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SE::Google::Trends::Suggest - Google Trends search suggestions parser

Overview​

A parser for search suggestions by keywords in Google Trends. The Google Trends suggestion parser solves one of the main SEO tasks, namely the rapid automated acquisition of an expanded semantic core. Thanks to the SE::Google::Trends::Suggest parser, you can automatically collect keyword databases from Google Trends suggestions upon request. Using the SE::Google::Trends::Suggest parser, you can easily and quickly parse Google Trends suggestions by query.

Thanks to the multi-threaded operation of A-Parser, the query processing speed can reach 2000 queries per minute, which on average allows obtaining up to 10000 results per minute.

You can use automatic query multiplication, substitution of subqueries from files, permutation of alphanumeric combinations and lists to obtain the maximum possible number of results. Using results filtering you can immediately clean the result by removing all unnecessary garbage (using negative keywords).

A-Parser functionality allows you to save parsing settings for the SE::Google::Trends::Suggest parser for future use (presets), set a parsing schedule, and much more.

Saving results is possible in the form and structure you need, thanks to the built-in powerful Template Toolkit which allows applying additional logic to the results and outputting data in various formats, including JSON, SQL, and CSV.

Collected data​

  • Suggestions for the query
    • suggestion
    • suggestion description (its type)
    • link to the image
    • topic ID
Collected data

Use cases​

  • Collecting keyword databases

Queries​

Search phrases should be specified as queries, for example:

write essay
Football  
Waterfall  
Speak in english  
Cats and dogs  
forex
cheap essay

Query substitutions​

You can use built-in macros for automatic substitution of subqueries from files, for example, if we want to add a list of other words to each query, let's specify several main queries:

essay
article
thesis

In the query format, we will specify a substitution macro for additional words from the file Keywords.txt; this method allows increasing query variability manifold:

{subs:Keywords} $query

This macro will create as many additional queries as there are in the file for each original search query, which in total will give [number of original queries(domains)] x [number of queries in the Keywords file] = [total number of queries] as a result of the macro's work.

For example, if the Keywords.txt file contains: 

buy
cheap

As a result, the substitution macro will turn 3 main queries into 6:

buy essay
cheap essay
buy article
cheap article
buy thesis
cheap thesis

Output results examples​

A-Parser supports flexible result formatting thanks to the built-in Template Toolkit, which allows it to output results in any form, as well as in structured formats like CSV or JSON

Exporting the list of suggestions​

Same as in SE::Google::Suggest.

Output to a CSV table​

Same as in SE::Google::Suggest.

Saving in SQL format​

Result format:

[% FOREACH results;
    "INSERT INTO serp VALUES('" _ query _ "', '";   suggest _ "')\n";
END %]

Result example:

INSERT INTO serp VALUES('write essay', 'Exam')
INSERT INTO serp VALUES('write essay', 'Testosterone')
INSERT INTO serp VALUES('write essay', 'Test')
INSERT INTO serp VALUES('write essay', 'Testicle')
INSERT INTO serp VALUES('write essay', 'TestNav')
...

Dumping results to JSON​

Same as in SE::Google::Suggest.

Results processing​

A-Parser allows processing results directly during parsing; in this section, we have listed the most popular cases for the SE::Google::Trends::Suggest parser

Filtering results (using negative keywords)​

Same as in SE::Google::Suggest.

Settings​

note

Common settings for all parsers

Parameter nameDefault valueDescription
LanguageEnglishLanguage selection