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When Big Data Boosts the Performance of Content Marketing

“Content is king”: this formula pronounced by Bill Gates in 1996 is repeated like a mantra. At this time, people who are interested in the web need to consider content marketing in their strategy.

If this expression is more or less true nowadays, it is important that brands do not take it literally. 20 years later, in 2017, many people are concerned about the expression of their brand on the web.

We have therefore witnessed a massive proliferation of content. Thus, 89% of B2B companies declare having used content marketing in their strategy.

However, what about the performance of these contents?

“Content is king, but less is more!”

Quantity certainly does not equate to quality

I see daily that many brands minimize this aspect and produce a lot of content (sometimes too much) without taking into account their potential performance in terms of audience. They are then found with sites whose content has not been pre-evaluated and we do not even know what will be the other ROI, the famous return on investment!

On the other hand, I also see a lot of companies with few means or which are not (yet) in logic of contents. These must be malignant and pragmatic, as they need to create the best performing content possible with limited resources and a defined budget. These same brands generally face larger competitors who have more means, hence the need to be even more inventive.

It is therefore necessary for brands to learn to produce intelligently, to identify relevant and effective content, to create by having a preliminary estimate of the potential for requests, visibility, conversions, that this can bring.

Produce content, yes, but do it blindly, no

In many minds, Big Data is mainly, if not only associated with mathematical data, algorithms. This definition is of course partial and incomplete.

Indeed, Big Data based on the analysis of unstructured data, texts and semantics, makes it possible to meet three marketing objectives:

1. Identify the expectations of users to be able to answer them better

Applied to content marketing, Big Data tools make it possible to find on the web, forums, blogs or social networks, new semantic territories unexploited, sometimes unknown to marketers.

For example, it may be for a brand to identify questions and remarks about its product that it would not have identified in its traditional marketing process.

2.Investing semantic fields with search engine query volumes

New expressions, 10x multiplication of key words, 100x multiplication of long tail expressions…the information provided by Big Data tools applied to semantics provides new ingredients for content creators.

This data allow detecting, in the mass of queries and contents of the web, expressions that a human being could not detect alone. By combining these semantic data with the query potential on Google, it becomes easy to prioritize content marketing to be developed.

3. Decide content that will differentiate itself from competitors

The tools of Big Data make it possible to map the semantic presence of the actors of a sectorial field and their relative weight.

For example, in a highly competitive field, it is possible to identify and prioritize the production of content on virgin territories. This content, which has not been pre-empted by competitors or exploited by the brand, represents the themes to be included as a priority in the editorial strategy.

To serve SEO performance

Experts working on the creation of content to bring value to the user and to promote SEO performance have now a very powerful tool to guide their decisions in terms of strategic areas and content.

However, differentiating content is not automatically or immediately effective.

It is important to link them together in semantic cocoons. These cocoons promote the retrieval of strategic keywords and long tail expressions in the search engine results pages.

Thus, by respecting the SEO criteria (semantic, technical and linking), themes present in the depths of Google are brought back in the first results.

The chain reaction provoked by this new content within semantic cocoons is very positive for natural referencing: which says conquest of untapped semantic territories necessarily means acquisition of new positions in Google.

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