[Article] Enhancing Your Customer Experience with Comprehensive Data Analytics

Table of contents

• Introduction
• Differentiated consumer experience
• The requirements of a data analytics solution
• The WSO2 solution
• Conclusion

Introduction

Connectivity has changed how businesses succeed. The power has shifted from the supplier to the consumer. Earlier, a business would be successful as long as it was able to supply to the majority’s needs. The service or product would mostly be about satisfying their immediate need. Now, with the advancement of technology, the disruptive forces of mobile, data, cloud, and social networking have drastically changed the status quo. Once, where the consumer purchasing decision was taken in-store, led by perception and driven by impulse, is now taken anywhere, led by comparative information and driven by research. This article will provide insight into how you can use several types of data analytics to meet the new and changing needs of your customers.

Differentiated consumer experience

In the age of real consumer power, an enterprise needs to provide a differentiated consumer experience to remain competitive. For example, when a consumer passes a shop at a mall they should receive a discounted offer for a personal favorite product on their mobile. This real-time information provided to the client is relevant, useful and most importantly, personalized and localized. This experience is emotional and makes the consumer feel valued, distinguished and powerful. The consumer experiences the power of exclusivity.

To provide an exclusive experience for the consumers, modern day businesses need to know, understand, respond to and anticipate their needs. There should be existing profiles of consumer preferences so that marketing interactions are unique to each of them.

The requirements of a data analytics solution

Consumers today leave trails of digital tracks in multiple channels. In order to make meaningful insight for this data, businesses invest in data analytics solutions. The majority of data analytics solutions available provide separate offerings for batch, streaming and predictive analytics. Batch analytics is required to understand what has happened through data aggregation of historical data. Real-time or streaming analytics is about the present where incoming data is analyzed to provide opportunity for actions to be taken in real-time. Predictive analytics is about the future where what could happen is analyzed through the usage of forecasting techniques and machine learning models.

Data analytics solutions should be capable of performing real-time actions by rapidly gaining insights from large volumes of structured and unstructured data and combining it with other relevant information such as customer profiles, social activity and demography. It should be able to respond immediately to any short-lived opportunity similar to how an alert is generated when the consumer walks past the mall.

Ideally, for an enterprise to deliver a real differentiated consumer experience, all the analytics types mentioned above need to be in one integrated platform. This provides a unified view of the consumer and their business interactions and enables consistent, accurate and reliable communication with the consumer across all channels.

The WSO2 solution

WSO2 Data Analytics Server (WSO2 DAS) provides you with the perfect solution. It offers batch, streaming, interactive and predictive analytics in one seamlessly integrated platform. WSO2 DAS incorporates the Lambda architecture, which consists of batch, speed and serving layers. Incoming data is sent to both batch and speed layers where the batch layer pre-calculates a historical view of the system and the speed layer calculates the most recent view of the system. This allows you to execute logic on both the batch layer and the real-time layer.

For example, the batch analytics engine can be used for building customer profiles, while the real-time analytic engine can be used to combine multiple simultaneous events such as customer location, customer profile and purchasing history to provide the consumer with a personalized real-time offering. The collected data is fed to the predictive model which learns from it and uses the learned information to accurately predict the consumer behaviour.

Figure 1

Having the capability of an integrated analytics solution alone is not sufficient. Providing real-time customer benefits requires high performing analytics engines that analyze data in batches of large volumes. WSO2 DAS’s batch analytic layer is powered by Apache Spark. Spark can process in memory data up to 100 times higher than Hadoop based batch analytic engines. WSO2 DAS also contains a streaming engine, powered by Siddhi (WSO2’s own solution), which is capable of processing 100K+ events/sec, making it one of the fastest realtime processing engines available.

Information on customer behaviour can be gained from vastly different touchpoints and channels such as social media and web interactions. This introduces different formats of data to the system. WSO2 DAS, which is capable of collecting data in any format or type, provides a pluggable architecture to store data, either in a relational data storage or a NoSQL (Cassandra/HDFS) schema, depending upon your storage needs. Note that many analytics solutions only provide limited options for data storage with the subscription costs tied to data volume, which may become a hassle as your data grows.

Once insights are gained, they must be communicated, for example, by notifying a customer about a preferred product discount. WSO2 DAS’s real-time alerting functionality together with its ability to provide personalized, customizable dashboards for comprehensive visualization of operational details can be used for this requirement.

Alerts are not the only way to provide data from analysis. When combined with WSO2 API Manager and WSO2 Data Service Server (WSO2 DSS), WSO2 DAS provides the opportunity to extend data both within and beyond an organization’s boundaries. This also opens up opportunities for revenue. Enterprises with exposable data can monetize by using WSO2 DSS to expose the analytical data as a data service and then provide access to external parties via managed APIs created through WSO2 API Manager.

Figure 2

Conclusion

For an enterprise to survive in the era of real consumer power they need strong client engagement. To differentiate themselves from their competitors, an enterprise needs to go beyond the norms and develop an emotional bond with its consumer by making them feel exclusive. WSO2 DAS helps you achieve this by providing a high performance, comprehensive and integrated data analytics platform that enables you to offer personalized and exclusive experiences for your customers.