How Data Analytics is Impacting Today’s Businesses

Data analytics is having the biggest impact on small to medium sized businesses right now, learn how data analytics can improve your business performance.

With an increasing number of companies ramping up their initiatives for digital transformation, there has been a huge surge in the implementation of data analytics.

For example, deep learning is allowing small businesses to improve and enhance their decision-making capabilities, while machine learning has begun to revolutionize the way in which brands are marketing to their customers. Overall, data analytics is providing small to medium businesses (SMBs) with incredibly detailed insights into every aspect of their operations.

And, big data adoption increased from just 17% in 2015 to a massive 59% in 2018, and is expected to rise even further.

There is an almost infinite number of uses for data analytics, allowing small businesses to become smarter, more efficient and of course, more productive. When it is used correctly, it can create an extremely noticeable competitive advantage for a brand, while at the same time increasing both revenue and conversions.

Here are some of the main data analytics trends that are having the biggest impact on small to medium businesses right now.

#1. Deep Learning:

As a society, we generate a whopping 2.5 quintillion bytes of data every single day. And, machines are becoming increasingly more adept at putting that action to good use, with deep learning capabilities having grown immensely over the past year.

Deep learning is a subset of machine learning, and utilizes artificial neural networks, which learn from vast quantities of data in a similar fashion to the functioning of the human brain. As a result, machines are then able to solve incredibly complex problems, with fine precision. And the more that deep learning algorithms learn, the better they are able to perform.

This year has marked a critical point, where deep learning is now helping all manner of small businesses to significantly enhance their capability for making the right decisions and take operations to new heights. For example, the development of chatbots is happening at a rapid rate, and through deep learning, they are now able to respond far more intelligently to an expanding list of questions in order to create useful and helpful interactions with customers. Thanks to deep learning, chatbots are provided with a framework on which they can continually build, allowing the knowledge base to grow exponentially.

#2. Dark Data:

Dark data might sound like a rather sinister term, but the truth is that it’s quite the opposite – dark data simply refers to the information assets that are collected, processed and stored by companies but are not put to use. This data often has a lot of value, but manages to slip between the cracks – for example, email attachments that are opened and then left undeleted, unused customer data, and old customer support tickets. And, with dark data predicted to account for a huge over 90% of data by next year, it’s no surprise that more companies are taking steps to utilize it as much as possible.

One of the ways in which companies are putting dark data to use is by using the data collected from old customer support logs in order to see which medium a customer preferred to use when initiating contact, and how long the interaction would last. This kind of dark data may have been forgotten about in the past, but is now being put to use and helping businesses determine a customer’s preferred method of contact, which then allows them to deliver a better and more personalized customer experience going forward.

Web data integration is also extremely effective when it comes to methods for generating unused data. Websites can be converted into structured, useable data that provides in-depth insights, which can then be integrated into both analytics and business applications. For example, web data integration allows companies to access updated data whenever a lead performs a targeted action, helping to ensure that leads are continuously up to date.

#3. Mainstream Machine Learning:

Machine learning is the process by which machines learn information through training algorithms. This form of sophisticated data analysis has become increasingly widespread in recent years. Some notable examples that you may recognize include Netflix and Amazon generating personalized suggestions for customers that are based on previous activities and queries.

In 2019, machine learning has been taken to new heights and has opened several new doors of opportunities for companies across a wide range of industries, as the artificial neural networks that make up the design and architecture of machine learning become increasingly more advanced.

Machine learning and data analytics used to be considered fairly disparate, but today, they are becoming increasingly more integrated, leading to a trend that has had significant benefits for small to medium businesses, particularly when it comes to the way in which brands are able to market to and engage with their customers. For example, companies can now analyze a large volume of marketing data to create a message that is fully personalized and optimized – this process is often referred to as ‘hyper-personalization’, and allows brands to target customers with customized promotions based on a range of factors including geo-location, demographics, and whether they are a new or returning visitor.

#4. How Can SMBs Utilize Data Analytics?

If you’re heading a small or medium business, then how can you use data analytics and reap the benefits for your own brand? Online data analytics courses can help you get to grips with the basics and understand the application of these three processes for your own company.

One of the main applications of using data analytics for small businesses is to track customers throughout the various sales cycle stages, making it easier to determine the small segment of visitors who are ready to buy, and when. And, data analytics can be used to significantly improve customer services – by analyzing conversations between leads and sales agents on channels such as email, social media and web chat, it becomes easier to gain an in-depth insight into not only common issues, but customer expectations – allowing your business to deliver a more personalized, satisfying customer experience overall.

Data analytics provides SMBs with a detailed insight into all aspects of operations, leading to improved sales, customer service and much more.