Real-Time Data Analysis

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Hello, my name is Naomi Burgess and I’ve written this post after coming across many instances of companies not understanding the concept of real-time data analysis and what it can mean for them. This entry aims to clarify what you might not understand about this concept and how it can benefit your company.

Real-time data analysis can do

Real-time data analysis is something that I’m almost certain you’ve encountered in your professional, as well, as personal, life. If you’d Googled something, for example, you can be almost certain that adverts related to the keywords would be displayed on your social media pages. Similarly, if you’ve purchased something from an online store, chances are that you’ve received the “you might also like” messages on several occasions. All of these suggestions are the result of real-time data analysis carried out by retailers. Real-time data analysis can be argued to be one of the consequences of the 24/7 customer service brought to you by the digital age. This method has proven itself to be quite lucrative and on average, companies generate 20% of their revenue from these suggestions.

It can save crimes

That’s not to say, however, that the public sector is lagging behind in its usage of the data analysis. While this post is primarily about private companies – and I’ll move onto them in a minute – I’m first going to give you a brief example of how helpful data analysis has been for the former. This example is the police force, and not just the British police force. We’ve all seen various TV shows about how the FBI uses data to take down complex networks of criminals – and it has proven to be quite helpful. The police across the US, as well as the UK aren’t hesitating to take advantage of data analysis in order to solve crimes. The data analysed in those cases includes prior arrests, locations, tools of the trade and many other variables.

Importance of Data Analysis

Going back to private sector, real-time data analysis can therefore be quite a reliable way for the businesses to obtain more revenue for growth and expansion. Data analysis is conducted by most businesses today and chances are that your company is engaging in it too. While real-time data analysis doesn’t work well for every single industry, it’s a very popular method for the private sector, and I definitely suggest looking into it if you haven’t already done so. You’re probably aware of how business intelligence technology that helps gather the data can help you with customer promotions, but it can also carry out real-time data analysis, based on which you can strategise about the next steps to be taken to expand your business. For example, if you’re running an online shop that sells organic hair products, and people of particular age, gender and income buy a lot of particular product during a particular time of the year, you should try and create more products targeted towards that audience during that season so as to gather more revenue and create more attractive offers.

Keep your Data’s secure and protected

If you’re been running a company for a few years and you’ve created several long-standing client relationships, you probably have a lot of data gathered from your dealings with them. If you analyse that data, you would inevitably see several patterns in the customers’ behaviour. These patterns can be quite helpful for launching various new projects. Loyalty coupons and their equivalent are just a single way for you to take advantage of the data that you have. Depending on your company’s confidentiality policy, you can also enter into partnerships with fellow business owners in order to determine how those patterns can affect them and see whether you can both benefit from the results of that analysis. However, this is a rather controversial business practice – given the current increased privacy concerns in the country, some clients might not be willing to work with you if they realise that you’re selling their data to third parties. Therefore, you should be careful if you want to implement that strategy and always try to obtain the customers’ consent. It goes without saying that you should also keep your data as secure as possible – unfortunately, the advancement of technology is directly proportionate to the increase in hacks and data loss. Make sure to implement and maintain proper security measures on all your electronic devices.

Data Analysis and other Business

Another thing you should be aware of when working with customer data is regulatory issues that are particularly significant in several industries. While these industries can afford data processing software that is more expensive and sophisticated than what small businesses can afford, making it easier at first glance to carry out various business intelligence, there are a lot of complex regulations governing data analysis in those industries. Banking and finance is a good example of such an industry. However, given today’s emphasis on connections, communications and engaging, it’s quite possible that some retailers that aren’t faced with such strict regulations might branch out into financing and use the customer data available to them to expand that branch. How the law is going to treat such expansions remains to be seen.

Knowing Diversification

The above notion of branching out is just one example of a concept called “diversification” at work. Diversification is a strategy for businesses to enter brand new markets and create products for those markets. The concept of real-time data analysis can certainly play a pivotal role in diversifying your business, and if you add partnerships with fellow professionals I’ve mentioned above, you both can benefit from the data analysis you conducted, depending on the regulations that govern your industry. To use my example about organic hair products sold online, one way you can diversify is enter into a partnership with a tech company and/or a healthcare provider – together you could create an app that analyses the state of a customer’s hair and sends the data over to you so that you can work on a product perfect for that customer’s hair. Of course, this approach might not work for your particular industry, but given today’s emphasis on engaging that I mentioned earlier, you would easily be able to come up with excellent ideas that would.

Data Analysis positive effect on your customers

Regardless of privacy and regulatory concerns, it can be suggested that in recent years, over 70% of customers in the UK have come to expect real-time data analysis results instantly provided to them and are somewhat taking it for granted. I would therefore not advise you to fall behind – most people today are quite busy to spend a lot of time on shopping, so they would certainly appreciate the “you might also like” types of suggestions based on their past preferences. All customers like to feel appreciated, and personalised approach developed with the help of real-time data analysis is an excellent way to appreciate them.

Designing your Personalised Data Analysis

What you should keep in mind, however, is that personalised approach has to be what it says it is – personalised. This means that no matter how good your IT data analysis systems are, what you make of the data is down to you, or your marketing department. Your software merely creates and traces the patterns – you’re the one deciding what to do with them and how to make what you’ve learned into a personalised message for a customer. The anomalies and opportunities in the analysed data are what is ultimately going to be the key to your business’ future income streams, and growth and expansion. Therefore, you should treat them carefully and not be overly reliant upon your advanced IT systems.

At the end of the day, data by itself is just pieces of information about your clients. However, if you carry out data analysis – whether real-time or not, depending on your industry – it becomes a lot more than that. When customers willingly share their data with you, they should be signing up for more than a one-off transaction, and you should be aiming for a long-term relationship with each and every one of them. Chances are that they expect to be provided with suggestions next time they approach your company, and these days, if you’re not providing those suggestions, to a significant part of your target audience, it would seem strange to say the least. However, if you carry out proper data analysis and manage to tailor your offers towards that audience, your chances at building long-term relationships with its members would increase significantly.

 

 

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