A Study of the WordPress SEO Plugins for Microformats

Sérgio Julião

and Mariana Curado Malta

1,2

CEOS.PP, Polytecnic of Porto, Portugal

Algoritmi Center, University of Minho, Portugal

Keywords: Metadata, Schema.org, Digital Marketing, SEO, Machine Readable, Rich Snippets.

Abstract: The evolution of technologies puts pressure on organisations upon its digital transformation. The content these

organisations make available on the Web and their strategies of Search Engine Optimization (SEO) have a

real impact in the achievement of the organisations’ communication objectives. Marketing departments are

increasingly dominated by SEO strategies to achieve the best positions in Search Engine Results Pages

(SERP's). To achieve the first positions increases the probability of new business opportunities. This paper is

focused on semantic SEO, and on the quality of the WordPress SEO plugins that incorporate microformats

(free-of-charge versions). We have studied 85 different plugins and concluded that only 20 incorporate truly

microformats. We concluded that 95% of the 20 use JSON-LD as mark-up language and the vocabulary

schema.org. All of the 20 plugins fall far short of expectations as they exploit very few schema.org types and

terms compared to the possibilities of descriptions defined by the theoretical analysis made. To date, if an

organisation needs to incorporate microformats in its Website Wordpress based contents, it will have to pay

to a programmer to do this, or use the paid versions pulgins, as the free plugins do not provide quality tools.

1 INTRODUCTION

The expression "Content is King" (Gates, 1986)

appears in an article by the Microsoft's founding

entrepreneur, where he already assumed that, in a

context of a large amount of online information, the

content would have great prominence and value due

to its quality, originality and exclusivity. Several

decades later, its expression still influences marketing

strategies based on content (Patrutiu-Baltes, 2016).

The internet specialists recognise the value of content

as a fundamental tool of digital marketing (Baltes,

2015). Currently, organisations outline their

communication strategies supported by content to add

value to their brands (Lemos, 2017).

In a context of new challenges for organisations,

with the attention of their consumers divided, where

digital media offers enormous communication

potential, with greater versatility and accuracy, they

are also more dependent on new marketing tools in a

more complex communication environment (Batra &

Keller, 2016). Several open source Content

Management Systems (CMS) provide a large number

See https://wordpress.org - Accessed in May 10, 2020

See https://support.google.com/google-

of free plugins for easy implementation, WordPress

is the most relevant, where every day new updates

and new Search Engine Optimisation (SEO) plugins

are announced. SEO becomes a significant necessity

for all online businesses, without which businesses

will not succeed (Sohail, 2012). These plugins present

themselves to the end-users as an indispensable tool

for any digital marketing strategy. SEO strategies and

SEO plugins have been imposed on online

businesses, promising the best results in organic

searches and achieving the desired notoriety,

converting the traffic generated into some kind of

benefit for organisations (Veglis & Giomelakis,

2019)

According to Google

there are only two options

for organisations to ensure good results in the ranking

of Search Engine Results Pages (SERPs):

 Advertising investment: this can be done

purchasing keywords in Google Ads (words

that are related to the websites, products and

services provided by the companies,

description of content), and;

 Organic results, which have to do with how

sites are optimised so that search engines

ads/answer/6335981 - Accessed in May 10, 2020

154

Julião, S. and Malta, M.

A Study of the WordPress SEO Plugins for Microformats.

DOI: 10.5220/0010014901540161

In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications (ICETE 2020) - Volume 3: ICE-B, pages 154-161

ISBN: 978-989-758-447-3

interpret them as having relevant content for

the search in question, so the search engine puts

them in the top positions of the resulting search

listing. To achieve this there are several

techniques. The most important one is the

Google’s Rich Snippets

that explore websites’

contents that have embedded structured data

called microformats.

According to Statcounter.com, the four main

search engines are Google, Bing, Yahoo! and Baidu.

All of them have evolved, focused on the needs of

their users, allowing websites to disseminate content

with new mark-up elements, inserting additional

semantic information, so that search results in the

SERPs appear according to relevance, displaying

meta-information of the landing pages (Marcos et al.,

2015). The technology that underlies the SERPs uses

algorithms developed by Google that insert additional

semantic information defining how search terms are

interpreted by their search engines. According to

Statcounter data

, Google represented 91.61% of the

global search market share (Desktop, Mobile and

Tablet) between May 2017 and May 2018.

Currently, search engines use structured data for

SERPs, select Rich Snippets, ratings, prices and

reviews, among others. This evolution reflects the

application of structured data technologies, the way

metadata usage is processed and the text embedded in

HTML

of web pages, defining what is relevant for

each specific search. Interoperability between

machines enhances the whole process of

interpretation of information embedded in HTML, a

reality that has encouraged marketing experts and the

business sector to have the ambition to have

organisations listed in the top positions of SERPs.

The flow of information technology is growing

and tends to increase the complexity and dependence

of companies on technology. This raises questions

about how well prepared they are to meet the

challenges of digital innovation. It also forces

managers and marketing departments to rediscover

themselves, to speed up decision making for the

digitisation of their processes. Organisations have to

reconsider their traditional business models and

processes to implement new opportunities in the

digital world, where resources for new marketing

technologies, with content experts, multi-channel

See https://webmasters.googleblog.com/2009/10/help-us-

make-web-better-update-on-rich.html -Accessed in May

13, 2019

See https://gs.statcounter.com/search-engine-market-

share#monthly-201705-201805-bar - Accessed in

December 20, 2019

See https://www.w3.org/TR/xhtml2/ - Accessed in May

campaigns, data analysts, among others, are key

elements to survive in a digital transformation process

(Świeczak & Eng, 2017).

This paper focus on the second option. Metadata

embedded in Web Pages positively influences search

engines, ultimately offering a better experience for

Web users. If this metadata, also called “data about

data” (Riley, 2017) , is structured i.e. is modelled and

coded with mark-up languages using standard

vocabularies (e.g. Dublincore.org or Schema.org

)

that give meaning to the metadata, this will enhance

data interoperability.

This paper presents an on-going research that

focuses on WordPress and on its SEO plugins which

add microformats to the webpages being built. The

aim is to identify the vocabularies and mark-up

languages used in the SEO plugins, and to

characterise the terms used.

We focus on WordPress since it was identified as

the most popular open source CMS on the market

(Cabot, 2018). The W3techs

platform states that

WordPress is used by 35.7% of the sites, worldwide,

having a 62.4% share of the CMS market, which

explains the huge attraction of developers; currently

WordPress has over 54000

plugins.

This article is organised as follows: next section

presents the methodological approach of the study,

section 3 presents the theoretical context of the study,

section 4 presents the results & the analysis: first of

the theoretical study, second of the plugins studied.

Finally we conclude the paper in section 5.

2 METHODOLOGICAL

APPROACH

The main objective of this study is to identify the

types of mark-up languages used by the SEO plugins

which insert microformats on the webpages being

built, and to analyse what vocabularies are use and

how. To achieve this goal, we followed the steps:

1. To create the theoretical framework - Perform

a literature review (LR);

2. To create the ecosystem – Define & Create the

contents;

14, 2019

See http://schema.org - Accessed in December 20, 2019

See

https://w3techs.com/technologies/overview/content_mana

gement - Accessed in December 20, 2019

See https://wordpress.org/plugins/ - Accessed in

December 20, 2019

A Study of the WordPress SEO Plugins for Microformats

155

3. To find the SEO plugins for the study –Search

on the WordPress Website for SEO plugins.

4. Sites preparation - Develop the sites;

5. To create our microformat description – we

analysed the content and decided the

vocabularies & the terms to be used in the

microformat descriptions;

6. Analyse the sites – Analyse the structured data.

The following paragraphs give the details of each

step:

Step 1: search on: EbscoHost.com;

Link.Springer.com; Semanticscholar.org;

Sciencedirect.com and Scholar.google.pt: We

searched papers in English, Portuguese and Spanish;

The search was done on the title with the keywords:

Metadata; Search Engine Optimization; SEO; Digital

Marketing; Wordpress; Semantic Web;

Microformats; Interoperability; Resource Description

Framework (RDF); Vocabularies. The search was

performed between May 2019 and December 2019. A

total of 221 articles were collected, 80 of which were

considered relevant and a total of 31 were selected.

We rejected articles dealing with outdated

technologies.

Step 2: To study each plugin we needed to work

in a common setting so that we then could compare

the results of each analysis. We created a fake

company “Marketing Digital Tools” (MDT)

(http://marketingdigitaltools.com), and a content

template for its website presenting the company and

an e-tailor type of shop that sells online services (e-

commerce) of site building. MDT seeks to take an

innovative approach by converting its services

through the creation of integrated and discriminated

service packages, for online sale.

We created different types of content so to have

diversity of information:

 Definition of the organisation: (i) Description,

Name, Image, URL, Brand, Mission, Vision,

Values, Social networks, Contacts, Opening

days & hours; Maps & Geo-coordinates; (ii)

Founder & CEO: Name, Image, URL, Social

Networks, Contacts;

 Description of the Services: Description,

Images, Brand, Price, Rating, Contact Point;

 HowTo: Name, Description, Images, URL,

Steps, Total time, Estimated Cost;

 Videos: Description, Thumbnail image,

Duration, Date of Publication, URL, Author,

Upload Date;

See https://www.dublincore.org/specifications/dublin-

core/dcmi-terms/ - Accessed in May 13, 2020

See https://www.w3.org/TR/json-ld/ -Accessed in May

13, 2019

 Blog: Content, Article Section, Headline,

Image, Alternative Headline, Publishing Date,

Modified Date, Language, Type of Content,

Publication, Comments Count, Accountable

Person, Author, Creator, Publisher, Sponsor,

Keywords, Genre;

 FAQs: Title, Content, Author, URL.

Step 3: The search was done in the WordPress

Website. We used the keyword "SEO" and only chose

the plugins that were: (i) compatible with WordPress

V 5.3.2; (ii) Free or Freemium, and (iii) in English.

The search resulted in a total of 3582 plugins. We

analysed each plugin reading its descriptions to

understand if the plugins were within the scope of the

study. We ended with 85 plugins (see the spreadsheet

“ListOfPlugins.xls” in

http://doi.org/10.5281/zenodo.3830889). This file

presents the plugins: the first column has the ID

number of the plugin, the second denotes if the plugin

works with microformats, the third the name, the

forth a description & notes, the fifth the version

analysed, the sixth the last update of the version, the

seventh the active installations, the eighth the average

rating and the last column the number of voters).

Step 4: We replicated a WordPress site with the

contents described in Step 2 as many times as the

plugins to be studied (85). We installed one different

plugin on each site. And created the microformats of

the information described in Step 2 with the plugin

user-interface.

Step 5: We created our view/description of the

contents using JSON-LD (see Section 4) as mark-up

language.

Step 6: We studied the microformats created by the

plugins. The goal of the analyses was to study, for

each plugin:

 The vocabularies used (e.g. http://schema.org,

dcterms

), the terms (e.g.

http://schema.org/organization) used and for

what;

 The mark-up languages used (JSON-LD

Microdata

or RDFa

The analyses was developed in a Descriptive

Research approach, according to the Case Study

method through which presentation tables are

developed, for the organisation of the collected data,

for later appreciation, comparison and publication

(Zainal, 2007).

See https://www.w3.org/2012/pyMicrodata/ -Accessed

in December 20, 2019

See https://www.w3.org/TR/rdfa-primer/ -Accessed in

December 20, 2019

E-BDT 2020 - Special Session on E-Business and Digital Transformation

156

We studied the pages with microformats and for

each plugin identified the mark-up language and the

terms used for each piece of information generated by

each plugin. The organisation of the data of the

analysis was done on tables (created in a spreadsheet),

one table per plugin. The levels of description were

noted through a numbering from one to four levels.

We used the testing tool of Google

to analyse the

structured data of the plugins.

3 METADATA & SEMANTICS

Metadata has always been part of the archive

management universe and is used to classify,

organize and search information related to specific

elements, such as location, dates, authors, subject,

among others. Metadata as structured information

allows us to make use or manage an information

resource (Riley, 2017). In the past, metadata used to

be embedded in the HTML header tag of the HTML

pages. Metadata is "data about data" (Riley, 2017, p.

11). Online metadata has grown exponentially in

recent years, generating a huge amount of digital

information, which consequently makes access to

relevant information difficult and significantly

reduces search engine efficiency (Palanisamy & Liu,

2018).

In 2012 Google created the Knowledge Chart

compiling more than 3.5 billion facts, as important as

the relationships created between 500 million entities.

The Knowledge Graph facilitates the search process,

decreases the time spent on the searches and develops

more intelligent searches. Google search incorporates

three main elements:

 Find the right thing, Google can restrict search

results because it interprets the entities and

nuances of their meaning.

 Get the best summary, Google can better

understand the search, to summarize relevant

content and the relationships between things.

 Go deeper and wider, the Knowledge Graph

allows for new discoveries and facts by

answering in advance.

See https://search.google.com/structured-data/testing-

tool - Accessed in May 13, 2020

See https://googleblog.blogspot.com/2012/05/

introducing-knowledge-graph-things-not.html -

Accessed in December 20, 2019

3.1 Digital Marketing & SEO

The search process in search engines, from the user's

point of view, is quite convenient because it allows

quick access to information. From the point of view

of organisations, SEO tools have become relevant

because they optimize the contents of websites and

improve the experience of their users. There are three

aspects that are relevant for users who benefit from

their browsing experience (Palanisamy & Liu, 2018):

 Originality and authority of the content;

 Ease of user interaction;

 Design, visual simplicity and easy navigation.

SEO tools are integrated into companies of online

marketing strategies in order to increase business

opportunities and better positioning in SERPs. In

economic terms it makes sense to opt for SEO

solutions to increase the visibility of a site compared

to advertisers who invest in advertising (Khraim,

2015). One of the focuses of SEO tools is to generate

opportunities to create relationships of trust and

loyalty that boost sales (Patrutiu-Baltes, 2016). SEO

is part of the strategies adopted by digital marketing

to give greater visibility to brands and their products

in search engine rankings, giving priority to content

quality and relevance (Khraim, 2015).

Google's goal is to generate relevant results for its

users, so the content of web pages is the main element

to be optimized. The content includes text, images,

videos, audios, documents that make up a web page

including the data embedded in HTML (Oliveira,

2016).

According to Sohail (2012) most people click on

the first five search results, generating more traffic

and more profit for these top positions, which arise

organically from search engine optimization.

Gifford (2010) states that the basic ingredients of

SEO are Quality content; Relevant keywords; Strong

metalanguage properties; Internal links throughout

the site; External links (backlinks) to the site.

In 2015, SEOmoz

elected nine factors with

impact on the ranking of searches to better understand

the complexity of the resources Google uses. It also

states that Google's search engines constantly work to

improve their calculations that define the rankings.

Google also makes recommendations on SEO for

beginners

, 2019 .

https://moz.com/search-ranking-factors - Accessed in

November 14, 2019

See https://support.google.com/webmasters/answer/

7451184?hl=en -Accessed in November 14, 2019

A Study of the WordPress SEO Plugins for Microformats

157

3.2 Semantic SEO

The technology used in search engines and SEO tools

has evolved to provide answers to web users'

expectations. Microformats, also called semantic

SEO, allow metadata in HTML pages to be machine-

readable, providing the possibility to search engines

to extract more detailed information, so that final

users have better search results and a better browsing

experience (Nevile & Brickley, 2018).

Microformats are a hybrid solution between the

embedded metadata in a HTML header tag and the

Semantic Web which has the RDF data model

. The

Semantic Web, also called Web of Data, is a

paradigm of Linked Open Data (LOD). The Semantic

Web has a construct called metadata application

profile (Coyle, 2017) – MAP. A MAP is a data model

for LOD that “mixes and matches” vocabularies

enhance interoperability among a community of

practice (Heery & Patel, 2000). The Linked Open

Vocabularies

(LOV) is a vocabulary directory

organised by application contexts, these vocabularies

can be used by any agent that publishes LOD. Any

person or community can create a vocabulary,

however it is important before doing so, to try to find

a vocabulary that has the term that can describe the

identified need. Sometimes the semantics of an

existing term may not be exactly what we need, but

we must find a compromise between semantic

accuracy and a high degree of interoperability.

Microformats are not the Web of Data.

Microformats are coded blocks of data descriptions

embedded in HTML. The mark-up language to add

this data, or metadata to the Webpages are: JSON-

, RDFa

, or Microdata

. RDFa and JSON-LD

have a better expressiveness than microdata since

microdata has limitations regarding interoperability

(Nevile & Brickley, 2018). RDFa provides a set of

mark-up attributes to enhance visual information on

the Web (Herman et al., 2015).

As in the Web of Data, Microformats use

vocabularies to add the semantic meaning to the thing

to be described.

Schema.org is a vocabulary created by Google,

Bing, Yahoo! And Yandex that gave to microformats

a big boost and came to fully dominate the context of

See https://www.w3.org/wiki/Choosing_an_HTML_

Data_Format#RDF_data_model - Accessed in May, 10,

2020

Originally called “Metadata schemes”

See http://lov.okfn.org/ - Accessed in May 16, 2020

See https://www.w3.org/TR/json-ld/ - Accessed in May

10, 2020

See: https://www.w3.org/TR/rdfa-primer/ - Accessed in

microformats. Schema.org has been increasing the

number of descriptive contexts, having increased over

the years the number of Types and Terms. For

example, a few years ago Schema.org integrated a

vocabulary called Good Relations

- now the part of

Schema.org that describes the context of ecommerce

is a copy of this vocabulary. As far as we see it,

Schema.org is still far from being able to describe all

the possible contexts, and a solution for the lack of

expressiveness is the use of other vocabularies of the

Web of Data to be able to fully describe our contexts.

According to Lopezosa et al. (2018) semantic

SEO helps sites to appear well positioned in the

SERP's. Lopezosa et al. (2018 also say that it is

predictable that SERPs will be oriented to be direct

response systems rather than information retrieval

systems.

4 RESULTS AND ANALYSIS

All documentation of the study is available at

http://doi.org/10.5281/zenodo.3830889.

4.1 Theoretical Study - Results &

Analysis

According to step 5 of the methodology a description

for the contents of the MDT Company was

developed. We used JSON-LD as mark-up language

and, 1) the ESSGLOBAL

vocabulary for a single

description (mission), and; 2) all other descriptions

developed using the http://schema.org vocabulary.

The JSON-LD coded document can be found at

the URL referred (see

“TechnologicalAnalysis.json”).

The analysis of the Terms and Types used can be

found in the spreadsheet file

“TheoreticalAnalysis.xls”. On this analyses we did

not include the ESSGLOBAL term since no other

plugin used it. Regarding the use of Schema.org

Types and Terms, we have used 29 different Types

and 71 different Terms, and in total we have used 122

Terms. As far as we can understand, this was the way

we found to make the most of the descriptive

December 12, 2019

See: https://www.w3.org/2012/pyMicrodata/ - Accessed

in December 2019

See http://www.heppnetz.de/projects/goodrelations/ -

Accessed in May 16, 2020

See http://purl.org/essglobal/vocab/v1.0/ - Accessed in

May 15, 2020

E-BDT 2020 - Special Session on E-Business and Digital Transformation

158

possibilities of Schema.org in relation to the contents

we wanted to describe.

Next section shows how each plugin used the

Terms and Types of schema.org to describe the same

contents.

4.2 Plugins Study - Results & Analysis

The results of the study of the plugins are available in

the spreadsheet file “Results.xls”.

The study of the 85 plugins shows that only 20 of

them integrate the functionality of microformats

(Column 2 of the spreadsheet file “ListOfPlugins.xls”

marks these plugins). Plugin “Slim SEO” is the only

one that is 100% automated in the extraction of

microformats. In all others, the user is asked to

describe the content through the interface provided by

the software.

Another fact that comes immediately to the eye is

that all plugins used one single vocabulary to describe

the content, there is no “mix and match” of

vocabularies as in the MAP construct of the Web of

Data.

The analysis of the results is presented in the

spreadsheet “Analysis.xls”. This file has a sheet per

plugin: the first column of each sheet presents the

Types of schema.org used by the plugin in question,

and the contents described, with the corresponding

Term marked in the following columns. Still in the

first column, we can see in the last row the total

number of Terms used. In the last cell of each of the

following columns we can see the number of times

the corresponding Term was been used. Finally, in the

last cell of the next-to-last column, we can see the

total number of different Terms used, and in the last

cell of the last column the total number of Terms

used.

The spreadsheet “FinalAnalysis.xls”For

compares all plugins. The sheet “Analysis Types”

presents the analysis of the used Types in the different

plugins. Each line represents a different plugin, the

1st column has the ID number of the plugin, the 2

the name of the plugin, the 3rd the mark-up language

used by the plugin, and the 4th the vocabulary used.

The following columns show the Types used by the

plugin in question. The last column presents the total

of Types used by the plugin in question in the

descriptions. The loose line, with the name

"Theoretical Analysis" presents the summary of our

proposed description, so that a comparison with the

plugins in analysis is possible.

See http://json.org – Acessed in May 14, 2020

The plugin that uses fewer Types is the

"Premmerce SEO for WooCommerce" (ID=28) and

the one that uses more different types is the "Markup

(JSON-LD) Structured in schema.org" (ID=53).

Schema.org is the most used vocabulary, since in

20 plugins, 19 use it. One plugin (“The SEO rich

snippets”) uses uses an obsolete vocabulary called

data-vocabulary.org. JSON-LD is the most used

mark-up language since it is used in 19 plugins. One

plugin uses microdata (“The SEO rich snippets”).

RDFa is not used by any plugin which is an

interesting conclusion since this language is a W3C

standard and JSON-LD not. The wide use of the latter

should be related to its ease of use and ease of reading

by humans, and because it follows a logic similar to

JSON. JSON

is a widely used data interchange

format, easy to use for those that come from the

context of C, C++; C#, Javascript, Perl or Python,

which encompasses a very large group of

programmers.

The spreadsheet “Analysis Terms” presents the

analysis of the used terms in the different plugins.

Each line represents a different plugin, the 1st column

has the ID number of the plugin (see file

“ListOfPlugins.xls”), the 2nd the name, and the

following columns show the Terms used by the

plugin in question. The next-to-last column shows the

number of different Terms used by the plugin in

question, and the last column the total number of

Terms used. The plugin less descriptive, because it

uses the smallest number of different Terms (3) and

the smaller total number of Terms (4) is “Premmerce

SEO for Woocommerce” (ID=28). The plugin plus

descriptive because it uses the biggest number of

different Terms (31) and the biggest total number of

Terms (51) is “markup (JSON-LD) structured in

schema.org” (ID=53). Compared to our theoretical

analysis, we find that there are many Types and many

other Terms that could have been used to describe the

information. In the case of the Types, we used a total

of 29 Types, and in the case of the Terms, we used a

total of 71 different Terms, and a total of 113 Terms,

far exceeding the numbers used by the plugins.

We conclude that the free plugins do not fully

exploit schema.org. One of the reasons for this to

happen is the fact that schema.org evolves over time,

and plugins do not have updates that follow that

evolution of schema.org.

Regarding the expressiveness of Schema.org,

some content remained unexplored in the theoretical

analysis since Schema.org resources do not absorb all

the specific needs of the contents. As an example, for

A Study of the WordPress SEO Plugins for Microformats

159

the description of the "mission" of MDT, we used the

term “mission” of the ESSGLOBAL vocabulary (see

Curado Malta (2014)). When testing the code on

Google

testing tool, it gave an error since the error

control tool only controls the terms and types of

schema.org, as far as we see it, it should allow a “mix

and match” strategy.

5 CONCLUSIONS

The digital transformation process is a challenge for

organisations. E-commerce provides many

opportunities for organisations to take the leap.

Semantic SEO, also called microformats is an

opportunity for organisations that seek to explore the

digital business and make the most of it. With

Semantic SEO, website contents can incorporate

microformats and become more accessible to

intelligent-machines, allowing search engines to

understand their contents in an intelligent way. Thus,

the pages will have a greater chance to position

themselves in the first places of SERPs'.

This paper presents a study of the WordPress

plugins which provide an interface that allows the

definition and creation of microformats according to

the contents of the Website. WordPress is an open

source Content Management System (CMS), with a

large community that develops plugins, i.e., software

that adds functionality to the core of WordPress. We

focus on WordPress since it was identified as the most

popular open source CMS on the market (Cabot,

2018), widely used by organisations to build

Websites. The plugins studied were the free plugins

that implemented SEO strategies and also add

microformat to the pages.

We performed a systematic search on the

WordPress Website plugins page, looking for SEO

plugins. The total number of plugins found were 85,

from those, only 20 incorporate microformats. We

only analysed these 20 plugins.

To compare the plugins, we created a template site

in WordPress, and replicated it, as many times as the

plugins. On each site we installed one plugin and

created the microformats with the plugin interface.

From there we created a common sheet, where we

collected the data related to the microformats created

by the plugins. We also developed a theoretical study,

where we explored the contents and described them

See https://search.google.com/structured-data/testing-

tool - Accessed in May 13, 2020

Note that we do not have information about the quality

using vocabularies, so that we could understand the

breadth of the plugins' descriptions.

We conclude that 95% (19 out of 20) of the

plugins use the vocabulary schema.org and the mark-

up language JSON-LD. One plugin used the data-

vocabulary.org vocabulary, a vocabulary preceding

schema.org that is already out of use, and microdata

as mark-up language. The trend is clearly JSON-LD

and schema.org

Schema.org has conquered the market because,

from the very beginning, it has positioned itself as a

strong brand: the great search engines have joined in

designing the vocabulary. This was a great sign that

it would have a large market share, if not a monopoly.

However, there are still descriptive contexts that

remain to be explored and that create voids for

information architects when it comes to describing

the business of organisations in the virtual world.

We also conclude that the free of charge

WordPress SEO plugins studied do not explore the

totality of schema.org, many content remains without

semantic mark-up.

This study does not explore paid versions of

plugins. We don't know if they would bring a better

exploitation of schema.org. But we do know that for

now, for an organisation, which has its website based

on WordPress, to aspire to be positioned in the top

positions of the SERPs will have to:

i) invest in advertising, an investment that will

always have to be fed over time, very volatile because

it depends on the competition and the prices attributed

to keywords, or;

ii) explore organic search solutions, which include

the optimization of contents through the use of

microformats. By choosing this route, it can: a)

choose to buy paid versions of SEO Plugins, since

according to our study the free versions do not fully

exploit all the possibilities that Schema.org

provides

, or; b) hire programmers to develop from

scratch the microformats in the contents.

One way or another organisations will have to

make an investment since the study concluded that

there are no microformat plugins for WordPress that

are free and of quality. We consider that the option

of investing in order to enhance the results of organic

searches on websites is the most advantageous

because it is a long-term investment.

of the paid versions, since as already said our study did

not include them

E-BDT 2020 - Special Session on E-Business and Digital Transformation

160

AKNOWLEDGEMENTS

This work is financed by portuguese national funds

through FCT - Fundação para a Ciência e Tecnologia,

under the project UIDB/05422/2020.

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