Dave Irwin
Increase Campaign Precision and Relevancy with Dynamic Predictive Audiences
simMachines, Inc., the leader in Explainable AI / Machine Learning applications, announces the launch of their latest product—Dynamic Predictive Audiences designed for data companies, publishers and media platforms.
Dynamic Predictive Segmentation is the Future of Marketing
Today’s digitally-empowered customers have high expectations for relevant, highly personalized customer experiences. Companies must keep pace with these growing demands or they will be left behind by their more perceptive competition.
Similarity Based Machine Learning Provides AI Transparency and Trust
Similarity is a machine learning method that uses a nearest neighbor approach to identify the similarity of two or more objects to each other based on algorithmic distance functions.
Dynamic Predictive Segmentation Will Upgrade Retailers Relevancy with Shoppers
It’s well known that the “Amazon effect” is wreaking havoc on retailers’ ability to lure and retain shoppers because of their inability to predict what motivates customers to buy and to be relevant in the moment of interaction.
AI Enabled Customer Segmentation Will Transform Marketing
Marketers are missing opportunities when they use static segmentation, which is not predictive of customer behavior and fails to take customer context into account.
Machine Learning with Transparency Changes the Art of the Possible in Marketing
Most marketers are just beginning to explore machine learning applications. Machine learning is already providing tremendous analytic efficiency gains and increased precision.
Speed to Insight – How Marketers Can Achieve Long Term Competitive Advantage
Machine learning helps level the playing field for all marketers if applied effectively, because it can quickly be deployed at speed and scale within critical areas of the business – such as preventing high value customers from leaving or more effectively attracting and delighting high value customers through more relevant dialogs.
Marketers Need Granular Transparency Behind Machine Learning Predictions
Demand for explainable AI over the last year has started to ramp up from a variety of perspectives. DARPA, the Defense Advanced Research Projects Agency, for example, has been calling for more explainable machine learning models that human users can understand and trust.
Revealing the Secrets of AI or Killing Machine Learning?
The General Data Protection Regulation (or GDPR) going into effect in the EU in 2018 requires that algorithms used to make credit or insurance decisions must be explainable to consumers.
The Financial World Wants to Open AI’s Black Boxes
For financial services firms, the fact that artificial intelligence algorithms are “black boxes” that don’t enable them to explain decisions is a major problem to due legislative requirements.
