Enterprises who have adopted Amazon Personalize solution have seen an uplift in their conversions & revenue. You can find case studies on Amazon Personalize here: https://aws.amazon.com/personalize/customers/

Recommendation engines are not optional in the new millennium. Every business can benefit from a retrofitted, scalable customer engagement platform. While building your own recommender system to deliver the individual customer can be costly and time-consuming, we make it simple and affordable.

This POV gives you the ability to see the results of adopting Amazon Personalize powered Recommendr at no cost to you.

Systech’s Recommendr offers organizations an advanced and sophisticated recommendation engine powered by Amazon Personalize that enables elevated user interaction, enriched shopping potential, enhanced customer engagement, and converted and satisfied customers.

Implementation begins through the construction of data pipelines to capture your enterprise’s internal and external data, from multiple data sources. This data is used to train (& retrain) the Amazon Personalize model using our on-and-offline metrics. Once completed, the data pipeline and model can be deployed and integrated with your other applications. The solution thereafter will produce Amazon Quicksight dashboards that allows you to monitor solution performance, and incorporate post-production, self-learning capabilities to adapt to changing user engagement.

Our end-to-end architecture not only integrates Amazon Personalize with CDP solutions, but also is equipped with Systech’s deep ML capabilities and experience to take the “guess,” out of “guessing” how to get somewhere profitable. This offering offers a low-cost entry point, hands-on experience from a member of our Systech Recommender team, and optimal results (equipped with Machine learning Models with Hyper Parameters).

After our proof of value, our technology will delivery such precise recommendation based on your needs that you’ll wonder why you waited so long to migrate!

Recommendr includes…

• Proof of Value:

• Identify the Use Case
• Analyze Data Elements available
• Perform Data Engineering
• Implement Feature Engineering
• Map Data Elements to Personalize Schema
• Feed Data into Personalize
• Build and Train Customized Models
• Showcase & Evaluate Results

• Review of Implementation Strategy:

• Analyze Customer Requirements (Real-time vs Batch vs Both)
• Identify and Design Recommendation Validation
• Design Data Integration
• Design Auto (Re)Training
• Develop Event Tracker for Real-Time Adjustments
• Integrate with the Current Solution/Environment

For more information, please contact platform@systechusa.com, or click here : https://systechlive.wpengine.com/aws/#recommeder