Arunas Vismantas

OTTO just handed sellers a new lever, manual keyword targeting for Sponsored Product Ads. Beta results show +120% ROAS and +50% CTR when brands take control. This is a big shift for Germany’s homegrown giant. Instead of relying only on contextual placements, you can now bid on the exact search terms shoppers type on otto. Booking runs in Partner Connect, you get an automated keyword report, you can mine auto-suggest, and you set bids per term. In practice, this puts OTTO closer to Amazon’s style of control, with EU retail media nuances. What it means 🔑 Precise query control, fewer irrelevant clicks and cleaner intent. 💸 Comparable CPCs and ROAS to benchmark, easier budget moves from awareness to intent. 🧩 Smarter mix, keep automated SPA for discovery, harvest winners into manual sets. ⚙️ Flywheel effect, search learnings feed titles, attributes, pricing and stock. What to do this week 🧪 Start with margin-safe heroes, confirm price, stock and delivery accuracy in ChannelEngine. 🎯 Seed 25 to 50 core queries per cluster from titles, attributes, synonyms and OTTO auto-suggest. 🧱 Build tight ad groups by use case or subcategory, set conservative starting bids and expand. 🔍 Read the keyword report frequently, add new winners, pause low quality terms fast. 📊 Track CTR, CVR and ROAS at query level, shift budget toward proven intent. Operator lens, this is German precision for your search spend. If you already run OTTO via ChannelEngine, a two week test is enough to see if keyword control beats your current automated SPA baseline. Curious which queries you would bet on first for your category? #OTTO #RetailMedia #MarketplaceAds #ecommerce #ChannelEngine

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According to iBusiness, 84% of the top 100 SEO agencies in Germany offer GEO services. For 30% GEO is already a top focus area. For 7% GEO is the number 1 priority!

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How I structured an account with 25,000 SKUs and different price points: We split our approach based on product price: 1. Low-ticket items: - Great for new customer acquisition - Can't deliver high ROAS immediately 2. High-ticket items: - Different pricing strategy needed - Higher profit potential Our solution: Structure for low-priced products: - Based on forecasted conversion rates - CPC cap with Max Clicks - Focus on cheap traffic Structure for high-value products: - Feed-only PMax campaigns - tROAS bid strategy Current results: - First optimization rounds completed - Some campaigns hit 5+ ROAS instantly - Others showed clear signals about AOV limitations The structure keeps evolving as we learn and adapt. My goal here is to show what structured, hybrid approaches can look like - instead of blindly going “all-in” on one campaign type. Just take a bit more time to think and don’t be afraid to approach the task creatively.

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When our search traffic started dropping about two years ago, we doubled down on SEO: did more primary research, published more content, updated content more frequently. And still, our Google traffic didn't grow. At first, it was probably just the algorithm & competition muting our extra effort. But as gen AI rolled out in search, it became clear: search engines becoming answer engines were killing the economics of educational SEO. Our blog content had always been a key pipeline driver. It generated search traffic and product signups. More importantly, it built up our domain authority up & helped us rank product-related content. We had a limitless amount of content we could create. Our 100+ integrations gave us an endless amount of topics. We published 5x/week at our peak.   But now, AI started giving those answers directly, without ever sending them to our site. Two quarters ago, we made a hard-right shift. We stopped fighting for Google scraps. And started showing up where conversations were actually happening. 👉 I went all-in on LinkedIn publishing. We began planning a small number of multi-format, multi-channel campaigns. We did more on other social sites, especially Youtube. But measuring impact? That’s where things got tricky. Getting someone to click from social to our website: not easy. The traditional marketing attribution models didn't capture the full picture.   So we built a new approach: 1. 𝗢𝗻-𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝘀𝗶𝗴𝗻𝗮𝗹𝘀. Impressions, engagement, follower growth. These tell us what content is resonating. It’s hard to prove that reach & engagement drive business, but it certainly gives direction on what content and topics might inspire action. 2. 𝗗𝗶𝗿𝗲𝗰𝘁 𝗮𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻. We still link to other content (events, research reports, surveys, dashboard templates, etc). We have no shortage of offers that can drive a conversion and we don’t have a problem creating social content that highlights those offers in interesting ways. 3. 𝗦𝗲𝗹𝗳-𝗿𝗲𝗽𝗼𝗿𝘁𝗲𝗱 𝗮𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻. We ask everyone who signups for our product, “How did you hear about us?”  It’s not perfect since they could lie on that form just to get past it, but the data is pretty consistent month over month. (If you want to see this data, follow me and click the bell. I’ll be sharing it.) 4. 𝗕𝗿𝗮𝗻𝗱𝗲𝗱 𝘀𝗲𝗮𝗿𝗰𝗵. Most readers don’t engage publicly on social media. But they remember. And weeks or months later, they show up in our CRM via branded search or a direct visit. Today, we get about ~27% of our signups from social media. So yeah, the shift worked. Not because social publishing replaces SEO. It's actually harder. But because it does something SEO no longer can: build preference before someone is even looking. PS. Wanna know if you're ahead or behind in transitioning your marketing strategy? We'll be revealing data we've collected from 300+ companies next week. Register for a seat -> https://lnkd.in/ePXBt9Mj

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ChatGPT is about to disrupt affiliate marketing—completely. There’s talk that OpenAI and Shopify are joining forces. Soon, users will be able to buy products directly inside ChatGPT—no ads, no clicks, no Google searches. Just seamless, in-chat purchases. Instead of monetizing through ad space, OpenAI would earn a commission on each sale. Case in point: I recently used ChatGPT to research a Polaroid camera for my kids. It helped me compare models, weigh pros and cons, and evaluate prices. But when I was ready to buy? I had to copy the product name and search for it elsewhere. That step is likely going away. From a user perspective, it’s frictionless. From a brand perspective, a commission model may be more attractive than paying for ad traffic that doesn’t convert. But this raises serious questions for businesses: How does a product get recommended? Will Shopify stores receive preferential placement? Can OpenAI truly ensure unbiased results? AI isn’t transparent—and visibility in ChatGPT could be a mystery. Will recommendation-driven sales be stable? Most brands will still want to supplement with paid visibility. OpenAI may resist ads for now—Sam Altman has stated he prefers commissions—but history suggests advertising always finds its way in. Which brings us to the bigger question: Why didn’t Google do this first? Because Google was upstream. Users searched for product recommendations, landed on affiliate listicles, and those third-party sites earned the commission. But LLMs like ChatGPT change everything. They don’t just assist in decision-making—they complete the entire purchase journey. No clicks. No websites. No payouts to content creators. The entire affiliate marketing model is about to be rewritten.

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🔥 3 pricing models. Same economics. Radically different results. Imagine selling a $200 product in an online marketplace. You know you’ll have to pay the marketplace a commission. But which would you rather pay? • Model A: Flat fee of $10 • Model B: $3 flat fee + 3.5% commission • Model C: 5% of sale price • Model D: You are Indifferent On paper, all three are identical. In each scenario the commission equals $10. 💭 Classical economics assumes we’re rational. If that were true, everyone should have picked Indifferent as all outcomes are the same. 👉 But when we ran this breakeven test across thousands of customers for a marketplace client, almost nobody did. Did you? And it doesn’t stop there: we’ve run similar break-even experiments at over a thousand companies. The “Indifferent” option has never won! 🚀 Lessons for founders: 1.     How you charge matters more than what you charge. 2.     Even identical economics can create wildly different customer behavior. 3.     => Pricing models need to be tested relentlessly — customers will always reveal more than your spreadsheets. I call this the Mental Model Axiom in my new book, Scaling Innovation. It’s one of many ways pricing exposes the myth of the “rational buyer.” 📚 If this resonated, you’ll love Scaling Innovation. Get a copy of the book now. It’s filled with these kinds of aha moments → https://a.co/d/dgyqdWP What’s the most surprising Pricing and GTM insight you’ve seen in your work?

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Remarketing spend hit $16.4B in 2024… 3.5× more than UA. During peak season, 85% of iOS budgets went to remarketing. Marketers are doubling down on LTV. But many still see influencer marketing as purely upper funnel. That’s a mistake. In the campaigns I run, influencers don’t just drive installs, they: ✅ Reactivate past users ✅ Trigger second purchases ✅ Reinforce brand value when it matters most Influencers can supercharge remarketing by: - Creating custom content for audiences who clicked an influencer’s affiliate link but didn’t purchase - Running Instagram Story ads targeting users who engaged with a sponsored post but didn’t follow or buy For example: If an influencer shares a skincare launch and people click through but don’t check out, you can later retarget them with a carousel ad featuring a time-limited discount or a relatable testimonial, right when they’re more likely to convert. 📣 My take: Creators don’t just drive discovery, they reinforce intent. If your remarketing mix doesn’t include influencer content, you’re leaving results on the table. 📊 Want to see the full picture? Get the latest data on UA trends, iOS loyalty, and why remarketing now dominates eCom budgets. Read AppsFlyer’s full 2025 State of eCommerce App Marketing report here: https://lnkd.in/e7_6kSQC

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What's changed in ecom SEO? Google turned search results into a shopping mall. After analyzing 35,000+ shopping queries, here's what happened in 2025: - AI Overviews replaced traditional product grids - Image packs jumped from 60% to 90% of searches - People Also Ask features increased while Reddit/forum content declined - Videos are getting pushed out by visual content Here's what to do: 1. Search your products in ChatGPT, Claude, and Google AI Mode - screenshot every mention or absence 2. Update your top product images with better alt text and lifestyle shots showing products in use 3. Add structured data markup to all product images 4. Convert your buying guides into FAQ format with clear questions and answers 5. Create "People Also Ask" style questions on product pages 6. Build comparison content using "X vs Y vs Z" format 7. Track your brand mentions in AI Overviews, not just organic rankings 8. Add schema markup for FAQs, products, and reviews 9. Focus on structured, scannable content over long-form descriptions 10. Optimize for conversational queries like "help me find" vs "what is the best" The brands winning aren't the ones with the best products they're the ones with the most AI-friendly content structure. P.S. At Taco, we help you rank on LLM's. If you need an audit on how you are ranking, dm me with the word 'Search' and we'll conduct an entire site audit. P.P.S. What is the ROI from your content team?

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