Improving Customer Service with a Data-Driven Strategy
83% of customer service decision-makers agree that the customer service function of their organisation is a strategically important function, and customers tend to agree – with 94% more likely to repurchase a product or service if they have effortless customer service interactions, with an 88% probability of an increase in spend.
By using big data to analyse how customers are engaging with your company, what their customer experience has been like, the expectations they’ve had, and where problems have occurred – you have the ability to create a customer service experience that is far superior to competitors who aren’t taking advantage of this data.
By empowering your customer support with a data-driven, strategic approach – you can position your business to be proactive, easy to use, and exactly what your customers are looking for.
Reducing Costs and Increasing Efficiency
When it comes to running your business, reducing costs whilst increasing efficiency should definitely be a serious strategic goal.
By using predictive analytics, evaluating trends, and applying data science to how a company is operating (viewing expenses, purchases, how time is being utilised, etc), you can identify what areas need a closer evaluation or change, where future problems may occur (and how to prevent them), and determine how best to invest your resources going forward.
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Developing More Effective Processes Against Operational Risk
There will always be a certain amount of loss due to human error – it may, for example, be internal, such as failure to adhere to processes, or lack of planned responses to disasters, etc – or it could be external, such as from hacking and breaches of security.
Big data can be used to analyse, observe, and detect certain processes or datasets, and then detect any issues that occur – this type of automation means there is less time between an error occurring and it being discovered to be dealt with.
This can be applied internally and externally, and it doesn’t even have to be applied only to risk – if you have certain processes that are currently handled by employees, but could be automated with the right tools – then it may be more effective, and less prone to operational risk, to apply data-science and big data processes.
Using big data is something that a huge number of businesses are getting on board with (97.2% of companies say they’re investing in big data and AI projects) – and as technology continues to evolve and grow, those who aren’t making the most of the information they’re gathering, are going to fall behind.