8 Different Big Data Use Cases For Your Organisation
This Big Data platform is all about bringing together organizations who want to create a Big Data strategy and match them with Big Data startups. For organizations it is therefore necessary to understand how to use Big Data within an organization. Therefore, we have created a top 8 of the best Big Data use cases for organizations. Please let us know if you have more or different use cases or other remarks via the comment section at the end.
1. Truly Get to Know Your Customers, All of Them in Real-time
In the past we used focus groups and questionnaires to find out who our customers where. This was always out-dated the moment the results came in and it was far too high over. With Big Data this is not necessary anymore. Big Data allows companies to completely map the DNA of its customers. Knowing the customer well is the key to being able to sell to them effectively. This can go to the extreme and cause privacy issues if not being implemented carefully. A perfect example of that is the case when Target found out about a teenager’s pregnancy before the father even knew.
But if companies make sure that the privacy of customers is not threatened, Big Data can deliver personalised insights about individual customers. Using interconnected social media data, mobile data, web analytics and other Big Data analytics it is possible to exactly know who each customer is, what they want, when they wanted it and all in real-time.
The advantage of truly knowing your customer means you can give recommendations or show advertising that are tailored to the individual needs. Amazon has mastered this to perfection, as the recommendations it gives its customers are not a coincidence. The recommendation engine used by Amazon bases this on what a user has bought in the past, which items they have in their virtual shopping cart, items they've rated and liked and what other customers have viewed and purchased. The algorithm that Amazon uses allows giving each individual customer a different webpage. And this strategy pays off: The company reported a 27% sales increase to $13.18 billion during its third fiscal quarter, up from $9.6 billion during the same time last year.
2. Co-create, Improve and Innovate Your Products Real-time
In the past we had consumer panels to discuss with customers what they want, to show them products that were finished and to find out what they thought of it. If they did not like it you were in trouble. With Big Data this belongs to the past.
Big data analytics can help organisations get a better understanding of what customers think of the products. Through listening on social media and blogs what people say about a product, it can give more information about it than with a traditional questionnaire. Especially if it is measured in real-time, companies can act upon possible issues immediately. Not only can the sentiment about your products be measured, but also how that differs among different demographic groups or in different geographical locations
Big data also allows companies to run real-time simulations, thousands at a time, to test a new or improved product digitally. With scalable computer power, combined with simulation algorithms thousands of different variations can run and be tested at the same time. Each design can be tweaked a little bit and the simulation program can combine all the minor tweaks that showed an improvement into one product.
Offline products, such as cars, can also be improved and innovated using Big Data, if it is know how they operate and perform ‘on duty’. Ford actually opened a lab in Silicon Valley to improve its cars. In order to improve their cars with regard to quality, fuel consumption, safety and emissions, Ford aggregates data from over 4 million cars that have in-car sensors and remote app management software. All data is analysed in real-time allowing engineers to notice issues in real-time, understand how the car responds in different road and weather conditions and any other forces affecting the car.
3. Determine How Much Risk Your Organisation Faces
Determining the risk a company faces is an important aspect of today’s business. In order to determine the risk of a potential customer or supplier, he is placed in a certain category, each with its own risk levels. More often than wanted a customer or supplier is placed in a wrong category and thereby receiving a wrong risk profile. A too high-risk profile is not so harmful, apart from lost revenue, but a too low risk profile could seriously damage a company. With Big Data it is possible to determine a risk category for each individual customer or supplier based on all of their data from the past and present in real-time.
Especially in the insurance business, predictive analyses are used to determine how much money a customer will cost in the future. They want to identify the right customer for the right product at the right price and lowest risk in order to ensure reducing claims costs and fraud. Using Big Data techniques such as pattern recognition, regression analysis, text analysis, social data aggregation and sentiment analysis (via natural language processing or monitoring social media) a 360-degree view of a potential customer is created. This holistic and up-to-data picture of a customer can reduce risk significantly. Such a 360-degree analysis can of course also be used to determine the potential risk of a new or existing supplier. For many financial institutions this is top priority for the coming years.
4. Personalize Your Website and Pricing in Real-Time
Companies have used split-tests and A/B tests for some years now to determine the best layout for their customers. With Big Data this process will change forever. Web metrics can be analysed constantly and in real-time. This will allow companies to have a fluid system where the look, feel and layout change to reflect multiple influencing factors. It will be possible to give each individual visitor a website specially tailored to his or her wishes and needs at that exact moment. A returning customer might see a different website a week or month later depending on his or her personal needs for that moment.
Big data can also have an effect on the prices offered. Yield management in e-commerce could potentially take on a whole new meaning with Big Data. Orbitz experimented with this already by showing Apple users more expensive hotels than PC users. Orbitz had found out that Mac users on average spend $20 to $30 more a night on hotels than their PC counterparts.
Using algorithms it will also become possible to react to events in the market or actions of competitors in near real-time and adjust prices accordingly. Companies that have started using Big Data to personalize online offering towards personalized needs are enjoying an increase in sales and profits.
5. Improve Your Service Support for Your Customers
With Big Data it is possible to monitor machines from (great) distance and check how they are performing. Using telematics, each different part of a machine can be monitored in real-time. Data will be sent to the manufacturer and stored for real-time analysis. Each vibration, noise or error gets detected automatically and a when the algorithm detects a deviation from the normal operation, service support can be warned. The machine can even schedule automatically for maintenance at a time when the machine is not in use. When the engineer comes to fix the machine, he knows exactly what to do due to all the information available. A good example is the construction business that already uses telematics to improve efficiency of operations.
6. Find New Markets and New Business Opportunities
More and more governments stimulate companies to make use of the massive amounts of open data collected by the government in some way or another. In 2011, the European Union organised the Open Data Challenge. This was Europe’s biggest open data competition to stimulate startups to come up with innovative solutions using the massive amounts of open data generated by governments. The Dutch government focuses actively on stimulating the re-use of open cultural datasets and organizes hackathons to come-up with new solutions.
Furthermore, companies can discover unmet customer needs using Big Data. By doing pattern and/or regression analysis on your own data, you might find needs and wishes of your customers you did not know they had. Big data can also help companies find where to market a product first or where to place a product. Vestas Wind Systems, a Danish energy company, uses Big Data and analytics to pick the best places to locate wind turbines around the world.
7. Better Understand Your Competitors and Stay Ahead of Them
What you can do for your own company, you can do more or less also for your competition. This will help you better understand your competition and knowing where they stand. It can provide you with a valuable head start. Using Big Data analytics, algorithms can find out for example if your competitor changes its pricing and automatically change your prices as well to stay competitive. You can also monitor other actions of the competition; such as automatically follow new products or promotions (and how the market responds to it). Don’t forget that so much that is done by you or your competitors is available as open data and thus can be tracked as well as own data.
8. Organize Your Company More Effectively and Save Money
By analysing all the data in your organisation you may find that you can be better organised. Especially the logistics industry can become more efficient using the new Big Data source available in the supply chain. Electronic On Board Recorders in trucks tell us where they are, how fast they drive, where they drive etc. Sensors and RF tags in trailers and distribution help on-load and off-load trucks more efficiently and combining road conditions, traffic information and weather conditions with the locations of your clients can substantially save you time and money.
Of course the above use cases are just a small portion of the massive possibility of Big Data, but it shows that there are endless opportunities to take advantage of Big Data. Each organisation has different needs and requires a different Big Data approach. So start figuring out how your organisation can benefit from Big Data or please let us know if you have already done that and want to share it with other on this Big Data platform.