addedIQ®

WE BUILD AI DECISION ENGINES

to help grow your revenue​

​

​

In today’s market, data intelligence is an increasingly important aspect of revenue growth, and the ability to leverage data smartly is key to achieving and maintaining a competitive edge.

Our services

Strategy

Machine Learning + AI

Consultancy

You know your data holds potential, but you don’t know how to access it. Our dedicated team of data scientists can help plan, build, and test solutions to solve your big data-related problems within a compact and efficient timeframe 

Your business needs custom machine learning or artificial intelligence tools and you need an experienced team to get it done right. We can work with you to build custom visualizations, recommendation engines, and AI tools to help your business reach its next breakthrough

Your organization needs to increase its data intelligence to solve important problems. Whether it’s working with your existing tools and reports, generating predictive models, we can work with you to advise your business on the best course of action using your own user and client data

Increase your organization's IQ

Today’s most intelligent companies know that leveraging their data to grow revenue is crucial to success in the current market, and addedIQ® understands the hurdles that many organizations face in adopting a comprehensive program when it comes to data science, AI, and machine learning. 

​

Our human-centered approach sets us apart in that we are able to distinctly understand your organization’s unique needs and questions at a high level and present our findings in our clear, real time data-informed dashboard, Clarity+® . This powerful dashboard combined with our consultancy support will allow your business to seamlessly boost your team's data intelligence and increase your revenue. 
 

Examples of Our Products at Work

Large Electricity Generator and Retailer

• The Challenge: Electricity traders needed assistance for better purchases of electric capacity across multiple generation plans and a multi-node distribution network against the backdrop of their competitors as well as factors such as weather. 

• Our Solution: We developed an artificial intelligence driven trading algorithms and platform that rapidly factors in a variety of new data and variables to recommend optimal trading strategies. In addition, we developed a data-science driven roadmap to guide management in additional added-value development to maintain a competitive advantage in this field.

• The Results: Management saw the potential of this technology to greatly enhance their business process and has begun development to integrate this capability into their energy trading platform.  Early tests of addedIQ’s algorithms and forecast model for the markets as a complement have shown a 5-10% improvement in price prediction relative to the model currently in use.
   

​​

Large Multi-family Software Company

• The Challenge: Management was unable to accurately consolidate key performance indicators that measure sales and their implementations for their business after years of company acquisitions that resulted in multiple data stores in a variety of formats.     

• Our Solution: We created a framework that standardized the definition and path from initial sale to implementation for multiple business units and products.  As part of this engagement, we developed an automated transformation layer that ingested data from a wide variety of sources, resulting in standardized metrics for their business. This transformation and calculation capability utilized advanced statistical techniques to harmonize the data, making it available for deeper analysis.  

• The Results: Management now has a clear vision into the state of their sales to implementation path at any point in time for those business units and now has metrics that can be relied on for reporting and planning.  The success of this project has resulted in our continuation of work for this client to add additional business units and metrics on the developed platform.  
   

Established Neurological Sleep Center Clinics

• The Challenge: Management had a sales and geographic growth mandate arising from a recent investment by a private equity firm. They sought a more informed strategy for growth into new markets, as well as understanding the potential within their own existing markets. In addition, they sought guidance on the optimal deployment of sales representatives within a market to achieve that growth.   

• Our Solution: Utilizing their existing enterprise data, which included sales data, representative utilization data, third party medical data, demographic data, as well as competitor data, we worked with them to develop a statistical and algorithmic approach that estimated the potential revenue value for the major markets throughout the United States. In addition, we developed models that optimized the number of sales reps needed to realize that market potential in any major markets.         

• The Results: The models developed were incorporated into their SalesForce instance, allowing management to visualize and develop their strategy for growth into new markets as well as understand how to better realize revenue in existing markets through an optimized sales representative placement.  The models developed continue to be integrated into their business process allowing management to consider multiple scenarios as needed for planning. 

​​

Major Eyewear Retailer

​​

• The Challenge: Management had a sales and geographic growth mandate arising from a recent investment by a private equity firm. However, Management did not have an analytic discipline to provide informed decisions with respect to understanding their customer, store selection and optimal advertising mix to reach that customer.   

• Our Solution: Successfully implemented consumer analytics capabilities including customer segmentation and store location recommendation models. ​Starting with no analytics team and minimal data reporting, addedIQ succeeded in advising this client on the development of a data-driven marketing and store selection capability

• The Results: Models developed help Management better understand their customers and the optimal way to reach that customer resulting in significant ad expenditure decrease while increasing the reach to their customers. Additionally, developed models assisted significantly in  
  A more informed store selection and an optimized marketing expenditure mix