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
Drive Revenue
- Mine the customer journey for deep insights into perceptions and habits
- Make loyalty programs more effective by predicting uptake
- Create omnichannel analysis across customer touchpoints
- Optimize product mix and pricing with algorithm-driven decisions
- Conduct market basket analyses to find powerful product combinations
- Boost the results of every campaign with more precise offers
Cut Costs
- Enhance merchandise planning with machine learning to auto-prune unprofitable products
- Optimize supply chains and eliminate stock outs without additional inventory
- Plan the most successful store sites and optimize in-store demand against staffing with AI
Avoid Risks
- Identify patterns that enable immediate detection of fraudulent purchases and returns
- Inject customer voice into decision-making with analytic-driven insights
- Enhancing product quality assurance programs with predictions of likely defects
- Find and retain the right staff by predicting which candidate hires will be the most successful employees
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.
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 has an amazing customer service philosophy. I have never had to wait long for an answer to a question and have even had them provide custom solutions within there tool as answers. They are very willing to listen to suggestions for improvement and have taken several suggestions and either implemented a change as a result or provided a solution to the issue.
Read the full review on Gartner Peer Insights
I have been very satisfied with my overall experience. Worth noting, when we initially onboarded with RapidMiner, they provided a series of consulting sessions to guide us through our initial use case. We were able to gain comparable results at a lower price point.
Read the full review on Gartner Peer Insights
I have been using RapidMiner for more than two years, and the experience with this platform is seamless. The frequent upgrades and innovations added to the platform are the ones that impressed me a lot. The support services through their community are also top-notch as we can ask any question related to their platform and general data science.
Read the full review on Gartner Peer Insights
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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CPG, retail & eCommerce business
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