DMI Analytics Engine

Better insights for better decisions

Our proprietary automation engine works with data integration and business workflow tools to quickly model and deliver predictive solutions. With the ability to configure and automate analytics and build business rules, the Analytics Engine makes it easy for users to access results through the business intelligence infrastructure. Several pre-constructed analytical models exist for standard business functions such as performance analytics to model general business performance, sales analytics or supply chain analytics. In addition, a variety of pre-built models have been constructed for specific industries to help our clients get a jumpstart on mining the insights they need.

What can Analytics Engine do for business?

the scenario

A business development manager is responsible for multiple products and geographies within his company. He knows that in order to stay ahead, he needs to be proactive. Unfortunately, he often has to make strategic decisions without a clear picture of what’s actually driving his business. The manager knows he achieved new business and organic growth over the past year, but also experienced some customer attrition.


To understand what’s driving revenue and profitability, the manager wants to know what specific changes in sales volume, product mix and pricing are having the biggest impact. That way, he will know where to focus his attention. The manager uses DMI Analytics Engine to analyze historical data across products, regions and segments to identify the changes in pricing, volume, cost or mix of units that were most significant in affecting results. The tool allows him to quickly identify the top three drivers contributing to revenue growth and profitability, as well as the top three missed revenue opportunities.


Analytics Engine helped the manager discover that price increases in supplemental products were the number one factor influencing revenue growth for the year. He also learned that even though volume was up in the northeast, that region hadn’t kept pace with the rest of the division and represented a significant missed opportunity. He used these insights to implement targeted growth and retention strategies. By using the “what if” analysis tool, the manager was able to play out different hypothetical scenarios and see how changes in certain variables would affect his division’s overall results. This information helps him save time, ask better questions and make better decisions.

Solution Components

Customizable Platform

Both frontend and backend can be customized and branded, a big value-add compared to

user profiles

App users can create personal accounts where they can store preferred payment information

personalized recommendations

Collect valuable customer data that helps create relevant suggestions for other events

location-based discounts

Target customers with personalized offers based on geo-location.

filtering options

Allow users to sort inventory based on their personal

social network integration

Increase your awareness and reach by allowing users to share info about recently purchased tickets and invite others to get in on events.

inventory tracker

Get detailed reports based on up-to-date inventory.

dynamic pricing

Update pricing based on supply and demand.

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