Use Machine Learning to Cut Down on CX Development Distractions

How AI-powered anomaly analysis can help guide customer experience

As businesses in the Experience Economy wrestle with Big Data, the use of artificial intelligence (AI) guided by human insight becomes ever more important when dealing with data anomalies.

Problems in Anomaly Detection

There are always anomalies that pop up — data patterns that don’t make sense, consumer behavior that falls outside of expected parameters, glitches in the customer experience — and much of the challenge is finding them within the flood of information that businesses must process on a daily basis.

The more information companies gather, the greater the challenges of managing and analyzing it. Writing in D!gitalist, Debbie Fletcher illustrates the weaknesses of conventional approaches to anomaly analysis in a world of Big Data:

On the one hand, that may mean that marketers pore over reports after the fact to discover patterns and scout for opportunities. In either case, they are necessarily working with a modest number of metrics and likely to miss many subtle but potentially costly anomalies. At the same time, they are working retrospectively and losing the impact of real-time insights. Alternatively, some businesses attempt to identify anomalies by setting thresholds on KPIs to trigger alerts when the numbers go either too high or too low, a difficult and overly objective task when compared to the efficacy of machine-learning systems.

Innovations in machine learning are giving businesses better tools for detecting anomalies in massive amounts of data in real time.

Applying Experience Intelligence to Anomaly Detection

Improving anomaly detection is only half of the equation. For organizations, the ability and insight to discern the importance of the anomalies is equally important. Resources are finite. In the Experience Economy, businesses should concentrate on solving anomalies that directly affect the experiences that customers are going to actually face on a regular basis.

How often does the anomaly occur? Does the anomaly scale enough to impact the customer experience? Innovation managers need to be able to avoid being distracted from the important issues their organization truly needs to engage to improve customer experience.

Incorporating Data Science

The data science experts at LMS can help your company put machine learning to use to improve anomaly detection and better leverage data analysis to improve the customer journey. Call us at 800.257.5902 to learn more or reach out to us today at [email protected]

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