If you keep track of popular science trends and things like that, you are surely familiar with the term big data. In case you are not, here is a quick recap. The very term 'big data' has been around for quite a while now. Originally, it stood for large stocks of data (naturally, the definition of 'large' evolved over the years) being gathered, organized, processed, and analyzed, putting it briefly. Eventually, however, the meaning of the term has shifted toward specifically the tendency of analyzing these piles of data and applying the results of such analysis in practice.
If you want to get a better idea about it and google 'big data' today, you will see that the concept is applied in all sorts of spheres – from science to sports. Naturally, like any popular concept, it gets its share of critique – both regarding its application and its very essence. However, one cannot argue that big data is not being effectively used by larger companies whose products and services we use every day, sometimes without even noticing it. So, even if you are a freelance copywriter working from the comfort of your home and (seemingly) having very little to do with the trends taking place outside, you are still a part of it, and it is always better to have a clearer idea of what you are using and how it works.
Today, we would like to talk about the ways big data changed and keeps changing the job of a copywriter:
1. Grammar- and Spelling-Checking
Those of us who have been on the job long enough can remember how annoying automatic grammar-checking was back in the days. It would constantly underline the words or phrases that we have double- and triple-checked and know for sure are correct. In the same time, it would overlook an obvious error if the word looked correct – such as confusing 'there' and 'their' - and getting us into trouble occasionally.
In other words, it was a total mess, and the demand for more sophisticated grammar- and spelling-checking tools was overwhelming. It took the developers quite some time to come up with some viable solutions, but eventually, it happened, and today we have such excellent tools as the favorite of legions of copywriters worldwide – Grammarly.
Present-day grammar checkers will not only fix your obvious typos and misplaced punctuation. They will also highlight the less obvious instances, such as 'desert' vs. 'dessert.' They will also tell you about cases where passive voice is not necessary, where a sentence is too wordy, etc. They will even tell you which words are overused and suggest synonyms to replace them with.
How is this possible? Well, as opposed to the grammar checkers of yore that simply had embedded vocabularies and sets of rules, modern-day tools additionally process and analyze tons of text from the Internet to learn which words, phrases, and other relevant details are used more often and how. Based on that, they come up with prompts for writing as to how you can improve your text, and you are free to implement these suggestions or ignore them.
2. Plagiarism Checking
None of us wants to be accused of plagiarism, because nobody wants to work with a plagiarist – not even the search engines, apparently. If we particularly like someone else’s idea or phrase and want to borrow it, we quote them and cite them appropriately. However, there are also instances of unintentional plagiarism where you dub something that’s already been written without knowing it. Intended or not, search engines will still recognize this piece as plagiarized and the page with this text will rank lower than it should.
This is why we use plagiarism-checking tools. Once again, they process and analyze all the text they can reach on the Internet to see if some portions of it have been written and published before. If there are such portions, the plagiarism checker will highlight them (and even show us the URL where exactly it found this portion), so we could paraphrase them into original ones before publishing and avoid the undesired consequences. This is one more way in which big data can save a copywriter's life.
3. Performance Analysis
For better or worse, copywriting is not art for art's sake, it is always aimed at particular readership. We cannot afford to put out simply well-written pieces. Regardless of whether you are a staff writer or a freelancer, you are clearly interested in your text performing well with the audience. So, naturally, you look at the stats of your posts: which get more views, which are shared more often, which generate more leads, etc. This way, you can see which texts are more effective so you can iterate their success. Even if your boss does not hold you accountable for your texts' performance, it is still a good idea to keep track on those stats, even out of sheer curiosity, because your boss should not be the only one interested in increasing your proficiency.
There are tools involving big data that will process and analyze the performance of myriads other similar pages in your niche to point out which of them performed the best and how, offering you an abundance of stats to draw your conclusions from (down to the places on a page where readers hold their cursors the longest).
As you can see, tools that employ big data can not only improve texts that you have already written or as you write them. It can also give you a better perspective of what you should aim for in the future.
Big data is one of those instances where a seemingly distant tendency or concept penetrates our everyday lives – both professional and personal – on multiple levels. Copywriters, for example, use various big data tools for checking their texts for grammatical and other errors and for plagiarism. They also employ big data to gain access to certain stats that help them improve their writing. Notably, we use it without paying any attention to it. However, whatever you are doing, it is better to do it consciously, with at least some knowledge of how it works. This involuntarily pushes your mind into thinking about ways to optimize and improve your use of this tendency or concept even further.