Use Cases
Financial Services Marketing Analytics

Marketing teams are often challenged to predict the propensity of how customers will respond to their campaigns. Several distinct and vastly different datasets are required to tailor a campaign – whether it be a loyalty campaign, or one directed at attracting net new business. Useful datasets include: historical data about how customers have responded to previous offers; demographic data; and financial data such as recent transaction records and credit scoring. Well-executed marketing campaigns are complex, they often span multiple product offering, and rely on several distribution channels. The goal is to understand what structure and messages will realize the greatest amount of revenue with as minimal spend as possible.

Datawatch Angoss will help marketers to easily maximize campaign spend by applying sophisticated optimization models to datasets without the need to manually create sophisticated algorithms from scratch. Even without experience in advanced analytics programming, data science teams can build models that examine the strength in patterns and relationships about the data. With the insight derived from visual outputs such as decision and strategy tree graphics, the marketing team can:

  • Accurately predict the propensity of customer segments to accept a special offer
  • Identify the highest-ROI combination of channels, customer segments, and product treatments
  • Determine which marketing strategy will yield the greatest revenues based on different campaign spend quantities and changes in channel capabilities
  • Create marketing dashboards with time series graphics to interpret the results of the campaign to easily demonstrate ROI of Marketing spend to an exec audience

Datawatch Angoss’ capabilities to automate and repeat common processes, using a rich visual interface allows data scientists and data citizens alike to make more informed decisions on how to successfully monetize campaign spend.

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