{"id":59509,"date":"2024-09-17T09:34:14","date_gmt":"2024-09-17T09:34:14","guid":{"rendered":"https:\/\/www.cloudthat.com\/resources\/?post_type=resources&#038;p=59509"},"modified":"2024-09-18T11:02:53","modified_gmt":"2024-09-18T11:02:53","slug":"boosted-sales-forecast-accuracy-by-30-reducing-stockouts-and-overstock-with-demand-estimation-models","status":"publish","type":"resources","link":"https:\/\/www.cloudthat.com\/resources\/case-study\/boosted-sales-forecast-accuracy-by-30-reducing-stockouts-and-overstock-with-demand-estimation-models","title":{"rendered":"Boosted Sales Forecast Accuracy by 30%, Reducing Stockouts and Overstock with Demand Estimation Models"},"content":{"rendered":"<p>The company leverages advanced technologies and data-driven strategies to optimize its operations, enhance customer engagement, and deliver superior products. By doing so, AB-InBev positions itself as a leader in the competitive global market, driving growth and ensuring long-term sustainability.<\/p>\n","protected":false},"author":325,"featured_media":59510,"parent":0,"template":"","cat_resources":[6],"technology":[27],"published_by":"324","primary-authors":["1104","489","892","881"],"secondary-authors":["325"],"acf":{"banner_image":59511,"resources_label":"","download_url":"https:\/\/content.cloudthat.com\/resources\/wp-content\/uploads\/2024\/09\/Ab-Inbev-Promo-Case-Study.pdf","client_logo":59513,"highlights":{"first_part":{"icon":336,"title":"30%","subtitle":"Improvement in ML Model Performance"},"second_part":{"icon":335,"title":"25%","subtitle":"Increase in Customer Engagement"},"third_part":{"icon":334,"title":"30%","subtitle":"Boost in Sales Forecast Precision"}},"the_challenge":"The client struggled with managing and analyzing large volumes of sales data to optimize promotional strategies and pricing models. They faced difficulties in merging and processing data from multiple sources in Snowflake, improving the accuracy of ML models through feature selection, and using clustering techniques to segment customers effectively. Additionally, they needed more precise demand estimation models to enhance sales forecasting and optimize pricing. To address these challenges, the client wanted a scalable, cost-efficient solution to boost ROI and improve decision-making.","client_testimonial":{"image":"","description":"","author":""},"solutions":"\u2022 Merged and cleaned data from Snowflake paths to create a unified dataset.\r\n\u2022 Conducted feature engineering to enhance model performance.\r\n\u2022 Applied DBSCAN and Hierarchical Clustering for customer-product segmentation.\r\n\u2022 Developed and tuned ML classification models for each cluster.\r\n\u2022 Built demand estimation models to predict sales and understand demand elasticity.\r\n\u2022 Created optimization models to determine optimal product pricing for revenue maximization.\r\n\u2022 Visualized all KPIs using Power BI dashboards.","the_results":"Improved data processing and ML models, boosting sales forecasting by 30%, optimized pricing for a 15% sales increase, and enhanced decision-making with Power BI.","about_client_left_side":[{"field_63315a4dc06e1":"15085","field_63315a5bc06e2":"Industry\u00a0","field_63315a61c06e3":"Manufacturing \/ Beverage"},{"field_63315a4dc06e1":"15083","field_63315a5bc06e2":"Expertise\u00a0","field_63315a61c06e3":"Azure Data Lake, Azure Databricks, Snowflake, Azure Machine Learning, Power BI"},{"field_63315a4dc06e1":"15084","field_63315a5bc06e2":"Offerings\/solutions\u00a0","field_63315a61c06e3":"Optimized data, improved models, boosted engagement, and enhanced forecasting."}]},"_links":{"self":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources\/59509"}],"collection":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources"}],"about":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/types\/resources"}],"author":[{"embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/users\/325"}],"version-history":[{"count":1,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources\/59509\/revisions"}],"predecessor-version":[{"id":59514,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/resources\/59509\/revisions\/59514"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/media\/59510"}],"wp:attachment":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/media?parent=59509"}],"wp:term":[{"taxonomy":"cat_resources","embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/cat_resources?post=59509"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/technology?post=59509"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}