DeepTarget Enhances Its Machine Learning Algorithms, Further Increasing Predictive Accuracy to Improve Consumer Experience and Engagement

DeepTarget Inc., a solution provider that utilizes data mining and machine learning to deliver targeted communications across digital channels for banks and credit unions, announced it has expanded its use of leading-edge machine learning techniques to further help community financial institutions use predictive campaigns to present more relevant offers with virtually no effort. In addition to more accurate targeting, this release expands the product types and enhances the overall quality of the customer and member experience. The enhanced algorithms are based on extensive updates to the data used and the machine learning models that have been successful in the past.

With its Digital Experience Platform (DXP) and innovative 3D StoryTeller, DeepTarget helps community financial institutions design and execute intelligent cross-channel marketing campaigns that leverage the latest machine learning technology. By utilizing a predictive model to target specific audiences with the highest propensity to purchase particular products, financial institutions can effortlessly yet more accurately calculate the likelihood that individual customers and members will open specific accounts.

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“We have been using DeepTarget’s predictive modeling targeting method for the past eight months and as a result, it has reduced the amount of time we need to spend setting up campaigns while also resulting in an increase in user response”

To further increase the accuracy and precision of predictive campaigns, DeepTarget has implemented stronger data sets that include the most recent customer behaviors and actions, based on years of advertising and demographic insights. In addition, new loan and deposit product types have been added for predictive campaigns. These enhancements enable financial institutions of all sizes to use techniques and insights previously reserved for only the largest institutions. ​

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“We have been using DeepTarget’s predictive modeling targeting method for the past eight months and as a result, it has reduced the amount of time we need to spend setting up campaigns while also resulting in an increase in user response,” said Adam Stevens, eBranch Manager, Eglin Federal Credit Union. “We are excited to hear about the new enhancements.”

“We continue to invest in innovation to drive success for our financial institution customers,” said Preetha Pulusani, CEO of DeepTarget. “By automating the process with machine learning algorithms, we are easing the marketing burden many community institutions experience. In our internal testing, our upgraded algorithm selected customers with a high propensity to open accounts 96.6 of the time – or ~30% greater accuracy related to improvements in the models and utilization of a wider array of data fields. Ultimately, it is about ensuring that predictive campaigns effortlessly and accurately target the right consumers enabling FIs to provide relevant and human-like engagements.”