A web and mobile software application based on SaaS that consolidates all your business channels is Orderhive. A service provider for shipping management, sales orders, inventory, and software that easily integrates all your business functions with single software.
Orderhive helps to streamline the way online vendors operate all around the world. With lots of data generated from social media and a parallel rise in the users, companies need to set the priority and resources to reach out to each of them.
It is essential to remove junk and assist with relevant data and improve user experience. And that is possible through the recommendation engine.
Significant companies are contributing to recommendation systems such as YouTube, Netflix, Amazon, Spotify, Social Media platforms, and more. As we see applications and technology advance continues to modify the way users choose and exploit information, the recommendation engine is one such solution and an integral part of software products.
Orderhive is cloud-based shipping management, sales orders, and inventory software that help you easily integrate for all your relevant data into the track and move your complete product from the warehouse to the end-customer. It is an answer to all of your questions about making business decisions smarter.
Significant and easy-to-use inventory managing software to keep your business up-to-date. The four main features from the many are:
- Simplified product management
- Just-in-time operations
- Real-time inventory reports
- To-the-point inventory visibility
What is the recommendation engine?
The recommendation engine is a data filtering tool that makes use of algorithms and data to advise the most relevant items to users.
Along with that, consumers expect a personalized experience and sophisticated recommendation systems to find relevant products and content. At the end, it saves consumers time and money. Ecommerce and significant online platforms are offering a high level of customer satisfaction and many service providers doing their actual business with recommendation engines.
Technical bits and pieces:
Established inventory system ensures secure process monitoring and managing all your orders by single software of shipping and sales management based on data by consolidating all real-time information and helps you detect any error and streamline your business online and enhancing the customer experience and solving bottleneck.
- Database- MySQL
- Programming language- Python
- ElasticSearch for logging file
- AWS for data rules
- S3 Bucket for data storage
How Orderhive works with Recommendation engine:
Recommendation engines determine data patterns from the set of data by knowing customers’ choices. It helps to co-relates to the needs and interests of others with a similar choice.
Recommendation engines as an algorithm been in the market from while but many of us don’t know the actual use of it in the business process, and there have been some key aspects to leverage for businesses:
- Frequently bought: Frequently bought products by other users, along with selected items, are recommended to the user.
- Similar products: Past actions and purchases drive new purchases, and the overlap with other people’s investments and activities is a fantastic predictor.
- Customers also view: A user’s responses are the best indicator to help and indicate other users.
Output comes in JSON (can be twigged accordingly).
There are three essential types of recommendation engines we are using:
- Collaborative filtering
- Content-based filtering
- Hybrid recommendation systems
Why you need Orderhive?
To track and order the products and manage the production channel according to client’s demand, Orderhive helps to make it possible. The organization is capable of knowing the most selling products and handling the remaining one. Business needs Orderhive for managing multiple channels and improves customer satisfaction with a single solution.
- To manage massive channels with a centralized inventory.
- Plug-in is made to increase the sales for the clients, thus increasing revenue.
- To increase product sales and manage inventory.
Using machine learning on a compute engine to make product recommendations, a typical recommendation engine processes data through the phases, namely collection, storing, managing, and operation.
- Inventory never runs out of stock
- A centralized inventory is managed
- All correct, all the time
- Track your business performance in real-time
We analyze the data in 3 different ways:
Here, we gather the data and filter it through using different analysis methods. It helps users to get instant recommendations as they are viewing the product, then you will need a more active type of analysis. Some of how we can analyze the data is:
- Real-time systems work as data procedures. A real-time system would be necessary for recommendations at the same time.
- Batch analysis asks for data processing periodically. A batch system functions well for e-mail at a later date.
- The near-real-time analysis allows you quickly to collect data so you can refresh the analytics every few minutes or seconds.
There is one more advanced type of recommendation engine: ALS – Alternating Least Square. Contact us for more detail:
- To manage stocks and overall distribution flow.
- To improve marketing strategy.
- To boost up the revenue.
- To get ROI by managing channels.
- Keep inventory levels optimized at all times.
- Centralized inventory visibility and actions.
- Minimize inventory management costs.
- Automate manual tasks and saves time.