Alec Haase

There are five large CPG companies (okay, maybe ten) capable of doing their own advanced measurement of digital media spend over an extended period of time – we’re talking about either multi-touch attribution (MTA) or sales lift and incrementality not solely tied to individual campaigns. The vast majority of top 25 CPG companies don’t have the internal resources or have partnered with data or measurement companies to help them understand what is working and what is not. Even the large CPG clients with massive data science capabilities find it difficult to sustain delivering insights where sales outcomes drive digital advertising decision making. They either lack the data, have challenges with carry through (comparing exposed audiences with users who actually bought) or simply have other priorities. Some CPG clients rely on their agencies for measurement work, but more than likely there are media and data providers helping with the measurement (sometimes grading their own homework) but ideally, third party measurement providers are involved. The “easy button” for activation in CPG has been to use major players like The Trade Desk and the LiveRamp Marketplace, even the Amazon DSP. CPG purchase data from a wide variety of sources is available, although a material source of inventory will be going away soon with Oracle Advertising ceasing operations in September. Measurement has gotten much harder. Changes in Apple’s privacy policy a couple years back has made it tougher to measure the effectiveness of digital campaigns in Apple devices. In spite of Google’s reversal on the deprecation of cookies, the writing’s on the wall and by giving consumers the choice to be tracked (or not) we all know how that’s going to end up – same way as 80% of iPhone users telling the App not to Track. I’ve been very encouraged over the last 6 weeks since I started my new gig at Scanbuy. Client-side execs at large CPG companies who own 1PD strategies are genuinely interested in the quality and scale of our purchase data: 100% opt-in from receipt scans and loyalty card programs, and 13MM MAUs representing spending across all classes of trade. Key brands and categories are well represented. The best part is we offer flexibility in measurement. Do it yourself if you have the data science team and the chops. Use our measurement partner. Use your own measurement partner after a short certification process with Scanbuy. Learn what is working and what is not. Optimize. Learn some more. You have to license the data in order to do measurement. Use this approach with your CTV spend. And other digital tactics. I find CTV the most interesting because so much spend is going there. Wouldn’t it be great to measure the sales impact? Hit me up or wait for me to ping you. We’re here to help CPG Innovators do cool things. #CPGmarketing #purchasedata #CTV #analytics

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Two types of MMM; manual and Cloud with 3 different providers. Each of the 6 cells has pros and cons which affect price, speed and integration. If you've never used Marketing Mix Models before because you think they are too expensive, slow or just unnecessary, talk to us you'll be surprised what has changed in data science in the last 4 years. https://lnkd.in/gcDMnKTU

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I tell every brand that I talk to - if you’re running DSP and don’t have an AMC instance, you’re actively leaving money on the table. In fact, you’re falling behind. The brands that are leveraging AMC have a massive competitive advantage over brands that haven’t. I’m seeing it in every conversation. One of my favorite customer stories is when a brand leveraged our multi-touch attribution model to calculate the optimal budget distribution across all ad products. Historically, their budget was heavily allocated to SP. However, our model told them to increase their DSP spend to a specific percentage of their budget. The result? A performance improvement of over 17%. AMC is only getting better and better. This means the gap between brands leveraging AMC and those that aren’t will only continue to get wider and wider. #AMC #AmazonAds #Amazonadvertising

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Why Traditional Marketing Mix Modeling Is Falling Behind Key Challenges: Inflexibility: Traditional MMM relies on outdated historical data, making it less effective in today's fast-paced digital market. Long Timelines: Annual MMM projects lead to outdated insights, hindering real-time decision-making. High Costs: Extensive consultant involvement drives up costs and delays analysis. Complex Market: Navigating numerous channels and touchpoints, including Retail Media Networks (RMNs), complicates marketing decisions. Revenue Attribution: Traditional models struggle with accurately attributing revenue to specific marketing efforts. Why Switch to Keen Decision Systems? In-House Control: Use your own data, custom models, and tailored plans for greater flexibility. Credibility: Demonstrate marketing's impact on business outcomes, securing stakeholder buy-in. Advanced Analysis: Keen’s platform uses machine learning for dynamic, data-driven decisions. Real-Time Insights: Stay current with real-time data processing for agile strategy adjustments. Ready to transform your marketing strategy? https://lnkd.in/e6PK2kWF #MarketingStrategy #MMM #MarketingOptimization #InHouseModels #KeenDecisionSystems #AgileMarketing #DataDrivenDecisions

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Got TWO great #webinars for you guys from two of my ridonkulously amazing Constellation Research, Inc. colleagues. First up...TODAY! Holger Mueller dives into a convo on the latest trends in #AI tech, its significant impact on enterprise #software, and practical strategies for integrating AI to enhance business operations. Register: https://bit.ly/3S6gVlk Then its over to Doug Henschen on 8/6 for an interactive roundtable discussion on the latest trends shaping the #data and AI industry, and the challenges orgs face in harnessing the power of data and AI. Register: https://bit.ly/3S9xL2Q And yes...ridonkulously is a word. Don't question the process.

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Some big news…. We just launched DemandGPT, a niche-LLM trained specifically on experiment data, advertising playbooks, forecasting models, step-by-step implementation guides, and much more from all of the collective learnings at Refine Labs over the past 5 years. Get instant answers to your most important Demand Gen questions and priorities, supported by data and detailed documentation. -How should I plan my Marketing budget for next year?  -How do I structure my Google Ads account? -How do I forecast my Demand Gen spend and impact for next year? -What are the most important KPIs to present at my Marketing QBR? -What metrics should I use to optimize my LinkedIn ads? -How do I launch Connected TV ads? -What are the best creative formats for Reddit ads? -How do I launch a podcast in less than 30 days?  -How do I implement all of the Demand Gen data and tracking in my CRM? The questions and answers are literally infinite. And the library of data, research and information is growing every day. __ Now, you don't need to bet your career or next year’s financial performance on a random blog you found in Google or anecdotal answers you got in a Slack community. Most of the information you find on the internet today about Demand Gen is outdated, written by someone in the Philippines (or now written by AI), anecdotal at best, not backed by data, and likely irrelevant to your situation. DemandGPT gives you instant answers, frameworks, best practices, implementation roadmaps and more with: -Contributions from more than 100+ leading Demand Gen experts like Sidney Waterfall, Sam Kuehnle, Ashley Lewin, Christian Williams, Tara Panu, Chris Walker, and so many more. -Data and learnings published from work at over 200+ of the leading B2B companies.    -Learning and insights gathered from more than 450,000 collective hours of work, tests, and data analysis There’s never been a more comprehensive hub of information to plan, launch, and optimize your Demand Gen strategy. #marketing #demandgen #AI #strategy p.s. You can get 15% off all Vault plans powered by DemandGPT using the coupon code "Chris15" at checkout. Offer valid until May 15, 2024 ✌️

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What's the difference between correlation and causation in media measurement? Correlation: Consumer sees an ad and makes a purchase. The ad must have caused the purchase. Causation: When we stopped running this ad in this test market, we saw sales drop X% in that same market, compared to control markets. The media is causing this many sales. The question remains, how do brands get to causal measurement? Mahesh Jeswani, Measured's SVP of Product breaks down how brands are leveraging automating geo-testing to uncover the cause and effect relationship between marketing sales. Don't sleep on this Q&A session! 🔥 #mediameasurement #geoexperiments

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Bonus point for the F*ck Survey Fraud shirt, Roddy! Good challenge to the industry about what we have done to create the current situation we are in where data quality is still an issue. First, he unpacked the MRX monster: - constrained budgets - pricing pressure - disengaged participants - survey farms and more sophisticated organized fraud - more bots (non-human) “participants” - AI being used for open-ends The answer is that instead of focusing on CLEANING the data we should be getting focused on it being real, representative and reliable data by not allowing fraud to even get into the survey. It’s a commitment to addressing the root of the problem and not spending money just mopping things up. There’s the dtect differentiation for sure. He had some really great figures to understand the actual hard and soft costs of fraud. Why do we find this totally acceptable??? Also fun scratch ticket below. Great presentation. At Quirk's Media here in New York. Little Bird Marketing #quirks #mrx

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Behind-the-scenes sneak peek at our future podcast episode where we’re doing a deep dive into: Google Performance Max. I sat down with Alex Kemp, our Director of Applied Analytics at Cardinal to talk about: ⭐The pitfalls of using PMAX incorrectly ⭐Why you shouldn’t use PMAX for lead generation ⭐How marketers can achieve better results with PMAX ⭐And more! Our episode drops on June 18th, so be on the lookout!

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If I was going to drive velocity at Target… …here’s how I would do it. Up front: Retail media supplements your demos and in-store promotions and other velocity tools. IMO, budget should be shared between them. The right mix usually depends on product type. But from a Retail Media perspective, here is how you do it: 1. Instacart Sponsored Product. -> Target-unique SKU’s allow us to focus on Target directly. 2. Instacart Display. -> Behavioral targeting, such as lapsed customer. 3. Criteo. -> Same as Instacart, but for Target.com customers. 4. DoorDash. -> Same as Instacart, but for DoorDash customers. (DoorDash is very hard to get into. Depending on total door count, we may be able to help.) What ROI are you going to get? It depends on a few factors: 1. Door count matters. ⬆️ doors, ⬆️ ROI. 2. Product type can influence ROI heavily. 3. Manual bidding, ⬆️ ROI. Auto bidding, ⬇️ 4. The longer you’ve been in-store, the ⬆️ your ROI. Oh, and great news for Frozen, refrigerated, dairy, produce, etc. You’re going to play this game on easy mode. Need help? 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 #royalfarms

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Churn prevention hinges on effective multi-threading. Here's a strategy I've used to wake the dead and build more champions. ↓ → Review an account list of your best-fit customers and identify where 2 or fewer actively engaged users. → Bucket those inactive users into categories of personas. 💡Tip: If you're using a solution like UserGems 💎, you can automatically categorize these users into specific personas and have them alert you in your CRM when similar personas are at your account. → Identify active users in your customer base that match the personas of the inactive users. → Create a matching program for the two groups (this can live inside your community forums or platforms) to connect and learn from one another. (Meetsy powered by Commsor 🦕 provides an automated matching program for individuals to engage without any interference from sales or marketing, allowing for conversations to remain largely unbiased and organic). 💡Tip: Provide topic prompts such as "What is the most surprising/underrated feature that [SOLUTION NAME] offers that you can't live without?" → Alert the account team on matches that occurred each month and plan a course of action for CSM and account owners to re-engage with inactive users to see how they incorporated the feedback. (Note that marketing has ample opportunity to share 1st party intent data from website and product usage to see how their adoption with the brand and platform has increased since matching, enabling the account team to be more personalized in their outreach). → Create content (audio, video, text) that highlights the use case and share it with customers, maybe even give a nod to the customer who came up with the innovative way to use your product! Rinse, repeat. Tactics like these can act as a shield for your future revenue and help you build champion relationships that last.

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Why are the knives out for ARPA 3.0? Claiming it's too strong? 🎈Advertisers, business groups want ‘significant changes’ to data privacy bill https://lnkd.in/e6zYwVjb 🎈Ad trades blast reworked data privacy bill https://lnkd.in/e8FkW93m 🎈House GOP leaders vow to block online privacy bill over intraparty pushback https://lnkd.in/eU6xBk5z (I think it's still soft on brokers and bad for consumer privacy, pushing a broken notice & consent model.) -- Is it a negotiating tactic to get more concessions? -- Is it a trap to make everyone think the current APRA bill is actually a strong privacy bill that will protect consumers? -- Are politicians feeling safer backing data brokers after lobbyists defeated the Vermont bill? What are your thoughts and feelings on APRA 3.0, privacy pros? ♥️ love it? 🤬 hate it? 😩 would hold nose and vote for it? Jodi Daniels, Hilke Schellmann, Cameron Ivey, Joe Toscano, Punit Bhatia 🔐 🌐, Todd Fitzgerald, Kimberly L. #apra #privacy #privacylaw #knivesout

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Retail Media Benchmarks A cheat sheet on how to grow the average Retail Media business **Hint: there's plenty of upside on-site** EMARKETER & Andrew Lipsman estimate that through 2027, ~70% of net new growth will come from on-site On-site gets double the ROAS, and is much higher margin too Rules-based complexity precludes many brands from adopting Retail Media Smaller websites (<36m visits) tend not to warrant as much advertiser time and attention Across global Retail Media, advertiser adoption is probably half baked, representing +60% upside through technology and operational improvement alone i.e. self-service will not scale until ease of use, and time to results is improved Outside of FMCG, search alone offers a comparatively smaller advertising opportunity Data from Particular Audience shows that in the most extreme cases, manual keyword approaches can make up less than 10% of Retail Media ad spend for slower moving consumer goods (!!) With PA's AI/ML deciding optimal timing and placement of sponsored products for the remaining 90% >>> demonstrating headroom an order of magnitude (10x) greater for similar retailers ONLY running manual keyword ad formats today So how do you: 1. Increase ad opportunities 2. Increase customer engagement 3. Increase advertiser adoption Slide right! #RetailMedia #Automation #AdTech #Ecommerce #AI

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The Product Marketing Alliance just issued their 2024 State of #PMM report.... And one REALLY telling survey chart has to do with the PMM TechStack. Dominating the list are core tools (analytics, reporting, CRM, collaboration, market research etc.). These are *great* benchmarks to help younger PMM teams decide where their gaps lie. But what I find interesting is that there are also a number of Demand Generation items on the list (email marketing, video marketing). Shouldn't these be owned by other teams? Or, do they just naturally fall into PMM? https://lnkd.in/g6KAccB4

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We're moving to "prompt-to-product," not just task automation. I think AI's longer term economic impact won't just be automating an increasing number of STEPs. It will be converting many PROMPTs directly to PRODUCTs. For example, in the movie industry, right now people think about AI automating things like script writing, scene generation, soundtrack generation, speech generation, all as discrete steps or tasks. But I no longer think that's the longer term outcome. Within a few years we'll have increasingly multimodal models that can do EVERYTHING in one step. Like, you'll be able to enter a prompt, and get back a full movie, with the script, video, soundtrack, and speech all generated together. I may be wrong, but this seems to be the way things are trending. For example, the full GPT-4o multimodal model can output text, speech, sound effects, and images (and possibly even more), and combine them, such as by including sound effects while narrating a story that it's generated. I think we're going to see this across an increasing number of modalities, ultimately leading us to a prompt-to-product future.

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This is so great to see! As we head into the Upfronts and Newfronts, brands need to know they can reach a massive audience, using video, that doesn't get skipped or ignored and is 4x more efficient on a cost per second viewed metric. Efficiency AND Impact from In-Scene Media #uninterrupted #advertising with #AI

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Three Things I Learned In SaaS, Sports, Tech, & Live Events:   1. They really will steal from you.   In the early days of TicketManager, we’d get calls from “Strategics” looking to “learn more” or “invest.” They’ll say things like they “have sincere interest” to get you to let your guard down.   Everyone around us told us this was normal. Don’t be too guarded. Just build and trust that they won’t steal from you. They almost shamed us for being so arrogant as to think others would take their time to steal from us.   They were wrong.   They all stole from us.   GMR, a major agency, feigned interest and even attended our customer conference in the mid-10's. They hit the market with a copycat just over a year later.   MSG took us to the contract phase—even assigning a project manager—and then built a cheap copy that looks exactly like our tech. The UI is so similar.   A private equity software currently for sale told us, after we rebuked their interest following two months of diligence, they were going to build a competing product. I respect they did.   A major, now public, ticket marketplace spent months in diligence with us then, in the StubHub case six years later, tried to testify they didn’t have “any real interest” in doing the deal and their IOI was “just preliminary.” (On the bright side, they were a star witness for us. They tried to bury us and it was so gross it backfired.)   And StubHub spent two months feigning interest in us before deliberately trying to crush our business, leading to four years in court and a $16m judgment.   Investors and bankers are wrong. Guard it all and protect yourself.   Yes, some sell and that’s the process, but others are just phishing. Protect your fish as best you can.    2. "I don’t give b--w jobs but I know when it's being done wrong"- Bill Maher.   When starting a business or becoming a new leader, there is so much pressure to let your team do their job and trust the experts around you. And that's great advice - most all of the time. But….there will be times those teammates or advisors have bad ideas. And you know they're bad ideas.   When that happened, I found it hard to stand up for myself.   An example: Back in 2013, right before we signed our largest customer, two of our advisors were adamant we sell the business for $10m and "find something more scalable." They spent an entire drive to dinner trying to convince us it was the right course of action and leaning on their vast experiences. I'm glad we didn't listen.   3. Scott Galloway is wrong: Part one million   Walking through baggage claim on Wednesday returning from the All-Star Game I mentioned to my wife I'd be working long hours the next few days as I'd been out of the office Monday and Tuesday.   Her response: "Tony, I didn't see you. You were at work events from the minute we landed"   Ignore the cynics. They only know their own path.   Do what you love and you won't work a day in your life. 

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