The big data revolution is the key to unlocking increased sales
In the current climate of uncertainty and change, companies must be able to adapt and respond to emerging market trends swiftly. Key to success is how well they use their data, not just measuring it, but using it to change strategy, drive product innovation and gain competitive advantage.
Jacyn Heavens, founder and chief executive of electronic point-of-sale company Epos Now, says: “The process of bringing new solutions to market more quickly and efficiently can be enhanced by analysing what has worked well and not so well in the past, and bringing that knowledge to bear in creating new product concepts and ultimately prototypes. This process must also be about gathering customer feedback and analysing to tweak and further enhance the solution moving forwards.”
Understanding the principles of using data to innovate is one thing, but are businesses putting them into practice? Research from Experian suggests senior executives are aware of the opportunities data provides to become more agile and more productive, but also highlights barriers such as limited budget (51 per cent) and volumes of data (47 per cent) that prevent businesses from exploiting these assets.
“A C-suite data champion representative will help,” says Experian’s data expert Rebecca Hennessy. “Only when the strategic value of data is realised at board level can businesses be in a better position to exploit data.”
For years the retail sector has lagged behind others in the use of technology to harvest data, but after a slow start the big data revolution is starting to emerge.
According to Dmitry Bagrov, UK managing director of technology consultancy DataArt, machine-learning using harvested big data is proving to be a Holy Grail for the retail industry’s marketing and strategy departments.
He says: “Firms that can better understand their customers’ unique desires and preferences will gain significant competitive advantage in deciding future strategy. For example, ‘scan as you shop’ devices are the easiest way to collect data in real time about how and why customers buy in a particular shop. Early adopters that apply machine-learning to harvested big data can build a far more detailed profile of their customers than those who lag behind.”
Data is one of the banking industry’s most valuable assets, yet most high street providers are still not using it smartly for upselling or improving customer services.
“If they want to keep the fintech challengers away from eating their lunch, heritage banks need to unleash and embrace the big data that is locked away in their 60-year-old systems,” says Nanda Kumar, president and chief executive of business software firm SunTec.
This could be achieved by using customer transactions to inform real-time offers, and create a personalised customer experience and additional value-add for an underappreciated market.
“When you book a holiday, for example, it’s likely that you also need travel insurance, money exchange and local offers at the destination,” says Mr Kumar. “Using their big data, banks have the power to help.”
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