2 min read
How AI Is Making Marketing Attribution Easier
How AI Is Making Marketing Attribution Easy: Scott on Ecommerce Coffee Break
I joined the Ecommerce Coffee Break...
Scott Desgrosseilliers
Recent posts by Scott Desgrosseilliers
2 min read
How AI Is Making Marketing Attribution Easier
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How AI Is Making Marketing Attribution Easy: Scott on Ecommerce Coffee Break
I joined the Ecommerce Coffee Break podcast to talk through something that trips up a huge number of brands: why the attribution data they rely on is quietly leading them astray, and how to fix it.
The root problem is that most brands lean on ad platform reporting to tell them what is working. The trouble is that every platform has an incentive to make itself look good, so it claims credit generously and reports on its own performance. Act on those numbers and you end up over-investing in whatever channel is best at taking credit, rather than whatever is actually driving new customers.
A big part of the conversation was about lookback windows. A default 30-day window sounds reasonable, but it can create false attribution signals, crediting a channel for a conversion it did not really cause, or missing the genuine first touch entirely. The window you use has to match the buying cycle you are actually measuring, not a platform default. Get that wrong and your scoreboard is telling you a story that is not true.
From there I got into the fix, which is having a real measurement strategy instead of trusting the platforms. That means prioritizing new customer acquisition in your paid media, and being able to segment new customers from repeat ones, because if you cannot tell them apart, you cannot tell whether your ads are growing the business or just re-converting people who were already coming back. It is also the reasoning behind the Five Forces system, which is designed to reveal whether your marketing is actually aligned, and to distill all that data down to a clear call: scale, chill, or kill.
We also talked about where AI fits. Used the right way, with strict guardrails, AI can take a huge amount of the manual work out of attribution and make accurate measurement far more accessible. Used carelessly, it invents confident answers that are wrong. The difference is entirely in how tightly it is governed.
If you run an ecommerce brand and you have ever suspected your attribution is not telling you the truth, this one is a quick, practical listen.
Topics: Wicked Reports Marketing Attribution Five Forces Methodology Wicked Reports Podcast Lookback Window
2 min read
Why Your Failed Campaigns Might Be Money-Makers
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Marketing Attribution Made Simple: Scott on The Agents of Change
I joined Rich Brooks on The Agents of Change to make the case that marketing attribution is not some enterprise-only luxury, and that a lot of the campaigns people write off as failures are quietly making them money.
I told Rich the story I always come back to, because it is the reason Wicked Reports exists. Back around 2013, a close friend of mine from Maine started Get Maine Lobster, shipping lobster all over the country. He told me Facebook does not work for lobster. He had spent four grand and made a single two-hundred-dollar sale, and he was ready to swear off it forever. I thought there might just be a delay in the sales, so I hacked together a way to track the full journey. It turned out he broke even within a month, and after ninety days he was at ten to one, once you accounted for the Facebook traffic that later converted through email and SMS. That campaign that looked like a disaster became a multi-million dollar channel. The attribution model he was using had been lying to him.
That conversion lag has not gone away. If anything it is more common now, and people still glance at their platform reports, see no sales today, and pull the plug on the thing that was actually working.
The framing I gave Rich for attribution is simple: it is a scoreboard for your marketing. It is not about which fancy model you trot out. The only question that matters is whether it gives you clarity on what to do next. And the biggest mistake I see is people hunting for one holy-grail model. I am vehemently against that. Your measurement strategy has to match your marketing strategy. That is what we call setting an intention: it decides which clicks count, how much credit to give, which KPI is your North Star, and how long the game is you are actually playing. Trying to acquire new customers needs a longer window and a focus on new customer acquisition cost. Nurturing existing customers needs something else entirely. You pick the tool for the job.
We also got into a few things I feel strongly about. If you have a small budget, ten grand a month or under, focus on one channel and start with lead attribution, because a click is a strong signal. Do not chase lead volume without connecting it to revenue, or you will end up buying cheap leads that never turn into customers instead of the fewer, pricier ones that do. And I will always tell you I hate survey data for attribution, because I barely remember what I did two days ago, let alone which ad I saw a month before I bought something. A click you can prove beats a fuzzy memory every time.
We closed on AI, where I gave my honest take: used the right way it is a huge time saver, but on its own it likes to show off, it hallucinates, and it genuinely does not understand the passage of time. For data, you want boring and consistent. It took my team and an AI engineering firm nine months to get ours governed enough to trust.
It is a practical, small-business-friendly conversation, and Rich is a great host. Give it a listen.
Topics: Wicked Reports Marketing Attribution Meta Ads Wicked Reports Podcast Meta Measurement Conversion Lag
2 min read
Why AI Gets Marketing Attribution Confidently Wrong
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Can You Trust AI With Your Marketing Data? Scott on Smart Agency Masterclass
I joined Jason Swenk on the Smart Agency Masterclass to talk about something a lot of agencies are quietly getting wrong right now: trusting AI with their marketing data.
Let me be clear up front, because this is easy to misread. I am not anti-AI. Used well, it saves an enormous amount of time, and it can take your team well beyond just cranking out blog posts and ad copy faster. The problem is what happens when you point AI at attribution and performance data and assume the confident answer it gives you is the right one. Because AI is very good at sounding smart, and it is often wrong with total confidence.
The core issue is that large language models do not really understand time, causality, or intent unless you force them to. Marketing data is full of exactly those things. A conversion today might trace back to a first touch six weeks ago. A channel that looks like a winner might just be taking credit for demand that already existed. If you feed AI bad inputs or ask it the wrong question, you get very confident, very wrong advice, and then you make budget decisions on top of it.
The fix, and this is the heart of the conversation, is intention. Attribution only works when you define upfront what each campaign is actually meant to do, and therefore how it should be judged. Once intention is set, the data has a frame, and so does any AI you point at it. That is a big part of what the Five Forces framework is for: giving you a sane, rule-based way to read performance instead of reacting to whatever number looks good today.
Jason and I also get into why ROAS obsession leads agencies astray, especially when you are not separating new customers from repeat ones, and how Scale, Chill, and Kill zones take the emotion out of optimization decisions. If you run an agency and you are leaning on AI to interpret client data, this episode is worth your time before it costs you a budget or a client's trust.
Watch the full conversation below.
Topics: Wicked Reports Marketing Attribution Marketing Data Wicked Reports Podcast AI in Attribution
2 min read
AI, the Dark Funnel and the Future of Attribution
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Is AI Rewriting Attribution? Scott on The Super CMO Show
I joined Swami on The Super CMO Show for a conversation about something that is quietly reshaping how marketing works: AI is changing how customers discover brands, and it is making attribution harder than it has ever been.
The big idea we start with is what I call the AI dark funnel. More and more customer research is now happening inside AI chats, before anyone ever clicks through to your site. That early discovery, the part of the journey where someone forms an opinion about your brand, is increasingly invisible to your analytics. First-touch attribution gets much harder to see when the first touch happens inside a conversation you were never shown.
That leads into a shift I think every marketer needs to take seriously: SEO is evolving into GEO. It is not enough to rank in a list of blue links anymore. You have to make your website AI-ready, with clear structure, specific intent on each page, FAQs, how-to content, and original research that AI systems can actually understand and cite. Generic content will not cut it. The brands that win visibility in AI-led answers are the ones that translate their proprietary expertise, their real data and point of view, into formats AI can reference.
We also get into the measurement side, which is where my head usually is. When clicks no longer tell the full story, platform-reported ROAS becomes even less trustworthy than it already was. Google, Meta, email, and SMS can all claim credit for the same conversion, and they will. Independent, deterministic attribution, measured against your real orders, is how you cut through that and see what actually drove new-customer growth.
The thread running through all of it is that brand and first-party data are becoming more valuable, not less. As AI puts more distance between your brand and the customer click, building a brand people trust, capturing owned audiences, and continuously testing new signals is what keeps you growing. It is a genuinely forward-looking conversation, and if you are trying to get ahead of what AI means for marketing, it is worth the listen.
Listen to the full episode below.
Topics: Wicked Reports Marketing Attribution SEO Wicked Reports Podcast AEO Deterministic Attribution
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Why Your Meta Ads Aren't Getting New Customers
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Fix Your Meta Ads : Why You're Not Getting New Customers
I was back on Jeff Sauer's Measure U podcast to tackle something most Meta advertisers get wrong without realizing it: they think they are running new customer acquisition campaigns, and they are not.
Here is what actually happens. You set up a campaign to find new customers, but Meta's algorithm optimizes for the fastest, easiest conversions it can find. Those almost always come from people who already know you, your repeat buyers and warm audiences. So the campaign you built to grow your customer base quietly turns into one that re-converts the customers you already had. It looks fine in the dashboard, because the platform is happy to take credit, but your actual new-customer growth stalls.
That is the trap this episode is about, and Jeff and I break down how to get out of it. The first step is being able to separate new customers from repeat ones for real, not guessing, but measuring it against your actual orders. Until you can see that split, you genuinely cannot tell whether your ad budget is buying growth or just recycling demand. This is also why ROAS on its own is so misleading, because it happily counts both and makes recycled revenue look like a win.
From there we get into the feedback loop that fixes it: offer the product most likely to lead to a valuable customer, send Meta the right signal so it optimizes for genuinely new buyers, and then measure the result correctly so you can validate what is actually working. When those three pieces line up, you stop fighting the algorithm and start training it to go find the customers you actually want, which is how you build a compounding engine of profitable new-customer acquisition instead of a treadmill.
If your Meta results look fine on paper but your business is not really growing, this episode is worth your time. Watch the full conversation below.
Topics: Wicked Reports Marketing Attribution Return on Ad Spend (ROAS) Meta ads efficiency Wicked Reports Podcast
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Using AI and Attribution to Scale Ads with Confidence
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Inside Wicked Reports : AI + Attribution on Measure U
I went on Jeff Sauer's Measure U podcast for a hands-on look inside Wicked Reports, and how AI and attribution work together to let you scale ad spend with confidence instead of crossing your fingers.
The premise Jeff and I start with is one I say a lot : your ad platforms are, in effect, grading their own homework. The default dashboards are built to make the platform look good, and most marketers trust them right up until the growth stalls and it is too late to easily fix. This episode is about replacing that blind trust with a measurement system you can actually verify.
We walk through the methodology top ecommerce brands use to fix broken attribution, and a big piece of that is segmenting new customers from repeat ones. If you cannot tell the difference, you cannot tell whether your ads are growing the business or just re-converting people who were coming back anyway. From there we get into setting rules-based bidding thresholds and letting budget scale or get cut based on real performance, rather than gut feel.
Because it is Measure U, we also do a proper platform demo. I show FunnelVision reporting, which maps the full customer journey across Google, Meta, email, and more, so you can see every touch that led to a sale instead of just the last click. I walk through the Scale, Chill, and Kill logic that buckets campaigns automatically based on performance thresholds, so a wall of data becomes a short list of decisions. And I show new customer signal tracking, which trains Meta to go after better buyers by feeding it the right signal, plus how the Five Forces framework bakes rule-based decision making into the whole ad strategy.
If you are a media buyer, agency owner, or marketing ops lead, this one is a practical blueprint for lining up your measurement with actual profit. Watch the full episode below.
Topics: Wicked Reports Marketing Attribution Marketing Attribution Cost Five Forces Methodology Wicked Reports Podcast Funnel Vision
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The Five Forces Framework for Marketing Attribution
The Five Forces of Marketing Attribution : Scott on Measure U
I joined Jeff on the Measure U podcast for a deep dive into something I care about a lot : how to actually use your marketing data to scale, instead of just collecting it.
Most marketers have no shortage of data. Dashboards, platform reports, spreadsheets. The problem is that having data and knowing how to act on it are two very different things, and the gap between them is where a lot of budget quietly gets wasted. That gap is exactly what the Five Forces framework is built to close.
In this episode I walk through the framework end to end. We get into how to define your North Star metrics, so your team is measuring the thing that actually reflects growth rather than a vanity number. We cover how to sort your campaigns into Scale, Chill, and Kill zones, which turns a wall of data into a clear budget decision. And we talk about diagnosing campaigns with precise attribution, so you can tell the difference between a campaign that is genuinely driving new customers and one that is just taking credit for demand you already had.
A big part of the conversation is about people, not just numbers. One of the hardest parts of measurement is getting a whole team aligned on the same scoreboard without drowning them in complexity. When the marketing team and the brand are not aligned on how success is measured, things go sideways fast, and I have seen that play out over and over. The framework is as much about creating that shared, trustable scoreboard as it is about the math behind it.
We also get into how to use AI to activate your analytics rather than just analyze it, which is where a lot of the future of this work is heading.
If you are a performance marketer, a CMO, or an analytics lead who has ever felt like you are data-rich but decision-poor, this conversation is for you. Watch the full episode below.
Topics: Wicked Reports Marketing Attribution North Star Metric Five Forces Methodology Wicked Reports Podcast
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Cutting Amazon Spend to Fix Stalled Growth : A Case Study
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5 Missed Forecasts. Then One Budget Shift. Then 4 Straight Hits.
I joined Ralph Burns and the Perpetual Traffic team to walk through one of the most instructive case studies Tier 11 has run, a story that starts with five straight missed forecasts and ends with four consecutive quarters of growth.
The setup will sound familiar to a lot of operators. Ad spend was scaling, the dashboards looked fine, but the results kept coming in under forecast and customer acquisition costs were creeping up. The usual instinct in that situation is to double down on the channels that report the best numbers. The episode makes the case that this instinct is often exactly backwards.
What the team and I dig into is how a platform's reported performance can hide what is really happening. The conversation covers Meta's recycling loop, where the algorithm quietly re-converts existing customers instead of finding new ones, and why a channel that looks efficient on its own dashboard can be misleading once you measure it against real orders and genuine new-customer acquisition. They get into how multi-touch attribution and incrementality testing were used to figure out which channels were actually driving new business and which were taking credit for demand that already existed.
The turning point in the case study is a bold reallocation: cutting the vast majority of Amazon spend and moving that budget to top-of-funnel channels. It is the kind of move that feels risky in the moment, because you are pulling budget out of a channel that looks like it is working. The episode is candid about that risk, and about how the decision was pressure-tested with attribution and incrementality data before it was made. What followed was four straight quarters of growth, lower acquisition costs, and a meaningful lift in overall marketing efficiency.
It is a genuinely detailed, practitioner-level breakdown, not a highlight reel. If you have ever suspected that your best-looking channels might be holding you back, this conversation is worth the full listen.
Watch the episode below, and if the case study resonates, the multi-touch attribution and new-customer measurement behind it are exactly what Wicked Reports is built to provide.
Topics: Wicked Reports Marketing Attribution Amazon Budget Optimization Wicked Reports Podcast
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The Attribution Truth Google Won't Show You
The Attribution Truth Google Won't Show You: Scott on Grow My Ads
Scott Desgrosseilliers sat down with Austin LeClear on Grow My Ads for a conversation every ecommerce advertiser should hear: the attribution truth Google won't show you.
Here is the uncomfortable premise. Every ad platform reports on its own performance, and every platform is incentivized to take credit. Google grades Google's homework. That means the numbers in your Google Ads dashboard are not a neutral scoreboard, they are a self-interested one, and they can look healthy while your actual business growth tells a very different story.
In the episode, Scott and Austin get into why that gap exists and what to do about it. The short version of Scott's argument, the one he makes across every channel, is that platform-reported ROAS tells you what the platform wants you to see, not what it actually cost to acquire a customer who was not coming anyway. A brand can post a strong blended number while its true new customer acquisition cost quietly climbs. The metric that matters is not how much revenue a platform claims. It is what it costs you to bring in a genuinely new customer, measured against your real orders rather than the platform's own math.
That is the shift the conversation is really about: moving from trusting a single platform's self-graded report to measuring the full customer journey with first-party data, so you can see which channels actually start and close new-customer revenue. It is a practitioner-level discussion, not a pitch, and it is worth your time if you run paid traffic and suspect your dashboards are flattering you.
Watch the full conversation below, and if it resonates, that gap between what Google reports and what actually grew your business is exactly what Wicked Reports was built to close.