Leading Home Service Website
Leading home service website uses machine learning anomaly detection to monitor site.
Credera partnered with a leading home service website to enable quick responses to unusual or improper website activity by utilizing machine learning anomaly detection.
At a Glance
The leading home services website engaged Credera to enable quick responses to unusual or improper website activity. Through machine learning, Credera implemented a platform to detect and address any contact issues. Using automation detection, the system now allows for real-time clarity into any issues and pushes notifications to the proper team.
Detecting anomalies in real time to serve customers.
A leading home services website updated the way they track how members contact service providers. With this new data they want to capture when irregular instances in this contact data appear so they can investigate issues in near real time. Credera was engaged to create the system to detect these anomalies as they appear and alert the correct teams to initiate action if needed.
Find the right machine learning and artificial intelligence technology for the long run.
Credera and the home services website company leveraged many technologies to find the right solution to accomplish the organization's goals.
Implemented platform for artificial intelligence in current AWS environment by onboarding them to AWS SageMaker for anomaly detection.
Created multiple machine learning models and delivered to production the one that most maximized the criteria defined for a successful model in this instance.
Investigated and delivered anomaly detection for first use case of number of contacts to service providers throughout the day.
Provided analytics expertise in machine learning to guide the employees through the process of implementing artificial intelligence projects. Now that the platform and best practices are provided, the organization can accomplish other machine learning goals.
Easily accessible data that keeps the organization up-to-date on anomalies while continuously learning.
Through the partnership, the organization achieved near real-time status on anomalies that are continuously learning to provide the best customer experience.
CLARITY INTO WHAT IS NORMAL VS. ABNORMAL
No longer is there an executive checking Kibana dashboards over the last few days to make educated guesses. The system is aware within the hour if something truly anomalous happens.
CONTINUALLY LEARNING SYSTEM
Weekly retraining of machine learning models means the system is continually learning and making incremental improvements in accuracy.
All outliers are discovered in near real time instead of over the course of a couple days.
IMMEDIATE ALERTING TO CORRECT TEAMS
Leverages current alerting platform to get notifications to the proper team as soon as the anomalous event is detected.
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