Real-World Case Studies and Customer Success Stories with Datatonic

Datatonic used Google Cloud, BigQuery, and Looker to help ASOS improve its marketing analytics. ASOS wanted to give its marketing team real-time, personalized insights and a single source of truth. D...atatonic built a Centralised Marketing Dataset (CMDS) to automate and scale reporting. The new system centralizes over 1 billion events daily from 9 platforms, improves reporting speed and accuracy, and enables self-service analytics. ASOS now makes faster, data-driven marketing decisions and runs more efficient campaigns.
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Datatonic helped Babyshop, a leading online retailer, improve its MLOps with a Google Cloud workshop. The team enhanced a machine learning pipeline using Kubeflow Pipelines. They focused on reusabili...ty, rapid experimentation, and automation. Babyshop now trains models at scale and uses best practices for pipeline code. The solution reduced manual work and sped up production.
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Datatonic built an image recognition system for Crocus using Google Cloud. The system identifies over 5,000 plant species in under 30 seconds. Crocus needed a fast, scalable solution to help customer...s identify plants and get care tips. Datatonic delivered a model that is easy to maintain and scale. The solution powers Crocus' Iris gardening app, making plant identification simple for users.
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Google Cloud Retail API helped Felleskjøpet boost conversion rates by 38% for "Others also bought" and 25% for "You may also like" recommendations. The retailer improved customer experience with pers...onalized product suggestions and more accurate search results. Felleskjøpet reduced the number of search refinements, making it easier for customers to find products. Datatonic led the implementation, optimizing data handling and search engine performance.
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Datatonic helped Gopuff migrate data from Redshift to Snowflake, improving analytics for global expansion. Dashboard load times dropped from 30 minutes to seconds, speeding up decision-making. The te...am refactored Looker assets to create a single source of truth. Over 500 micro-fulfilment centres saw reduced inefficiencies. Gopuff now has a stronger data infrastructure for essentials delivery.
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Datatonic used Google Cloud and machine learning to redesign INTERSPORT's store segmentation. INTERSPORT has over 5,400 stores in 57 countries, each with unique needs. The new segmentation model grou...ps stores by product mix and revenue, helping INTERSPORT offer better product recommendations. This approach simplifies supply chain decisions and improves supplier negotiations. The solution aims to increase sales and reduce decision-making complexity.
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Datatonic used Google Cloud and machine learning to help a leading online retailer predict customer lifetime value. The retailer wanted to improve digital media spend by finding high-value customers.... Datatonic built a model with over 270 features in five weeks. The automated workflow retrains daily and improves audience targeting for paid search and social. The retailer now finds high-value customers that were missed before and optimizes marketing spend.
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Datatonic used Google Cloud and machine learning to help a top UK retailer predict which brands customers will buy next. The new solution made purchase predictions 1000x more scalable and 100x faster..., processing 10 billion scores in hours. Accuracy improved by 3% in GINI score. The retailer's marketing team can now act on insights quickly and personalize product recommendations. The Customer Insights team uses data from thousands of touchpoints for better demand forecasting.
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Datatonic helped LUSH improve their Lush Lens app using Google Cloud and machine learning. The new image recognition model increased f1-score from 45% to 98%. LUSH now has a cross-platform solution f...or Android and iOS. The automated ML pipeline lets LUSH retrain models as new product images arrive. This supports LUSH's goal to eliminate in-store packaging and labels.
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Datatonic automated digital marketing campaigns for MandM Direct using Google Cloud. The new pipeline exports customer audiences from BigQuery to Facebook and Google Ads daily. This replaced manual u...ploads and enabled over 200 custom audiences across six European markets. The solution improved personalization and data security. MandM Direct can now scale campaigns and replicate the process in new markets.
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Datatonic built a Spend Optimiser Tool on Google Cloud for a global technology retailer. The tool uses machine learning to predict ROI and guide digital marketing budget allocation. Marketers now use... an easy tool to test 'what-if' scenarios and optimize spend. The company moved from agency-managed media to in-house, ML-driven mixed modelling. This led to better ROI and less wasted digital marketing spend.
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Datatonic built a Customer 360 Analytics Platform for Pets at Home using Google Cloud. The solution broke down data silos and created a single customer view. Pets at Home now uses insights from over ...20 data sources to improve customer experience. The platform increased efficiency and enabled fast, flexible analytics. It set the foundation for future AI and analytics innovation.
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Vodafone used the AI Booster platform on Google Cloud, built with Datatonic, to add Generative AI for employees and customers. The challenge was to speed up AI deployment and improve efficiency. The ...solution enabled fast rollout of use cases like HR Assistant and Marketing Content Creation. Vodafone reduced machine learning model deployment time from three months to two weeks. They enabled over 600 models in production and cut manual effort by over 70%. The platform supports high security, compliance, and responsible AI.
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Datatonic used Google Cloud, BigQuery, DocAI, and Generative AI to help Liberty Shared Services automate invoice processing. LSS wanted to cut costs and reduce manual errors. The new system reduced i...nvoice processing costs by 70%. It also made the process easier for suppliers and gave the accounting team better visibility. The solution sped up exception handling by 95% and simplified invoice management for LSS.
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Datatonic and Google Cloud helped Telia upskill its employees in data and AI, including Generative AI. Telia wanted to improve efficiency and decision-making by training its teams on Google Cloud AI ...tools. The solution included a week of tailored training events, hands-on sessions, and a Generative AI Hackathon. Over 50% of Telia's employees (450+) were upskilled. This led to better decision-making, increased productivity, and faster adoption of Google Cloud AI solutions.
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AI Accelerator from Datatonic and Google Cloud cut BT Group's AI deployment time from six months to six days. The MLOps platform automates and monitors AI model rollouts across BT's 29 petabyte data ...estate. It uses standard tools and templates to speed up production and ensure safe, ethical AI use. BT aims to generate over £500m in internal value from data and AI in five years. The platform frees up data scientists to focus on new projects and drives innovation in telecommunications.
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Datatonic built an MLOps platform on Google Cloud for Inmarsat. The solution enabled real-time anomaly detection for satellite operations. Inmarsat's team can now use advanced analytics and machine l...earning to manage satellites better. The new system allows real-time data streaming, model deployment, and self-service analytics. This platform helps Inmarsat reduce costs and scale AI across the business. It also improves response times to satellite anomalies.
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Vodafone used the AI Booster platform, built on Google Cloud and Vertex AI, to scale AI and machine learning across 8+ countries. The solution reduced time-to-value for ML models by 80%, cutting PoC-...to-production from months to just four weeks. Vodafone automated ML lifecycle compliance, improved security, and enabled predictive analytics for better customer experience and network performance. The MLOps platform streamlined data science processes and accelerated business value from analytics.
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Datatonic used Looker to build a self-serve analytics tool for a Series D-funded asset management fintech. The client needed dynamic Population Stability Index (PSI) analysis for loan applicants. The... new tool let data scientists create and analyze populations easily, reducing manual SQL work. It enabled deeper KPI insights and cut the time spent on PSI analysis. The fintech now gets faster, more flexible credit risk insights.
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Datatonic built a real-time fraud detection model for a global payments provider using Google Cloud. The solution achieved over 90% fraud detection accuracy and a false-positive rate below 6%. It pro...cessed decisions in about 20ms, helping the client stop around $100M in fraudulent transactions yearly. The new system improved agility and let the client build specialist models for different regions. The project used machine learning and MLOps best practices to modernize fraud prevention.
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Datatonic built a new analytics platform for MoneySuperMarket using Google Cloud. The legacy system slowed machine learning and analytics. The new platform cut machine learning pipeline deployment fr...om 11 hours to 5 minutes. Datatonic also upgraded dashboards, making them easier to use and reducing training time. MoneySuperMarket now updates models daily, improving marketing and customer offers.
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Datatonic used Google Cloud to power MuchBetter’s real-time analytics. MuchBetter needed to scale analytics for better customer experience and marketing. Datatonic built a CDC solution with Datastrea...m, BigQuery, and Looker. The new system enabled real-time data, improved reporting, and fraud prevention. MuchBetter now adapts quickly and keeps costs low. The project finished in 5-6 weeks with close teamwork.
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Datatonic built an MLOps platform for a leading media company using Google Cloud. The company wanted to personalize content across many channels and needed to speed up its MLOps maturity. Datatonic d...eployed two machine learning models for automated tagging and ranking of content. This improved personalisation for customers and freed up data scientists' time. The new platform reduced risk, effort, and time to production for machine learning models.
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Datatonic built a real-time recommender system for News UK using Google Cloud. The system personalizes content for The Sun and The Times, increasing digital viewership and user engagement. Advanced A...I features like explainable AI and automated model retraining help News UK understand and control recommendations. The project improved transparency and reader satisfaction. News UK is now testing these capabilities across more products.
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Datatonic built a streaming analytics platform for Sky using Google Cloud. Sky tracked over 1 billion events daily and achieved 100% data retention, up from 50%. The new solution replaced a failing o...n-premise system and enabled rapid service improvements. Sky's teams now use Tableau dashboards to visualize data and focus on growth. The platform processes up to 500 million events daily and scales globally.
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Datatonic used Google Cloud AI and BigQuery to help TV4 improve ad targeting. TV4 wanted to match ad delivery to age and gender more accurately. The machine learning solution increased prediction acc...uracy by over 2 percentage points. TV4 reduced advertising waste and can now update segments for millions of viewers. The new pipeline is scalable and flexible for future needs.
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Datatonic used its Gemini-powered GenAI accelerator to help localsearch migrate its ERP and CRM data warehouse from Microsoft SQL Server to Google Cloud. The migration used BigQuery Migration Service... and improved dashboard load times by 80% and reduced time-to-data by 75%. localsearch also lowered operational costs by moving to a cost-elastic BigQuery solution. The new platform supports real-time insights and future AI use cases. localsearch now has faster, more efficient data access and better decision-making.
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Datatonic used Google Cloud to help HOME, a marketing agency, improve their news article detection. They built an automated machine learning pipeline for object detection and natural language process...ing. Model performance increased from 59% to 75% mAP@.50. Training time dropped from hours to under 100 minutes. The solution powers HOME's centralised search engine for better marketing insights and bid management.
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Datatonic optimized Looker for Kargo, a digital advertising company. Kargo faced slow query times and lacked a unified client-facing data platform. Datatonic reviewed and improved Kargo’s Looker setu...p, cutting query runtimes by 30%. They reduced heavy merged queries by 22% and increased the share of queries returning in under 10 seconds from 58% to 71%. Kargo now has a more efficient BI platform and faster access to business insights.
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Datatonic used its Gemini-powered GenAI accelerator to help localsearch migrate its ERP and CRM data warehouse from Microsoft SQL Server to Google Cloud. The migration cut dashboard load times by 80%... and reduced time-to-data by 75%. localsearch lowered operational costs by moving to BigQuery and decommissioning its old data warehouse. The new platform supports real-time insights and future AI use cases. localsearch now makes faster, data-driven decisions with improved analytics.
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Datatonic built a scalable MLOps platform for Delivery Hero using Google Cloud Vertex AI. Delivery Hero faced challenges with many teams, manual retraining, and model failures. The new MLOps solution... automated workflows, improved collaboration, and reduced manual work. Data scientists now spend less time on maintenance and more on new projects. Models for customer lifetime value and churn prediction stay accurate longer, cutting costs.
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Datatonic built a machine learning recommender system for Nordward Seafood Group AB using Vertex AI. Nordward wanted to give customers better product suggestions in their mobile app. The new AI-power...ed system increased average purchase size by 6.3%. About 65% of items ordered were from the recommended shortlists. The solution also reduced the sales team's workload by automating customer-level shortlists.
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Datatonic used Google Cloud to help Hedvig, a Swedish insurance company, improve profit by 15-20%. They built a Member Lifetime Value (MLV) model to predict customer value over time. This helped Hedv...ig reduce customer churn and optimize marketing costs. The solution improved targeted marketing and decision-making. Hedvig can now reward loyal members and offer fair prices.
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Dataform helped Usay Compare move siloed data into a single BigQuery data warehouse. Datatonic built a scalable, easy-to-use data management solution using Google Cloud and Dataform. The new system r...educed manual reporting and improved data reliability. Usay Compare's team can now manage and scale their data models in-house. The project enabled better analytics and business insights. Dataform's integration made data testing and transformation more efficient.
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Datatonic used Kubeflow on Google Cloud to help Realeyes improve their AI model performance. Realeyes saw 1.5x faster latency, 4x less memory use on mobile and browser, and 75% lower model re-trainin...g costs. The new MLOps setup made R&D more scalable and efficient. Realeyes now has better experiment tracking and automation. The solution also reduced power consumption and made model updates easier.
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Datatonic upgraded RICOH Spaces to an enterprise-grade platform on Google Cloud. The new microservices architecture enables high scalability, reliability, and multi-region deployment. The platform no...w supports 50+ customer migrations, with over 20 migrated in a single day. Security best practices and data residency requirements are met. RICOH Spaces can now expand quickly across the USA, Europe, and Asia Pacific.
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Datatonic used Google Cloud Generative AI to help Hotelplan Suisse plan holidays faster. Hotelplan staff can now give better and quicker travel advice to customers. The AI tool combines expert knowle...dge and data to answer questions in minutes instead of hours. The solution improved sales staff efficiency and made holiday planning easier for customers. Hotelplan also uses GenAI to speed up writing travel blogs and location descriptions.
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Cineverse used cineSearch, an AI-powered search tool built with Google Cloud’s Vertex AI Search and PaLM 2 LLM, to improve its streaming service. Users can now chat with Ava, an AI video adviser, to ...get movie and TV recommendations. This solution reduced content search and discovery times by 90%. Cineverse also saw a 15% drop in customer churn. Costs related to customer churn fell by 25%.
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Datatonic built a platform for the Zoological Society of London (ZSL) using Cloud AutoML. ZSL needed a faster way to identify wildlife species from camera trap images. The solution used deep learning... and transfer learning to create custom image recognition models. Conservationists can now process thousands of images quickly and share models with other organizations. This saves hundreds of hours compared to manual identification.
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Datatonic built a future-proof data lake for LKQ using Google Cloud. LKQ needed a unified data platform for over 20 European markets. The automated solution cut data ingestion, transformation, and lo...ading time by 99%. Data processing dropped from 48 hours to just 30 minutes. Analysts now get quick insights and can scale the platform to new markets fast.
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Datatonic built a data analytics platform on Google Cloud for a global cargo handling leader. The company moved from on-premise Hyperion Financial Management to a cloud-based single source of truth. ...Over 100 million rows of financial data are now ingested and visualized in BigQuery and Data Studio. Business users can do ad hoc analysis and share insights. The solution improved data governance, access control, and enabled new use cases like demand forecasting.
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Google Cloud’s Data Loss Prevention (DLP) helped a large UK energy provider unlock new Generative AI use cases while protecting customer data. The company used DLP for anonymisation, encryption, and ...decryption of sensitive information, including PII. This enabled secure call transcript analysis and improved customer experience. The solution scaled to manage over 2 PB of sensitive data and used reusable DLP templates. Datatonic also upskilled the client’s teams to ensure future adoption of secure AI solutions.
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Fullscript used dbt Cloud to manage complex analytics after acquiring a company of equal size. Datatonic helped Fullscript scale its dbt Cloud project, migrate app data from 17 models, and extend dat...a models to handle new data sources. The team delivered 20 KPIs for operations and improved reporting efficiency. Fullscript now processes more data, reduces errors, and gains business insights faster with dbt Cloud.
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Datatonic used Google Cloud AI and machine learning to help Mulberry improve product recommendations. Mulberry wanted to boost online engagement and sales with better personalisation. The new recomme...nder system increased click-through rates in email campaigns by 37%. Facebook Ads saw a 110% boost in ROAS. The machine learning model scored 112% more customers, making recommendations more effective.
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Datatonic used Google Cloud and AI to help UNDP improve energy planning. They built a machine learning model to find solar energy assets in Africa using satellite images. The solution used over 40,00...0 images and open-source tools for labeling. This helped UNDP plan energy infrastructure for millions of people. The project shared open source code for others to use.
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Datatonic helped Loop Returns cut Google Cloud costs by 30%. Loop Returns used Looker and BigQuery for e-commerce analytics. Datatonic rebuilt five key dashboards and optimized data integration. They... also integrated dbt for better data models. Loop Returns now runs analytics at scale and spends less on business intelligence.
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Datatonic used Google Cloud and machine learning to help a leading manufacturer optimize stock at branches across the UK. The new demand forecasting solution predicts which products to stock, reducin...g logistics costs and stockouts. The company saw a 31% increase in sales volume, a 64% rise in order fill rate, and an 86% drop in costly logistics orders. The AI-driven approach replaced outdated business rules with data-driven recommendations for every branch and product.
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Datatonic built a unified data platform for the United Football League (UFL) using Google Cloud, BigQuery, and Looker. The UFL needed to control and unify its ticketing, revenue, and marketing data, ...which was previously siloed and hard to access. The new platform lets the UFL quickly access and analyze data, create high-value fan audiences, and improve fan engagement. Data retrieval time dropped from hours to minutes. The UFL can now make better decisions and offer a better fan experience.
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Wizards of the Coast used Generative AI solutions from Datatonic and Google Cloud. They wanted to improve digital gameplay and player experiences. Datatonic built three GenAI Agents: a Personalizatio...n Agent for player Q&A, a Productivity + Insights Agent for analytics, and a Code Generation tool for developers. These tools helped Wizards increase customer retention, speed up game development, and gain better player insights. The project improved in-game experiences and made development faster and more secure.
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Datatonic used Google Cloud Generative AI to help Hiber make game creation easier. Hiber users can now type what they want and see 3D worlds appear right away. The solution uses a chatbot and Python ...API to turn text into code and 3D assets. This makes it faster for anyone to build new worlds in HiberWorld. Hiber can now reach more users and help creators work faster.
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Datatonic used Google Cloud and AI to automate content creation for HVNT's AR mobile game. HVNT's team used to write clues for treasure hunts by hand, which took a lot of time. The new system uses ma...chine learning to generate clues, cutting down manual work. HVNT can now add more clues and expand to new cities faster. This helps them reach more players and grow their game quickly.
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Datatonic built a Command Line Interface tool using MLOps best practices for a leading game developer in the mobile gaming industry. The tool helped over 150 data scientists train machine learning mo...dels faster and more easily on Google Cloud. It enabled seamless scaling of AI and ML models across large datasets. The solution improved collaboration with built-in experiment tracking and reduced manual work. The company now accelerates model training and focuses more on innovation.
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