CPG, Retail & eCommerce
Consumer-oriented companies have tremendous opportunity to maximize profits at every stage of the value chain, from optimizing pricing to perfectly aligning supply and demand.
Digitally transform your customer journey from end-to-end
Businesses in the retail, eCommerce and consumer goods industry are gearing up for some major changes, as if they haven’t undergone enough already. But, change often presents opportunities for major improvements.
RapidMiner can help companies take these industry shifts in stride and excel past their competition. From understanding buying behaviors to setting the optimal price to ensuring supply meets demand, we help consumer goods companies and retailers around the world maximize profits at each stage of the value chain.
CPG, Retail & eCommerce Use Cases
Why AI Now?
No industry has weathered change in recent years as much as retail, eCommerce and consumer goods. Machine learning can be used to assist the digital transformation of your customer journey to accurately segment customers and target them with personalized and relevant messages and offers.
Social media, in particular, is a treasure trove of customer insight, both at the individual level — where brand advocates and detractors can be addressed one-on-one — and as a resource to understand broader sentiment towards brands and products.
RAPIDLY GROWING NATIONAL HOSPITALITY VENDORAccurately forecasting customer service times with AI mitigates risk and improves customer satisfaction. Learn how this company boosted customer loyalty while cutting staffing costs by $2M.
DOMINO'S PIZZAMultimodal AI platforms unify the development and deployment process across teams, while lowering costs and improving performance. Learn how Domino's prescribes accurate 8-week supply chain forecasts across 4,000+ locations.
AUTOMOTIVE ECOMMERCE VENDORWith a mix of web scraping and topic recognition, you can monetize valuable insight from publicly-available information. Learn how this organization increased sales by $500k.
Overcoming the computational demands of time series analysis
Ryan Frederick of Dominos explains how his data science team improved their supply chain by providing highly accurate and scalable demand forecasts through extensible time series forecasting and scaled R-based models using RapidMiner. Watch the full presentation here.
What Our Customers Say
RapidMiner Studio is an awesome tool! It really speeds up the data exploration process and provides a firm foundation for building machine learning models. The support staff is excellent! They really helped me and my team build and prove out our use case to put into production. They also helped us integrate seamlessly with Tableau, which was critical for our user group. Overall, would highly recommend the tool to anyone who is looking at taking their predictive analytics/machine learning capabilities to the next level.
Predictive analysis is one of the important things to analyze the future highs and dips, RapidMiner Studio provided the ability to speed up and automate the creation of predictive models with a visual interface, connect with any data source, support data base processing and more. We like this application because it's super fast and easy, which provides accurate and perfect analysis.
We started using RapidMiner Studio years ago. The goal of the use case was to analyze POS data and detect fraud. We wanted an easy way to load the data from the server and write calculated identifiers back. The analysis of the data was easy and fast, thanks to the very successful interface in RapidMiner. Auto Model made it quick and easy to extend the analysis to other areas of applications. The excellent results speak for themselves, so we have been very satisfied with our cooperation with RapidMiner for a long time. The support is remarkable and leaves nothing to be desired.
Gartner Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences, and do not represent the views of Gartner or its affiliates.
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