Most retail media teams already know what they can change. The more difficult decision to make is when, especially once a program spans multiple retailers and a large product catalog. Executing a plan slows down during the time between noticing a change and getting the right fix applied across the account. While it might be easy enough to spot a change, it is harder to update multiple SKUs across several campaigns without taking on a day’s worth of manual work. 

In campaign management, I push for a simple operating rule: treat retail media optimization like a routine you can run even when the week is busy. That routine does two things well: It helps you spot movement early, and it makes it easier to apply updates across many campaigns without turning the work into a click marathon. Here’s how to make this routine work. 

Start by looking at what changes week by week

Instead of looking at a snapshot summary of what happened, compare so you can see what changed. Start every review by comparing performance to a prior period that makes sense for your business. For example, for daily work, compare to yesterday. For weekly work, compare to last week. For monthly work, compare to last month. Also pull the same time period from last year when seasonality matters. Year-over-year context helps you separate a real performance shift from a predictable calendar pattern, especially around holidays, promotions, and category cycles. 

Once you look at change over time, you can sort what you see into the three buckets that matter: 

1. A product or retail condition changed. That might be availability, pricing, Buy Box status, or competition changes (their promotion strategies could have changed). 
2. Campaign settings or targeting changed. Pacing, targeting mix, bids, or placement performance shifted. 
3. The reporting view changed. Retailers do not all report the same way, and attribution can differ by ad type and placement. 

That sorting step keeps you from doing bid work to solve a product issue, and it keeps you from blaming the retailer when the campaign setup is the real problem. 

One practical note: not every retailer provides the same fields. Use what you have on each network and treat additional commerce context as a bonus signal when it is available. 

Daily retail media optimization review: keep budget pointed at what can convert

A daily review is meant to look at where you can prevent obvious waste and protect coverage. This is different from a review where you’re looking to optimize the whole account.  

It helps to look at delivery and pacing. If a campaign is not serving or a budget is pacing wrong, nothing else matters until that is corrected. 

Next, it’s important to look at concentration. Spend almost always clusters. If the top set of SKUs is shifting, the day’s performance shifts with it. 

After doing that, check whether the SKUs you’re paying to promote still have a fair shot to compete today. Look for changes that can undermine conversion even if your campaign settings did not move, such as pricing shifts, inventory pressure, slower fulfillment, weaker product page content, or a change in the competitive set, like a new promotion, a competitor price drop, or more aggressive bidding in the category. 

Were there sharp swings on the same set of top spenders? Look at whether there was a big move in CPC, conversion rate, or sales. This can help you confirm inputs, then decide whether to act. 

Daily actions should stay simple. Pause what cannot convert and redirect spend to the next-best set. Reduce exposure when you need to buy time. Save deeper structure work for the weekly pass. 

Weekly retail media optimization review: fix patterns and cut back on manual work

With daily reviews, you can catch exceptions. Weekly reviews allow you to improve how the account runs. If you see the same problem across a set of campaigns or SKUs, apply one change across the set of SKUs and move on. 

The weekly review also gives you a cleaner window for decisions that need more than a single day of signal: 

• Tighten targeting based on what repeated, not what spiked once. 
• Adjust bids and budgets where performance held steady long enough to trust it. 
• Decide which SKUs earn more investment and which ones need constraints. 

Weekly is also where testing belongs so you can learn and not create chaotic changes. Pick one change you can explain, write down what you changed and why, then review it the next week before you add another variable. 

Monthly retail media optimization review: reset budgets, structure, and measurement 

Monthly work should feel different from weekly work. Weekly work improves performance inside the current plan. Monthly work checks whether the plan still matches the business. 

This is where you make the decisions that reduce rework later: Rebalance budget by retailer, category, and the product sets the business actually wants to grow. Then clean up structure that slows execution or muddies reporting. Once you’ve done that, you can confirm the measurement view answers the question your stakeholders care about.  

Where Rithum fits in the day-to-day work 

A review routine only helps when it leads to fast, consistent changes. Most delays are a result of repeat work that gets handled one campaign at a time. 

That is the gap our digital marketing, retail media managed services, and tooling are designed to close. We use rules-based automation and filters to improve bidding, keyword, and dayparting strategies, and we automate key campaign components like bidding, dayparting, and ad status.  

On the operations side, we also take on the work that tends to clog a week: campaign creation, tracking, and reporting across multiple channels. 

The benefit is speed and consistency, especially when the same change needs to roll across a large catalog. 

If you want a quick way to assess whether your current approach will scale, look at one week of account work and count how often you made the same change in more than one place. When repetition is high, the best process in the world still slows down without a better execution path. 

A better way to value support 

If you are considering a platform, managed support, or both, do not start with feature checklists. Start with a workflow question: 

When performance shifts midweek, how quickly can your team apply the fix across the full catalog, across retailers, without creating a second job in spreadsheets? 

If you want to pressure-test your current process, our team can walk through the cadence above using a recent slice of your program and identify where repeat work is slowing you down. The retail media services overview is the right place to start if you want a team to help run execution day to day. 

Nick Szeto is Senior Manager, Advertising Account Management, at Rithum.

The post You already monitor retail media and digital marketing campaigns; build a routine that gets updates live faster appeared first on Rithum.

TL;DR 

• ROAS stays useful when you read it inside one retailer and within specific placements. Once you carry it across retailers, the comparison gets noisy unless you bring context with it. 

• Every retail media network behaves like its own environment. People shop differently, products appear differently, and performance attribution varies greatly. 

• Strong retail media strategy starts retailer by retailer, using insights on a retailer-by-retailer basis to meet the customer where they are in their shopping journey. 

• Price, availability, and assortment shape shopping outcomes in ways ROAS does not show. 

• Reporting is most valuable when it connects ad spend to product-level outcomes and uses the language that aligns with the business 

On the weekly call with the retailer’s ecommerce team, the deck opens with ROAS (return on ad spend) and a tidy spend line. Everything looks good, until someone asks about which products are they trying to move the next week. Answering that question requires looking beyond the fast sellers to address the products that haven’t been as successful to find out how to change that. 

It’s easy to keep spending on the products that already sell efficiently. Brands and retailers also have other priorities, like giving a new launch enough visibility to earn repeat purchases, supporting a focus line ahead of a seasonal moment, or putting weight behind an item that reliably introduces shoppers to the rest of the brand. That’s why ROAS belongs in the overall update, but it won’t tell you whether the budget supported the week’s priorities. 

Picture a snack brand whose variety pack always delivers strong ROAS. Left alone, the plan keeps feeding that winner. Then the retailer flags next week’s focus: a new flavor launch tied to a seasonal feature. The brand shifts some spend to the new item and a few related products shoppers often buy together. The report may still credit the variety pack, but the plan does the job the retailer asked for, and the brand can watch whether more of the lineup starts moving. 

What ROAS tells you, and what it can’t 

ROAS is a strong efficiency signal for retail media strategy. Within one retailer, with consistent placements and stable measurement, it gives teams something practical to steer by when they manage bids and pacing. 

But overall brand profitability is a separate question. There are many dependencies for that level of measurement, including products sold, margin on the items that absorbed spend, and whether the outcome matched what the business needed that month. Those details often live outside the ad platform view, even on teams with solid measurement habits. 

A high ROAS can also happen when spend simply follows the easiest conversions. Budget concentrates on the fastest conversions, product conditions change midstream, and the report still looks strong. Nothing is “wrong” with the metric. It just doesn’t explain whether the spend supported the products the business needed to move. 

Retail media strategy is unique to each retailer environment

Retail media networks don’t follow one set of rules. A single approach template can feel efficient, but it smooths over the very differences that drive performance. What tactics may work in Amazon may not resonate the same in a Walmart or Target Roundel.  

Rithum points out just how scattered retail media still is: more than 220 networks, and each retailer reports results in its own format. 

Assortment varies by retailer, and a brand’s winners in one store may not even be listed in another. Shoppers also bring different expectations depending on where they shop, which changes how they respond to ads and merchandising. Retailer programs add another layer, from exclusives to promotion structures that alter which products deserve investment. Reporting varies as well, sometimes in small ways and sometimes in ways that change what a familiar metric appears to mean. 

Start by assuming the retailers won’t behave the same way. Then you can plan around the few things that change every time. 

What changes from retailer to retailer: 

• Assortment 

• How shoppers behave 

• How results get measured and reported 

Even one of these differences can force you to change plans. When combined, a one-size-fits-all or copy-and-paste strategy is risky. 

A retailer-by-retailer retail media strategy that holds up 

1. Decide what this retailer needs to do for you 

Start with intent before you touch the media plan. You need to ask what is this retailer supposed to deliver? 

Some retailer environments are volume drivers, while others are where shoppers discover and compare brands in a category, and still others matter because the relationship shapes promotions and visibility beyond media. Those differences should guide which placements you prioritize, which products get budget, and what you consider a good week. 

If you skip this step, the conversation turns into a debate about numbers that weren’t built to match. Rithum helps clients to look beyond the biggest networks, where a brand can often reach new shoppers and earn more visibility for the same effort. 

2. Choose the products that deserve the budget 

The question worth answering every week is what products is the retailer trying to sell more of next week? 

For instance, imagine a brand that sells both pantry staples and premium seasonal items. Last week’s ROAS winner might be the staple that sells year-round with a predictable conversion rate. But this week, the smarter list could look different. The retailer has a seasonal event running, the premium item is in stock and priced competitively, and the brand needs to build visibility for it before the moment passes. Meanwhile, a different product might be selling fine without paid support, or it might be tight on inventory, which makes it a poor candidate for extra spend. 

The right product list won’t be the same everywhere. Each retailer has a different assortment, different shoppers, and different moments week to week. 

Advertise based on where your target consumers are in their shopping journey. People come to each retailer with a purpose. Some visits are quick purchases; others are browsing and comparison. Creative works better when it matches that mindset instead of forcing one generic message everywhere. 

Retailer programs and exclusives matter here too. A promotion, a bundle, or an exclusive item can change which products make sense to push that week. 

3. Keep ads synced with what shoppers can buy 

Prices can change overnight. Inventory can tighten without warning. Monday’s campaign leans on the hero product; by midweek, shoppers can’t buy it, and the ads keep sending traffic anyway. 

Rithum’s Product Feeds materials describe low-latency syncing for inventory and pricing, with near-real-time changes to price, stock, and new items, with the stated goal of reducing wasted ad spend and preventing out-of-stock recommendations. 

4. Don’t let fast sellers swallow the budget 

Retail media spend tends to gravitate toward a handful of products that already convert. The signal is clean, and dashboards keep reinforcing the same winners. 

That pattern can crowd out the products you’re trying to grow. A best seller keeps getting budget because it makes ROAS look great, while a new line never gets enough exposure to prove itself. 

Rithum’s retail media advertising materials describe product-aware optimization that leverages inventory, pricing, and margin data insights powered by RithumIQ. 

5. Translate unique retailer metrics into business terms 

Retailers deliver performance data in their own formats, and standard metrics aren’t consistent across networks. Comparisons can still be useful, but they require clear definitions before anyone draws conclusions. 

Rithum’s retail media advertising materials also describe closed-loop reporting that ties spend to sales at the ASIN level for profitability measurement. 

The scenario where ROAS is enough 

ROAS can carry more weight when a program stays inside one retailer, within a stable set of placements, and the assortment doesn’t change much week to week. In that setup, the comparison is cleaner. 

As soon as a program spreads across retailers, the differences return. Assortment, shopping behavior, merchandising, and reporting depth still vary enough to change what “good” looks like. 

Where tools help, and where they don’t 

Most teams already know retailers work differently. The hard part is execution: keeping product reality, campaign decisions, and reporting connected without rebuilding the workflow every week. 

Rithum’s public materials describe product-aware optimization that leverages inventory, pricing, and margin data insights powered by RithumIQ, along with closed-loop reporting that ties spend to sales at the ASIN level for profitability measurement. 

Tools don’t replace judgment. They can make a retailer-by-retailer approach easier to run consistently. 

ROAS belongs in the update, but profit terms live at the product level. Look at the items that received budget in each retailer, the margin behind those sales, and the total margin dollars the week produced. Keep price and in-stock status in view at the same time. That view makes it easier to judge whether the budget supported the week’s priorities, not just the items that earned the cleanest attribution. Learn more about retail media strategy and how Rithum can help. 

Meghan Barden is Director of Global Retail Media at Rithum.

The post Why a high ROAS doesn’t always mean high profit  appeared first on Rithum.

To no one’s surprise, AI talk was everywhere at eTail West 2026. But the sessions that stuck with me focused more on returning to basics: Product information, checkout, measurement, customer trust, internal readiness and meeting the customer where they are in their shopping journey. Even as shoppers start their journeys using the advanced technology of AI, those basics carry more weight than ever. Here’s what I’m still thinking about after soaking up all eTail West had to offer.  

AI answers are a storefront now  

As the referral to external websites from LLMs decreases rapidly, retailers and brands need their products to be the answer when shoppers use AI, not a click along the way. Jessyca Frederick, Director of Digital Product at Wine Enthusiast, said: “LLM priority #1: answer your questions completely . . . prevent linking out.”  

Jessyca talked about how these systems gather information: “RAG agents pose fan-out queries to search engines.” RAG stands for retrieval-augmented generation. It means the system searches for sources, pulls what it needs, then writes using what it found. A fan-out query is one question that triggers several searches. Think of one shopper question, many search runs.  

“The more fan outs you appear in, the more likely you’re to be cited,” Jessyca said. 

AI answers reuse what they can read and trust. Product catalog management accuracy with an emphasis on data hygiene is key. The fit, price, availability, policies must be accurate. If your details are incomplete, inconsistent, or stale, the answer engine moves on.  

Jessyca suggested putting a window for time for “freshness” of that information of 3 months. She emphasized that teams need a routine for keeping key pages current across the places customers browse. The biggest thing to remember is that AI bots simply skip information they can’t access. Jessyca advised to put critical product details in formats they can read, keep pages fast, and clean up broken paths. 

Shoppers move. Your product story has to beat them there. 

The “everywhere customer” panel put a name to what many teams see in their analytics and support queues. With Jodi Williams from Ulta Beauty, Lauren Price from COS, Feliz Papich from Crocs, Jason O’Toole from Gildan, and Jacob Ross from PebblePost, this panel all agreed that brands need to stop thinking they can tell consumers where to shop. Discovery happens in one place, validation in another, purchase somewhere else. A TikTok Shop presence can end up influencing an Amazon transaction.  

Instead of focusing on where the conversion came from, the panel advised asking what shaped it. Measurement is important, but post-click attribution gives the final click most of the credit, even when the decision was made three touch-points earlier.  

“Post click conversions are heavily flawed.” according to the panel. Instead, the panel talked about the importance of incrementality. Measure lift against a baseline. Set up a holdout, compare outcomes, and see what changed. Try to reduce guesswork. 

Checkout decides revenue  

Once discovery is multi-surface and measurement is catching up, it’s tempting to treat checkout as an afterthought. The checkout panel pushed back on that.  

Pat Suh from Affirm (joined by Jack Phung from Newegg and Henry Spear from JD Sports) said, “Ideally the AI already knows the options, but we aren’t there yet.”  

While agentic commerce grows in popularity to discover products, consumers still abandon carts when checkout creates friction or surprise. Brands and retailers often treat checkout as a problem to solve later, then watch conversion drop after they’ve invested in everything upstream. It’s an expensive way to learn the lesson.  

Instead, panel members recommended that to reduce surprises, brands should put key payment details where customers look for them, make choices clear, and keep terms readable.  

Personalization needs intent, not a dossier  

Anna Downs, Digital Personalization Manager at The North Face, noted that consumers want to shop without feeling monitored. and Michiel Dorjee from Optimizely said, “A lot of people don’t like the creep factor of knowing too much about my persona.” The better target, they argued, is intent. “Think about it more of their intent and serve that to them faster, then their experience improves.”  

Intent is what the customer signals in the moment: what they search, what they click, what they compare, what they’re trying to solve. That’s more useful than demographic profiles and less likely to make someone feel surveilled.  

Automation raises output, then it raises the stakes  

The AI panel with Keri McGhee from Attentive, George Davis from Cozy Earth, and Tommy Kowalski from HeyDude covered what teams are truly using AI tools for: scaling creative volume, speeding up lifecycle messaging, and turning one idea into hundreds of variations. The panel cited AI-driven lifecycle journeys producing 200-300% revenue lifts in some implementations.  

Despite that growth, the panel noted there are still retention risks, because consumers will leave the brand if they have a bad experience with AI. Brands and retailers should understand what automation can do and where a human needs to be involved. Going back to the basics: Customers have always remembered when a problem is handled poorly. AI is no exception.

Trust keeps working after the purchase 

There is no replacement for consistency, according to the authenticity and transparency in retail panel. Angela Clark from Patagonia, Catherine Hayden from Kate Farms, Elton Graham from Sur La Table, and Sara Jensen from Hugh & Grace talked about the importance of brand stories that customers can recognize and believe.  

The big takeaways:

• Details like packaging inserts and QR codes drove high engagement to further brand loyalty.
• Customers want context after purchase. They want to understand what they bought and why it exists. It’s another way to retain customers.
• Clear context reduces returns, reduces support load, and strengthens repeat purchase behavior.  

Internal readiness decides who moves fast  

With all the technology changes happening so fast, it’s easy to fall into a reactive stance. A panel with Jennifer Conrad from Inc., Steve Schwartz from Art of Tea, Jonathan Weiss from Raw Sugar Living, Bridgit Lombard from Francesca’s, and Ron Tarter from MNEE Pay spoke about resilience as brand culture. 

“Give yourself permission to pause between stimulus and action.” They called that habit equanimity—the steadiness of mind to absorb new information before reacting. Brands and retailers need to move thoughtful, not make decisions in a half-panic. Be thoughtful and move faster when you need to, but don’t default to a reactive stance. 

The CMO panel echoed the same idea from the growth side. Kate Huyett from Bombas, Aaron Magness from Full Glass Wine Co., Ed See from Zeta Global, Richard Jones from Wunderkind, and Taryn Rayment from J.McLaughlin talked about what it takes to create profitable customers. The work crosses functions: inventory planning, finance, sourcing, marketing. When those conversations stay siloed, growth slows. The marketers gaining ground are the ones willing to get into other teams’ processes and build from there.  

In 2026, brand and retailer teams are fixing the basics. That way, any automation they use is working with accurate data. Looking for continued thought leadership? See how we’re partnering with Amazon MCF on stage at Shoptalk Spring 2026. 

If you’ll be at upcoming industry events, we’d like to compare notes. Meet with Rithum at Shoptalk Spring, booth #1775, March 24-26 in Las Vegas. 

The post What ecommerce teams are focused on right now in 2026 appeared first on Rithum.

During Prime Days 2025, one client brand Rithum works with saw their conversion and average order value slide early. Instead of throwing more budget at weak campaigns, the team held spend, watched the data, and waited for cleaner signals. When performance improved later in the event, they pushed onward and finished strong. 

An apparel brand during the same period saw similar issues. But they decided not to wait. Reliable performance signals showed a shift toward back-to-school demand. So, the team pivoted mid-event and adjusted assortments to focus on back-to-school products, introduced bundle offers, and optimized product titles and keywords. That shift resulted in a 15% increase in sales year over year vs. the previous Prime Day. 

Both brands took different approaches, based on having the visibility and confidence to act on what the data was telling them. There wasn’t a one-size-fits-all approach, but the key was data and agility. 

But according to the 2026 commerce readiness index, a survey of 200 brand and retail leaders across the U.S. and U.K, many brands don’t have that level of confidence and visibility to make it work.

According to the survey data, economic instability and inflation are the top hurdles to market expansion for both retailers and brands. But close behind sit technology and data challenges, rising operational costs, shifting consumer behavior, and supply chain issues.  

Some of that drag is the market. But lot of it is self-inflicted. Using the survey responses from commerce leaders, these are the three internal drags you say you feel the most . . . and what you can about them. And one external headwind you can only prepare for. 

Hidden drag 1: Manual ecommerce operations that slow omnichannel growth 

This drag shows up in the everyday work that still runs on spreadsheets and email, even as your sales channels and partners multiply. 

According to the survey, leaders say they’re “stuck at spreadsheet speed.” Fully automated workflows are rare, with many retail and brand leaders saying that 26% to 50% of their workflows still rely on manual steps like spreadsheets and email. 

In practice, this might look like retail vendor analysts pulling late-order reports into Excel, pivoting them, emailing suppliers one by one, and manually editing product descriptions before listings go live. On the brand side, manual work often involves pulling performance signals from multiple platforms, reconciling conflicting reports in spreadsheets, and chasing analysts for validation before anyone can act. 

You can see the impact of that manual overload in the data. Nearly three quarters of leaders say they at least sometimes make decisions based on inaccurate or inconsistent data, and more than a third say it happens often or all the time. 

53% of retailers say they act on important performance signals within 48 hours; brands are more likely to need three to five business days. Even the fastest groups say they are still acting on incomplete or inconsistent data and largely manual processes. 

If you’re selling through marketplaces, dropship programs, retailer.com sites, and your own direct-to-consumer (D2C) website, this is more than an internal annoyance. Manual listing updates, inventory syncs, and routing decisions become the places where channels drift and small errors balloon across your entire network. 

To turn this drag into an advantage, teams are: 

• Automating onboarding of assortments, content updates, inventory synchronization, and order routing where possible. 

• Consolidating product, inventory, and order data so a change to a SKU is reflected wherever you sell it. 

• Replacing “hero” spreadsheets with shared rules and playbooks that run on current, accurate data. 

Hidden drag 2: AI running on messy product and inventory data 

This drag appears when AI is built on data that is incomplete, inconsistent, or scattered across systems. 

AI is already live for many of the retailers and brands surveyed. 41% of retailers and 29% of brands use AI-based automation across functions like pricing, inventory, and marketing, and another 57% of brands and 41% of retailers say they are getting ready to implement it. 

At the same time, nearly three in four leaders say AI is advancing faster than their organizations can apply it effectively. 

The gap is visible: 

• 49% of retailers and 62% of brands say they still struggle with too many manual processes. 

• 91% of retailers and 78% of brands say poor data quality is a challenge. 

The same leaders rolling out AI across pricing, inventory, and marketing are also telling us they don’t fully trust the data underneath it. When catalog attributes are inconsistent, stock numbers are unreliable, or order and return data live in different silos, AI trained on that information doesn’t fix the issues, it magnifies them. 

This can show up as: 

• Retail media campaigns bidding on SKUs that are already out of stock on key partners. 

• Pricing models making decisions based on incomplete fees or cost data in certain channels. 

• AI “optimizing” assortments based on stale sell-through and margin data. 

How to make AI actually useful 

Start by fixing the inputs. Clean up product data, improve inventory accuracy, and connect orders and returns back to their source channels so you know what really happened and where. 

Then shorten the path from insight to action. If every AI-driven price or bid suggestion still has to be pasted into a spreadsheet and debated in a meeting, you will never see the benefit.  

Apply AI where it matters most: margin pressure from fulfillment and logistics, inventory stock-outs, and wasted media on low-quality traffic. Those are natural places to focus AI, once the data is ready. 

Hidden drag 3: Margin erosion across marketplaces and retail media 

This drag shows up in the small gaps where money and customers slip away across channels. 

Brands say the biggest hits in the past year came from fulfilment, logistics, and product costs. Retailers point first to tariffs and trade disruptions. Both groups also call out discounts, paid media inefficiency, and listing errors or inaccurate product data as other margin drains. 

Retailers most often lose shoppers before checkout, especially when ads do not match the product experience or when payment fails. Brands are more likely to have problems after the sale, in customer care and returns or refunds. 

At the same time, 91% of retailers and 84% of brands say they have changed their marketing channel mix in the last year, often in response to shifting consumer behavior and strategy.  

Some examples where customers and profit are lost in operations: 

• Broken links or mismatched product pages that cause pre-checkout drop-off. 

• Ads driving to SKUs that are out of stock or unprofitable to ship once fees and costs are counted. 

• Returns and service policies that vary by channel, leaving some experiences noticeably worse. 

The fix is to connect performance metrics with operational and margin data to see where the problems really come from. Are you losing money because of traffic quality, or because of content, availability, or fulfillment issues that could be fixed centrally and rolled out across channels? 

The drag you can’t fix: External volatility and ecommerce expansion 

This force comes from outside your walls, but it still shapes how fast you can grow and where. 

When retail and brand leaders rank their top hurdles to expanding into new markets, economic instability and inflation come first for both. Close behind are technology and data challenges, rising operational costs, shifting consumer behavior, supply chain issues, regulatory complexity, and tariff or trade uncertainty. 

Tariffs in particular stand out. 46% of retailers and 60% of brands say they are at least somewhat concerned that tariff and trade shifts will disrupt their sourcing strategies. More than 60% of both groups say they are re-evaluating sourcing relationships to prepare, while many are also cutting business costs and investing in supply chain resilience. 

You cannot control that volatility. However, you can decide how much internal drag you stack on top of it. Focus on what you can change by building stronger operations, reducing technology barriers, and creating more flexible, integrated customer experiences so you can pivot channels, partners, and assortments when conditions change. 

For a deeper look at the data behind these drags and more benchmarks you can use in your own planning, download the full 2026 commerce readiness index report. 

The post Three hidden drags you can fix (and one you can’t) appeared first on Rithum.

At Rithum LIVE—our flagship event that brought brands, retailers, and partners together in New York and London—the pattern was clear: shoppers are changing how they find products, clean data is more important than ever, AI is everywhere (though not being optimized), and retail media is being redefined. As CEO Lou Keyes put it, “The battleground is shifting from persuasion to precision . . . You can no longer convince consumers to buy with just more ads or louder ads.”  

Here are five of our favorite big moments from the sessions, focused on how leaders are fixing data quality, proving AI ROI, preparing for agentic shopping, adjusting retail media, and turning dashboards into decisions. If you’re curious about what’s coming for commerce in 2026, start here—then dive into the full talks on Rithum LIVE On-Demand.  

Data readiness: close the confidence–accuracy gap 

Suzin Wold Chief Marketing Officer at Rithum, ran a reality check in her Rithum LIVE keynote: “80% of you know the data you are using is bad, while 100% feel confident in your performance reports. You have really super high confidence, but you have really, really low accuracy,” Suzin said. Her rule is straightforward: “It is not about acting faster. It is about reacting smarter.” This takeaway, and the rest of the data analysis from her keynote, was built on The 2026 commerce readiness index, which reports on 200 retail and brand executives’ responses to industry-landscape questions. It points to heavy manual effort and inconsistent data as the root of slow, error-prone reactions. Bad data doesn’t just slow work; it produces the wrong results like mispriced items, wasted ad spend, and higher returns. 

Watch Suzin’s full session for more industry trends from the readiness index, which is built on a survey of brands and retailers.  

AI and ROI: clean inputs, measurable outcomes 

95% of AI projects fail to deliver ROI and only 5% move beyond pilots, Ali Irturk, Chief Technology Officer at Rithum, said. “If you have bad data you’re going to make bad decisions a lot faster.” 

Here’s what it looks like for retailers and brands when the inputs are right. “We found that 200 SKUs were driving 15.5% of the returns,” said Seb Spiegler, Head of AI at Rithum, in discussing one Rithum client use case. Updating titles, materials, and size charts fixed the problem. “Returns went down, margins went up,” Seb said. 

Rithum’s Magic Mapper, powered by RithumIQ, cut categorization and attribute mapping from days to minutes in 100+ channels and in more than 30 languages, Seb said. Because publishing, inventory, and advertising run on the same source of truth in Rithum, those changes travel quickly to the places that matter. “Models matter, but outcomes matter even more,” Seb said.

Watch Ali and Seb’s session where they show how they spotted the 200 SKUs, which edits they prioritized first, and where the gains surfaced (returns, margin, rank).  

Agentic shopping: make claims machine-readable 

Discovery is changing as consumer behavior changes. “In the past, [discovery] was user initiated. Now it’s going to be AI agent initiated,” Arun Kumar Global Head of AI at Accenture Song, said. Agentic AI doesn’t react to slogans or ad spend. “Your brand actually is the moat and agents see it as data and rules.” They verify off the website, too: “If you are best in something, I want proof that you are best in something. I’m going to go to Reddit. I’m going to read your reviews.” 

Arun suggests that the biggest thing to do now is to encode the facts—materials, price, availability by location, shipping cutoffs, and returns policy—in your website so assistants can confirm them. For the rest of his best practices and examples on getting ready for agentic shopping, watch his session here.  

Retail media: let spend listen to inventory and returns 

Media works harder when it runs on commerce truth. “We decided to move back and double down on our own platform,” Louis Camassa, Director of Product for the Brands Platform at Rithum, said. “We’re using that data to show where clients could spend and get the best ROI.” 

Shelf control completes the loop. “See where you rank, your brand’s share of shelf or share of voice, then make strategic decisions from an advertising and organic perspective,” Meghan Barden, Director of Global Retail Media at Rithum, said. When retail media and commerce data live in one platform, bids and budgets can adjust to stock, margin, and delivery promise in real time, steering spend toward products that can ship and convert. Keeping media and commerce signals together inside Rithum helps avoid wasting spend on items that are out of stock or likely to bounce back.

Watch Louis and Meghan’s session for examples of routing budgets to in-stock, high-margin SKUs. 

Decision intelligence: define the choice, then act 

“Companies don’t have insight problems. They have decision problems,” Daniel Hulme, Chief AI Officer at WPP, said. Pick the wrong formulation and the option set stretches “longer than the age of the universe.” Pick well and a machine solves it in milliseconds. 

The talk reframed AI, saying most companies don’t suffer from a lack of insight—they struggle to turn insight into consistent, high-quality decisions. According to David, our “fast brain” loves intuition. But the real world runs on hard trade-offs where the wrong algorithm can turn a millisecond task into an “age-of-the-universe” problem. He drew a sharp line between automation and AI, where automation just repeats yesterday’s choice. AI, properly defined, is goal-directed and adaptive—it makes a call, learns from the outcome, and updates the next call. 

“Large language models are really good at knowing things about the world,” says David. “They are not good at making predictions. They’re definitely not good at making complex predictions.” The business gains show up when you pair them with explainable machine learning and optimization for things like allocations, pricing, routing, and channel mix.  

The takeaway was refreshingly human: start by naming the decision you need to get right, be explicit about the objective and constraints, and then choose the method. If AI learns over time and can explain why it works, you’re building intelligence—not just another dashboard. For the full talk, watch Daniel Hulme’s keynote here. 

Watch these sessions and more on Rithum LIVE On-Demand here. 

Quotes have been lightly edited for clarity. 

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At Rithum LIVE, one of the most engaging discussions came from the audience Q&A with Accenture Song’s Caitlyn Ford and Brittny Cantor. As brands and retailers wrap their heads around Generative Engine Optimization (GEO), this unscripted session got into the harder questions about AI bias, agent monetization, liability, and what commerce looks like when the product page isn’t the final destination. 

Here are some of the highlights. 

Q: If AI agents start recommending products, how do we know they won’t be biased by paid placement? Can brands “bribe” the agent? 

Brittny: That’s the million-dollar question. OpenAI is already standing up monetization capabilities. We expect some form of sponsored placements to roll out this holiday season, likely in beta. The big unknown is how they’ll balance monetization with trust. If sponsorship tilts results too far, it could undermine the whole experience. 

Caitlyn: It’s like the early days of retail media. Brands need to prepare for both tracks: getting their product information right for organic visibility, and being ready to test sponsored placements as those capabilities come online. 

Q: Who’s responsible when an AI gets it wrong, like recommending the wrong product or misrepresenting information? 

Brittny: It’s still a gray area. Right now, no one’s eager to raise their hand and claim full responsibility. It’s a bit of the Spider-Man meme: brands pointing to marketplaces, marketplaces pointing to LLM providers. What we need is a set of shared guardrails that define ownership: who owns the inputs, who governs the outputs, and who steps in when something breaks. 

Caitlyn: Until that’s clear, the best risk management is having a strong human-in-the-loop process. That means validating your content before it goes live, especially as more content is generated or summarized at scale. 

Q: How close are we to “buy in agent” experiences where shoppers don’t even visit your site before purchasing? 

Brittny: Closer than most people realize. Perplexity is already experimenting with it. Shopify is forming tight integrations with ChatGPT. Once these flows are normalized, conversion may happen entirely inside the agent. But that raises new challenges for brands: inventory accuracy, pricing consistency, fulfillment handoff. One bad checkout experience—say, ordering one item and receiving 15—could turn off a shopper for good. 

Caitlyn: Expect early adoption with lower-cost, low-stakes items. As comfort builds and trust deepens, agent-led purchasing will grow. The infrastructure just needs to catch up. 

Q: In a multi-channel world, should brands still invest in their own .com or focus on winning inside agents? 

Brittny: Your brand site still matters, just not the way it used to. No one cares about animation or hover states anymore. They care about whether your PDP content can be parsed by an agent. So yes, invest in brand.com. But optimize it for machine readability, not just visual design. 

Q: How should brands measure ROI on GEO? 

Brittny: This is the question we get all the time. One simple model we use is: if shoppers are 4 to 7 times more likely to convert after interacting with generative content, and your AOV stays constant, you can estimate the lift. But that’s just the starting point. 

Caitlyn: Treat GEO like you’d treat a media campaign. Set a flight window. Isolate your tactics. Measure the lift in-store or online. And remember: not all conversions are immediate. GEO can drive long-tail impact—people don’t always click, but they remember. 

Q: What does agentic commerce look like in the long run? 

Brittny: Picture your own Jarvis: an always-on assistant that knows your preferences, limits, timing, and priorities. That’s where this is heading: personal agents transacting across the internet on your behalf. We’re not there yet, but the foundation is already being built. 

Final thought: Don’t panic. Focus.  

As Caitlyn put it in her closing remarks: focus matters most. Whether you’re cleaning data, refining PDP content, or choosing a tech partner, the best approach to agentic commerce is to double down on clarity, credibility, and control—because that’s what machines are trained to trust. 

Watch the Rithum LIVE sessions on demand here.

The post AI agents, monetization, and the future of GEO: A Q&A with Accenture Song  appeared first on Rithum.

October’s Amazon Big Deal Days, flanked by rival events at Target and Walmart, confirms that for today’s shoppers, extreme sales operate as planning windows more than purchase windows. Billions still move through carts, but before they click purchase, consumers are comparing prices, checking delivery windows, and weighing return policies—and with the help of agentic AI, they can do it all without even visiting the retailer’s website. 

Most of all, they seem to be waiting. Many of the highest GMV days took place after the sales window. What does that mean for Black Friday, and the rest of the holiday season?

What we learned from October 2025 

Walmart opened its October event to everyone (with a head start for Walmart+), and Target deepened member-led offers. This broad access framed the holiday season’s opening moves.  Amazon buyers focused on everyday essentials with 58% saying they were satisfied with the deals, 23% saying they already purchased gifts, and 84% plan to buy holiday items on Amazon in the next three months. October sales, in other words, were the first round of the peak holiday shopping season, with shoppers starting early, but planning on more shopping to do. This is another sign that shoppers aren’t responding to urgency-driven hype the way they used to. They’re shopping on their own terms, watching closely, waiting longer, and buying based on intent, not impulse. 

Shoppers plan, retailers widen the window, and mobile and agentic AI set the terms. Here are some of the biggest patterns we saw in October’s sales push:. 

• Demand is real, but disciplined. Forecasts call for a sizable holiday spend, driven by mobile and a fast increase in AI-assisted shopping traffic, up 520% year over year. Shoppers are doing more research in less time. 

• Access beats exclusivity. Walmart’s “no membership required” positioning and Target’s member perks ran in parallel with Amazon’s event, giving shoppers many options  rather than anchoring them to one singular price drop  

• October is a staging ground. Reuters and Adobe flag October’s Amazon event as a multi-billion-dollar catalyst that pulls forward  holiday spend without exhausting demands. The shopping that started with October sales is expected to stretch longer, not be done earlier. 

• Category mix matters. Numerator’s early read shows baskets heavy on household essentials alongside selective gifting. Consumers are being mindful about what they spend. 

Shoppers are comparing across channels, pacing their purchases, and prioritizing convenience and trust. They check prices, delivery windows, and return policies before they buy. With Rithum, that behavior works in your favor: pricing, promises, and product details stay consistent across every touchpoint. Your returns policy doesn’t change from one channel to the next. And when the market shifts, you shift with it—because Rithum connects marketplace data, retail media, and fulfillment in real time. One update moves across platforms, so you can reallocate spend or inventory seamlessly.

Holiday 2025 retail strategy: next steps

Adobe expects U.S. online holiday spend to reach $253.4B, with mobile driving a majority share (56.1%) and buy now, pay later (BNPL) adding another $20.2B—evidence that convenience and flexibility, not just markdowns, will shape conversion. 

October sales set the tone for the season. Now is the time to stay consistent and make sure you’re keeping the same price, promise, and product facts everywhere. Push what is already selling and remove the friction that shoppers flagged. Start here: 

• Plan promotions around what shoppers actually want at different times, instead of relying on the same event-driven discounts.  

• Adjust product mixes and creative in real time to highlight what’s trending or to support categories that need a lift.  

• Connect messaging and offers across marketplaces, retail media, and owned channels so shoppers get a consistent experience wherever they buy. (Most teams are already shifting where they show up: 91% of retail leaders and 84% of brands changed their marketing channel mix in the last year.) 

• Use first-party data to personalize offers and reduce dependence on paid ads.  

• Measure success by long-term value don’t focus on short-term sales spikes. Repeat customers, lifetime spend, and loyalty are the your better long-term value drivers..  

• Partner with marketplaces and vendors to build limited-time experiences that create excitement and reach new audiences.  

• Re-engage peak-season buyers after the event with thoughtful follow-ups that turn one-time shoppers into loyal customers.  

• Put delivery dates and a clean returns promise on the page. Return policies are a decision filter at scale. 41% say the returns policy influences where they buy — so make the promise visible and easy to use. 

October shows that the 2025 shopper is steady, selective, and ready to buy when the facts are clear. Keep the same price, promise, and product story everywhere, make the mobile experience flawless, and turn returns into trust. To see how Rithum connects your marketplaces, media, and fulfillment so you can act on this now, contact Rithum to learn more. 

The post How October’s big sales set the stage for holiday 2025  appeared first on Rithum.

Back-to-school (BTS) shoppers started earlier, spent more cautiously, and favored targeted value over blanket discounts. Back-to-school shopping was a stress test for holiday readiness. Here’s what the data tells us, and how to respond. 

Back-to-school sales: what changed and why it matters 

BTS shopping kicked off early this year, with 67% of K-12 and college shoppers already starting shopping by early July—the biggest early start since NRF began tracking the back to school season. Tariff-related price increases were a big driver, with half saying they moved faster into buy mode to avoid those hits.  

Families planned to spend $858 on average for K-12 (down from 2024), but total K-12 spend prediction ticked up to $39.4B, signaling more shopping despite tighter wallets. This might be because there’s not a ton of choice: if your kid needs new shoes for school, it’s not a discretionary purchase (vs. the holiday season, when gifts are not thought of as the same level of necessity). Online remains the top choice for 55% of consumers, with discount stores getting more traction as shoppers looked for value over loyalty.  

Households are distinguishing “need” vs. “want,” more than ever, expecting uneven price increases as tariffs and cost-of-living costs roll through the commerce world. More deal hunting, more shop-hopping, and more comparison across big events is the norm.  

These patterns—early research, cart building, and channel switching—mirror what we saw over the big summer sales events, and what we told you to prepare beforehand. 

That discretion has also affected buy-now-pay-later (BNPL) usage, which is rising into late summer. Consumers spent $7.8 billion via BNPL in July, up 16.6% yoy, a clear signal for Q4 budgets, according to Adobe Business. 

Key differences in 2025 back-to-school shopping

• Earlier start and longer purchase window. Families chipped away at lists during July events like Prime Day and Walmart Deals, then paused to wait for district lists and late-season apparel decisions, according to NRF.

• Targeted value offers beat blanket discounts. Shoppers respond to relevance (bundles, student perks, durability claims) as much as raw price. Deep, across-the-board cuts aren’t necessary to win the cart.

• Cross-channel comparison is the default. Pricing parity and clean content matter more than ever to prevent abandonment.

What we’re seeing in-market  

Several leading retailers we work with rode out BTS seasonality with no major promotions, and still saw strong demand. For most companies we’re working with who rely on BTS sales, they’ve had little paid push but are still finding that the calendar itself fueled conversion. 

In August, the following categories surged (and cooled): 

• Apparel and footwear stayed resilient as “needs,” helped by off-price and pointed promos, according to NRF. 

• Tech and audio sold well from July through college move-in (laptops, headphones, small appliances), according to Adobe. 

• Backpacks, lunch boxes, and calculators sold fast during July sales and when schools posted supply lists. 

• Shoppers chose store brands and value packs, but mid-season sales slowed and retailers sold fewer items, according to Circana. 

What will this mean for holiday season? 

Everything we’re seeing—value scrutiny, channel switching, event-day triangulation—will define peak shopping season. Here’s what you can expect:  

• Two conversion waves: early research, late-season purchase. Summer event shoppers researched early and converted when the price felt right; BTS saw the same, so expect more coming into the holidays. Plan two waves: early season list building and end season urgency. 

• Tariff news may shift purchase timing. If price-rise rumors accelerate, shoppers pay attention and try to get ahead. If it cools, more will likely look for promotions instead of focus on that anxiety of getting ahead. With the White House’s 90-day extension of the China tariff truce into mid-November 2025, shoppers may be more inclined to wait for big promos. But if the Office of the U.S. Trade Representative’s product exclusions are not extended beyond Aug. 31, some tariff-sensitive purchases could be pulled forward into September, according to KPMG. 

• More cart building, abandonment, and reactivation. Shoppers build their “list” within your cart, they look around for better deals. Track why shoppers are waiting (price watching, incomplete lists, budget staggering) and answer with saved carts, wishlist nudges, and price-drop alerts.  

Want more? Check out our primer on peak season preparedness.  

Meghan Barden is Director, Global Retail Media, Rithum.

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Amazon Prime Day 2025 is on track to break records, just as it did in 2024 where U.S. shoppers spent $14.2 billion online during the 48-hour sales event.¹ This year, Prime Day will span over four days in July, offering some unprecedented opportunities for sellers.

July may seem far off, but by planning early, you can better keep up with consumer demand and increase conversions.

Here are the five things to do right now to get ready for the biggest Prime Day event in history.

1. Lock down inventory early and always leave room for the unexpected.

Don’t be stuck scrambling to meet Amazon’s FBA deadline. Instead, forecast based on past Prime Day and holiday sales data, and work on adjusting SKUs and preparing backup plans.

Keep these milestones in mind:

• Submit Best Deals and Lightning Deals by May 23.
• Keep an eye on Price Discounts. The submission window opens May 5 and closes 6 hours before the event starts in July (check back here for the official sales event dates once released).
• Make sure all your FBA inventory arrives by June 9 for minimal shipment splits or by June 18 for Amazon-optimized splits.
• Diversify fulfillment to reduce delivery times and increase Buy Box eligibility.
• Use Rithum to monitor inventory during the sales event across all channels.

2. Price to win the Buy Box, without killing your margins.

The Buy Box is essential during Prime Day, when buyers are moving fast and clicking even faster. If you don’t win the Buy Box, your listing won’t get the visibility it deserves. It’s important to understand pricing floors while using automation to move quickly when the market shifts.

Focus on preparing by:

• Reviewing last year’s deal performance to find pricing sweet spots.
• Using repricer tools (like Rithum’s) that adapt to competitor moves and inventory levels.
• Set up Lightning Deals and Coupons with >5% discounts for Prime members. Thereby ensuring access to the nearly 189 million U.S. Amazon customers that had a Prime membership as of September 2024, up 9% from the year before.²
• Ensuring price parity across Amazon, Walmart and other marketplaces to avoid suppression. Features like Rithum’s repricer automation, performance monitoring, stock alerts, order routing and management, shipping integration, and returns management help sellers avoid errors on marketplace listings.

3. Don’t wait to launch retail media ads.

Successful sellers launch ad campaigns weeks in advance and use that time to optimize. Now’s the time to spread your budget wisely across different ad types and audiences.

Focus on:

• Running Sponsored Products, Brands, Displays, and Video campaigns.
• Segmenting campaigns into branded, non-branded, and competitor targeting.
• Automating budget increases during Prime Day traffic spikes.
• Using Rithum’s real-time ad performance tools to shift spend where it matters most.

4. Craft pages that stop the scroll and convert.

Your product page content is crucial to your conversion rate. A shopper is much less likely to click “Buy Now” on a weak product page. But investing in content that converts is a long-game that needs to happen well before the big sales event.

Focus on:

• Optimizing images, titles, bullets, and descriptions across your catalog.
• Creating A+ content boosts conversion by up to 20%, according to Amazon.³
• Scheduling storefront updates to showcase Prime Day deals and promotions.
• Using Amazon’s A/B testing tool (Manage Your Experiments) to find what works best.⁴

5. Don’t just sell on Amazon; drive traffic to it.

Smart sellers proactively reach out to shoppers, rather than waiting for shoppers to find them. Use external channels to fuel Amazon sales and collect referral bonuses in the process.

Focus on:

• Running social, search, and email campaigns with Amazon Attribution tags.
• Earning brand referral bonuses to offset referral fees (up to 10% back).
• Using Rithum to track and optimize multichannel performance and profitability.

Bonus tip: Stay on top of the right metrics in real time.

The sellers that sell well are those that keep their eyes on the dashboard. That way, you’re able to quickly see what’s working versus what’s not.

Focus on:

• Watching seller health metrics like on-time shipping and cancelation rates.
• Tracking Buy Box percentage, ad ROAS, and low-stock alerts hourly during Prime Day.
• Using Rithum’s centralized dashboard and custom reports to adjust on the fly.

Want to learn how Rithum can help you be prepared before, during, and after Amazon Prime Day in July? Schedule a demo today to learn more.

Sources
1. https://blog.adobe.com/en/publish/2024/07/18/adobe-analytics-prime-day-drove-billion-online-us-retailers-growing-yoy
2. https://cirpamazon.substack.com/p/amazon-prime-membership-is-a-big
3. https://sell.amazon.com/blog/prime-day-tips
4. https://sell.amazon.com/blog/prime-day-tips

The post Sellers Who Win Amazon Prime Day 2025 Will Do These 5 Things appeared first on Rithum.

Preparing to step onto the floor of Shoptalk 2025 this week with my comfy shoes on and hydration packs ready, one thing is clear: e-commerce is undergoing a transformation unlike anything the industry has seen before.  

In reviewing the Shoptalk agenda, and in the conversations the Rithum team is having as we set up meetings, I’m seeing three major themes at the top of everyone’s mind:   

1. The growing role of AI/genAI: how to capitalize on it without losing track of value
2. The rise of retail media networks and what it means for brands working with major retailer
3. Tariffs and supply chain concerns (oof)

Together, these forces are redefining how retailers and brands operate, innovate, and stay resilient in an increasingly unpredictable global market. Experts across retailers and brands of all sizes and shapes are looking for new ways to redesign strategies and mitigate risks before they impact their bottom line (while working relentlessly to truly understand their profit margins)  

Shoptalk couldn’t be coming at a better time.  

Here are my top 3 predictions for what everyone will be talking about the most across the floor this week. 

Prediction 1: AI Has its Breakout Moment  

AI has been a retail buzzword for years, and the emergence of genAI has turned that buzz into a full-on roar. AI/genAI is one of the most agenda-heavy innovations at Shoptalk 2025. And it’s no wonder, with brands leveraging it to drive personalization, optimize logistics, and improve customer engagement. This year, I’m particularly excited to hear how industry leaders are using AI to: 

• Supercharge Personalization: Retailers are using AI-driven recommendation engines to suggest products based on browsing history, purchase patterns, and even real-time behavior. AI chatbots and virtual shopping assistants are enhancing online and in-store experiences by providing instant support and tailored product suggestions. With genAI, chatbots and virtual assistants are leveling up, delivering more human-like customer service at scale. 
• Optimize Supply Chains: Predictive analytics help brands and retailers forecast demand, reducing overstock and understock issues. AI-powered automation in warehouses and logistics is improving efficiency and reducing fulfillment times. 
• Enhance Visual Search & Augmented Reality (AR): Shoppers can now snap a photo and instantly find similar products (changing the competitive landscape across the real-world and e-commerce). Brands are increasingly rolling out AI-driven AR tools for virtual try-ons, and according to Macy’s and Shopify, this tool has had a drastic impact on return rates (something I also expect to hear a lot about at Shoptalk). 

What to Watch for at Shoptalk:

Google, Amazon, Shopify, and others will be showcasing the latest AI tools that help brands increase efficiency, cut costs, and enhance customer experiences. AI is the new baseline for retail success and Shoptalk is going to be a showcase for this technology in all its forms. 

Prediction 2: Retail Media Networks Make Waves 

There’s been an explosive growth of retail media networks(RMNs) and retailers are transforming their digital platforms into powerful advertising hubs. As third-party cookies phase out and brands seek new ways to reach shoppers, retailers are leveraging their first-party data to create highly targeted ad opportunities within their own ecosystems. Major players like Walmart, Amazon, Target, and Kroger are expanding their retail media networks and enabling brands to place sponsored product ads, display ads, and even video content directly within their shopping platforms. This shift is reshaping the digital marketing landscape, with AI-driven personalization enabling real-time ad placement, dynamic pricing strategies, and seamless integration across e-commerce and in-store experiences.  

What to Watch for at Shoptalk:

At Shoptalk, I expect to hear industry leaders emphasizing how retail media is becoming a multi-billion-dollar revenue stream, offering brands a direct line to high-intent shoppers while giving retailers new ways to drive profitability beyond traditional sales. If you haven’t yet explored this arena, Shoptalk is a great place to explore the pros and cons.

Prediction 3: Tariffs at a Tipping Point  

Retailers have spent years optimizing their supply chains, especially coming out of COVID’s chaos, but sudden policy shifts are throwing a wrench on even the most carefully calibrated operations. This year, brands are facing: 

• A 25% tariff on select imports from Mexico and Canada, with some exceptions. This could force many to rethink North American sourcing strategies.
• A 10% tariff on goods from China, impacting pricing and sourcing strategies and making cost optimization more critical than ever.

I expect we’ll get some deep discussions in the panels and roundtables about how retailers can maintain profitability and customer satisfaction despite rising costs. And I know from my discussions that many are already putting new strategies into play that will help them stay competitive while navigating higher costs and supply chain disruptions, including:  

• Supply Chain Diversification: Many brands are talking about shifting manufacturing to Southeast Asia, India, and Latin America to reduce dependency on China. Some are even exploring near-shoring and re-shoring to bring production closer to home and minimize risk. 
• Real-Time Inventory and Pricing Adjustments: Machine learning and AI-driven demand forecasting and dynamic pricing tools are emerging as the chosen solutions to manage fluctuating costs (and ensure those fluctuations don’t derail margins). 
• Trade Policy Awareness: Retailers are working closely with trade experts (and even policy analysts) to stay ahead of regulatory changes and avoid unnecessary supply chain disruptions. 

What to Watch for at Shoptalk:

I expect that speakers will emphasize that in this era of global trade instability, agility is the key to survival—and that extends beyond supply chains into digital commerce strategies as well. 

What are your thoughts on how AI/genAI, tariffs, and retail media networks will shape e-commerce, brands, and retailers’ strategies in the coming years? Stop by booth #1536 to let me know this week! See you there!

The post 3 Predictions for Shoptalk 2025: How Tariffs, AI, & Retail Media Networks Are Transforming the E-commerce Landscape appeared first on Rithum.