Website content writing is not similar to other write-ups that you may have been working on for all this time. It can be a challenging task as this type of content involves a promotional tone that blends in with helpful information about a service. If it is a Big Data analytics client you are writing for, then this becomes a very essential point so that the target audience of CEOs, and CTOs can be targeted better.
Without further ado, let us take a look at how this can be achieved.
-
Initiate the content with SEO- based keyword research:
A number of websites generate a lot of revenue from the organic traffic that reaches them every year. To generate that much organic traffic one has to have proper research of keywords before starting with website content writing.
For your big data analytics client, some popular keywords can be ‘Hadoop’, ‘R Programming’, ‘Predictive Modelling’, ‘Deep Learning’, ‘Data Science’, and ‘Clustering’. Keywords are nothing but words that your Big Data client’s customers will type and then discover them on Google.
By using the keywords meaningfully within content (without making it appear stuffed) ensures that your client’s ranking improves significantly and allows your client’s brand to reach out to total strangers (i.e. new leads)
Read more here to know how to do keyword research in a smart way.
-
Be short and factual:
A lot of content on the web incorporates fluff and generic content that readers are usually aware of. Instead of just filling up the content with words that are repetitive, it is more advisable to choose short and factual statements that add value to the website content. Just stick to the point that will indulge readers with an interesting fact leading to a positive impression.
-
Educate your readers with engrossing content:
Did you know that most of the Big Data companies’ customers look for the latest and most relevant content to gauge the industry authority of the Big Data Company? If you are writing content for such a company then make sure to come up with engrossing content that is fresh and unique. Some such references will be exploring the ‘long tail’ of big data to explore its variety or checking out the way Apache Spark has gone mainstream in 2017 and beyond. Writing content on these time-contextual things will elevate your Big Data client’s industry credibility.
-
Bullet points are helpful:
Another key tip to use in your web content is the use of bullet points. Bullet points are more legible and factual that will give readers the right information that they need to know. Moreover, studies say that any visitor who looks into a website tends to read the part about the bullet points more than the paragraphs. This is why web content should have high-quality bullet points that summarize all the key aspects related to the content.
-
Take care of the headings:
Besides the body part, the titles also need to be correctly written so that they have a broad and definite meaning about what the reader is about to find in the content. Moreover, the content writer needs to make sure that the heading is correct to the body part without any fake information that may not be present in the paragraphs or bullet points.
-
Engage in active voice:
While passive voice is not wrong, the use of active voice simplifies a statement and is much easier to grasp. Any reader who will be taking a look at your content will want to stay active while reading it, but the passive content may drift a reader away from the real motive of the web content. This method does not mean that you should avoid passive voice to the fullest, just keep in mind that the ratio of the active to passive is in favor of the former.
Conclusion:
With the above key tips to keep in mind, you may have a better idea of how to enhance your website content writing for Big Data analytics clients. Make sure that you feel what your readers want to read and keep them engrossed with the quality tips mentioned above. Keeping your content crispy, clear and precise will ensure better visibility and higher conversions for your Big Data analytics client.
