculate the maximum allowable cost per lead from the client’s margin and sales cycle. That number becomes the referee. When two channels overlap, the question isn’t “who touched the customer first?” but “does cutting this channel push our cost per sale above the limit?”

The lesson that made me more confident: a cheap lead isn’t a good lead. CPL is tempting because it’s easy to see, but on its own it lies. Once every lead is tied to the final invoice in the CRM, priorities become obvious. For Plum ProExteriors, an exterior remodeling company in Massachusetts, that end-to-end view showed local SEO was the channel to invest in: organic traffic grew 900% in two years, the company grew from $1M to $10M in revenue, and its current ROMI is 675%.

Measure to the invoice, not to the click.

I prioritize the metric that maps to the business outcome we care about most, such as quotes or pipeline value, rather than surface metrics like cost per lead. For a manufacturing client with an $80,000 average order, we deliberately shifted budget to LinkedIn even though leads cost $280 versus $95 on Google because LinkedIn leads requested quotes 39% of the time versus 8% from Google. That experience taught me to fix tracking so it reaches the quote or close event before judging channel performance. Let the end-to-end measurement, not platform dashboards alone, guide where you invest.

When you’ve got multiple channels that all seem to be influencing the same decision, trying to figure out which one deserves the most credit can be a real challenge. The truth is, it’s not always possible to assign perfect credit, so spending too much time on it can be a waste. Instead, I like to take a different approach: I test each channel by turning it up or down and seeing how it affects the overall result. The channel that has the biggest impact on the outcome is the one that’s really driving the pipeline, regardless of what the attribution model says. By doing it this way, you can get a better sense of which channels are truly making a difference.

I learned a valuable lesson that boosted my confidence: don’t rely too heavily on last-click data, and don’t put all your faith in a single model. We had an experience with a channel that seemed to be performing exceptionally well based on last-click metrics, but when we decided to cut it, the total number of leads barely decreased. It turned out that this channel was taking credit for conversions that other channels had actually earned. On the other hand, there was another channel that our model had underestimated, but it ended up being a crucial player in the early stages of the process.

I don’t look at channels just by the numbers or ratings they get, but by how they actually impact everything.