Data analytics centres on providing business leaders with insights that are visually cohesive and understandable. In contrast to manual-based queries, these are based on the inherent logic related to mathematical formulae and algorithms. Even though this analysis happens in milliseconds, giving it the appearance of being real-time, it is always after the fact. Yet, no organisation who wants to be digitally transformed can do without it.
Analytics relates to accessing numerous data volumes instantaneously. It is an inherently technology-driven and automated process requiring no manual intervention to effectively deal with the big data involved.
In practice, this enables financial services providers to perform real-time credit scoring. For instance, a person applying for credit using an online site will receive a virtually instantaneous response if they have qualified for a loan.
By using behavioural analysis, real-time data analytics can maximise customer satisfaction. Just consider how online stores make recommendations based on prior buying habits, items saved on wish lists, or products recently browsed. It can also assist with fraud detection. So, if a card gets swiped, alerts are triggered if the purchase type or value are significantly different from previous buying history and typical customer behaviour.
Companies can also use the data to identify other opportunities to target customers for relevant cross-selling. Even financial traders can benefit from data analytics and be sent real-time alerts on market fluctuations that they can react on faster than before.
Furthermore, the healthcare industry can combine analytics with monitoring devices such as heart and blood pressure to receive life-savings alerts when any irregularities are detected.
Real-time data analytics can increase business agility. In retail, this could translate to making faster decisions in relation to stock management when products are almost sold out.
It can also help address any operational issues. In manufacturing, predictive maintenance becomes a critical differentiator to identify machines likely to break down. Banks can benefit from receiving alerts to better service their ATMs.
A personalised customer experience is also possible to increase end user satisfaction. After all, a customer who is directed to relevant products and pages on a Web site based on their previous behaviour, will be more responsive to such a more customised approach.
Incorporating real-time data integration from various sources and even service providers, analytics can further improve customer service levels. So, agents can better manage queries and organisations can develop new products based on this analysis. Analytics can help business leaders act on market changes and respond in more agile ways.
The overarching benefit to real-time data analytics comes down to companies benefitting from faster decision-making. However, even if this is in place, the organisation must have the willingness and ability to react to such near real-time insights.