If you are eager to start experimenting with an AI-writer, read the full article. At the end, I will give you a script to help you write meta descriptions on scale using BERT: Google’s pre-trained, unsupervised language model that has recently gained great momentum in the SEO community after both, Google and BING announced that they use it for providing more useful results.
I used to underestimate the importance of meta descriptions myself: after all Google will use it only on 35.9% of the cases (according to a Moz analysis from last year by the illustrious @dr_pete). In reality, these brief snippets of text, greatly help to entice more users to your website and, indirectly, might even influence your ranking thanks to higher click-through-rate (CTR).
While Google can overrule the meta descriptions added in the HTML of your pages, if you properly align:
- the main intent of the user (the query you are targeting),
- the title of the page and
- the meta description
There are many possibilities to improve the CTR on Google’s result pages. In the course of this article we will investigate the following aspects and, since it’s a long article, feel free to jump to the section that interests you the most — code is available at the end.
- What are meta descriptions?
- How long should your meta description be?
- What meta descriptions should we focus on?
- A quick introduction to single-document text summarization
- Extractive vs Abstractrive
- The carbon footprint of NLP and why I prefer extractive methods to create meta descriptions
- What is BERT?
- Long live AI, let’s scale the generation of meta descriptions with our adorable robot [CODE IS HERE]
- Final thoughts and future work
What are meta descriptions?
As usual I tend to “ask” “experts” online a definition to get started, and with a simple query on Google, we can get this definition from our friends at WooRank:
Meta descriptions are HTML tags that appear in the head section of a web page. The content within the tag provides a description of what the page and its content are about. In the context of SEO, meta descriptions should be around 160 characters long.
Here’s an example of what a meta description usually looks like (from that same article):
How long should your meta description be?
We want to be, as with any other content on our site, authentic, conversational and user-friendly. Having said that, in 2020, you will want to stick to the 155-160 characters limit (this corresponds to 920 pixels). We also want to keep in mind that the “optimal” length might change based on the query of the user. This means that you should really do your best in the first 120 characters and think in terms of creating a meaningful chain by linking the query, the title tag and the meta description. In some cases, within this chain it is also very important to consider the role of the breadcrumbs. As in the example above from WooRank I can quickly see that the definition is coming from an educational page of their site: this fits very well with my information request.
What meta descriptions should we focus on?
SEO is a process: we need to set our goals, analyze the data we’re starting with, improve our content, and measure the results. There is no point in looking at a large website and saying, I need to write a gazillion of meta descriptions since they are all missing. It would simply be a waste of time.
Besides the fact that in some cases – we might decide not to add a meta description at all. For example, when a page covers different queries and the text is already well structured we might leave it to Google to craft the best snippet for each super query (they are super good at it ?). We need to look at the critical pages we have – let’s not forget that writing a good meta description is just like writing an ad copy — driving clicks is not a trivial game.
As a rule of thumb I prefer to focus my attention on:
- Pages that are already ranking on Google (position > 0); adding a meta description to a page that is not ranking will not make a difference.
- Pages that are not in the top 3 positions: if they are already highly ranked, unless I can see some real opportunities – I prefer to leave them as they are.
- Pages that have a business value: on the wordlift website (the company I work for), there is no point in adding meta descriptions to landing pages that have no organic potential. I would rather prefer to focus on content from our blog. This varies of course but is very important to understand what type of pages I want to focus on.
This criteria can be useful, especially if you plan to programmatically crawl our website and choose where to focus our attention using crawl data. Keep on reading and we’ll get there, I promise.
A quick introduction to single-document text summarization
Automatic text summarization is a challenging NLP task to provide a short and possibly accurate summary of a long text. While, with the growing amount of online content, the need for understanding and summarizing content is very high. In pure technological terms, the challenge for creating well formed summaries is huge and results are, most of the time, still far from being perfect (or human-level).
The first research work on automatic text summarization goes back to 50 years ago and various techniques. Since then, they have been used to extract relevant content from unstructured text.
“The different dimensions of text summarization can be generally categorized based on its input type (single or multi document), purpose (generic, domain specific, or query-based) and output type (extractive or abstractive).”