Big data has become a big game changer across most modern industries. In the last two years alone, we’ve created 90% of the world’s data — that’s two and a half quintillion bytes. It’s no surprise that businesses are drowning in unstructured data and understanding the value in this information is challenging. Gartner reports that over 75% of companies are investing or planning to invest in big data, and this number is only set to grow. With the introduction of new technologies to make sense of this information, cognitive computing is steadily combining machine learning, reasoning and natural language processing to mimic the functioning of the human brain to help improve human decision making.
Big data is being used across a range of industry verticals to enhance customer experience, reduce operational costs and create better targeted marketing campaigns. To capitalise on big data, it’s important to understand industry specific challenges and match market needs. Read on to find out how the below 3 industries are being smart with data and revolutionising how they work.
Banking & Finance
The banking and finance sector face especially unique challenges when considering their core business needs and the application of big data solutions. Analytics are a critical game changer here, and offer a unique perspective on problems. Technological capabilities can be applied to improve business process, particularly in the area of customer service where there is a high opportunity to increase conversion and revenue.
Commonwealth Bank of Australia are using big data as a key component of their risk management strategy to combat fraud and customer risk. Tracking customer behaviour in real time allows computer applications to alert relevant parties of any suspicious activity. This real time evaluation can detect fraud signals, and analyse them using machine learning to accurately predict illegitimate users and transactions.
Retail has been a challenging and dynamic vertical in recent years, having experienced a boom in the growing online space. eCommerce has changed the way customers shop, and this has created new challenges and interesting opportunities. One of the key unique considerations in big data management here is how to aggregate the influx of data from the many different sources. Loyalty programs, POS, store inventory and local demographics all represent different data. Stores are beginning to adopt data first strategies on and offline to better understand buying behaviour to map customers to products. Before big data integration, the closest that customers could get to a personalised experience with retailers was through loyalty programs, now marketing automation and site behaviour analysis ensures that every piece of content a retailer is serving to their customer is personalised and relevant. This data driven personalised customer experience is enabled by cognitive technologies and is helping retailers stay ahead in this competitive space.
Target utilise big data campaigns to focus on expecting mothers before their babies are born. Understanding women’s shopping habits, Target was able to effectively identify that women buying large quantities of unscented lotion, cotton balls and supplements might indicate that she is pregnant. Hooking a shopper before their baby is born ensures that Target have made a new customer for life. In one instance, Target were able to identify a pregnant customer before she could even announce her pregnancy.
Media & Entertainment
The media and entertainment industry face a specific key challenge in their space, and it’s to do with keeping the user’s attention for long periods of time. Great content is one step, but introducing a scientific, measurable element that was previously missing enables media industries to serve content that the user is more likely to keep coming back too. Collecting and analysing consumer insights, leveraging mobile and social media content to understand patterns of real time media and content usage are all important in creating a meaningful experience for their user.
Appealing to over 100 million subscribers worldwide, Netflix is one major player that’s breaking boundaries with the use of powerful technologies that focus on delivering the best possible customer experience. Netflix use the Apache Cassandra database to manage their huge influx of user generated data. This technology dynamically scales when needed, ensuring high availability while handling very large amounts of data across its servers. This software is particularly great for multiple geographies — great for cross-datacenter and cross-regional deployments while maintaining an extremely flexible data model. This means that the user is served content quickly and their behaviour is tracked and measured to ensure that future content is still on track to meeting expectation. The only obstacle that Netflix now need to battle for your attention is sleep!
Leveraging big data to make business decisions is an important consideration for ongoing success and futureproofing. In order to efficiently capitalise on big data opportunities consider your industry specific challenges and distill them into key goals. Understand specific data characteristics of your industry and customer to learn where your customers are spending their time, attention and money, then consider how to match your offering with your users needs.