Precision recommendations – beyond collaborative filtering

A recommendation engine is the most obvious of eCommerce strategies for any business trying to boost revenue from its existing client base. Collaborative Filtering is the most commonly recognized technique for finding likely customer-product matches, given only sparse purchasing history data. A recent innovation, known as Factorization Machines, far exceeds collaborative filtering in recommendation precision, to the point where a single customer-product pair can be identified to set the recommendation score. In addition, this new technique incorporates cross-feature influences, which may be too important to be overlooked. For example, a viewer may actually dislike romance and comedy movies, but is fascinated by romantic comedies.

Detection of prospect funnel state ­ buyer readiness

The sales funnel is an important marketing concept used to direct sales efforts and organize campaigns. While marketing automation platforms offer prospect scoring, the feature is always set manually. Advanced analytics, such as Hidden Markov Model (HMM), can automatically and optimally score each prospect based on their digital behavior. Digitally intelligent enterprises can leapfrog the competition with aggressive adoption of data-driven innovations and harness these important hidden indicators.

Advanced classification for market segmentation

While fine-grain personalization is well within the capability of today’s app serving platforms, from a management perspective, it is of practical necessity to conduct campaigns at a cluster level. Analytically sophisticated organizations can make guided decisions in choosing among a host of clustering techniques from simple (k-means) to advanced (latent classification) to handle data at the extreme scales of volume and complexity. Mathematically-derived classifications reduce dependency on gut feelings in favor of consistent returns.

Streaming analytics for real-time customer monitoring

There are a number of use cases where a timely response from an organization is vital to success. A dissatisfied customer can exhibit familiar disapproving behavior patterns right before defecting to competitors. Other digital signatures are indicative of high receptivity to promotional efforts. The concept can be extended to fraudulent transactions to help predict and prevent loss. The urgency for response in these cases are self evident. Streaming data analytics brings real-time pattern detection within reach of every progressive organization.

Data Management Platform can help you design and build your Data Management Platform (DMP) to help drive your marketing initiatives. A DMP can help incorporate unique data including online retail transactions and catalogs, social media, and online advertising. With a focus on actionable business results, a well-designed DMP supports hypothesis­-driven, high-impact analyses; helping your organization move from simply collecting data to surfacing actionable insights.