Undecided about the value of Big Data analytics? In this post, we’ll look at how much these technologies are already helping companies earn and save.
Big Data might be high tech, but it’s not just for the tech industry. With existing competitors and new startups jostling for position, every enterprise must pay attention to Big Data. Why? Well, look at what could happen if companies began optimizing their data:
Every industry vertical is recognizing that analytics can drive success: telecom giants are forecasting customer purchase patterns through predictive analytics; major automobile companies are using data to make better buying decisions; online companies are leveraging a combination of in-house and third-party Big Data technologies to develop a complete view of their customers.
Let’s consider some specific examples of how Big Data and the Internet of Things (IOT) are already saving a significant amount for companies across industries.
In the retail sector, Big Data and the IOT can be used to monitor changing weather conditions in real time, track seasonal and historical purchase trends by geographical area, and monitor the activity of the competition — all of which helps decision makers stay current with buyer behaviors. And by being aware of consumer habits, demand, and their competitors’ pricing, retailers can dynamically change product prices at the store level. But that’s not all; Big Data systems are also being used to accurately predict production and commodity prices. This gives procurement teams an advantage when negotiating sourcing costs.
Companies with a tight focus on customer relationships can also benefit from Big Data technologies. These businesses aim to provide the absolute best customer experience, either through social media or other channels. By incorporating techniques like speech analytics, companies are able to improve interactions with customers and give them a more positive feeling about their brand, which often leads to repeat purchases.
Maintenance is a key cost in industries which rely on heavy equipment, such as manufacturing, mining and energy.
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