Research
 
A multi-product software company
The company used Abacus.AI to score and prioritize leads to efficiently allocate its sales and marketing resources
Problem
The company wanted to optimize marketing and sales resources by prioritizing the leads to target
Solution
Trained and deployed an Abacus.AI lead scoring model that helps the Company determine the top leads to target
Results
Lead scoring helped the company optimize its sales & marketing resources and achieve higher growth
7X improvement in conversions
Trained on ~10M leads
Handled 2Bn+ events
Large Audio Books Publisher
Abacus.AI reduced customer churn by identifying customers most likely to churn and engaging with them
Problem
The company wanted to reduce customer churn
Solution
The company used Abacus.AI to develop a customer churn prediction model to identify and engage with customers most likely to churn
Results
The company reduced its customer churn by 20%
Reduced customer churn by 20%
5M predictions / month
4X improvement in predictions
A popular tools company selling product on multiple platforms including Amazon and HomeDepot
The company used Abacus.AI to optimize inventory to ensure high availability of stock while limiting excess inventory
Problem
The company wanted to optimally manage inventory
Solution
The company used Abacus.AI Demand forecasting model to predict the inventory requirement for various SKUs
Results
Resulted in predictions that are 72% more accurate than what the company achieved using its models
Forecasted on ~5,000 SKUs
Decreased the forecasted percentage error by 42%
Forecasted for 1 month to 12 month timeframes
A customer insights company
The company used Abacus.AI to generate personalized recommendations to its customers and increase revenue
Problem
The Company wanted to generate recommendations tailored to its customers
Solution
The Company used Abacus.AI personalized recommendations model
Results
Increased revenue by ~20% based on an A/B test
Increased revenue by 20%
Handles millions of requests/day
Under 20ms latency
A popular satellite television company
The company used Abacus.AI to build an Anomaly model to detect Quality of Service issues
Problem
Reduce churn by proactively reaching out to customers experiencing quality of service issues
Solution
Used Abacus.AI anomaly detection model to identify abnormalities in user session data
Results
Identified 12 types of service issues that could cause a customer to churn using 3 different methods
Processed user session data from 2.5M customers in real time
Calibrated on 2+ TB of data and over 1Bn events
Identified 12 types of service issues
Very large retail company
The company used Abacus.AI to generate cart recommendations using Abacus.AI’s vector matching engine
Problem
The company wanted to recommend items to users based on what’s already in their cart in real time
Solution
Abacus.AI vector matching engine was used to generate recommendations
Results
Generated recommendations under 20ms latency
Under 20ms latency
Scales upto 10,000+ Queries/Second
Handles millions of requests/day
A financial services firm
The company used Abacus.AI to identify key pieces of information from customer call transcripts and classify them
Problem
The company wants to reduce costs by automating the categorization of calls based on the transcripts
Solution
Used Abacus.AI Named Entity Recognition to automate this process
Results
Achieved 99% accuracy in classifying, saving multiple hours of human effort
Classified call records into 15 classes
Achieved accuracy of 99%
Aggregated over 100 datasets
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