2026年年初至今,配送类零售媒体网络(RMN)的竞争格局已从Grubhub向Instacart倾斜。Instacart占据49%的配送零售媒体曝光份额,较2024年同期的24%大幅提升;Grubhub份额则降至13%。DoorDash以28%的曝光份额排名第二,并拥有最大的广告主基数(496个品牌 vs. Instacart的306个)。Instacart广告主数量较少却产生更高曝光,说明其平台上的品牌平均投放规模更大,广告变现效率和单广告主贡献更高。
各配送零售商在2026年年初至今形成了差异化的广告主品类结构。Grubhub最偏餐饮,88%的曝光来自Fast Food & Fast Casual广告主;Uber该品类占比为48%,McDonald's同时是Grubhub和Uber两个RMN的第一大广告主。Instacart以CPG品牌为核心,Food Items占47%、Beverages占18%,其他头部品类包括Pet Food、Hair Care和Household Cleaning。DoorDash品类组合最均衡,没有任何品类曝光占比超过22%;Credit Cards占16%,主要由Chase通过DashPass信用卡权益合作驱动。
渠道组合上,Facebook和Instagram仍是各配送RMN的曝光基本盘:Grubhub有87%的活动、Instacart有77%的活动来自这两个平台。Uber的渠道组合最多元,TikTok分配占比达11%、YouTube达13%;TikTok活动由Jersey Mike's的免费三明治优惠主导,YouTube则由McDonald's围绕Uber McDelivery合作投放。这意味着广告主在配送RMN上不能只依赖Meta系渠道,而应根据平台用户心智和 campaign 目标配置TikTok、YouTube等补充触点。
广告主使用配送RMN的场景已明显超出餐饮外卖。2026年年初至今,四大网络合计的最大广告主是Chase,其通过DoorDash合作向符合条件的信用卡持卡人提供DashPass。CPG品牌则把配送定位为日常与即时需求解决方案,例如Uber Eats配送Tums、Pantene在Instacart鼓励用户订购Hair Care时“放松休息”。零售合作进一步扩展配送场景,DoorDash突出Urban Outfitters配送,Instacart推广Lowe's商品接入;餐饮广告主以McDonald's为代表,常用零售媒体推广免费菜单项和折扣。对广告主而言,配送RMN已成为覆盖CPG、金融、零售合作和餐饮促销的增量投放场景,需按平台品类心智、渠道组合与创意形式进行差异化投放,并以增量提效和归因分析评估ROAS。
值得关注的是,配送类 RMN 的竞争重点已从「覆盖多少广告主」转向「承载多大预算」:Instacart 以更少的品牌换来近半曝光,DoorDash 用更宽的广告主基数换取份额,两者对应的竞价密度与库存定价逻辑并不相同。关键信号在于信用卡、CPG、零售商等非餐饮类广告主成为主要买方,说明交易数据正被当作通用媒介资产来售卖,而不只是餐饮流量的变现出口。另一层背景是曝光仍高度依赖 Meta 系分发,自有 DSP 与站内闭环尚未成型,归因也仍受第三方链路制约。
对 UA 与变现团队而言,库存集中于少数大买手所带来的竞价波动,以及跨渠道口径的可比性,是这类渠道进入常规媒体组合前需要看清的前提。
TikTok is offering new advertisers up to $6,000 in ad credits through a tiered spend incentive ($100/$500/$1500) that includes 1-to-1 expert support at the top tier. However, eligibility is restricted to new SMB self-serve accounts, and credits expire. Alongside the offer, TikTok has rolled out several ad tech innovations—Symphony AI creative suite, Streaming Ads, Agentic Hub, Market Scope, and new MMM data—that provide actionable opportunities for testing and scaling performance. Ad ops teams should review eligibility criteria carefully and consider leveraging these tools to maximize ROI during the promotional window.
This TikTok for Business landing page promotes a limited-period new-advertiser incentive program offering up to USD 6,000 in matched ad credits. Three self-serve tiers are presented: 50% off first 30-day spend (up to $200), dollar-for-dollar match up to $500, and match up to $6,000. A separate headline offer advertises Spend $100/Get $100, Spend $500/Get $500, and Spend $1,500/Get $1,500 plus 1-to-1 expert onboarding support. Registration requires email or phone sign-up with 2-step verification. Eligibility is restricted to new SMB self-serve accounts, excluding agency, Business Center, and TikTok Shop accounts; credits post within 7 days of hitting the highest threshold or after the 30-day window.
TikTok for Business is promoting tiered first-30-day ad credit incentives for new self-serve SMB advertisers: spend $100 get $100, $500 get $500, or $1,500 get $1,500 plus 1-to-1 expert onboarding support, with a headline entry offer of 50% off first-month spend up to $200 and matching credits up to $6,000. Credits are applied within 7 days of hitting the highest threshold or after the 30-day accumulation window. Eligibility excludes agency, Business Center, and TikTok Shop accounts, and limits one ad account per new TikTok For Business account. For ad ops teams, these terms dictate budget pacing, account structure, and credit-expiry planning.
TikTok's UK/Europe scale (30M+ UK, 200M+ EU) and content graph make category objections obsolete. For ad ops, success comes from relevance, not trends: proof-led demos, explainers, reviews, and problem-solving content can reach high-intent audiences without a large follower base. Case studies show material performance: Toyota CPA -38%, BCP 10x registrations, Randstad 2.81% CTR/17M impressions, Prep Kitchen +44% conversion and +374% orders with Smart+, PureGym CPA -77%, HydroClean cost per conversation -74%. Action: test utility/creator content, use Smart+ for scaled creative testing, layer TopView on trusted content, and target niche communities rather than broad reach.
Attribution fails because platforms self-report, data is siloed, identity breaks across surfaces, and traditional models answer the wrong question. The same purchase is often claimed by three or four platforms, inflating attributed revenue 2–4x and distorting ROAS and budget decisions. For ad ops leaders, the fix is not another dashboard but an independent, deduplicated measurement layer with cross-surface customer ID, full coverage of mobile, web, CTV, and retail media, plus incrementality testing. Clean attribution is also the prerequisite for reliable AI bidding and budget automation; broken inputs scale misallocation faster.
Cross-channel marketing analytics isn't about putting Meta, Google, and TikTok numbers side by side—they often double-count the same customer journey. Fragmented identity is the real culprit; without a first-party Customer User ID, attribution measures platform credit, not customer value. The article explains that deduplicating conversions across mobile, web, and CTV can lift attributed revenue by 30–60% and improve ROAS by 20%. It walks through attribution models, warns against platform-native analytics, and advises using an independent MMP for true cross-channel measurement. Ad ops takeaway: fix identity resolution first, because AI-driven optimization and budget allocation depend on trustworthy, deduplicated data.
CTV often looks flat in last-touch because it rarely earns a click and conversions appear later on another device. Ad ops teams should treat this as a measurement gap, not a channel failure. Use cross-device attribution to connect CTV impressions to downstream installs or purchases, then run incrementality tests such as geo-holdout to prove causal lift. Measure in four layers: delivery, engagement, outcome, contribution. Configure impression URLs, VTA lookback windows with a 24-hour minimum, and disable deep linking for CTV. Do not optimize CTV on last-touch; compare holdout results before scaling or cutting.
Target’s 2026 back-to-school retail media campaign became more concentrated: impressions fell 66% YoY to 781M and participating brands dropped 28% to 236, while the top eight advertisers captured 46% of BTS impressions, up from 15% in 2025. Crayola led with 94M, followed by Overtime (75M), Pokémon (53M), and LoveShackFancy (43M), reflecting a shift toward exclusive partnerships and style. Channel mix moved away from Facebook (27% share, down from 41%) toward Instagram (+13 pts, 120 brands) and OTT (22%, only 7 advertisers); TikTok fell to 2%. Ad ops should plan for fewer, larger buys, tighter brand-partner coordination, and Instagram/OTT-heavy allocations.
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