How would you benefit from real-time customer data?
Gartner forecasts that the number of connected IoT devices will reach 20.8 billion by 2020 – driving data volumes to a scale of 44 Zeta bytes (1 Zeta byte = 1 Billion terabytes). This data proliferation presents opportunities for enterprises to capitalise on the information, analyse and act on it in real-time. Thereby augment customer engagement by driving exceptional customer experiences through real-time events detection, which can be actioned on for business benefits.
Security improvements and advanced capabilities have increased the widespread adoption cloud infrastructures. As a result, enterprises now have access to on demand, pay-per-use cloud-based software for processing information, gaining insights and providing better customer understanding at speed and lower costs.
Let’s briefly review how real-time actionable customer insight is applied across different industries.
Retailers can create targeted offers and product recommendations based on a buyer’s online transaction data. They can use real time customer information to drive engagement and satisfaction, increasing sales as a result.
Banks can access customer credit/debit card transaction data in real time against a customised, pre-trained model. This information could be analysed against transactions from unfamiliar locations. For instance, an exceptionally large tip at a restaurant or transactions that defy usual customer spend patterns can be tracked. Notifications can be generated to alert customers of suspicious activity and prevent fraud.
Healthcare professionals can monitor wearable device feeds from individuals with heart problems and other chronic ailments. These changes can be identified and mapped in real time against preconfigured parameters. As a result, timely medical intervention can be provided by alerting medical or emergency services of the impending health crisis.
This ability to adapt to the velocity and variety of streaming data and convert it into actionable insights quickly can redefine the way businesses engage with customers.
There are increasing advancements in the big data technology stack. Couple this with cloud platform progress including availability, scalability, security, interoperability, flexibility, cost and maturity. All of which enable real-time actionable insights across extensive data and diverse channels.
The key steps to converting streaming raw data into intelligent actions are highlighted in the Figure above and include:
machine learning models process the enriched data to make predictions, classifications and recommendations. The data will also be used to further train and improve the models themselves.
The analysed data output will drive, fast decisions to initiate appropriate actions, which in the context of the examples specified above could be:
These architectures could be best implemented using cloud technologies, as the cloud provides the required flexibility, availability and PaaS (Platform as a Service) capabilities. These can handle huge volumes of data and provide computing strength to drive analytics through in-memory databases. The cloud also provides on-demand computing infrastructure with the financial model flexibility of OPEX, as compared to an upfront CAPEX investment.
As customer expectations continue to rise, real-time insights and actions can help improve customer engagement, increase revenue, maximise operational efficiency and even detect threats really quickly. This will minimise the time from the business event occurrence to a corrective action or notification being initiated.
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