IoT Analytics for Retail
Bring together data, analytics and marketing processes to gain an omnichannel view of your customers across all devices.
Retailers are striving to find ways that the IoT can create a direct channel between retailers and consumers, and to use IoT data streams to inform the customer relationship at every step along the customer journey. The differentiation with IoT will come from a retailer’s ability to sense, understand and act on IoT data with analytics. To take advantage of this new promising area, retailers will need to focus on IoT applications that better serve customers and create value.
How SAS Can Help
IoT solutions from SAS bring together data, analytics and marketing processes to help you:
- Sense customer needs and preferences in real time. Use smart devices to gather location-based information. Then integrate that data with previously known information to form contextual, real-time insights that you can act on.
- Gain a deeper understanding of customer patterns. Merge detailed, online customer behavior data with data from offline channels for a complete customer view that reveals what customers truly need so you can respond in real time with relevant, meaningful offers.
- Provide profitable new services to customers. Combine what you’ve learned from previous customer experiences with what you anticipate about future needs – then take action to seize opportunities ahead of the competition.
As the leader in advanced analytics, SAS has the experience and expertise to deliver cutting-edge IoT capabilities that give you:
- A comprehensive view of your customers and business. Our customer information mapping technology means your data is always available and accessible – no matter where it comes from or where it resides. And you can integrate multiple online and offline data sources, including IoT, customer, merchandise and location information.
- Automated, large-scale forecasting. An unmatched library of retail forecasting models takes into account underlying trends, seasonality, promotions, inventory effects and more. The best-fit model is selected automatically based on each individual time series.
- High-performance predictive analytics. Create memorable, personalized interactions – across channels and in real time – using analytically driven scoring, segmentation and decision making based on historical and current interactions, combined with context.
- E-Book Four Use Cases Show Real-World Impact of IoT
- White Paper Understanding Data Streams in IoT
- White Paper IoT in Retail: Engaging the Connected Customer
- E-Book Internet of Things: Understanding the Journey
- Article 오늘날 유통 산업에서 사용하는 5가지 IoT 응용 분야_(영문원본)_5 IoT applications retailers are using today
- Article Analytics at the edge Examples of opportunity in the Internet of Things
- Article 오늘날 유통 산업에서 사용하는 5가지 IoT 응용 분야
- Article The connected consumer: IoT's impact on the future of retail
- Solution Brief Expand Retail Analytics with SAS and Red Hat
IoT Analytics Solutions for Retail
- SAS® Data PreparationQuickly prepare data for analytics in a self-service, point-and-click environment with data preparation from SAS.
- SAS® Event Stream Processing실시간 빅데이터 스트리밍을 통하여 분석을 통한 인사이트를 기업의 의사결정에 즉시 반영할 수 있습니다.
- SAS® Intelligent Decisioning분석에 기반한 실시간 고객 소통을 실현하고 전사적 비즈니스 의사결정 프로세스를 자동화하십시오.
- SAS® Supply Chain Intelligence안정된 공급망 전략으로 품질 개선, 고객 만족, 수익 제고의 효과를 동시에 얻을 수 있습니다.
- SAS® Visual Analytics모든 데이터를 시각적으로 탐색하고 새로운 패턴을 찾아냅니다. 또한 사용자는 웹이나 모바일 기기를 통해 보고서를 게시/공유할 수 있습니다.
- SAS® Visual Data Mining and Machine LearningSAS 비주얼 데이터 마이닝 및 머신 러닝은 통합적인 시각화 인터페이스를 통해 모든 데이터 마이닝, 머신러닝 프로세스를 지원할 수 있습니다.
- SAS® Visual Text AnalyticsSAS 비주얼 텍스트 애널리틱스는 자연어 처리, 머신 러닝 및 언어학적 규칙을 결합하여 비정형 데이터에 숨어있는 인사이트를 제공할 수 있습니다.