Financial companies struggle to find the balance between maximizing revenue when offering a line of credit to an applicant and minimizing the propensity of the applicant to default on payment. The conflict between maximizing profit and the constraints put on customer authorization campaigns to minimize risk often leaves significant revenue opportunities unrealized.
The sheer number of mathematical possibilities when profiling hundreds of thousands of data points against many possible increases in incremental credit line offerings means traditional tools such as spreadsheets are ineffective. Using Altair, data science teams can build models to determine the appropriate budget required for a campaign that would return the highest revenues; predict which distribution source (ex: email, call centre, direct mail) an applicant would likely respond from to an offer of a credit line increase; and understand which applicant would be considered at risk if an increase in line of credit was accepted.
Well-executed marketing campaigns are complex, they often span multiple product offering, and rely on several distribution channels. Marketing teams are often challenged to predict the tendency of how customers will respond campaigns. Whether the campaign is to increase customer loyalty or to attract new business, it is common for several distinct and vastly different datasets to be used, including historical data about how customers have responded to previous offers; demographic data; and financial data such as recent transaction records and credit scoring.
Altair helps marketing teams to more accurately predict the propensity of customer segments to accept a special offer, determine which marketing strategy will yield the greatest revenues based on different campaign spend quantities and changes in channel capabilities, and create marketing dashboards with time series graphics to interpret the results of the campaign that demonstrate the ROI of Marketing spend to an executive audience
Whether it be scheduled or unscheduled, the cost of downtime in manufacturing environments can be extremely costly to the business- to the tune of millions of dollars annually. Unexpected downtime can significantly impact tangible and intangible operating costs. To mitigate risk associated with downtime, manufacturing operations often develop equipment maintenance calendars, servicing equipment regardless of whether it is needed, leading to higher than necessary overhead expenses.
Advances in technology have enabled organizations to collect real-time data about how their equipment is operating. This data contains hidden indicators of future equipment failure. Using predictive analytics manufacturers can extract these hidden insights so they can choose to do maintenance when the risk becomes high. The result is avoidance of costly or dangerous unplanned downtime and more efficient scheduling of repair and maintenance personnel and resources.
Altair’s Data Analytics Predictive Maintenance (PdM) models have helped manufacturers avoid high costs related to unplanned outages, have optimized planned maintenance schedules, and have created efficient, cost-effective repair cycles.
Today’s consumers have taken full advantage of online retail sites to compare product offerings, pricing, and purchasing options. It is not uncommon for shoppers to visit a physical store, look over merchandise, and then purchase it online. While seen by the consumer as a positive shopping experience, to the retailer this leads to inventory overstock, higher operating costs, and eroding customer loyalty.
To address this, retailers are looking to their data they generate every day- from their websites, point of sale systems, supply chain systems, loyalty card use, in-store sensors and more. Altair Data Analytics helps retailers to segment and profile consumers to understand their propensity to react to different product marketing offers and to trace in-store behavior to better understand how consumers will respond to product placement, purchase incentives, and experiences that lead to impulse buying behavior.
Altair Knowledge Studio helps retailers find insight about consumer behavior and market trends which can lead to greater market share, higher customer loyalty, and more efficient distribution of products and services.