There is one aspect that reigns true across all of ecommerce – Amazon advertising strategies are spearheading sales. For instance, an ecommerce company experienced a 28% revenue increase after one year of running Amazon Ads, with acquisition costs 18% lower than campaigns on other platforms.
Despite understanding the value of this advertising, many brands we’ve spoken with continue to struggle with executing a successful strategy. We’ve covered ecommerce advertising extensively and have decades of experience in the space, but a recent LinkedIn post by Joon Choi, Senior VP of Xnurta, captured it perfectly:
“1) Define my objective - I’d start with a clear goal: maximizing incremental growth from Sponsored Ads. (2) Focus on key query pillars - My focus would be on Audience Behavior and Incrementality. 3) Build a query system that scales - I’d set up a library of reusable queries to answer the most pressing questions. (4) Identify winners and scale intelligently - I’d double down on what works—shifting budgets to high-performing keywords and segments. 5) Turn insights into ongoing growth - This isn’t just about reporting; it’s about creating a repeatable growth loop: query → learn → optimize → scale.”
This insight aligns closely with many of our own brand strategies at Spreetail, so we wanted to hear more from Joon. Having launched his career at Amazon during the debut of its sponsored ads program, he had a front-row seat to the evolution of Amazon advertising. Joon recently sat down with Amit Dodeja, Spreetail’s CMO, to discuss Amazon ads, emerging strategy trends, and the growing role of AI in the future of retail media.
Help us understand what sparked your LinkedIn post about AMC (Amazon Marketing Cloud). Was there a specific inspiration for wanting to share your thoughts?
The AMC post was inspired by its rapid growth about nine months ago. From my time at Amazon, I saw how AMC offered everything clients had been asking for. Once Amazon launched this data, I knew widespread adoption was inevitable. So, I dove deep into AMC, eager to learn as much as possible. Fortunately, I work in an environment where AMC is a top priority, and that post was just a reflection of my thoughts on its impact and how brands, advertisers, and agencies should be leveraging it.
How do you ensure your advertising dollars are making a real impact without cannibalizing your own efforts? How are you leveraging AMC or other data sources to answer these questions and build confidence in your strategy?
Incrementality has always been a key question in advertising—everyone wants to measure it, but no one has perfected the calculation. The first thing I ask is, how do you define incrementality? because it varies for everyone. At its core, it's about determining whether certain sales would have happened without a specific action.
If someone asked me to calculate incrementality today, I’d say we’re not quite there yet. However, AMC is the closest tool we have to get us there. One of the most valuable aspects of AMC is its ability to provide insights through new-to-brand metrics, which many advertisers are increasingly prioritizing. That said, these metrics don’t apply universally. They’re more relevant for brands with frequent purchase cycles rather than high-ticket, infrequent purchases—like TVs, for example.
The key to leveraging AMC for incrementality lies in clearly defining what you want to measure and using the platform's analytical capabilities to get as close as possible. When asked if we can fully calculate incrementality, my response is always: We’re not there yet, but AMC is bringing us closer.
What makes AMC so powerful is that it's essentially a blank canvas. The data is there, and you can pull whatever you need. But the real advantage goes to those who think creatively about how to use it. The most successful advertisers will be the ones who approach AMC in unique, strategic ways that others haven’t considered yet. This competitive edge will set apart the brands and agencies that maximize AMC’s potential from those still playing catch-up.
How do you approach the foundational question of defining success in advertising, whether it's revenue growth, profitability, or new-to-brand sales, and would you recommend setting multiple objectives to balance these priorities effectively?
I recently shared a post on this topic that I think illustrates it well. When discussing AMC with brands, the primary objective isn’t necessarily top-line growth—it’s ensuring every advertising dollar is spent as efficiently as possible. That often comes back to ROAS, a metric many brands have relied on for years. However, I believe ROAS is outdated because it doesn’t account for repurchase rates.
For example, if a consumable product is purchased frequently, a traditional ROAS analysis might label a campaign as underperforming, even if it's driving repeat purchases. AMC changes this by enabling brands to measure lifetime value ROAS, which factors in long-term sales impact. Instead of stopping at an initial ROAS figure, brands can now analyze total revenue generated over time which can often reveal that a campaign is far more valuable than it first appears.
Another key advantage of AMC is its ability to track when customers return to purchase. If data shows that 30% of first-time buyers repurchase in the third month, brands can use AMC custom audiences to retarget those customers at the right moment, maximizing ad efficiency.
The biggest challenge with AMC isn’t access to data—it’s knowing how to use it effectively. Many in the industry are still figuring out how to transform raw data into actionable strategies. The real opportunity lies in building a scalable, automated query library, allowing brands to efficiently analyze insights, optimize campaigns, and stay ahead of the competition.
How do you turn audience behaviors into tactical campaign strategies and then do that in a way that's repeatable and scalable to create a functioning system?
The biggest challenge with AMC is the technical barrier, which Amazon is actively working to lower with no-code solutions. However, truly optimizing AMC requires deeper data analysis, and without a no-code tool it becomes difficult. Most marketers don’t know Sequel, let alone Amazon’s version, which has slight but important differences.
Step one is ensuring your team has the right tools to access and analyze data beyond Amazon’s native console. The next step is focusing on granular, specific use cases that drive meaningful impact. Many organizations don’t have the experience or bandwidth to spend days learning AMC from scratch, so it’s crucial to lean on experts who are already leveraging it effectively.
For example, one fundamental use case is LTV (Lifetime Value) analysis, particularly for CPG (consumer packaged goods) brands. Another powerful model is cross-product association, which reveals how customers interact with hero ASINs. This analysis shows what products are frequently bought together, what higher-priced items customers purchase after visiting a hero ASIN, and how brands can refine their upsell or bundling strategies.
One brand used this model to maximize Prime Day performance, aiming to increase average order value (AOV) by 15% over those two days—a period worth an entire month’s revenue for them. By analyzing AMC data, they discovered product associations they hadn’t previously identified, bundled those items strategically, and came close to achieving their 15% AOV increase. That insight alone drove a significant bottom-line impact.
Once brands establish a foundational layer of data access and see tangible results from low-lift, high-impact use cases, AMC becomes a test-and-learn environment, unlocking even greater opportunities for optimization.
You hit on the specific skill sets needed to collect and leverage this type of advertising data. How do you see the makeup of an ecommerce marketing team evolving over time?
One of the biggest shifts in marketing teams over the past year has been the increasing focus on data analytics roles. A year ago, many brands were just starting to ask, What is AMC? Six months ago, the conversation shifted to, What are the basic levers we should be pulling? Now, AMC is a core part of nearly every media plan.
As a result, mid-market and enterprise brands are evolving their marketing structures to include more technical, data-driven roles. Many are hiring analytics managers specifically focused on AMC, tasked with extracting and leveraging data for better decision-making. Rather than traditional marketing teams operating in silos, we’re seeing brands build internal analytics hubs to harness AMC’s potential and act on insights more efficiently.
This shift shows how quickly AMC has become essential. Companies now recognize its value and are investing in the right talent to ensure they can analyze and apply AMC data at scale.
You mentioned middle market and Enterprise CPGs, how do you approach leveraging AMC and other available tools differently based on the size and structure of a company? Specifically, how does the strategy vary for a single-brand company versus one that owns 5 to 10 brands, or even larger organizations that work with hundreds of brands?
AMC has effectively leveled the playing field between smaller brands or agencies and larger enterprise brands. Historically, only the biggest brands had access to extensive data, the resources to extract it, and the ability to act on it efficiently. The brands that leveraged data most effectively were the ones that won.
What makes AMC unique is how it has bridged that gap. Now, brands that may not be large in scale but rely entirely on Amazon for their revenue and growth have access to the same level of data. With the right tools these brands can pull, analyze, and act on data just as efficiently as the biggest players.
Interestingly, some of the most innovative ideas come from these smaller brands. Because their business depends on Amazon, they are constantly experimenting, learning, and finding new ways to use AMC to maximize efficiency. This has led to a shift where the speed at which brands can gain insights and optimize their ads—what I call “speed to insight”—has dramatically improved.
A great example of this happened during an AMC Masterclass workshop we hosted. As we walked through key use cases, a brand owner raised his hand and asked whether AMC’s custom audiences could be layered with sponsored ads to effectively geo-target campaigns. After thinking it through, we realized—yes, you absolutely can. By leveraging AMC custom audiences, you can target only those who have seen an ADSP ad and then apply a bid modifier for sponsored ads to refine the targeting. This wasn’t an idea coming from a massive enterprise but from an individual brand owner deeply engaged with AMC every day. It’s a perfect example of how creative thinking, paired with AMC’s accessibility, is reshaping the landscape of Amazon advertising.
We learn a lot about things when we win, but we learn even more when we lose. Where have you seen brands stumble or, what obvious mistakes should be avoided?
A common pitfall we see with AMC is that some advertisers expect it to be a one-stop solution for all their challenges. They come in with the belief that AMC will solve everything, but in trying to do everything, they end up accomplishing nothing.
While AMC provides access to a wealth of reports, many users don’t know how to extract actionable insights. They get excited, pull a ‘Path to Conversion’ report, and then hit a wall—unsure of what to do next. After investing time and resources into generating reports on multi-touch attribution and other metrics, they often fail to connect those insights back to campaign performance, which is ultimately what matters most.
For those new to AMC, the best approach is to start with a clear objective. You don’t need to do everything at once. Identify a single problem, choose one report that aligns with that goal, and work backward from there. What often happens is that one insight sparks new ideas, leading to ongoing testing and learning.
All that to say, the biggest mistake at this point is simply not using AMC at all. There are still many brands that haven’t even set up an instance, and they’re missing out on a major competitive advantage. As more advertisers get tactical it’s becoming clear that success comes from taking a step-by-step approach, rather than trying to boil the ocean all at once.
In terms of AI, what is your perspective on it’s trajectory relative to the Internet? What are you seeing in terms of who is pushing the envelope and how it’s being adopted?
I’d say we’re currently in a phase comparable to the late 2000s or early 2010s in terms of AI adoption—where businesses are starting to uncover actionable use cases that drive real impact. However, unlike past technological shifts, AI’s rapid advancement is accelerating this timeline dramatically.
Over the last two to three years, we’ve seen an exponential curve in AI development, with various open-source models reshaping what’s possible. While many expected AI to evolve quickly, I don’t think anyone anticipated just how fast this space would move. That’s what excites me most, especially when it comes to AI’s potential in advertising.
Retail media, in particular, presents one of the best use cases for AI. It involves high-velocity, highly manual tasks that machines can handle far more efficiently than humans. AI doesn’t need to sleep, eat, or take breaks. It can continuously monitor changing market conditions, assess performance, and make adjustments instantly.
Looking ahead, I believe agentic AI (AI-driven agents that act autonomously) will be a game changer in this space. We’re actively pushing for this within our organization because it represents the next leap in automation. Imagine an AI agent that integrates with APIs and external data sources. For example, if a major snowstorm is approaching, the AI could recognize the potential impact on consumer behavior and automatically adjust bids and campaign strategies in real-time.
Any final takeaways that you'd want brands and ecommerce marketers to keep in mind to start applying?
When it comes to AI and AMC in retail media, the most important mindset is a commitment to testing and learning. These are exponential technologies that are rapidly transforming advertising, and if you’re not at least experimenting with them, you’re likely falling behind.
We've seen firsthand how brands that actively test, iterate, and adapt with AI and AMC achieve compelling results. Many of these brands initially stuck to their traditional methods, believing they were already optimized. However, as they faced year-over-year revenue targets with little to no increase in marketing budgets, they needed a new approach. By leveraging AI and AMC, they uncovered new efficiencies in targeting and campaign performance, unlocking growth they hadn’t thought possible.
My biggest advice? Stay curious. Test, learn, and adapt. Even small experiments can lead to game-changing insights.
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You can learn more about Joon and the Xnurta team through their website, as well as at key industry conferences and events. They will be attending Prosper, ShopTalk, Accelerate, and Unboxed, along with hosting AMC master classes and workshops each quarter.
As a company, their core focus is on AI and AMC, continuously pushing the boundaries of what’s possible. Xnurta is always experimenting with the latest AI models, and this year, have some exciting innovations in the pipeline that will showcase just how powerful today’s technology can be.
Chief Marketing Officer
