Retail Digital Marketing in 2026: Types, Strategies, Costs and Examples

Retail digital marketing is how retailers use online channels—search, social, email, retail media, connected TV and in-store screens—to bring shoppers into a store or a cart and keep them coming back. It covers the paid media that creates demand, the owned experiences that convert it, and the measurement that proves which of the two did the work.

TL;DR:

• What changed in 2026. AI agents can now complete a purchase without the shopper ever reaching your site. An open checkout standard launched in January, and shoppers arriving from AI assistants convert better than shoppers arriving from anywhere else.
• Where the money is going. US retail media reaches $72.97 billion in 2026, up 20.3% year over year. Commerce media now accounts for 21.5% of all US digital ad revenue.
• What most retailers get wrong. Optimizing channel by channel. The budget goes where the dashboard looks best rather than where the sale actually came from.

Retail digital marketing in 2026 works as a system. Retailers that connect data, creative, media and measurement into one operating model outpace those running each channel as its own business with its own scoreboard.

This guide covers what the term means, the four types of retail marketing, ten strategies you can run with today's tools, what a realistic budget looks like, and the KPIs worth reporting to a CFO.

💡 Dive deeper into AI in digital marketing in our primer: How artificial intelligence is transforming strategies in 2026.

What is retail digital marketing?

Retail digital marketing is the coordinated use of data, content, media and measurement to attract shoppers, convert them, and keep them coming back. It works as a strategy tied to clear outcomes rather than a set of channels run in parallel.

At a practical level, that system connects:

• Data and analytics to understand audiences and performance
• Owned experiences (site, app, store tech) that convert and collect consented data
• Content and messaging that answer real buying intents
• Paid media (search, social, retail media, CTV) that creates demand and proves impact
• Measurement and experimentation that guide what to scale next

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The distinction that matters in practice is between channels that capture demand and channels that create it. Search and retail media harvest intent that already exists. Connected TV, social and creator work build the intent that search later collects. A program weighted entirely toward capture looks efficient on a last-click report and slowly runs out of people to convert.

💡 For the technology stack that enables this system—CDP, CRM, ad platforms, attribution and more—see MarTech: Complete Guide to Marketing Technology in 2026.

What is the retail marketing mix? The 4 Ps and the 7 Ps

The retail marketing mix is the set of controllable levers a retailer uses to create demand and convert it. The classic version has four:

• Product. Assortment, range architecture, private label, bundling. In digital terms this is also your product data: titles, attributes, imagery and structured markup.
• Price. List price, promotional cadence, markdown strategy, financing options. Price is now dynamic and visible across every comparison surface, including AI assistants.
• Place. Where the transaction happens—stores, your site and app, marketplaces, social commerce, and increasingly agent-mediated checkout.
• Promotion. Paid, owned and earned media that carries the offer to the shopper.

Services marketing adds three more, and retailers benefit from all of them because a store is a service business as much as a product one:

• People. Store associates, service teams and the clienteling tools that make them effective sellers.
• Process. Fulfillment, returns, replenishment. BOPIS, curbside and ship-from-store are process decisions with marketing consequences.
• Physical evidence. Store design, packaging, visual merchandising, and the digital equivalents—page speed, review density, delivery promises.

The 7 Ps are useful as a completeness check rather than a planning framework. Run through them before a season and the gaps tend to be in people and process, because those sit outside the marketing team's direct control and get assumed rather than verified.

Types of retail digital marketing

Four arenas, and most retailers operate in at least three at once.

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Offline and in-store retail marketing

The physical store still carries the majority of retail sales, and the marketing that happens inside it is the oldest discipline in the category. Window displays, visual merchandising, planogram decisions, pop-ups, in-store events, sampling and local print all shape what a shopper picks up.

The digital adjacency is local search. Local inventory ads, store-level landing pages, Google Business Profile hygiene and accurate opening hours drive footfall from queries with immediate purchase intent. A shopper searching for a product with "near me" attached is closer to a transaction than almost any other audience you can buy.

In-store retail media sits at the seam between the two. It remains small—in-store accounted for 3.3% of non-Amazon retail media spend in 2025—and adoption has run slower than forecast because execution is hard rather than because demand is absent. The structural argument for building it anyway is concentration: no Amazon-equivalent gatekeeper exists in physical retail, so traditional retailers can win spend in the aisle that online auction dynamics deny them.

Online retail marketing

This covers the digital storefronts you own or rent: your website and app, marketplaces (Amazon, Walmart, eBay), and social commerce surfaces.

The work is get found, convert, and retain. Practically, that means fast product pages, relevant on-site search, trusted reviews, smooth checkout, and remarketing that respects consent.

Treat marketplaces as performance channels with clear targets—share of voice, ROAS, new-to-brand—and use your own site to build first-party data you can activate across paid media and CRM.

Omnichannel retail marketing

Omnichannel connects discovery, purchase and service across web, app and stores so a shopper can start anywhere and finish anywhere.

Two signals show why. Shoppers who used four or more channels spent 9% more in store than single-channel shoppers in a 46,000-shopper study conducted for Harvard Business Review in 2017, and 85% of BOPIS customers made an extra purchase when picking up.

Plan around one customer profile, consistent offers and shared inventory so tactics like BOPIS, curbside, ship-from-store and clienteling compound rather than compete.

⚡ One identity, one offer engine, one inventory view. Everything else is orchestration.

Phygital and in-store digital experiences

Phygital brings digital utility into the aisle: guided selling on associate devices, AR try-ons, interactive signage, and store apps that recognize loyalty members.

In Deloitte's 2025 US retail outlook, 47% of surveyed shoppers said digital screens positively affect their in-store grocery shopping. Use these touchpoints to improve the experience and to capture consented data that improves the next interaction online or in store.

Agentic commerce and AI shopping: what changed in 2026

The largest change to retail discovery since mobile arrived in January 2026. Most retail marketing plans were written before it.

An open checkout standard now exists

Google announced the Universal Commerce Protocol at NRF on 11 January 2026. It was co-developed with Shopify alongside Etsy, Wayfair, Target and Walmart, and endorsed at launch by more than twenty companies including Visa, Mastercard, Stripe, Adyen, American Express, Best Buy, The Home Depot and Zalando. The specification is open source under Apache 2.0.

UCP defines how an AI agent discovers products, builds a cart, completes a purchase and handles the aftermath. Checkout went live in Google AI Mode and the Gemini app at launch. Cart and product discovery capabilities followed in March, simplified Merchant Center onboarding in April, and at Google Marketing Live in May the protocol gained Universal Cart across retailers, buy-now-pay-later inside Google Pay, YouTube Shopping checkout, and availability in Canada, Australia and the UK.

The competing standard is the Agentic Commerce Protocol, built by OpenAI with Stripe. Several companies back both.

The first attempt at in-chat checkout failed

OpenAI launched Instant Checkout in September 2025 and retired it in March 2026, roughly five months later. Around a dozen Shopify merchants ever went live.

The retreat reads as an implementation problem more than a demand problem. At launch the feature handled single-item purchases from US Etsy sellers only, with no multi-item carts, no promotional codes and no state sales tax remittance. Purchases now route out to merchant apps and storefronts instead. Agentic checkout continues elsewhere, through UCP and Universal Cart.

AI-referred shoppers are your best traffic, and there aren't many of them

Both halves of that sentence are true, and most coverage picks one.

Adobe Analytics tracks more than a trillion visits to US retail sites. AI-referral traffic grew 693% year over year across the 2025 holiday season, 393% across Q1 2026, 138% in May and 62% in July 2026. Growth is decelerating quickly as the base grows. Against October 2024, when Adobe began tracking, the increase is 1,219%.

Quality runs in the other direction. In March 2026, AI-referred visitors converted 42% better than non-AI traffic, a reversal from twelve months earlier when the same traffic converted 38% worse. By May they were spending 53% longer on site and viewing 23% more pages per visit.

Shopify's platform data points the same way and shows the same slowdown. On its Q2 2026 earnings call the company said AI-driven traffic and orders each tripled year over year, with new-buyer orders from AI channels arriving at nearly twice the rate of other channels and half of AI-referred sessions landing directly on a product page. Shopify had reported Q1 growth near 13x, so tripling reads as deceleration rather than acceleration. These figures come from the earnings call rather than the published results, and absolute volumes were not disclosed.

The counterweight comes from Contentsquare, which measured AI referrals at 0.2% of total traffic in Q4 2025 across 99 billion sessions and 6,500 sites. A channel converting 42% better at 0.2% of volume is worth preparing for rather than reorganizing around.

Google's share of US search advertising falls below half

EMARKETER forecasts Google will earn 48.5% of US search ad spending in 2026, the first time below half in more than twenty years, with Amazon taking the largest share of what it gives up. Note the measure: this is search advertising revenue, not search usage, where Google still holds roughly 85% of the US market. Demand capture is fragmenting across more sellers, and the budget line called "search" now has to cover several of them.

What to do about it

The practical constraint is product data. Adobe's AI Content Visibility Checker scores how much of a page a large language model can actually read, and its retail benchmark found product pages score worse than most other page types on retail sites. An agent that cannot parse your price, availability, variants and return policy will recommend a competitor that it can parse.

Structured product markup, clean feeds, machine-readable specifications and explicit availability data are now demand-capture infrastructure. Strategy 9 below covers the work.

The retail market in 2026

The numbers that should anchor a plan.

1. Ecommerce keeps taking share. US retail ecommerce sales reached $340.2 billion in Q2 2026, 17.1% of total US retail sales on a seasonally adjusted basis, up from 16.3% a year earlier. One caution when comparing against older coverage: the Q2 2025 base was later revised upward to $303.3 billion, so year-over-year growth of 12.2% is calculated against the revised figure.
2. Attention has moved to streaming. Streaming accounted for 48.5% of US TV usage in June 2026, against 19.8% for broadcast and 19.5% for cable. Read that figure with one caveat: Nielsen is recalibrating The Gauge onto new universe estimates with the start of the new TV season, and analysts expect streaming's share to read lower on the new basis.
3. Retail media is now infrastructure. Global retail media investment reaches $200.4 billion in 2026 and rises 11.5% to $223.4 billion in 2027, by which point it accounts for 15.2% of all advertising investment worldwide. In the US the channel reaches $72.97 billion in 2026, up 20.3%.
4. Commerce media is now a fifth of digital ad revenue. US commerce media revenue grew 18.0% to $63.4 billion in 2025, or 21.5% of all digital ad revenue, within a total market of $294.6 billion. In the same report, social overtook search for the first time—$117.7 billion against $114.2 billion—and search growth slowed from 15.9% to 11%.
5. Payment flexibility shapes the basket. Buy-now-pay-later contributed $20 billion in online spend across the 2025 holiday season, up 9.8% year over year, with 82.2% of those purchases made on a smartphone.

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Key elements of retail digital marketing

Five building blocks, each wired to the same data and measurement so they reinforce one another.

• Data, analytics and AI. Unify consented first-party data from site, app, store and loyalty, then segment, predict and automate on top of it. Adoption is broad but shallow: 88% of organizations report regular AI use in at least one business function, yet only about a third have begun scaling it across the enterprise, 7% describe it as fully scaled, and 39% can attribute any enterprise-level EBIT impact to it. Priorities: a clean data layer, privacy-safe audience building, propensity and churn models, incrementality testing, and AI whose decisions can be explained to a merchandiser.
• Website and ecommerce optimization. Your site and app are the highest-control sales channels. About 70% of online shopping carts are abandoned, per Baymard Institute's ongoing checkout usability research (last updated September 2025). Fix fee transparency, guest checkout, payment reliability and mobile page speed before testing anything clever.
• Content and SEO. Answer real buying intents—comparisons, sizing, how-tos, care guides—and structure pages so both search engines and language models can parse them. Measure assisted conversions and email capture, not rankings alone.
• Email and CRM. Lifecycle messaging (welcome, browse and cart recovery, replenishment, win-back) coordinated with SMS and push. Report revenue per recipient and incremental lift rather than opens and clicks.
• Paid media. Search and retail media for capture, social and creators for discovery, CTV for scalable reach against audiences you can also reach elsewhere. Tie every channel back to one measurement plan so creative, audiences and budgets get reused rather than rebuilt.

10 retail digital marketing strategies

Start with evidence, then scale what proves incremental.

⚡ Any retail digital marketing strategy is a hypothesis. Test, measure, adjust, repeat.

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1. Data-driven optimization and predictive analytics

Great retail marketing runs on evidence rather than hunches. Optimization means proving what causes lift, then reallocating budget and creative toward the winners. Predictive analytics adds foresight: models estimate the likelihood of purchase, churn or response so you can act before the outcome.

Playbook:

• Define truth sets (holdouts, geo splits) to measure incremental impact.
• Use model outputs as signals; validate with controlled tests before scaling.
• Centralize insights in one dashboard tied to the same identities across media, site and sales.

2. AI-powered optimization and automation

AI is best at high-volume, high-speed decisions—budget pacing, bid moves, audience expansion, creative versioning—while humans set strategy and constraints. The payoff is responsiveness: campaigns adapt to new signals in minutes instead of days.

💡 Read more in The future is now: how AI Digital embraces AI technologies to change the programmatic game.

Playbook:

• Set guardrails (target CPA and ROAS bands, frequency caps, exclusions) and audit logs.
• Rotate creative systematically; let exploration run, then prune low performers.
• Instrument every automated change so cause and effect are traceable.

3. Privacy-first and cookieless marketing

As third-party identifiers weaken, durable performance comes from consented data, clean measurement and tactics that do not depend on cross-site tracking. First-party and zero-party data anchor targeting and personalization, while clean rooms and server-side conversion APIs maintain signal quality.

The cookie question resolved differently than the industry expected. Chrome confirmed in April 2025 that it would maintain existing cookie settings rather than deprecate third-party cookies outright. Third-party IDs persist but remain unstable, subject to user settings, enterprise policy and browser restrictions.

💡 See In a cookie-less world: new challenges and opportunities.

Playbook:

• Offer a clear value exchange for consent and preference capture.
• Map cookie-dependent tactics and define channel-specific replacements.
• Align legal, data and media on retention rules and partner data sharing.

4. Personalization at scale

Personalization should reduce decision effort. Start where choice is hardest—homepage hero, category sort, PDP recommendations, cart cross-sell, lifecycle messages—and let behavior, product attributes and economics decide what appears. Keep the system explainable so merchandisers can audit outcomes and prevent bias.

Playbook:

• Write eligibility rules first to avoid mismatched offers.
• Limit variants; measure against conversion and order value, not clicks alone.
• Mirror rules across web, app and email to keep messages consistent.

5. Omnichannel integration

Customers think in tasks—discover, compare, buy, return—rather than channels. Integration means one identity, one offer engine and accurate inventory across web, app and stores. It also means reporting that recognizes digital influence on store sales.

Playbook:

• Unify profiles and orders; expose nearby store inventory online.
• Standardize promotions and pricing across touchpoints.
• Attribute store impact with loyalty IDs, receipt capture or geo-based tests.

6. Community and creator-led trust building

Trust compounds when real people advocate for you. Creator partnerships and owned communities supply credible product proof and ongoing dialogue. Aim for long-term relationships measured by attributable sales, assisted conversions and lift in consideration.

Playbook:

• Build a roster by niche and audience fit, not follower counts alone.
• Repurpose top creator assets into paid social, retail media and PDPs.
• Close the loop: gather questions from the community to inform content and product updates.

7. Leveraging retail media networks

RMNs blend shelf position with performance media, using retailer first-party data to reach shoppers near purchase. Treat each network as a distinct market with its own auction dynamics and measurement rules, and compare them with a standard taxonomy.

Concentration is the planning reality. Amazon accounted for 78% of US retail media spend in 2025 and Walmart 7.5%, leaving 14.5% for every other network combined. The same forecast has US retail media network spend growing 13.6% in 2028 to $74.9 billion, so the pool those smaller networks compete for stays thin even as the category grows. Budget accordingly, and treat a long-tail network as a test rather than a diversification strategy until it earns otherwise.

💡 For fundamentals, see What is a retail media network: definition, trends, insights.

Playbook:

• Split tactics: search for capture, display and video for discovery, on-site sponsorships for category dominance.
• Align bids to profit, including trade funds and retail fees.
• Sync promos and inventory with RMN calendars; use retailer clean rooms to verify lift.

⚡ Winning the digital shelf takes product detail pages that deserve the win, not just higher bids.

8. CTV and streaming advertising for retail

CTV delivers television-level attention with digital addressability. Use audience packages you can also reach in search and social for follow-up, and make spots shoppable with QR or send-to-phone options. Prove value with geo or household-level lift tests.

💡 Learn more in Connected TV advertising and Streaming TV advertising.

Playbook:

• Pair CTV prospecting with RMN and search retargeting to harvest demand.
• Control frequency; rotate short and mid-form edits by objective.
• Use holdout markets to quantify incremental sales before scaling.

⚡ Plan creative for the mute button first. A story that works without sound works everywhere.

9. Agentic commerce readiness

New for 2026. The goal is simple to state and slow to deliver: make your catalog legible to a machine that will summarize it, compare it and buy from it on a shopper's behalf.

Product data quality has moved from an SEO concern to a demand-capture dependency. An agent needs unambiguous price, availability, variant, shipping and returns data. Where it cannot find that, it recommends a retailer where it can.

Playbook:

• Audit machine readability of PDPs, category pages and policy pages before adding new content.
• Complete structured product markup: price, availability, ratings, GTIN, variant relationships, return window.
• Decide a protocol position—UCP, ACP, both, or neither for now—and document why.
• Segment agent-referred sessions in analytics so the channel can be measured rather than absorbed into direct traffic.
• Keep feed hygiene on a schedule; stale availability data does more damage in an agent context than in a search one.

10. Local and in-store demand capture

Also new for 2026, and the strategy most often missing from a digital-first plan.

Local search converts because the shopper has already decided to buy and is choosing where. In-store media reaches them at the last decision point before the shelf. Both are measurable with geo-based testing, which sidesteps the attribution problem that makes store impact so hard to prove.

Playbook:

• Run local inventory ads against your highest-margin in-stock lines, not your whole catalog.
• Build store-level landing pages with real inventory, hours and directions.
• Define in-store screen inventory against IAB's in-store impression standards so it can be sold and audited.
• Design geo-holdouts by store cluster, matched on footfall and demographics, before scaling any in-store media spend.
• Feed loyalty IDs captured in store back into online audiences within your consent framework.

How much should a retailer budget for digital marketing in 2026?

Start with the two benchmarks that get cited most, and note that they disagree.

Gartner puts marketing budgets at 7.8% of company revenue in 2026. The CMO Survey says 9.0%. Gartner samples large enterprises, The CMO Survey a broader mix of US firms, and smaller companies spend a higher share.

Neither survey breaks retail out separately, and category variation runs wider than the gap between the two averages. A working range for retail: 7% to 10% of revenue for an established business, higher during a growth push or a category entry.

Three adjustments turn a benchmark into a budget:

• Margin structure sets your ROAS target. A 4x blended target is comfortable at 60% margin and punishing at 25%. Work backward from contribution margin rather than adopting a competitor's number.
• Split capture and creation deliberately. Demand capture spend is self-limiting; it can only harvest intent that exists. If capture is fully covered and the budget still has room, the marginal dollar belongs in creation.
• Hold back a learning allocation of 5% to 10% of media budget—a different denominator from the revenue figure above—for testing new channels, formats and creative.

On retail media specifically, sponsored products price on CPC and display prices on CPM, with rates varying more by category competition than by any other factor. Published benchmark ranges circulate widely but come almost entirely from vendor blogs rather than primary research, so treat any single figure as a loose prior and price against your own auction data. 

The honest answer to the budget question is that percentage-of-revenue benchmarks tell you whether you are unusual, not whether you are right. Unit economics tell you whether you are right.

Retail marketing KPIs, in plain English

Six metrics cover most decisions.

• CAC (customer acquisition cost). Total acquisition spend divided by new customers acquired. Useful only against contribution margin, never in isolation.
• CLV (customer lifetime value). Expected contribution from a customer over their relationship with you. Model it by cohort; a blended average hides the segments worth acquiring.
• AOV (average order value). Revenue divided by orders. Moves with bundling, cross-sell and free-shipping thresholds.
• Conversion rate. Orders divided by sessions. Segment by traffic source before drawing conclusions, since a source mix change moves this number without anything on your site changing.
• Retention and repeat rate. The share of customers who buy again within a defined window. The cheapest growth available to most retailers.
• New-to-file and new-to-brand. Customers you did not have before. Retail media networks report this natively, which makes it the most comparable acquisition metric across platforms.

Those six answer "what happened." Three more answer "what caused it," and this is where most retail programs stop short:

• Incrementality testing isolates the sales that would not have happened without the ad, using holdouts or geo splits. 
• Marketing mix modeling attributes contribution across channels at an aggregate level without relying on user tracking. 
• Clean rooms let you match your data against a retailer's or platform's without either side exposing raw records.

The ordering is the point. Report the six basics to the business, run the three causal methods to decide where money goes, and never let a platform's self-reported ROAS be the last word on its own performance.

💡 If you need a refresher on why good dashboards can still mislead growth decisions, see Why your marketing metrics are lying about growth.

Top digital retail tools

Five categories cover most retail stacks:

• Ecommerce platforms—Shopify, Adobe Commerce, BigCommerce, Salesforce Commerce Cloud. The foundation, and the decision that constrains SEO flexibility, checkout conversion and agent readiness. AI features are now standard rather than differentiating.
• CRM and marketing automation—Salesforce, HubSpot, Klaviyo, Braze. The orchestration layer for lifecycle programs. Integration quality determines how much value you get: when CRM connects cleanly to ecommerce, POS and service systems, triggers fire in real time; when it does not, you have an expensive email tool.
• Retail media platforms—Amazon Ads, Walmart Connect, Target Roundel, Instacart Ads. Cross-network management becomes a real operational tax as brands add networks, which is why tools like Pacvue and Perpetua exist. Over half of advertisers are now reallocating display spend from open-web DSPs to retail media DSPs, with 57% citing closed-loop attribution as the reason.
• Analytics and attribution—Google Analytics 4, Adobe Analytics, AppsFlyer, Rockerbox, MMM platforms. Multi-touch attribution has limits that get worse as user-level signal degrades; platforms bundling attribution with MMM and incrementality testing are the practical answer.
• AI-powered media intelligence—Elevate and Smart Supply. Elevate is AI Digital's intelligence platform, planning, forecasting and optimizing campaigns across platforms and explaining every move, with spend aligned to custom KPIs rather than proxy metrics. Smart Supply orchestrates where ads run, prioritizing premium brand-safe inventory and short supply paths, filtering low-quality and IVT traffic, and building custom Deal IDs tuned to your KPI.

Assembling it: start with ecommerce and CRM for owned data, add analytics and attribution to verify what drives sales, layer retail media and paid channels where you can close the loop, and use AI to automate repetitive decisions so people stay on offers, creative and assortment.

⚡ Models don't fix messy data. They amplify it. Clean the inputs first.

Examples of retail digital marketing in action

Three retailers, three published sets of numbers, and what each one is actually evidence of.

Amazon Sponsored Products lift for a niche beauty brand

Made for Locs used Sponsored Products to expand reach and test bundles. In six weeks, campaigns delivered a 10x ROAS and a 40% increase in average order value as shoppers explored the broader routine. Amazon's case study attributes the lift to product bundling and traffic to the Brand Store rather than bidding alone.

Takeaway: treat Sponsored Products as more than keyword auctions. Pair them with on-page merchandising so clicks convert into bigger baskets.

Shopify-powered omnichannel growth for Mizzen+Main

Mizzen+Main unified ecommerce and stores on Shopify POS and online, giving associates a single customer profile and real-time inventory. In 2023 they recorded 27% growth in retail revenue, 16% in retail orders and 15% in online revenue year over year after rolling out the integrated stack and clienteling workflows.

Takeaway: a unified platform turns store staff into informed sellers and keeps promotions consistent across channels, which shows up in both store and online results.

Shoppable CTV drives action near stores

A skincare advertiser targeting households around department store locations ran a CTV campaign with QR-enabled creative. Results: 96% video completion, 4% click-through rate and 3.4x higher sales in optimized markets versus the rest, across premium publishers.

Takeaway: make TV actionable, localize delivery around stores, and confirm impact with market-level sales comparisons.

💡 If you're weighing addressable versus CTV buys, this primer can help: Addressable TV vs connected TV.

Benefits and challenges of retail digital marketing

A clear view of the upside and the trade-offs helps you plan with intent.

Benefits

• Reach that matches intent. Search, retail media and marketplaces put products in front of people already shopping, while CTV and social supply efficient scale for discovery.
• Proof of impact. Event-level data, clean-room analysis and incrementality testing show which channels and messages move sales.
• Personalization customers can feel. Unified profiles and product signals power relevant recommendations, timely reminders and tailored offers that reduce decision time and lift basket size.
• Faster learning cycles. Always-on testing and AI-assisted optimization shorten the loop from insight to action.
• Resilience across channels. A connected mix reduces dependence on any single platform and keeps growth steady when one channel softens.
• New revenue lines for retailers. Retail media networks monetize digital real estate and first-party data, adding high-margin income alongside product sales.

Challenges

• Data stitching and governance. Without shared IDs, standardized events and clear permissions, personalization and measurement stall.
• Attribution you can trust. Walled gardens limit transparency and cross-platform comparability. When a single network holds 78% of US retail media spend, comparability is a structural problem rather than a vendor complaint. Use controlled tests and model triangulation to avoid false confidence.
• Rising acquisition costs. Auction pressure in search, social and RMNs erodes margin unless bids are tied to profit and creative is refreshed frequently.
• Privacy and compliance. Consent, retention and partner sharing rules require discipline. Plan for fewer third-party identifiers.
• Operational complexity. BOPIS, ship-from-store and free returns add cost and coordination. Without accurate inventory and consistent offers, customer trust suffers.
• Talent and workflow. Modern programs need analysts, engineers and marketers working from a single source of truth.

⚡ A metric that can't change a decision is decoration. Promote the few that can.

Trends shaping retail digital marketing in 2026

Eight developments worth building into a 2026/2027 plan, in rough order of how soon they'll affect budget.

1. Retail media concentrates as it matures. Growth continues, but it is narrowing. WARC forecasts global retail media growth excluding Amazon falling to 9.8% in 2027, the lowest rate since it began tracking the sector. The category is also renaming itself: EMARKETER now forecasts US commerce media at $142.07 billion and 23.9% of all digital ad spending by 2030. The vocabulary change reflects a real one, since media sold against purchase data has moved beyond retailers into travel, finance and delivery.
2. Retail media creative is underperforming, and the industry is starting to admit it. A simulated shopping study cited in WARC's The Future of Commerce Media 2026 found memory encoding fell 47% for ads appearing on retailer platforms compared with generic off-site environments. Among undecided shoppers, high-quality creative delivered a 12% lift in short-term brand choice. Retail media converts existing demand well and builds brands poorly, and the gap is a creative problem before it is a targeting one.
3. Measurement standards finally exist. IAB Europe released its Commerce Media Measurement Standards V2 on 22 January 2026, setting a 30-day lookback as the default, defining gross and net sales, adding quick-commerce metrics, formalizing incrementality methodologies and expanding new-to-brand timeframes to five options. The six-month grace period for compliance ended on 31 July 2026. IAB and the MRC have issued their own guidance on retail media, in-store measurement and incrementality since 2024. If your networks have not confirmed which standard they report against, that is a question worth asking this quarter.
4. Experimentation is still the gap, not the answer. Among 166 US retail media advertisers surveyed by Skai and Stratably for the 2026 State of Retail Media, only 15% report strong confidence in their measurement, 14% are not measuring incrementality at all, and more than half name limited analytics and data science resources as their biggest barrier. Seven in ten say they meet or exceed their retail media goals, which is difficult to reconcile with the first three figures and tells you something about how those goals are set.
5. Creator advertising becomes a core channel. US creator ad spend reached $37 billion in 2025 and is projected at $44 billion in 2026, growing faster than the broader media market. Nearly half of creator ad buyers now describe creators as a must-buy, ranking them behind only paid search and social. At that scale, fuzzy scope and anecdotal reporting become procurement problems.
6. In-store retail media stays small and stays interesting. In-store accounted for 3.3% of non-Amazon retail media spend in 2025, and EMARKETER has pushed back its growth milestones because execution has proven harder than demand. The opportunity is structural rather than immediate.
7. CTV is planned like performance media. With streaming at 48.5% of US TV usage, retail plans pair shoppable CTV with search and RMN retargeting and lift tests at geo or household level.
8. Omnichannel becomes plumbing. Unified identity, inventory and offer engines move from pilot to core infrastructure, with reporting that credits digital influence on store sales rather than online last-click alone.

💡 For broader context on where media is heading, see The State of Media. For how shifts in TV buying shape retail plans, see Upfront trends and implications for marketers.

Conclusion: building a winning retail digital marketing strategy

Treat retail digital marketing as a system. The retailers that win in 2026 connect four pillars into one operating model: 

• omnichannel execution with web, app and stores sharing identity, inventory and offers; 
• paid media that can prove outcomes across search, retail media and CTV; 
• personalization that reduces decision effort through contextual rules and explainable models; and
• AI-driven insight loops that reallocate budget and refresh creative based on results.

The addition this year is a fifth: machine legibility. A growing share of shoppers meet your catalog through an intermediary that summarizes it before they ever see your site. Product data has become a demand-capture asset.

What's practical on day one:

• Align teams around a single customer profile and a single measurement plan.
• Wire your ecommerce, CRM and analytics so owned data powers media and messaging.
• Use incrementality tests and clean rooms to decide where each extra dollar works hardest.
• Audit whether a language model can read your product pages.
• Let AI handle speed and scale while humans set the rules and guardrails.

💡 For a deeper look at how to operationalize this, see How AI Digital helps seize retail and commerce media opportunities.

If you'd like us to build a 2026 plan or pressure-test your current mix, reach out. We'll audit your data and measurement setup, size the opportunity across channels, and propose a pilot that proves lift before you scale, using Open Garden access, Elevate for intelligence and Smart Supply to keep every impression working.