Messaging and Queuing for the Retail Industry
Pandio leads in messaging and queuing for the Retail industry by hosting Pulsar with an integrated AI neural network. Our resulting increase in performance is unmatched in performance, reliability and security – the KPIs of online retail applications.
Common Use Cases
- Customer preference forecasting, recommender systems
- Engage and communicate with customers
- Drive customer satisfaction and long-term customer loyalty
- Optimize logistics and operations with live event streaming
- Optimize pickup and delivery routes and locations with real-time data
- Locate targeted merchandise with real-time streams
- Sales and returns data analytics and forecasting
- Geographical and demographic product demand forecasting
- Harvest insights from pre-existing customer behavior datastores
Retail and Ecommerce Data Analytics
Edge by Ascential’s Featured Use Case
As we have seen with many enterprises, Edge originally used a constellation of technologies like Apache Kafka, laboriously tooled together with AWS Kinesis and Lambda, to hatch a pub/sub messaging app. The intended outcomes, including message queuing, processing, and logging, were achieved at high cost under the burden of Kafka’s poor scalability.
Fortunately, Edge had the foresight to unify all these objectives in the fully supportive and unified Apache Pulsar platform. Use cases included improved customer communications via Pulsar’s unified messaging and queuing system. Edge developers enjoyed the advantage of Pulsar Functions to reduce coding overhead where Pulsar had anticipated many of their needs in its inherently Cloud native architecture. Edge used Pulsar to pipe vast customer behavior data to revolutionary ML algorithms for prediction of future profitable merchandising outcomes.
Restaurant Customer Preferences Prediction
Max Kelsen’s restaurant Ecommerce algorithms predict transactions by using Pulsar event streams to a machine learning system that they recently built for a global quick service restaurant chain. Pulsar’s data pipeline feeds transaction data from web apps to calculate predictions about eCommerce session outcomes. The overhead of adding this intelligence and insight is less than one second of latency. Pulsar combines with Elasticsearch to make predictions about more than a million sessions per week.
Innovative engineering used in this system is poised to become a retail industry standard, one which sets the bar for competitors in all areas of Ecommerce. Retailers like Max Kelsen can take pride in knowing they are a leading-edge AI developer leveraging the fastest and most reliable technologies like Pulsar at precisely the optimal moment in their niche.
Optimizing Pickup and Delivery
Narvar Concierge is an innovative Ecommerce service which provides pick-up and return locations to online shoppers with the benefit of reducing shipping costs. Narvar’s clients include hundreds of the world’s largest retailers who plug Concierge into their Ecommerce portals to improve user experience. An imperative challenge to Narvar developers is to guarantee prompt and accurate communications between clients and their customers. To accomplish the feat, Narvar built its platform on the fastest and most reliable messaging and event streaming technology available today – Apache Pulsar.2
Narvar began with a typical development strategy which split the two common messaging paradigms among Kafka and RabbitMQ. However, as exciting new business use cases emerged, Kafka could not handle the explosive scalability requirements. In particular, many new applications required event streaming which increased maintenance overhead and used expensive Amazon Lambdas. Fortunately, Narvar met these challenges heroically by migrating all its queuing and messaging to Apache Pulsar, which handles everything in a single platform.
As Narvar developers described the edge Pulsar gave them, Pulsar architecture is inherently cloud-native. Pulsar scaled elastically with minimal coding and maintenance. Pulsar is containerized and crucially it deploys easily with Kubernetes, making the task of spinning up and scaling processes a simple matter. Many new business use cases were naturally facilitated with Pulsar Functions, which provide rich methods for event streaming. Pulsar also eliminated the requirement for expensive Lambda functions. Overall, Apache Pulsar accelerated Narvar Concierge to the level required by its behemoth Ecommerce retailers.
Top Retail Companies Utilizing Pulsar
Pandio has perfected distributed messaging by integrating a neural network into Apache Pulsar, creating unparalleled performance and efficiencies as a fully-managed service.
- Scale with confidence
- Pay only for what you use
- Ready-to-go in minutes
- One Click Deploy
- Nothing beats Pandio
- < 10ms latency at any scale
- 2 million messages per second per partition
- Optimized with Artificial Intelligence
- Proven capability
- 99.99% uptime guarantee SLA
- Mission critical applications
- Enterprise grade
- Your trusted partner
- Zero operational burden
- Teams of messaging experts
- There when you need it most
- Pandio has it all
- Streams, Queues, & PubSub
- Integrate Quickly With Stateful Functions
- Distributed SQL Query Engine
- Powerful API and CLI
- Cloud and/or on premise
- Flexible deployments
- Bridge clouds to/from on premise
- Retain control
Apache Pulsar As a Service
Customer behavior and transaction forecasting is among the leading research topics in the online retail and Ecommerce industry. Big data from retail transactions is a gold mine of insight opportunities for retailers with vast datastores. And now, Apache Pulsar provides the data pipeline infrastructure to meet the needs of ML and AI algorithms which leverage this data to keep you informed about trends in your markets. Furthermore, Pandio is the leader among hosted solutions for Apache Pulsar, with experts to bring you quickly up to operational speed in your strategy to adopt Pulsar for event streaming, messaging, and queuing.