What are the topmost NodeJS practices for developers?.
Node.js, a platform based on Chrome's JavaScript motor assists with growing quick, adaptable system applications. It utilizes an occasion driven,...
Sir Francis Bacon is the first person known to have said that “knowledge is power” — regardless, it’s been a reliable truism for hundreds of years. But like they saw, with great power comes greater headaches! And that holds true for knowledge as well - it is a huge headache for SEO.
That’s because knowledge was something to be acquired slowly back then, at a pace that the human brain could handle. Books came out only as quickly as people could write them, and developments spread slowly. Fast forward to today, and that analog trickle of information has given way to an unrelenting torrent of digital data.
The easiest solution is to simply ignore most of it and carry on as usual, but that provides a fresh problem: if you want to compete online, you need to use every resource at your disposal. Enter big data, the practice of collecting vast quantities of data before using technology to parse it faster and in greater detail than a human ever could.
Here are 5 reasons why big data deserves a prominent place in your SEO strategy:
While ranking algorithms all across the web are improving, the main focus must go on Google’s all-powerful sway over the world of search. And Google’s ranking system has come a long way from the days of keyword stuffing and Page Rank. With every update, it gets more sophisticated, and more capable of perceiving and comprehending nuance.
One of the main factors behind this is the development of NLP (natural language processing) technology. Machine systems are notoriously bad at parsing human language, but recent years have seen huge strides in building semantic webs allowing search engines to deconstruct content and reach reasonable conclusions about what it actually says.
As a consequence, it’s much harder for SEOs to identify quick and easy ways to get content ranking well. The loopholes are being found and filled in at a rapid clip. Does that mean that SEO efforts are losing their value? No, not at all — it simply means that they need to change with the times, and only by getting very granular with data can today’s SEOs find clever ways to outperform the competition.
Dominated as regular organic search may be by Google, there’s definitely room in the SEO world for other channels capable of driving traffic, and we’ve seen it proven through the rise of social media networks. Just think about how many references stem from Facebook Messenger conversations, and how much information is now filtered through Amazon’s Alexa service.
Businesses that could once get away with being myopic must now open their eyes to all the possibilities out there, and the rise of intuitive integrations is making it possible to adopt a truly multichannel approach to SEO. The consequence is inevitable: an exponential increase in relevant information. Through filling in the gaps, it’s now possible to form a fully-formed image of a site visitor’s online journey, both before and after they reach your site.
If you don’t know where your traffic is coming from, and which social network is providing the most conversions, then how can you meaningfully improve your SEO strategy? How can you properly allocate resources to the tasks that warrant them? You can’t. Without big data, you can only go by your gut instinct, which is never a sensible tactic when it comes to SEO.
If a large company like Amazon or Google is investing in Big Data, it’s advisable to assume that there’s a compelling reason to do so. And since Amazon has been investing in big data since its early days (and has leaned heavily on it to become the biggest retailer in the world), it’s fair to say that there’s a compelling reason to take it up.
But it doesn’t stop with Amazon. Consider how Coca-Cola has relied on big data to help it retain and grow its customer base. Because it has such great insight into what its customers want and how they think, it can carefully target all of its marketing efforts to maximum effect. Yes, you won't be investing the same amount as these companies, but you have to start somewhere.
You should also think about how heavily Google itself is investing in big data. Look at something like structured data: as much as some dislike them, featured snippets are clearly here to stay, and one of the keys to winning a featured snippet is marking up your content with structured data code. The more data you collect, the more usefully you can tag your content, and the more easily you can find opportunities to feature in snippets for popular terms.
Perhaps the greatest practical reason to start thinking about big data is that the barrier to entry has been greatly lowered through the advent of excellent (and fairly low-cost) research tools. Ahrefs, Pitchbox, SEM Rush, Majestic. That means there’s no need to invest heavily in developing an in-house solution, or hiring niche developers to overhaul your CMS.
We already looked at how the push towards multichannel strategy is a reason to use big data, but it’s also been a driving force behind its rise as a mainstream concern. And the eCommerce sector has contributed to this in a big way.
Time and time again, eCommerce SaaS companies have been able to take complex practices and turn them into accessible services. It happened with online store building, retail accounting, inventory management, and shipping management, and it’s currently happening with multichannel selling — for instance, Shopify Plus is aimed squarely at multi-channel selling, taking something that would have required complex manual integrations just a few years back and making it a straightforward 24/7 solution.
Consequently, when you decide to attempt some high-level data analysis, you’ll find that all the tools are already there for you, most offering free trials so you gauge their usefulness before you commit. With everything so intuitive and easy to access, what reason is there not to at least try it? If it doesn’t prove useful, you can simply stop.
Big data helps massively with identifying overarching patterns and making it clear where the value lies. Given the amount of guesswork that often goes into SEO (an industry that largely strives to defy Google’s wishes and figure out how its algorithm works), you need as much information as you can possibly get if you want to use your time well.
Imagine that you were courting an influencer, trying to get them to promote your products in an effort to get some referrals. A big data analysis of their background might reveal some invaluable details: maybe every site they’ve ever promoted has seen zero positive momentum from it, making it worthless.
If you don’t know these things, then you end up wasting your time on SEO projects that ultimately don’t produce results. Let big data guide your hand, showing you where you shouldn’t spend your time so that you can better determine where it truly belongs.
To deny big data as a core priority today is to turn a blind eye to the essential demands of the fast-paced online world. You might be able to get by without it, but when your rivals are no doubt looking into it, how long do you think you can last using old-school methods? SEO must change with the times — and so must you.
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