DinMo

🎙️ 𝗗𝗮𝘁𝗮 𝘀𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻𝘁𝘆, 𝗰𝗹𝗼𝘂𝗱 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲, 𝗴𝗲𝗼𝗽𝗼𝗹𝗶𝘁𝗶𝗰𝘀! In the latest episode of Couch Confidentials, Oussama Ghanmi, CEO of DinMo, joins Matthew Niederberger, founder of Martech Therapy, for a deep dive into one of today’s most pressing questions: 𝗜𝘀 𝗶𝘁 𝘀𝘁𝗶𝗹𝗹 𝘀𝗮𝗳𝗲 𝘁𝗼 𝘁𝗿𝘂𝘀𝘁 𝗨𝗦 𝗰𝗹𝗼𝘂𝗱 𝘁𝗼𝗼𝗹𝘀 𝘄𝗶𝘁𝗵 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮? This conversation explores the shifting landscape of tech independence in Europe: What are the risks tied to foreign jurisdictions? Why is digital sovereignty becoming a strategic priority? How do composable CDPs ensure both agility and compliance? Curious to learn more? Don’t skip this one 🎧 Listen to the full episode — links just below in the comments #ComposableCDP #DataPrivacy #EuropeanCloud #CloudSovereignty

𝗕𝗶𝗴 𝘄𝗶𝗻𝘀, 𝗻𝗲𝘄 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀, 𝗲𝘃𝗲𝗻𝘁 𝗿𝗲𝗰𝗮𝗽 — 𝗮𝗹𝗹 𝗶𝗻 𝗗𝗶𝗻𝗠𝗼’𝘀 𝗹𝗮𝘁𝗲𝘀𝘁 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿! From exciting international wins to product updates and major events across Europe, there’s a lot to unpack this month 🚀 👇

Your data project isn’t being blocked because it’s technical. It’s because the business don't care enough...   As data teams, we're often deep in the weeds of technical jargon—ETL, machine learning models, data governance, and whatever else. But here’s where I see the challenge: the success of data initiatives depends hugely on cross-functional buy-in. To get the buy-in from stakeholders across departments, we need to translate our data projects into something that resonates with their objectives, and ultimately makes them care.   Here are my top strategies that can help you achieve this 👇   1️⃣ Start with business goals Always begin by tying your data initiative to the business objectives. Whether it's increasing revenue, or improving customer experience, make it clear how your data project directly supports the company's strategic goals. 🔑 Example: Instead of saying "we’re implementing a data lake," say "this project will help us deliver personalised customer experiences that can increase conversion rates by 25%."   2️⃣ Use their terminology Different departments speak different languages. Make sure your data initiative speaks directly to their goals and pain points. 🔑 Example: For the marketing team, talk about how customer segmentation will improve targeting, leading to more effective ad spend and better engagement rates.   3️⃣ Highlight quick wins & tangible benefits Nobody wants change unless it has a direct positive impact on their role. Show quick wins and tangible outcomes to build momentum and prove the value early. 🔑 Example: Data quality improvements can quickly lead to more accurate sales forecasts, saving time and reducing mistakes in financial planning.   4️⃣ Frame data initiatives as problem-solvers Data must be about solving real business problems. Frame your data project as a solution to specific challenges faced by the business. 🔑 Example: Instead of "we’re improving our data governance," use "this will ensure data accuracy, which improves decision-making and trust across departments."   5️⃣ Collaborate Early and Often Bring in stakeholders early—before you finalise the project scope. This collaboration will align the project with business needs, and everyone will feel involved in the process, increasing their commitment. 🔑 Example: Sales, marketing, and finance teams should be consistently inputting and testing to validate direction and outputs.   6️⃣ Use your data storytelling powers with visuals Good, visual aids like dashboards, charts, and infographics can communicate how the data initiative will benefit the business - this is a data persons superpower.   🔑 Example: Show stakeholders a live dashboard prototype (even a mock-up works) that highlights the decisions they can now make Ultimately, the success of your data initiative depends on alignment. By speaking the language of your stakeholders and focusing on business outcomes, you’ll unlock the full potential of your data strategy 🚀

🚀 𝗪𝗵𝗮𝘁 𝗮𝗻 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲! Our DinMo team had the pleasure of attending the Retail Technology Show in London, one of the UK’s leading retail events, bringing together the most innovative minds in tech and e-commerce. Those two days were full of great meetings, inspiring exchanges, and valuable discussions around real-time customer data activation. A huge thanks to everyone who took the time to visit us! We truly appreciated the meaningful exchanges and shared passion for data-driven growth. 👏 Hats off to the Retail Technology Show organizers for creating such a dynamic and forward-thinking space. If we did not get a chance to meet, it's not too late. Feel free to reach out to our team for a chat! Edward Gibbs Alexandra Knight David Bentham Logan Woodbridge  #RetailTechShow #ComposableCDP #RetailTechnology #DinMo

What happens when your customer data is governed by the wrong jurisdiction? In this episode of Couch Confidentials, I sit down with Oussama Ghanmi, CEO and co-founder of DinMo, a composable CDP vendor headquartered in Paris. With growing political tensions between the US and Europe, and cities like Amsterdam actively moving away from US-hosted platforms, I wanted to understand whether it’s still safe (or smart) for European companies to continue relying on US-based cloud tools. Oussama offers a candid look at the risks European businesses face when their data leaves the continent, and why composable, locally governed architectures are gaining traction. We also talk about building privacy-first tools, data sovereignty, and what it takes to offer enterprise-grade CDP capabilities without compromising on control. This episode is equal parts geopolitics, growth strategy, and a reminder that where your data lives, really does matter. 🎧 Watch/listen to the episode on my Substack channel (https://lnkd.in/eX-ukGNH) or on Youtube (https://lnkd.in/eeQJFTH4). #composablecdp #dataprivacy #gdpr #customerdata #martech #datagovernance #europeancloud #dinmo #cloudsovereignty #saasfounders #martechtherapy #couchconfidentials

AI alone won’t save your customer experience. There’s a common misconception that simply adopting AI will automatically enhance your customer journey and skyrocket your growth. But after working closely with companies leveraging customer data, I’ve realized: AI without operational empathy and execution often fails. Why? 1. AI amplifies what’s already there—both good and bad. If your foundational customer experience is poor, AI will only magnify that. 2. Operational readiness beats AI sophistication every time. Teams overly focused on AI tend to overlook simpler, quicker fixes that provide real value. 3. Relevance matters more than personalization. Your customers don’t care how sophisticated your AI models are—they care about relevance, clarity, and ease of interaction. Instead of chasing shiny AI features, first ask yourself: - Is our core customer experience clear and user-friendly? - Have we addressed operational bottlenecks? - Are we using AI to enhance relevance, rather than complexity? Start with operational empathy. The results will follow. What’s your take? Have you seen AI projects falter due to ignoring these principles?

 🚀 𝗪𝗲 𝗮𝗿𝗲 𝘁𝗵𝗿𝗶𝗹𝗹𝗲𝗱 𝘁𝗼 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲 𝘁𝗵𝗮𝘁 𝗗𝗶𝗻𝗠𝗼 𝗵𝗮𝘀 𝗯𝗲𝗲𝗻 𝘀𝗲𝗹𝗲𝗰𝘁𝗲𝗱 𝗮𝗺𝗼𝗻𝗴 𝘁𝗵𝗲 𝗖𝗹𝗼𝘂𝗱 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝗿𝘀 𝗧𝗼𝗽 𝟭𝟬𝟬 – 𝟮𝟬𝟮𝟱 𝗲𝗱𝗶𝘁𝗶𝗼𝗻! The Notion Cloud Challengers Report identifies companies that have the potential to disrupt markets, achieve significant growth, and become tomorrow's industry leaders. It’s an honor to be a part of it. This recognition rewards our vision, the value we deliver, and the daily dedication of the entire DinMo team to rethinking how companies leverage Customer Data Platforms! A huge thanks to Notion Capital and Google Cloud for this recognition, as well as for the outstanding work behind this report. Our sincere appreciation also goes to Jos White, Kamil Mieczakowski, Radu Bozga, Michelle Cheng, and Claire Walker for their essential contribution to this benchmark publication.  The 2025 edition highlights several key trends: 💡  49% of selected startups are AI-native 🌍  69% are based in France, Germany or the UK 🔥  And most impressively, Cloud Challengers have raised over $500M in just one year 👏 Congratulations to all the startups selected this year! Your ambition and capacity for innovation are shaping the future of B2B software in Europe and beyond. kapa.ai, Understory, Kerno, Octomind, phospho (YC W24), dltHub, Stackfix, Runware, Crafthunt, Langdock, Workflow, Volter, fynk, Symbe, Phare Health, GlassFlow, Anam, Neuphonic, TORTUS, atla, Lovable, Stema, Round Treasury, simplyblock, montamo, Pruna AI, Langfuse (YC W23), Verax AI, Albatross AI, Quesma, Tibo Energy Management Software, FERO 📥  Curious to see the full ranking and insights? Find the report in the comments! #CloudChallengers #Top100 #AI #CustomerDataPlatform

Migrating legacy data systems to the cloud: what you won't hear from your new vendor in the sales pitch?   I always see cloud migrations promise a lot—scalability, performance, cost savings.   But most of the time, its more like delayed deadlines, blown budgets, and business users still stuck exporting CSVs   Why? Because most migrations start with a tech-first mindset, not a strategy-first one.   Here’s what I’ve learned from real-world migrations 👇   𝐖𝐡𝐚𝐭 a𝐜𝐭𝐮𝐚𝐥𝐥𝐲 w𝐨𝐫𝐤𝐬:   1️⃣ Start with business-critical use cases, not just “migrating tables” In a recent migration, we prioritised rebuilding the sales forecasting dashboards (used weekly by the CRO) over warehouse tables no one had touched in months.   💡 Impact-led migrations always gain more traction internally.   2️⃣ Respect the complexity of legacy systems You’ll find SQL logic embedded in Power BI reports, Excel macros linked to Access DBs, and ETL scripts no one has touched in years, but still run. Don't migrate what you don't understand.   💡 Use tools to map undocumented dependencies before you break something critical, and take the time to truly understand use case and value   3️⃣ Refactor incrementally   Trying to migrate AND re-model everything into a new dbt framework in a single sprint is high risk. And makes reconciliation 10x more time-consuming. The result? Broken pipelines, and a complete lack of trust from stakeholders.   💡 Decouple migration from transformation. Replicate first → validate → then rebuild models the right way   4️⃣ Validate with the business — not just in dev   Your numbers might match row for row, but if the marketing team’s dashboard gives a different revenue figure than the new one, they won’t use it.   💡 Set up a 30-day parallel run with sign-off from business leads on mission-critical reports   5️⃣ Get ahead of access and ownership One team migrated without defining who owned the tables in Snowflake post-migration. Chaos ensued. You MUST map your stakeholders as much as your systems.   💡 Define ownership, access levels, and SLAs before launch 𝐖𝐡𝐞𝐫𝐞 𝐦𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐜𝐚𝐧 𝐟𝐚𝐢𝐥:   🚫 Lift-and-shift mentality - don't just migrate bad models and flaky pipelines to the cloud   🚫 Underestimating tech debt - take time to really understand legacy systems and the years of undocumented logic built into them   🚫 Over-investing in tools, underinvesting in people - buying Snowflake and Fivetran won’t solve anything if your data analysts are still waiting on engineering to deliver tables.   🚫 Not setting a clear data ownership model - Who owns the transformation logic? Who manages data access? If these aren’t clearly defined pre-migration, you’ll be stuck firefighting post-migration. 💬 What lessons have you learned from migrating legacy systems to the cloud?   #CloudMigration #DataEngineering #ModernDataStack #DataOps #DataArchitecture #DataLeadership #Snowflake #dbt #AzureData #CDAO

Instinct ou données : en qui avoir confiance ? 🤔 Le timing et la pertinence sont la clé d'un média e-commerce. Vous publiez le bon contenu au bon moment, et c’est un succès. Vous ratez la cible, et votre post disparaît dans l’oubli. Alors, faut-il faire confiance à son instinct… ou aux données ? L’instinct joue un rôle. Avec l’expérience, on arrive à repérer les tendances avant qu’elles n’explosent. Mais s’appuyer uniquement sur l’intuition, c’est prendre le risque de se tromper. 👉 C’est là que les données entrent en jeu. Elles permettent de confirmer (ou d’infirmer) une intuition, de révéler des opportunités cachées et d’affiner sa stratégie en continu. Le problème ? Exploiter les données n’est pas toujours aussi simple qu’il devrait l’être. Entre les silos de données, l’accès limité aux insights et la dépendance aux équipes tech, les entreprises passent plus de temps à chercher l’information qu’à l’utiliser. Et ce n’est pas qu’un problème lié aux médias : les équipes e-commerce vivent exactement la même chose. Beaucoup de données, peu d’actions, car accéder aux bons insights relève du parcours du combattant. Sans une vision claire et accessible, optimiser ses campagnes, personnaliser l’expérience client ou améliorer son ROI devient un jeu de hasard. C’est exactement ce que DinMo résout. Avec son CDP composable, la donnée devient immédiatement exploitable, sans créer de dépendance entre les équipes : ✅ Les équipes marketeting accèdent directement aux segments dont ils ont besoin. ✅ Les data teams gardent le contrôle et évitent la surcharge. ✅ Les décisions sont alignées entre le marketing, le support et au-delà. Fini les jours d’attente pour transformer les données en actions. Envie d’en savoir plus ? Je vous partage ce lien ➡️ https://bit.ly/nchevalier

🎙️ 𝗨𝗻 𝘄𝗲𝗯𝗶𝗻𝗮𝗿 𝗿𝗶𝗰𝗵𝗲 𝗲𝗻 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗲𝘁 𝘂𝗻 𝗿𝗲𝗽𝗹𝗮𝘆 𝗱𝗶𝘀𝗽𝗼𝗻𝗶𝗯𝗹𝗲 𝗱𝗲̀𝘀 𝗺𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝘁 ! Merci à tous et à toutes d’avoir participé à notre webinar "CDP Composables, l'approche idéale pour réduire ses coûts tout en augmentant son impact", avec fifty-five. 💡 Vos questions et votre participation active ont rendu cette session particulièrement riche. Ensemble, nous avons exploré les enjeux clés autour de cette nouvelle approche des Customer Data Platforms. Lors de ce webinar, nous avons partagé : ✅ Les bénéfices concrets d’une CDP composable ✅ Le stade de maturité data auquel cette approche devient pertinente ✅ Des exemples concrets qui montrent comment structurer un projet composable étape par étape 🎥 Vous avez manqué la session?  Le #replay est désormais disponible (lien en commentaires) vous permettant de revisiter les moments partagés par Oussama Ghanmi, CEO chez DinMo et Philippe Kuhn, E&I Director chez fifty-five. Assurez-vous de ne rien manquer et de profiter pleinement des connaissances partagées ! #CDPComposable #DataStrategy #MarTech #Personalisation Aymen Ben Guirat Jean-François Wassong Pierre Harand DEBORAH CARUGE Clément Sirvente Alexandra Augusti Anouck Geday