If you’ve been in the industry, you know how this goes. Clients started asking questions, internal teams started looking for a company POV, we needed to produce something so people could understand what just happened.

Ideally yesterday.

So I defaulted to speed. I sent my initial thoughts to an AI agent I had already built for this exact type of thing, let the team know I could have it blow out the POV and kept moving.

At least that was my instinct.

Then Ben Hovaness stopped me. His response was:

Mike - think it would be helpful for the group if you could articulate your personal thesis on the significance of the news in a single paragraph. Once we are aligned on that THEN we can have an agent blow it out. But we need to start from human expertise and insight.

I really liked that.

I liked it because he wasn’t saying it was the wrong process, it was more about the order of operations. I took what he was saying as:

Give me the human thought first. Then go off, king!

AI makes it really easy to skip a step

I am a pretty aggressive user of AI.

It’s really twofold for me. First, I have always gravitated toward being a practitioner. I like to get under the hood and really learn something. When AI was getting popular, I decided to go deep on ChatGPT and I have never really looked back.

I also tend to be in roles where people ask me about the latest trends and how we should take advantage of them, so going deep is basically required learning for the job.

The second is obvious, productivity. Move faster (like yesterday), synthesize more information (and then compare it to a whole other data set), pressure test an idea (and then automate the insights into action).

With some basic knowledge of the platform and only having a few opinions of my own (to put it lightly), AI makes it possible to go from zero to sixty instantly.

If I have an idea for an app? I can start vibe coding it. I (with no actual skills) made a Family Feud style game to play with my two boys the other day. It’s that easy.

Need a POV for this big announcement that everyone is asking about? Great, I built an AI agent for that specific purpose.

I love that for me! So much time for other activities.

It also makes it incredibly easy to skip the moment where you stop and ask, what do I actually think?

That was the part of Ben’s note that stuck with me.

Before we go do the thing, he wanted the actual thesis. Something a human being was willing to put their name behind.

The order of operations matters

I don’t think the lesson is that humans should be the only ones doing the thinking and AI should only do the production.

I don’t know about you but AI helps me think all the time. I use it to challenge assumptions, organize messy thoughts and analyze ridiculous amounts of data to try and identify patterns. I even ask it to tell me I’m wrong just to hear the other argument.

Sometimes it helps me better understand the things I thought I already knew.

But there is an important gate before we accelerate. Particularly a human gate.

What are we trying to say? What do we believe? What is the actual judgment? If a group of humans cannot align around that, generating 100 other docs filled with slop probably doesn’t solve the problem.

It just makes your uncertainty look more polished.

I learned this one the hard way with Field Notes

When I first started experimenting with these Field Notes, I had a similar approach.

I recorded this really long voice note with all my thoughts on the topic. I gave AI a ridiculous amount of context on the idea, what I wanted to say, the flow, etc. We went back and forth and eventually I had a beautiful first Field Note that I loaded into Substack.

If you are not aware, Substack recently rolled out a partnership with Pangram where you can scan any article for AI text. I ran my very humanly concepted but very AI produced newsletter through it.

100% AI.

I literally went to my wife and asked if I should just not do the newsletter anymore.

Not because I think an AI detector gets to decide whether an idea is mine. I knew the stories were uniquely mine. But after the score and when I read through the piece again, I understood the value of the score.

My writing was too clean, too complete, the prose was too predictable and it just felt too far away from how I naturally speak human to human.

I made the decision that if I am going to publish something called The Modern Commerce Field Guide under my own name, it needs to sound like me.

So after that, I completely changed my process. The Field Notes are now a whole lot messier but they are a whole lot more like me (and frankly, I get more out of it when I write them now).

Turns out Ben was pushing me toward something I had already learned the hard way with the Field Guide. Before you go full speed with the machine, there better be something real underneath it.

Speed makes the stop moments more important

The faster the machine gets, the more valuable the gates become. This is going to sound like third grade all over again, but maybe we need to get really good at knowing when to stop, think and ask a question before we keep going.

Because imagine this situation applied beyond writing a quick POV.

In our industry, we are moving toward a world where more and more media buying could (will) become agentic.

That means you are going to be able to tell the system what you want. Give it a budget and then it’s going to go nuts. Buy, optimize, shift budgets based on certain KPIs and keep going.

But before the rocket launches, somebody still has to establish the human intent.

What business outcome are we trying to drive? Who are we trying to reach? What are we willing to spend? What are we not willing to do? What tradeoffs are acceptable? What is the machine allowed to decide without asking us? What does good actually look like? How do we even know it’s good?

If anything, the easier execution becomes, the more important those questions get.

Give me the human sentence first

I have to admit it, Ben was absolutely right.

I was optimizing for speed but I was one step too early. My mindset was the news happened, clients were asking, teams needed something…AI agent.

There will absolutely be moments where that is good enough.

But my learning was that before I do that, I need to identify the human gates first. What do I need to not just articulate, but actually understand myself before I move to production?

In this case it was a paragraph. Sometimes it may just be a single sentence. It’s really about taking the time to work through one question, what do I actually believe here?

So before we go from zero to sixty:

Give me the human sentence first.

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Here is my hot take: I think my goal should be to put myself out of that job.

*For anyone at Omnicom: I want to be very clear, I love my job and would very much like to keep my employment for a long time. Please continue reading!

I don’t mean literally put myself out of a job. I mean something I challenge myself to think about whenever I take on a new role.

What would have to become so normal that people stopped asking for the specialty team to jump in and simply just know what to do?

I have spent most of my career in specialty roles. First it was digital activation, then performance marketing, retail media, commerce and the list goes on.

That means I have also spent a lot of my career hearing certain barriers. That’s their team or this sits over here, as if the org chart somehow changes the business problem in front of us.

I understand why specialties exist (again, I am one). There is always a need to have that deep expertise. Particularly on new and fast moving areas. But I have never been very interested in protecting artificial barriers between teams. I usually want to know how I can make the rest of the system work better together

So now that I am Global Head of Commerce, there is one question I keep coming back to:

What would Commerce look like if we didn’t even need to call it Commerce?

I have tried to kill retail media before

This is not the first time I have gone down this path.

Earlier in my career, I moved from a role on the brand side of the industry at Georgia-Pacific back to the agency side to help build out the Commerce & Retail Media practice at dentsu.

It was 2019, so I was doing a ridiculous amount of education around what retail media even was. I may be prone to hyperbole but I really think I did a State of Retail Media presentation over 100 times. If there was a tech malfunction I could describe the slides while presenting the thing.

A lot of legacy media people could not understand why on earth CPG brands were suddenly moving so much money into what looked like an antiquated media buying model.

At the time, brands and agencies were pushing media partners for self-service buying, custom audiences and deeper platform integrations. Retail media was exploding too, but it was harder to operate in the same way. There was lots of managed service, retailer-owned audiences, no third-party tracking and systems that barely talked to the rest of the media ecosystem. Basically the let us grade our own homework phase. Even when we pushed back, the response was basically, yeah…but they are the retailer.

That disconnect confused people. Why were CPG brands pouring more money into something that looked like media buying was moving backward?

It wasn’t just the agencies either. Brands were feeling conflicted. Retailers kept asking for more investment and it was causing tension between brand marketers and sales teams. The different perspectives ranged from this is a great marketing opportunity to this sounds like some form of extortion.

I was constantly explaining retail media from every direction. I even did education sessions for retail organizations to help them understand how brands experienced them (see commentary above).

Every single time I had one of those presentations, I used the same slide to define Retail Media.

It said Retail Media as the headline. Except I would put a strikethrough through the word Retail.

Retail Media.

My talk track was simple, retail media is just media. I thought I was being so clever every time I got to share my definition. Retail media is simply a retailer monetizing its data and properties.

The reason I used that definition was because it’s not particularly unique to retailers. That’s ANY media publisher. They monetize their data and their properties.

If you have ad inventory and data worth monetizing, chances are you will eventually try and monetize it. That’s just showbiz.

But the inventory was never the most interesting part about retail media (although some really cool stuff now with Prime Video, VIZIO and more). It has always been the data for me.

Retailers know what people actually bought and were getting increasingly more effective at identifying which marketing activities influenced the sale. That felt much more interesting to me than simply creating another way to buy ads.

That became the part of retail media I obsessed over. As you can probably tell, I still do.

I still believe retail media is just media

For years, my argument was that brand media and retail media are just media.

I said that they should be connected because separating them creates wasted spend (literally millions), inconsistent behaviors and competing objectives.

I may have been onto something back then but 2019 Mike was thinking too small.

I thought the convergence was mostly about where media got bought. Retail media. Brand media. It’s all just media. Let’s stop forcing consumers into the same boxes we use in our orgs and on our P&Ls.

Today my focus is about what the rest of marketing can learn from Commerce.

Social is where this becomes really obvious to me

Let me play this scenario out. Give me a CPG brand, their Meta account and permission to ignore their org chart for five minutes.

I would start by going heavy on organic social. Let’s make a whole lot of content. Different hooks, different claims, different product benefits, formats, creators, etc. Put all of it into the market and let actual human behavior tell us what resonates (measure this based off organic reach as Meta rewards distribution for content that resonates).

I love a good creative waterfall test. Find your winning variables and establish thresholds for when a creative really hits and warrants paid amplification.

Once we start putting media behind it, it’s Commerce’s time to shine. I want to use retail data to identify if the audience is new to the brand. Are they already loyal? Do they currently buy a competitor? Which messages actually change purchase behavior by cohort?

Retailer integrations enable rich signals for targeting AND data to inform more accountable measurement. Did they buy after seeing our ad? Did they buy at Kroger? Somewhere else? Did they ever buy it again? Are we using real time inventory signals? Personally, if the product is out of stock around me here in Atlanta, please stop spending money convincing me to go buy it (we both end up losing).

The more frustrating part is that we still cannot always run it that way. We have one social campaign running through the brand team and another campaign through an RMN managed-service. The result is essentially two completely separate campaigns with zero connectivity. Different buying structures, different audiences. Even basic things like frequency management cannot be tracked across the two initiatives.

That’s the part that drives me crazy. We have all this incredible data and then put it in a separate campaign where it doesn’t even matter.

I want to run Meta the way great teams run Meta. I just want to add Commerce intelligence to the system.

Buy like Brand. Learn like Commerce.

That is increasingly where I think the industry is going.

Brand media has spent decades getting really good at creating demand. We can reach people at scale and tell stories that resonate. Commerce has built on a different foundation, using purchase data and sales outcomes to understand what actually changed behavior.

So if I could wave my magic wand, I would buy media using the best of Brand, then learn from the outcome using the best of Commerce.

What actually drove sales? What changed behavior? What should we do differently next time?

That’s the future of Commerce I care about.

Maybe Commerce is a way of thinking

I used to think the big convergence was retail media eventually becoming part of all media.

Fast forward to today and I think the bigger opportunity is Commerce becoming part of how marketing decisions get made.

Purchase behavior improving audience strategies (and IDs used as the connective tissue across platforms). Inventory signals used to keep us from spending money to create demand in places where there is nothing available to buy.

And it absolutely works the other way too.

I grew up a media practitioner. There are things a creative leader sees in culture, storytelling and human behavior that I simply do not. It’s why I try to befriend so many.

The goal is pretty simple: the good stuff needs to travel.

Commerce should learn from creative. Creative should learn from sales. Media should get smarter from purchase behavior. And none of us should particularly care which part of the org gets credit.

If that makes the lines between Commerce and everything else a little messier, then I am here to roll up my sleeves and figure it out together.

So what exactly am I trying to put out of a job?

Not Commerce practitioners. And certainly not Commerce expertise (I’d argue we need more!).

Amazon will keep launching new capabilities. Walmart will keep evolving. TikTok Shop will keep disrupting our perceptions of what modern commerce looks like. Something none of us are talking about yet will eventually show up and become the next big thing. (Did your mind immediately go to Agentic Commerce?)

This is why I believe deeply in specialists. Most of the innovation I’ve seen starts with someone getting under the hood, nerding out and getting a few steps ahead simply by understanding how the thing works first.

But once we figure something out, the goal isn’t to hoard that knowledge forever. If every media planner still needs a Commerce person sitting next to them just to use purchase-based audiences or measurement, we’ve already lost.

The specialty should keep moving toward the next frontier. The intelligence should spread behind it.

Back to the new job

Which brings me back to the new job. Or soon to be my old job? *Again, kidding.

I am still very early. At the time of this writing, I am still doing onboarding 1:1s, so I have a lot more to learn before I pretend I know exactly how everything should work. That is part of why I write these Field Notes in the first place.

But I do know one thing on my mind as I enter the role. I do not want to build a bigger Commerce island.

I want Commerce showing up in the places where decisions are being made. And I want to add confidence when we answer questions like did our efforts work and did it move the business (sales).

When I said retail media is just media back in 2019, I meant it. I just don’t think I understood how big that idea could become.

If I do this job really well, the job itself should keep changing.

For someone who spent years crossing out the name of the thing I was building, that feels like the right place to start.

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I knew I had a busy week planned at Amazon unBoxed, so my Field Note had been scheduled in advance. But after arriving in San Francisco yesterday and then the opening keynote this morning, I had too many thoughts bouncing around my head to leave it alone.

What a day! Whew.

There were a whole bunch of announcements. New ad products. More AI. More automation. New ways to build campaigns, analyze performance, reach audiences and help people shop.

As a marketer and storyteller, I also love how certain words get positioned at these types of events.

Amazon called the first section of the day “Conversations and Commerce.”

That immediately got stuck in my head. I actually brought it up later with someone at Amazon right after the session. I was telling them how much I liked the wording but couldn’t remember the exact phrase for a second. Then it came back to me.

Conversations and Commerce.

I told them I needed to start practicing saying it until it just naturally came out of my mouth. I liked it that much.

Needless to say, I was on the edge of my seat.

My commitment with this series was to send notes from the field, and today the field is unBoxed. Rather than force everything into a perfectly packaged thesis, I figured I would try a little something different this week.

Here are some meandering thoughts coming out of the unBoxed Day 1 keynote.

Branded Conversations is the big one

If I had to pick my favorite announcement with the biggest implications, it’s Branded Conversations.

Amazon opened the day with a great agentic innovation. Branded Conversations creates an AI-powered shopping conversation for the brand inside the Alexa for Shopping experience.

The way I am initially thinking about this is like a brand-specific conversational experience inside Amazon’s larger agentic ecosystem.

The use cases are obvious. You create more bespoke and contextualized chat experiences with this shopper but the part I found especially interesting was what Amazon told brands to do first.

Get your product content and Brand Store in order. Then understand the questions your shoppers are actually asking. After that, if you want, you can provide even richer product information to help shape the conversation. Alexa for Shopping is then going to combine that brand expertise with product details, reviews and its own shopping signals.

As crazy as this sounds, I have read that story before.

OpenAI is doing something adjacent with shopping, particularly around helping consumers discover and research products. Approved brands can provide structured product feeds so ChatGPT can better understand product catalogs, attributes, prices and availability when helping people shop. Same story, different platform.

We are entering a world where brands don’t just optimize product content for the human who eventually lands on the page. We now have to thread the needle of a PDP that can communicate to both humans and machines at the same time.

Speaking of marketing to those humans, I’ll give this one away for free:

If you want to know what questions your shoppers actually care about, go read your Amazon PDP.

Read the reviews, read the questions and then use that language and answer those questions right in your content. Your shoppers have already written your conversational-commerce research brief.

Then, the most exciting part, Amazon makes the whole thing accountable. They can connect the conversation to the purchase to measure the impact.

Commerce wins again!

There is so much focus right now on GEO and improving share of recommendations. Amazon takes that a step further because it can connect the conversation back to the thing Commerce cares about most: Did the consumer actually buy? What did they ask about before they bought? Could that eventually help us understand which questions, needs and barriers correlate most closely with purchase? The possibilities are endless.

It also left me with a heavier question:

What happens to Sponsored Products?

Not tomorrow. But if product discovery increasingly shifts from search to conversations, how will the advertising model move with the interface?

That one is going to keep me busy for a while.

Conversational creative: show me the behavior

Amazon also showed prompts embedded directly into Responsive eCommerce Creative.

My reaction was immediate. I’ve seen this type of thing before. It looks awesome and demos incredibly well. I can already see it showing up in executive meetings and pitch decks.

But then I put my human-being hat on for a second.

There is a difference between something becoming technically possible and consumers deciding that is actually how they want to interact with ads. I need to see the actual human behavior happen before I get invested in the potential of the creative.

For now, I’m watching this one. Objectively cool. Waiting on the adoption.

Sponsored Services was not on my bingo card

This one pleasantly surprised me.

I mean sure I was expecting lots of AI and automation announcements but Amazon announcing Sponsored Services, which connects people with service providers based on what they’re searching for or purchasing, got me particularly excited.

I think the broader strategic move is smart. Amazon’s advertising opportunity keeps expanding beyond brands that sell physical products on Amazon. Services opens up another huge category of advertisers while letting Amazon use something it has in abundance: signals around what consumers may need next.

But forget Mike the marketer for a second, I absolutely need this in my life!

My house (and life) is currently in the phase where we seem to order something from Amazon and then immediately need a human being to install, repair or replace something related to it.

Simply put, thank you Amazon.

Reviews just became even more interesting

Amazon spent a lot of time talking about Review Requests.

And part of me was sitting there thinking, don’t they know that we know that reviews matter.

Brands have been trying to make review generation easier for years. So much so that there are entire companies built around helping brands generate more reviews within the constraints of the platform.

So my biggest question here is a gating one at this point: How much does it cost?

Amazon’s version reaches verified purchasers natively on Amazon and uses a performance-based model. A number of the existing solutions brands use for this are performance-based too, so the comparison against the alternatives already in market is going to matter a lot for early adoption.

In Amazon’s favor, if the cost is right and all else is relatively equal, doing it natively through Amazon feels pretty darn compelling.

That’s kind of how my mind works. I immediately jump to how would I sell this thing. But after thinking about it for a bit, something started to make this announcement much more interesting this year in particular.

Reviews are becoming AI fuel.

We just heard about how Amazon is using reviews inside AI-powered shopping experiences. Alexa for Shopping highlights customer sentiment, suggested questions and more right on the PDP.

Reviews are becoming one of the richest human signals available to AI shopping experiences. Reviews indicate what shoppers liked, what they hated, how they actually used the product, who they think it’s good for, whether the claims on the PDP actually hold up to consumer perception.

Now go back to Branded Conversations. Someone asks if a product is easy to clean. What do you think Alexa is going to trust more, your PDP bullet saying easy to clean, or hundreds of actual customer reviews saying it was the reason they returned it?

That makes review generation more strategically important than I think a lot of brands realize.

Agentic isn’t a KPI

This was probably my favorite bit of timing from the keynote.

Last week, I wrote a LinkedIn post arguing that I think we’re going to waste a lot of money making perfectly good automations agentic.

My point was that if an API already executes a predictable action reliably and cheaply, putting an AI agent in the middle does not magically make the outcome better.

You have to use agents where the reasoning changes what is possible. Things like complex campaign orchestration, cross-system decisioning, removing significant technical barriers and more. If the objective is to make something agentic, you are likely going to be wasting money. That is a potential risk of MCP integrations in our industry today.

Then Amazon showed an MCP architecture that I actually really like.

Their MCP Server gives agents access to tools across campaign management, reporting, measurement and other workflows. But Amazon also spent time on the fact that simply giving an agent more and more tools creates its own costs and complexity. Their approach includes mechanisms to keep the agent focused, along with more specialized expert tools.

That is a very similar approach that I am used to myself. Enterprise solutions and then craft tools. The AMC SQL Generator is a great example.

I can ask the business question, like I would to my analytics partner if I was looking for some research or a POV. The agent can then delegate the specialized work to the AMC SQL Generator, which turns that request into the query needed to get the answer.

That feels a lot like how I already work with an analytics counterpart today.

I love this because the agent doesn’t need to know everything. It needs to know where the expertise lives. The more specialized craft tools we build underneath it, the broader the questions I can ask without pretending the generalist agent suddenly became the specialist.

Agentic coordination (if that’s a thing) seems critical.

Then my brain went to the future of video

Publisher Insights takes data like what shows people watched, content genres, web-page activities and more into Amazon Marketing Cloud so advertisers can connect that context with downstream outcomes (what content types and partners actually drive sales).

Amazon also showed new Geographic Insights and activation capabilities using shopping, location and third-party signals to identify high-potential geographic opportunities.

I like the announcement, but I had even more fun connecting the dots on this one. To be very clear, this next part is me connecting dots, not something Amazon actually announced. But I think there are some really interesting implications for CTV.

If Amazon can identify geographic pockets where a brand is under-penetrated or has unusually high growth potential using commerce signals AND Amazon has premium video supply through Prime Video, how can those two things eventually connect?

Could I identify a geographic sales opportunity and then disproportionately create demand in that exact market with customized video creative in an automated workflow?

Could commerce intelligence make CTV planning more responsive to where the actual business opportunity exists?

I don’t know yet but that’s sure what I plan on asking about.

Conversations and Commerce

Which brings me back to the phrase that got stuck in my head at the beginning of the day.

Conversations and Commerce.

I just love that because I think there is something deeper there.

I think about my own behavior and what I am seeing on the consumer side of our industry. The shopping journey is increasingly starting with asking questions and getting answers on the way to eventually making a decision.

Amazon’s interface is now moving in a similar direction.

Think about the information hiding inside those conversations. What I need. What I’m confused about. What matters most to me. Where I’m willing to compromise. What stopped me from buying. What finally got me there. Those are incredibly rich commerce signals.

But before I ramble on and start to miss some of the sessions, I will leave you with this:

Language is becoming the new search bar. And when the interface is a conversation, context is what determines whether the answer is actually helpful.

That’s why Conversations and Commerce got stuck in my head so quickly. It didn’t just kick off Day 1 of unBoxed.

I think it’s where the purchase journey is going.

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As we were diving in to understand what happened, someone shared a piece of context that was supposed to explain why the feedback was surprising.

“This was the exact same approach we used last year and the client said they loved it.”

Not just loved it, we were their favorite agency partner ever last year (or something like that) and we received nearly perfect reviews.

At first glance, that sounds like pretty compelling evidence in the team’s favor. We know this works.

Except there was something about this situation that had the opposite effect on me.

The second I heard we were using the same approach as last year, I stopped immediately. What if that is the problem in the first place?

Not because the previous feedback was wrong or new stakeholders or anything like that. I feel pretty confident the deliverable last year was indeed excellent.

But a great score from the past only proves one thing. That it worked in the past.

It does not automatically mean it is the right thing to keep doing. The more I thought about it, the more I realized how often we confuse those two things.

Best practices have a half-life

We love best practices.

It is one of the most reassuring aspects of work. Something works. We learn from it. We document it. We scale it. That is how organizations get better.

But best practices become routines. As teams, we use the same reporting structure year after year even though the metrics and capabilities have completely changed. I get that it takes time to align stakeholders on the KPIs that matter most but let’s make sure those KPIs are the best available to actually correlate to business outcomes.

Whether it is a long-standing meeting that has lost the plot, a pitch deck that got repurposed one too many times or just any of those types of projects (you know what I mean). This is how we do it, this is how everyone likes it, etc. Well, have you proposed a stronger solution?

The conditions for success are constantly changing. Think about the bar for good commerce reporting in 2026.

Retailers are making incredibly rich purchase signals more readily available than ever before. Amazon Marketing Cloud is one of the more powerful and connected clean rooms out there. Walmart has rolled out APIs for Scintilla. And there are countless other opportunities as well from Kroger, Instacart, DoorDash and other developing data solutions.

The tools are getting better while the barrier to using them gets lower. That means the bar for good is climbing through the roof.

Sometimes success is the thing you have to question

Here’s a bit of the uncomfortable part. We all hear so much about learning from failure. And if you are reading this newsletter, you are probably the type of person that uses failure to get curious.

You are also a human being and like all human beings, if we get top marks on something, we are highly likely to preserve that approach. Words of affirmation are my love language and so if someone looks at a report I made and says great job, I am extremely likely to keep doing it the same way to get the same result.

That is completely rational.

But the question I have learned to ask is not, did this work. It is under what conditions did this work. And are those conditions still true today?

A media strategy can be brilliant one year under one market condition and look like you completely missed the mark the next year. Look how much discussion there has been around GEO and Sponsored Prompts in the last year alone.

The past is useful evidence. We just can’t ever let it get veto power over what will drive the business forward.

Re-pitch the client

There is a topic I have written about extensively to internal teams throughout my career: I think we should re-pitch our clients.

Not literally tell them to go give us an RFP but I firmly believe that mentally, at least once a year, we should be asking ourselves as a collective group some really critical questions and see what comes back.

If we had to win this business again today, would we show up the same way? Would these still be our recommendations and priority deliverables? Are we getting value out of our current meeting cadence? Do these insights matter? What are we not doing?

Clients are not paying agencies because they want to keep running the same play again and again and again. There is an AI for that.

They want direction. An inspirational partner to push the thinking and the ideas. And as lofty as that may sound, frankly it’s just a partner with their hands on the wheel, helping them understand what changed and what they should do differently because of it.

The benchmark cannot only be, was this better than last year’s version. I like to challenge teams with the question: What is possible now that wasn’t possible before?

AI raises the bar for the humans

In a world of AI, more is more.

With LLMs and the latest data science capabilities available, we can process insane volumes of data. We can now review significantly larger data sets AND reduce the time we spend monitoring them, spotting anomalies and drafting summaries.

But I think that undersells what is happening. That really only makes us more efficient at capturing today’s value.

If technology can watch, detect, summarize and report, then the human value gets to move somewhere else. Judgment and discernment.

Time gets reinvested to pressure test the context. Connect things that we are seeing with our own eyes and human experience. Know when the signal feels misleading, understand the consumer truths and make a hard recommendation when the obvious choice is staring right in front of us.

That time (and mental energy) can go toward something new. Getting curious, discovering new metrics and unearthing new insights to drive the business forward.

You have to let go to grow

Forget about business for a second. I care about this deeply on a personal level. Doing the same thing over and over again sounds like an incredibly boring way to live life.

I may be a little crazy but I just absolutely love the craft of work (I mean I did start a newsletter in my free time to write about work).

There is such a mentally stimulating aspect of innovation. What did we learn? What changed? What can we try? What has technology enabled now that we could not do before?

I don’t want to show up every morning and run the exact same ten plays because they worked last season. I want to know what the next play should be.

It can be incredibly hard to let go. Particularly if something worked really well. It’s easy to move on from failure because you have immediate permission.

But how do you move on from success when every other reason points to defending the thing?

Would we build it this way today?

I keep thinking about the comment that we had nearly perfect scores from the client.

I still think it was an important signal. We created value in that moment.

But it was just that, a moment, and certainly not permission to stop evolving.

Here is the question I asked back to the team: If we were starting today, knowing everything we know and using everything that is possible now, would we still build it this way?

If the answer is no, just let it go.

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She was talking about two ways she thinks about the value a commerce partner brings: execution and decision quality.

Pretty simple distinction. I wrote it down immediately.

Because the more I thought about it, the more I realized how much of commerce has been built around the first one.

And how so much of the opportunity ahead is in the second.

Execution got us here

Commerce agencies and brands have spent years getting incredibly good at execution.

Run the campaign. Optimize the bid. Find the audience. Track the conversion. Measure the return. We are essentially a heat-seeking conversion missile. You point us at the conversion end point, and we will hit it more efficiently and effectively than ever before. That’s what commerce execution does!

In fact, I think one of the reasons commerce and retail media have earned a bigger seat within the marketing industry (including ~20% YoY growth for the last decade) is because so much of the work happens close to an actual business outcome. Did our marketing actually drive sales?

Retailers don’t just have panels or modeled data. They have some of the largest first-party datasets tied to actual consumer purchase behavior. That is a huge benefit for brands looking for more accountability out of their marketing investments (and a whole other Field Note worth on this topic).

The biggest benefit is that we can reach audiences and measure campaigns based on what consumers actually search on the retail site, what they actually buy in-store, what they buy again (and again), which products are gaining momentum and which marketing activities actually drove sales.

But just because we can continue to optimize toward a target doesn’t mean we should always continue to do so.

You can optimize the heck out of a branded search campaign and just be defending the demand that already exists. You can deliver incredibly efficient reach without showing any incremental impact on sales. You can find the perfect audience and negotiate the best rates with your partners, but if the creative is garbage, the campaign is too…

Those aren’t necessarily execution problems. A lot of them get solved through better decisioning upstream.

And that is where commerce can become a lot more critical to the entire marketing industry.

What should we do next?

In our industry (and life) we are inundated with information. There are more reports and data points coming across our desks (or feeds) in a day than anyone could seemingly action in a month. The most important question isn’t what data or insights we can get. It’s what should we do next?

Where does the next dollar go? What is actually driving growth? Which consumer cohorts have the highest potential? What creative elements are actually changing behavior? Are we creating demand or just getting really good at capturing the demand that already exists?

These questions are not exclusive to the commerce or retail media team. In fact, I would argue, the more of your teams can answer those questions in the same way, the better (more connected) your org will be. There is so much demand for integrating planning in our industry but too often we discuss the competing objectives within the same brand initiative.

At their core, these are strategy decisions that cross media, brand, creative, sales, finance, product, supply chain and many others depending on how your organization is ultimately built. What commerce provides are signals that can help answer those questions with more accountability than ever before. Are we ultimately driving sales with our decisions?

For a long time, commerce was one of the places we went to understand what is happening at the end of the purchase journey. Advancements in clean rooms, audience IDs and technology have enabled commerce signals to move further upstream, that means marketers can shape their plan with sales-based insights before the first dollar ever gets invested.

That is what I mean by commerce becoming a decision layer.

Commerce signals need to leave the commerce teams to help improve the decisions and recommendations of others.

If a signal can improve a media channel decision, it should make its way into media. We shouldn’t always have to wait for the next MMM readout to learn something that commerce signals may already be telling us about the sales impact of our marketing.

Commerce signals can also tell us which creative elements are most closely associated with sales. Imagine bringing that intelligence into the next creative brief and now the creative team has a stronger input grounded in actual purchase behavior.

There is so much talk in our industry about outcome-based buying. And while I’m obviously biased, it’s hard to beat an outcome where the consumer actually voted with their wallet. How can we be taking those commerce signals to turn insights into action?

Sometimes the signal improves a retail media campaign. Sometimes it changes how we allocate dollars across brand and performance. Sometimes it informs a better creative brief or audience strategy. And sometimes it helps answer the question every marketer inevitably asks:

If I had one more dollar to spend, where should I put it?

The opportunity is being able to answer that question across all of your marketing alternatives, not just inside the commerce team.

The feedback loop is faster than the organization

One of the things I love about commerce data is the speed of the feedback loops.

Those feedback loops let us learn whether audiences, creatives, tactics or investments are translating into purchase behavior. Particularly when run through RMNs and performance marketing channels, you are able to achieve statistical significance with an extremely limited amount of spend and impressions. It’s a very powerful way to learn but many brand organizations don’t usually move at that type of speed.

I’ve seen channels, partners and audiences that are driving significantly more incremental sales, but the media plan was already locked so we couldn’t adjust the approach. I’ve seen certain product claims or creative hooks outperforming everything else, but the next creative brief was already shipped and it’s too late to update. I’ve seen demand accelerating faster than forecast only to see supply chain and sales unable to keep up and teams completely miss the opportunity.

As much as I could tell you about how awesome commerce data is, it doesn’t automatically create better decisions. Somebody has to see it, understand it, own the decision and actually have permission to do something about it.

Too often the budget belongs to someone else. The brief already went out. The planning cycle happened six months ago. Two teams are optimizing toward different goals. Or the person who sees the opportunity simply doesn’t own the lever required to act on it.

At that point, let’s call it what it is, it’s a decision rights issue.

That is why I think decision quality is such an important distinction. The challenge is not just creating better signals. It is building organizations that can actually move when those signals tell us something important.

Start with the decision

Data helps tremendously to set the direction but it’s important to understand what changes or impact you are ultimately trying to make.

If the goal is to improve decision quality, I like starting somewhere specific. What decision are we actually trying to make better? Then work backward.

Take video investments in our industry right now. Video increasingly spans brand and retail media budgets. Whose objective are we optimizing toward? Who owns the allocation decision? And if the data tells us to move money, does that person actually have the authority to move it?

Better data helps. But the decision layer also requires ownership, shared outcomes and the permission to act.

The organization has to let people move toward a shared outcome (I strongly recommend sales if you couldn’t tell).

What does this change?

I keep coming back to Tiffany’s distinction. Execution and decision quality.

Commerce will always need incredible execution. We still need to pull the right levers to capture demand when the consumer is ready to buy.

But I think the larger opportunity is using what commerce learns at the end of the journey to make better decisions further upstream.

Where should we invest? Which audiences have the most potential? What creative actually changes behavior? What did we learn, and where should that learning go next?

Which leaves me with the question I keep coming back to:

What does this change?

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So obviously I kept looking.

Consumer Edge estimated that TikTok Shop accounted for roughly 2% of U.S. online retail spend in July. That exceeds the online businesses of retailers like Target, Costco and more.

That was a pretty loud signal.

Not just that TikTok Shop was important but the real signal for me was that I needed to get under the hood and understand what was actually going on.

I know enough about TikTok Shop to be dangerous. Perhaps even a little more. I spend enough time in client and industry discussions that I can usually hold my own.

But there comes a point when a trend gets big enough that knowing the headline is not good enough anymore.

When the signal gets loud enough

This connects pretty directly to what I wrote about in the first Field Note and the need to stay closer to where the work is actually happening.

With TikTok Shop, I felt like I was a fan of a sports team. I knew the players, I knew the rules, I knew the strategy, I could talk about the game but if you asked me to lace up, I’d be the worst player out there.

So I did what I do when I realize I do not understand something well enough. I found people smarter than me and started asking questions. Lots of them!

In this case, I reached out to Deren Baker and Molly O’Bryen, two people I have a ton of respect for personally and who also happen to know this space incredibly well.

I talked to Deren that morning. Molly that afternoon. There was no formal agenda, it was a Slack message asking if we could talk TikTok Shop.

The way I like to approach these conversations is to understand two things. What levers can I pull and how does that impact the recommendations I would ultimately make. Most platforms have lots of fancy stuff, my general priority is to figure out what I am eventually going to do with all of it so I usually start with a few high-level questions but from a specific lens.

Pretend I am a brand. Walk me through this thing from beginning to end. How do we win? What do I physically need to go do next? How do you know when it’s working?

I find that I learn the best when I pressure test a real scenario.

Okay, but how does this actually work?

This is one of my favorite ways to learn.

Deren did an incredible job of setting the landscape for me and updating me on the biggest factors in the space. Then it came time to go deep into the platforms and I got on the call with Molly.

I realize the likelihood that I start running the day-to-day TikTok Shop operations for a brand is highly unlikely but I do this type of thing because I want to understand how it all actually works.

I like to think about it from the perspective of the brand selling on the platform. If this was my first time launching a shop, how would I start? I was personally well versed on the product and assortment best practices so we were able to skip ahead and get into the demand generation. Shoutout to Molly here because this is where we went an entire hour over on our call.

How do I find creators? How many creators do I actually need? HOW DO YOU EVEN KNOW THAT!? How do I contact them? Wait, what!? How do we get them the product? How do we know when it’s working? How do we make that better?

I went into the conversation already having two primary mental models. I knew creator affiliates were the engine of TikTok Shop and I knew volume mattered. What I had not quite appreciated was what happens once you start finding the creators who actually work and how that scales (or doesn’t).

I learned that you have to start incredibly wide. You don’t necessarily know ahead of time who is going to sell (in fact, most creators don’t sell). The creator who looks perfect for the brand based on perceptions or what was in the brief may not be the one who actually moves product. I heard multiple stories of brands not wanting creators because they didn’t meet their perception of who the brand audience was but after results came back that they were top sellers, it became an interesting conversation. Specifically centered around the question, if sales are the goal, why not consider creators based on sales vs. perception of fit?

Once you find the creators who do work, the game took a turn I was not quite expecting.

It seems obvious now, but coming from a media and performance background, I expected something different. It really wasn’t about the slickest platform or AI tools. The difference between a good TikTok Shop program and a bad one was centered around relationship management.

Some teams move their best creators into Discord groups. They give them earlier access to products, deals and more direct communication. There are literally people now in our industry whose entire job is texting and messaging with creators. In some cases founders and brand leaders are getting involved directly in the chats and discussions.

My expectation from wanting a tech demo was that I assumed technology is what was required to find and test an enormous number of creators (that volume thing we keep hearing so much about). What surprised me was how much the game changes after you find the good ones. The clearest recipe for success also had very little to do with technology. It was more closely correlated to how human you were with your creator partners.

Then my brain went somewhere else

Once I understood that creator-affiliate engine better, I immediately started thinking about other marketplaces differently. Amazon in particular.

Amazon already has one of the largest affiliate networks in the world through Amazon Associates and Creator Connections. It has millions of products and more data points driving their commerce intelligence than anyone would practically know what to do with.

That is usually the moment I get excited. I love going deep because there are so many little nuggets, tips and tricks that are highly transferable from one specialty to another. In a lot of cases, the levers end up being pretty similar, just positioned in a slightly different way.

I set out to get under the hood a little more on TikTok Shop and left inspired by what we could potentially do to bring that to Amazon and other retailers.

Knowing enough to be dangerous has an expiration date

There are plenty of areas in my job where I know enough to be dangerous.

Honestly, I think that is unavoidable in our industry with the amount of fragmentation. As much as we all pretend to be the masters of all, nobody can possibly be an expert practitioner across commerce, media, retail, creators, AI, identity, measurement, marketplaces and every new capability appearing every single day.

The skill is knowing when surface-level understanding is enough and when it is time to go deeper.

When clients start asking the same questions over and over again, I pay attention. When other teams start asking questions around a particular topic. Or, as we saw in the case of TikTok Shop, when the growth numbers start looking legitimately insane.

That is my cue. Find the people closest to the work and get curious. Ask dumb questions and have somebody share their screen and walk you through the actual process.

If you can find the right people, don’t stop asking questions until you can fully understand what actually separates good from bad and understand the inflection points well enough that you’re confident calling something good or bad in the first place.

That is getting under the hood.

All this for what?

I am not responsible for running TikTok Shop every day. There are people who know more about the platform than I ever will. That is a bit of the point for me.

The goal of this Field Guide is not for me to pretend I have mastered every emerging part of modern commerce. It is to stay curious enough to know when something deserves a closer look.

Then go into the field. Learn from the people actually doing the work.

This week, TikTok Shop got loud enough that I wanted to look under the hood. I went in expecting the interesting part to be the technology required to manage thousands of creators. I came out thinking the competitive advantage is how you manage the human side of it once technology has already done its job.

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It needed to introduce the series. Explain what I believe. Establish where modern commerce is going. Set up everything I might write about later. Basically, I was trying to make the first note carry the weight of all the notes that might come after it.

So I decided to change the question.

I thought if this were Field Note #17, what would I write about this week? That was much easier for me to think about. My mind immediately jumped to what I keep coming back to at work:

The further ahead you are trying to see, the closer you need to stay to the front line.

Building the car of the future

I get the pleasure of spending a lot of my professional time thinking one to three years out.

Where is the puck going in our industry? What will AI make possible? How will commerce and media connect differently? What trends are starting to converge?

That last question is probably my favorite. I have been obsessed throughout my career with finding the places where 1+1 can actually equal 3.

Recently, I was talking with a senior leader about where we are going and what it takes to build the car of the future. My argument was that the people designing that car still need to be deeply connected to the people driving today’s car. You can’t lose sight of the front lines.

I feel this in my bones. I have seen and experienced too many examples where the frustrations, workarounds and the things that simply do not work today become the things that tell us what needs to exist tomorrow.

Necessity drives innovation as they say!

The future is often hiding inside today’s friction

There is a concept from Bain that I have always liked.

Their Founder’s Mentality language describes how companies often begin as insurgents. The glory days of a startup on a rocket ship. Bain describes that stage as being close to customers, obsessed with the front line and always moving quickly. Then those same companies grow. While scale creates enormous advantages, it inevitably also creates complexity and ultimately separation from the front lines.

I am sure there are plenty of people who could better explain Founder’s Mentality but what makes me really fascinated is diving into what signals I am looking for in that connection. Why does it ultimately matter?

The front line is one of the best places to get a read on the challenges of today which lead to the solutions of tomorrow.

When I say front line, I mean wherever strategy encounters reality. Practitioners using the tools. Clients asking the questions. Consumers behaving in unexpected ways. Systems revealing where they break.

There have been countless times in my career where I have had teams spending hours and hours of their time doing the same manual and repeatable tasks. It is one of the strongest signals out there to your product and AI teams on what should be automated.

Seemingly every brand organization in the last year has asked about ways to improve the planning process between brand and retail media. That is a massive signal that our operating models need to change.

How many times have we seen a campaign absolutely crushing it only to have the item run out of stock? It’s absolutely devastating. But it is also a pretty big signal that it is time to better align your demand creation (marketing, media, etc.) with your demand capture (sales, supply chain).

The challenge is that these signals rarely show up with a big blinking sign saying LOOK HERE.

One of my favorite questions to ask teams and clients is: What is one thing keeping you up at night?

I pay close attention to those answers. It is one of my favorite opportunities to gather signals worth exploring.

Necessity creates a pretty good product roadmap

I may not be a Product person in the traditional sense but I do know you can’t design for the future exclusively from the sidelines.

You can strategize and pontificate all day long but eventually somebody has to go use the thing. I think we can all agree that reality has a great ability to expose our assumptions (insert the assume wordplay joke here).

I know I have personally been fooled by a great looking product demo that I later found required six steps before I could actually get any use out of it.

We all hear the stories about the promise of AI and how there are some of the most transformative workflows you have ever seen…until you realize the model doesn’t account for the data or context or anything required to make the best decision possible.

There have been countless times in my career where I have pulled together a recommendation to get incremental investment to take advantage of new consumer trends or innovation in the marketplace. I proudly brought it to my client a dozen different times only to have it revealed that no one at the organization actually owns the budget required to act on it.

The more I see the same problem appearing across clients, teams, platforms and markets, the stronger the signal becomes for where we should build.

How to tune for what actually matters

Being close to the front line does not mean reacting to everything you hear. As a reformed people pleaser, I am here to tell you that it would drive you insane.

Every client request is not the next playbook we need to rally around. Every practitioner frustration does not deserve a product enhancement. You need to be able to look for patterns, not reactions.

If you’re going to take away one thing, it’s this. Get curious and start asking questions:

Why does this keep happening? What changed that made this problem more common? Where else are we seeing it? What needs to be true for the problem to disappear? Where is this taking us?

That last one is where I really like to explore further for those 1+1=3 opportunities.

Build to the future. Learn from the present.

I do not think innovation means asking people what they want and building exactly that.

There is a great line often attributed to Henry Ford: If I had asked people what they wanted, they would have said faster horses.

I love this because it just shows that people are usually better at describing their problems than designing the solution.

As I relate that back to the part of my job where I get to think one to three years out, I find that the skill required for the job is often synthesis (more to come here in a future Field Note).

The front line gives the raw material but then it’s up to me to investigate. What is the actual problem underneath the request? Is it foundational, contextual or temporary? Once I gather enough information, it’s time to synthesize and move forward.

If the job is to build the car of the future, I would argue it’s important to understand why today’s car keeps getting stranded on the side of the road.

That is why I am starting Field Notes

Once I thought about it this way, I realized it was also the reason I wanted to write this series in the first place.

I don’t want The Modern Commerce Field Guide to become a bunch of predictions about what commerce will look like someday. I will absolutely get those wrong.

My goal is to truly create field notes.

Things I am seeing in the work. Questions that keep getting asked. Signals that seem unrelated until suddenly they do not. And then the attempt to turn those moments into meaning.

Some weeks that will mean talking about commerce. Other weeks may be retail media, AI, creators, marketplaces, clean rooms, leadership or whatever thing is occupying my brain that week.

I want to spend a lot of time in this Field Guide looking toward the future. I just do not want to look so far ahead that I lose sight of where we are currently.

Today’s constraints. Today’s questions. Today’s challenges. The future is often hiding inside all of it. You just have to stay close enough to see it.

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