Business intelligence analytics is the number one priority of CIOs around the globe and financial services businesses are in a strong position here. They are data rich, usually with resources to apply high-quality analytical procedures. Traditionally, data has been used reactively, but the volume of social data and ever evolving tech means that a more proactive approach is possible and is becoming the smart way to make big business decisions. Here we look at the types of approaches and how they can use social data.

Reactive – big data and business intelligence

Reactive data analysis can take place only after a stakeholder has experienced the company’s product or service and provided some form of feedback. Reactive analysis on this static past is often, although not always, seen as negative, since the feedback received is in many cases complaints or technical support calls, and similar.

Because the stakeholders often offer the information directly without being sought, reactive data is typically easy to gather, the difficulty coming with turning large amounts of qualitative data into more usable numbers. So, even in the context of ‘big data’ and larger data sets it is still reactively pulling past static reports and is ultimately flawed as the overheads it requires versus the accuracy of can slow businesses down.

Proactive

Proactive data gathering is far more difficult, as it can take place before, during or after a potential customer has had experience of the company. This includes predictive modelling and social sentiment measurement.

Using social data in the context of real-time analysis, allows trends to be measured at any given snapshot in time, and therefore measured against real-world events to be a more accurate reflection of the impact of business changes, communications and reaction.

This has been a more complicated way of using data, and therefore a more expensive and resource-draining activity. With the advancement of new technology, and algorithms to allow social data to be interpreted in a customised way, this is going to be much more accessible and cost-effective. The benefits of a platform like Trendensity will allow businesses to spot trends, weaknesses and determine conditions for making decisions.

This cannot be achieved with ‘big data’, because processing times cannot keep up with real-time action. So, the businesses who invest in these ‘smart’ and innovative apps, platforms and tools, will be able to gain competitive advantage.

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