Data in businesses today is more valuable than it has ever been. The world now has advanced forms of analytics as well as the ability to collect thousands of data points conveniently. A combination of technology tools and methodologies can now provide insights faster and more accurately than at any other point in history. Any business that is creating data has the chance to draw value from such data to build efficiency or take advantage of new opportunities. Some of the capabilities that data science has unlocked in the past decade are radically transformational. Autonomous systems and conversational AI will revolutionize manufacturing, marketing, financial services, and other sectors. Here are a few surprising insights data science services can uncover.
1. Detection of Anomalies through Data Science Services
In sectors that generate large volumes of data, such as financial services, being able to detect anomalies in big data can have huge consequences. Statistical methods have for a long time been able to identify outliers in small data sets. However, doing so manually or using simple statistical packages is unfeasible. However, with more powerful tools now, it’s possible to analyze petabytes of data more efficiently.
This can help identify possible fraud and respond on time. For instance, credit companies can quickly flag suspicious transactions on its clients’ cards and initiate proper responsive actions. Constant monitoring of IT systems also helps to flag and prevent cyber-attacks. Such things as service portals for customers can be the source of attacks and it’s therefore prudent to develop ways to differentiate between normal customers and attackers attempting to gain access to the network.
2. Service Planning through Predictive Modeling
Predictive modelling is a direct result of improvements in the data science technology. Machine learning algorithms can now handle large data sets more accurately and make valuable predictions with applications in numerous industries.
Airplane manufacturers have a duty to maximize the uptime of their aircraft as this is a big measure of their reliability. Therefore, predictive modeling helps to plan a maintenance schedule that keeps the airplanes in use as much as possible. They monitor thousands of data points on the health of the aircraft and service is done proactively.
Companies in the oil and natural gas sectors also take a proactive approach to maintenance of their expensive machinery because breakdowns are much more costly to fix.
3. Manufacturing Defects through Data Science Services
IoT devices can wireless connect to a network and transmit data. They are installed with sensors and the ability to process and exchange data over the network. IoT technology can help a business that’s dealing with warranty problems uncover an underlying issue in their manufacturing line. By installing IoT sensors in devices being shipped to customers, it becomes possible to monitor device health. The company can then correlate data on device health to warranty claims to find the root cause of failure. In the long run, this approach improves the customers’ experience.
4. The Right Way to Segment Customers
Businesses must realize the different needs of its customers to serve them well. Data science can help identify the different needs of customers and use that create groups or segments. Segmentation is crucial for the development of marketing plans. Customers can be grouped by age, gender, income levels, location, previous purchases, and so on. With a proper marketing plan, the business can drive conversations aimed at different segments. This makes the communications more focused, and no segment is ignored. The business is likely to get a higher return on its marketing efforts.
5. Best Content Strategy
Businesses often struggle to quantify the effectiveness of their content strategies. A lack of proper assessment can leave your content strategy looking like a trial-and-error experiment. However, with data science tools, it’s possible to measure how customers are responding. The application of serial testing in content can help tell the effects of certain choices of words and color have on customer reactions. By collecting enough results from serial testing, it becomes possible to create predictive models to help make the best choices for future creative content in order to maximize reach and impact.
6. Customers’ Sentiment on a Brand
Being able to measure customers’ sentiments on a brand is extremely valuable today. People today can easily share their reviews on a brand through social media. They have a community of followers and friends, however small. Brands today are opting to work with micro-influencers because of the power of those communities.
Social media listening is thus an important endeavor for brands today. Natural language processing makes it possible to tell whether comments on a brand are positive, negative, or neutral. The brand can highlight positive customer experience and respond to negative ones. Social media listening tools help brands engage more organically with audiences on social media avenues.
Businesses can also identify trends and changing customer tastes by following conversations on social media. Travel companies can discover new destinations of interest or new experiences that people are enjoying and capitalize on them. Customer-generated content is a great resource for businesses if correctly leveraged.
7. Personalized Offers to Customers
Data will help you know your customers truly. No two people have totally identical preferences. Therefore, businesses that offer may products should try and recommend what best suits a particular client best. This is possible with data driven recommendation algorithms. Media-streaming platforms such as YouTube and Spotify have managed to implement this successfully to recommend content based on a person’s past content consumption.
By continuously collecting information from a customer, a business can build a profile to help serve the client better. The business can move past segmentation to personalization. If a business makes a consistent effort to build profiles of its customers, it will be able to uncover needs even the customer did not realize they had. The customer will then become loyal to the brand.
Taking the Right Approach to Data Science Services
Indeed, handling large volumes of data can be overwhelming even for data scientists. First, businesses must decide what data to collect and what to measure to find valuable insights. Every business is different and finding help can help save time and resources spent in trial-and-error. If your business is seeking data science services, Transcendent Software can help set up and implement a proper data strategy. We can help collect, organize, analyze, and draw useful insights from your big data. To learn more, set up a call with us.