John Michael (Jay) Bargayo

Kroger just launched keyword bidding to drive retail velocity. If you’ve used 8451 to drive your shelf turns… …you’ve probably been frustrated with their Auto campaigns. The real magic is always in Manual bidding. And Kroger has just never had the option. Well, they launched Bid Modifier last week. After a week of testing, here’s how it works: -> It is built off of auto campaigns. -> The campaign gets a starting bid. -> Kroger selects the keywords, 100 per campaign. -> You can then “boost” any of the identified keywords. Is it fully manual? No. It’s more of a hybrid. And heads up: the keywords selected are not great. But early results look promising, and ROI is 🚀 If you need help driving velocity at Kroger, shoot me a DM. —— 🔹 We grow brands on Amazon. 🔹 We increase velocity in Whole Foods, Walmart, Target, Walgreens, CVS, Kroger, Sam's, COSTCO, and lots of other cool retailers. #cpg #cpggrowth #retailgrowth #retailvelocity #omnichannel #retail #amazonagency #retailmedia #shoppermarketing #instacart

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Physical sampling is NOT dead. But your approach might be ☠️ Most brands still treat product sampling like it's 1985. ❌ Blast samples to as many people as possible ❌ Choose channels based on price, not targeting efficiency or results ❌ Accept no direct attribution or way to measure campaign success In 2024, that just doesn't cut it anymore. Sampling is an incredibly powerful tool to: ✅ Acquire new customers ✅ Grow awareness ✅ Create advocacy ✅ Drive WOM + earned media ✅ Collect ratings & reviews ✅ Gather valuable data & insights ...IF you do it right. But most brands aren't set up to track, or even obtain any of this! They couldn't tell you the ROI of a single sampling activity, at best the "success" is simply measured by how many products were given out. That's where performance sampling comes in. It's not about distributing the highest volume, at the lowest cost and accepting no level of attribution or measurement of true impact. It's about engaging the RIGHT audience, extracting the highest value return from every product sample, and measuring everything along the way! Hyper-targeted, strategically-aligned, fully measurable sampling. So you can actually attribute the direct returns - measuring success from what came back - not what went out. It might be time to question the outdated spray-and-pray sampling tactics. Sampling can REALLY support growth. If you go about it the right way. Learn how the top brands are doing it in 2024: https://buff.ly/3Y1irJd

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TikTok Shop AOV is WAY lower than website b/c: 1. Discounts are CAPPED which does not incentivize higher cart sizes (in the below example, you think it's 50% off, but the coupon is maxed at $20 discount) 2. Upsells/cross-sells in the CART are below the fold and ppl will rarely scroll below the "checkout button" 3. These are largely impulse purchases. If TTS doesn't incentivize higher AOV, brands are stuck in low AOV purgatory. If I'm TikTok, I start considering a solve for both of the above.. honestly pretty easy Despite TTS low AOVs, we're noticing 2.5-7x higher conversion rate than the DTC site. B/c of this- TikTok Ads performance has been higher driving to the Shop (vs website) for every client we've touched on TikTok in 2024.

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Understanding Key Concepts in Google Analytics 4: Sampling, Threshold Limits, Cardinality, and Engagement Metrics Starting on July 1, 2024, you will lose access to Universal Analytics data in the interface and the API, and via any product integrations like Google Ads, or Search Ads 360. Google Analytics 4 (GA4) introduces several new concepts and metrics that are essential for understanding and optimizing your website’s performance. Among these, sampling, threshold limits, cardinality, and the distinction between bounce rate and engagement rate are critical. Sampling vs Threshold Limits Sampling occurs when GA4 processes only a subset of your data to generate reports. This usually happens with large datasets to ensure faster processing times. While sampling can provide quick insights, it may lead to less accurate data compared to unsampled reports. Threshold limits, on the other hand, are applied to ensure user privacy. When viewing data, especially in segments or with low user counts, GA4 might apply thresholds to prevent the identification of individual users. This ensures compliance with privacy regulations but can limit the granularity of your insights. Cardinality Cardinality refers to the uniqueness of values in a dataset. In GA4, high cardinality can occur when there are many unique parameter values, such as user IDs or custom dimensions. High cardinality can complicate reporting and analysis by creating an overwhelming number of unique entries. Managing cardinality is crucial for maintaining clear and actionable reports. Bounce Rate vs Engagement Rate In GA4, bounce rate has been replaced by engagement rate. Bounce rate traditionally measured the percentage of sessions where users left the site without interacting. Engagement rate, however, provides a more nuanced view by tracking the percentage of sessions that last longer than 10 seconds, have at least one conversion event, or involve multiple page views. This shift allows for a better understanding of user interaction and engagement with your content. Mastering these GA4 concepts—sampling, threshold limits, cardinality, and engagement metrics—can significantly enhance your ability to analyze and improve your website’s performance. #GoogleAnalytics4 #GA4 #WebAnalytics #DigitalMarketing #UserEngagement #DataSampling #ThresholdLimits #Cardinality #BounceRate #EngagementRate

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The average American sees 100-350 ads a day. Yeesh. So, here’s how we help CMOs at CPG Food & Bev shops get more clicks against the competition. The #STANDOUT ! Process. We: 𝗦tart with objections → Define clear goals, perform audits, and prepare briefs. 𝗧arget the right people → Identify ICPs using lazer-targeted avatars 𝗔nalyze what's unique about you → Conduct competitor analysis to carve out a USP 𝗡ail your brand → Craft its voice and identity across all touchpoints 𝗗etermine the right channels. → Map out the customer journey on each channel 𝗢pen up to your audience. → Distribute content and ramp the reach up on social 𝗨nleash the power of data. → Go deep on the stats to optimize your strategy 𝗧ake everything to the next level. → Scale up marketing efforts with continual testing The result? hashtag #FreshExpress went from: — 18k Youtube views — 6k Pinterest Followers — & a 36 hour consumer response time in 𝟮𝟬𝟭𝟵, to: — 2.2 Million Pinterest users — 1.3 Million Youtube views — & Less than 12 hour consumer response time in 𝟮𝟬𝟮𝟰. PS: If you're a CMO or VP of marketing in CPG Food and Bev. And you're looking to become the only option for your ICP Just DM 'STANDOUT' And we can explore how we could bring you higher quality marketing at scale.

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Is Bing intentionally monetizing organic map listings in search? For a large #retail client’s  #affiliatemarketing program, we uncovered an anomaly in the Bing Map SERP (search engine results page) that turned a seemingly benign search into an affiliate-sponsored result. We’ve outlined some findings here: https://lnkd.in/dQr_DqiU #SEM #affiliatemarketing #marketingROI #searchengines

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It turns out, users want answers not links. Here is an enlightening breakdown from ✌️Olaf Kopp ☀️ of how product SEO is changing (as we speak). #Digitalmarketing #SEO #ecommerce Search Engine Land

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CPG/DTC Friends: Here's how I FORCE Meta ads to be profitable and SCALE on autopilot with little to no manual work required. 1. Launch a few ASC+ campaigns with 10-20 new ads (all of which will be variants of a proven concept). This will depend on your budget and how many effective creatives you can source. 2. Define your target CAC. Let's say your target CAC is $60. 3. Set up 3 automated rules at the ad level: a. Kill ads when target CAC > $60 and amount spent = 2x CAC b. Kill ads when Purchases < 1 and amount spent = 1x CAC c. Revive ads when CAC < $60 (this will ensure ads with delayed reporting keep running) 4. Set up 2 automated rules at the campaign level: c. Increase budget by 20% once a day when total CAC < $60 (last 2-3 day window) d. Decrease budget by 20% once a day when total CAC > $60 (last 2-3 day window) 5. Let your campaigns run. What will happen? Winning ads will keep running, losing ads will stop, and the campaign will scale and keep running for as long as it works. Once the campaign reaches its peak, and the ads die out, the campaign will de-scale itself so you'll never have to worry about CAC spiking. You can forget about media buying (for the most part), and use most of your time producing creatives – which is where the big bucks are made. Any caveats in this strategy? Just two (big) ones. - You'll need to have a proven AD CREATIVE formula that's repeatable, which is something brands often struggle with. Sometimes UGC will work, sometimes stills will work. Most of my brands work with direct-response UGC. - You'll need to have a proven LANDING PAGE with a proven positioning strategy and an acquisition OFFER that converts browsers into customers WITHOUT diminishing your brand's value, or acquiring "cheap" customers that won't come back – which brands also struggle with. Once you figure out those 2, then you can basically force scale without relying on unpredictable cost caps which often don't even deliver. #meta #facebookads #shopify #dtc

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Some solid advice here!

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Google made some important changes to the SERP yesterday. Here are some notes and recommendations from Backbone Media on what the Search Generative Experience means for brands/clients/retailers and how to evolve your SEO and SEM strategies in this new environment.

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Hot take: selling in B2B is actually easier than DTC. (My B2B team is probably rolling their eyes right now). In DTC, the brand is selling and communicating to the buyer directly. That buyer's decision making is non-linear and subjective: • Do I want this thing • Do I even need this thing? • What about these 5 other things? • Will it actually make me feel better / happy? This is where a lot of the concept of "brand" comes from. There's a status association with certain products and the network effect of that individual buyer's psychology with all of their other "inputs." In B2B, it's actually super simple. A product or service needs to do one of two things: 1. Make the company money 2. Save the company money Really highly valuable products do both. If you -- as a seller in a B2B context -- can demonstrate to your prospective client justification for why it will do one or both of those things (make or save money), then it's an "easy" decision. The difficulty in B2B comes in from the nature of the buying committee, high contract values, budgets, and long decision cycles. You have to do the convincing at multiple points of the organization, and those stakeholders might have different priorities, might not believe you, etc etc. But again, if your pitch is clear and credible, and the scenario that you present is pretty undeniable, why would any organization refuse you? (Note: this doesn't really apply to true enterprise sales because enterprise is more like dealing with a small country than an actually functional and coherent organization). But if you're, like me, selling services for 5-6 figures a month to brands that are sub $1 billion in revenue, it's straight forward: "Here's how I'm going to make you more money than I cost." "Here's how I'm going to save you more money than I cost." If you want to see my pitch first hand -- reach out and I'll show you how we can pay for ourselves easily. #b2b #sales #revenue

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Back up your Universal Analytics / Google Analytics Data before it's too late ❗JULY 1st DEADLINE ❗ Last year, everyone went through the tumultuous process of migrating to and getting accustomed to GA4. Now, Google has announced that they’re going to delete all Universal Analytics data on July 1, 2024 (in 7 weeks from now). What does this imply? 1️⃣ No more historical UA / GA3 data to look at. No more trends, no more comparison of today’s performance with historical performance. 2️⃣ Incomplete data leads to incomplete insights, which then leads to potentially incorrect decisions on a marketing front. Who is this NOT for? ❌ If you’re a business that didn’t rely on Universal Analytics / GA3 before you installed GA4, you’re fine. ❌ If you’re a new business that started it’s journey in the GA4 realm, you’re fine ✅ IF you’re anyone else, this is VITAL for you! ✅ There are 3 things you need to be aware of: 👉 You need to first back up all your UA data into a server or excel sheets 👉 You then need to be able to access that data (either through some data visualization tool or in the form of data tables in spreadsheets or other tools) 👉 And lastly, you would want to have all your historical UA data ‘transformed’ so it blends into GA4 data smoothly. Else, you’ll be left with 2 separate data blocks (UA and GA4 separate), which won’t be comparable with each other. Luckily enough, we’ve built a done-for-you solution, so you don’t have to get your hands dirty in this entire data storage / data transformation business. 🍺 Focus on what makes your beer taste good. Let us handle this for you. To back up your Universal Analytics data before it gets deleted in the next few weeks, just get in touch with us. Check us out at www.analyticssafe.com or email us at varun@tealbox.digital or hrishikesh@tealbox.digital.

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What matters to us as marketers doesn't always match up with what buyers care about (or will even see in their shopping journey). Most conversations about GenAI that I hear about are focused on synthetic production (making ad assets faster and at lower cost)... great for operational efficiency, but not necessarily contributing to any "surprise and delight" for your buyers. The GenAI solutions that really wow me 🤯 and make me curious 🤔 about the future of the digital ad experience are the ones that can permanently alter user behavior by making new experiences possible. Seeing what we can ALREADY do with Virtual Try On and Virtual Shopping Assistants really just makes me wonder what online buying will look like in just a few years... makes me think of AR views for furniture shopping: slow to become widely adopted, but now a key feature on all major furniture brands' PDPs. #Ecommerce brands 🛍 should pay attention, these aren't just expensive trends, they can permanently alter consumer behavior. https://lnkd.in/eAK4bx3s

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What really excites me about this campaign is that it validates what we, as consumers, intuitively feel about advertising. Whether we’re alone scrolling late at night or curled up on the couch with family ready to binge our favorite show, mindset matters. Signal loss is real, but the one signal that won’t deprecate is our love of stories. If you know what interests your customers, then reach then when they are watching the shows and movies they love. As a viewer, I’m excited that advertising is going to be a whole lot better. As a member of IRIS.TV, I’m excited that we can make game-changing AI solutions like Captify®, GumGum, KERV Interactive, Pixability, and Silverpush accessible to brand pioneers like CKE Restaurants, Inc. and their CMO Jennifer Tate and marketing innovators like PMG and their visionaries Sam Bloom, Michael Treon, Doug Paladino, and Stephen Governale who are showing us all how to bring the art and science back to marketing. #innovation #marketing #advertising #digitalmarketing #streamingmedia #streaming #ai #adtech #programmatic #FAST #ctv #connectedtv #contextualadvertising

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Hive Mind... If the media budget is less than $10MM, what's your favorite MMM/MTA measurement platform for eCommerce? The few (budget right sized) solutions that I have seen so far, tend to lack a key element or two in my mind... maybe I'm expecting too much but a boy can dream, right? #marketinganalytics #MMM #MTA

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Tons of people are talking about the value of sending better server-side CAPI data to ad platforms like Meta, TikTok, and Google. But no one has explained why it works or why its better? Here's the why... 1 - More signal for low volume accounts Small accounts with low volume generally struggle to exit learnings and don't get any of the benefits of modern ad products. More signal means faster learnings and better chances that machine learning optimizations start to work. 2 - Better use of broad targeting Broad targeting is increasingly popular, but it only works when you teach the ad platform how to tell between high value converters and people who bounce. More data with higher match rates means broad targeting will work even better, for even longer. 3 - Better ad optimization Once digital ads start working, learning models kick in and start to make micro-optimizations to boost performance. Choosing the right combination of who to reach, where to reach them, and what version of creative to show them leads to better ad optimization and more efficient ad spend. 4 - Better auction performance Most people think that the winner of an ad auction is simply the highest bidder. But it turns out these algorithms reward ads for being high quality. Better data leads to higher quality scores. Low bids with high quality scores outcompete high bids with low quality scores. 5 - More accurate attribution Missing data and modeled data are the root cause of inaccurate attribution. When you send better data to an ad platform, it relies less on guessing and more on the crystal clear picture of what really happened on your site. Businesses with high quality data connections don't have issues with miss-attribution, even on Meta. This isn't rocket science. Ad platforms are learning engines that run on data as fuel. There's no reason to continue using basic/free data connections. Upgrade to a high performance advanced data connection to upgrade your ad performance.

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Announcing Aperiam's Latest Investment: Gigi! 🍒 Aperiam continues to make strategic bets in commerce media and CTV, the fastest-growing segments of digital advertising. With Amazon Ads being the largest commerce media channel AND the fastest-growing Streaming TV ad platform, we are excited to introduce our latest investment: Gigi. Why Gigi? 1) The product. Gigi’s unique ability to integrate a brand's first-party commerce data with Amazon's data for audience enrichment and deterministic omnichannel measurement sets it apart. This powerful combination enables brands and agencies to buy and measure Amazon Streaming TV ads more effectively. 2) The team. The founders behind Gigi consists of experienced commerce media executives - led by cofounder and CEO, Adam Epstein - who have a bold vision for the future of Streaming TV, commerce media, and data collaboration and a history of success in commerce media. Their expertise ensures that Gigi is at the forefront of innovation in this space. We believe Gigi’s capabilities and the vision of its team will drive significant advancements in how brands leverage data to enhance their advertising strategies on Amazon’s platform. Check out Gigi here: https://gigico.tv/ cc: James Borow Joe Zawadzki Danilo Tauro, PhD

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Your site’s content should conform to best practices as disclosed in the Search Quality Ratings Guidelines with an emphasis on: ✅ Being unique and offering value. ✅ Matching search queries. ✅ Satisfying user intent. ✅ Being of high quality. ✅ Satisfying the fresh content algorithm.

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