Generate Keywords for SEM Campaigns

A big part of setting up SEM campaigns consists of generating keywords, and properly mapping them to landing pages and ads, as well as putting them in the right campaign and ad group structure.

Keyword research is the part of this task that takes the most time. It is very tedious, yet extremely important.

The shift here is that we are going to be generating keywords as opposed to researching them.

What is a keyword anyway?

It is basically a phrase that contains two things:

Product: This is the thing that you are selling. It is simply the name of it. "barcelona", "guitar", "rio de janeiro", "accounting". The product on its own is not enough for us to understand what the user is looking for. "barcelona trips" and "barcelona football club" are completely different "keywords" for example.
Word: To give meaning to the product, it has to come with a word. The word can be a verb like "buy" or "purchase", and it can also be another noun, but with a clear intent expressed; "price" and "offers" for example clearly show purchase intent.

So, to generate keywords we need phrases that contain both, the product and the descriptive word(s). It is very easy to get the products as you know what you sell. The next thing you need to come up with are the words that work within your strategy. The most import idea here is that once you determine that you sell courses for example, there aren't really that many words that can describe that intent; course, courses, tutorial, certification, learn, learning, education, etc. How many can you come up with? How many exist in any language? Fifteen, twenty? Once you have those are basically done.

Depending on what service you provide and what segment of the market you target it shouldn't be difficult to come up with ideas for words (not keywords yet). You might have an e-commerce site, but want to mainly focus on cheap and discounted products. Or maybe you have luxury items, and want to exclude words that signify price sensitivity.

Let's say you have a job site and you know that you provide jobs for engineering, graphic design, and marketing. The words are easy to come up with; "job", "jobs", "careers", "vacancies", "full time", "part time", "work", and so on.

Now what we can do is use the kw_generate function to come up with all possible combinations (order doesn't matter) and/or permutations (order matters) and get a ready-to-use table to upload and start running the campaign.

import advertools as adv

products = ['enginering', 'graphic design', 'marketing']
words = ['jobs', 'careers', 'vacancies', 'full time', 'part time']

kw_df = adv.kw_generate(products, words)
kw_df

         Campaign    Ad Group                             Keyword    Criterion Type               Labels
  SEM_Campaign  Enginering                     enginering jobs             Exact                 Jobs
  SEM_Campaign  Enginering                     enginering jobs            Phrase                 Jobs
  SEM_Campaign  Enginering                   +enginering +jobs             Broad                 Jobs
  SEM_Campaign  Enginering                  enginering careers             Exact              Careers
  SEM_Campaign  Enginering                  enginering careers            Phrase              Careers
..            ...         ...                                 ...              ...                  ...
SEM_Campaign   Marketing       part time vacancies marketing            Phrase   Part Time;Vacancies
SEM_Campaign   Marketing   +part +time +vacancies +marketing             Broad   Part Time;Vacancies
SEM_Campaign   Marketing       part time full time marketing             Exact   Part Time;Full Time
SEM_Campaign   Marketing       part time full time marketing            Phrase   Part Time;Full Time
SEM_Campaign   Marketing  +part +time +full +time +marketing             Broad   Part Time;Full Time
[630 rows x 5 columns]

Check the kw_generate() function for more options and details. Once you have your keywords done, you can start creating ads using either the ad_create function (bottom-up approach) or the ad_from_string function (top-down approach).

kw_broad(words)[source]

Return words in broad match.

Parameters: words (list) -- list of strings
Returns formatted: words in broad match type

>>> keywords = ['[learn guitar]', '"guitar courses"', '+guitar +tutor']
>>> kw_broad(keywords)
['learn guitar', 'guitar courses', 'guitar tutor']

kw_exact(words)[source]

Return words in exact match.

Parameters: words (list) -- list of strings
Returns formatted: words in exact match type

>>> keywords = ['learn guitar', 'guitar courses', 'guitar tutor']
>>> kw_exact(keywords)
['[learn guitar]', '[guitar courses]', '[guitar tutor]']

kw_generate(products, words, max_len=3, match_types=('Exact', 'Phrase', 'Modified'), capitalize_adgroups=True, order_matters=True, campaign_name='SEM_Campaign')[source]

Generate a data frame of keywords using a list of products and relevant words.

Parameters

products (list) -- will be used as the names of the ad groups
words (list) -- related words that make it clear that the user is interested in products
max_len (int) -- the maximum number of words to include in each permutation of final keywords
match_types (list) -- one or more of ('Exact', 'Phrase', 'Modified', 'Broad')
capitalize_adgroups (bool) -- whether or not to set adgroup names in the "Ad Group" column to title case or keep them as is, default True
order_matters (bool) -- whether or not the order of words in keywords matters, default False
campaign_name (str) -- name of campaign

Returns keywords_df

a pandas.DataFrame ready to upload

>>> import advertools as adv
>>> products = ['bmw', 'toyota']
>>> words = ['buy', 'second hand']
>>> kw_df = adv.kw_generate(products, words)
>>> kw_df.head()
       Campaign Ad Group          Keyword Criterion Type       Labels
0  SEM_Campaign      Bmw          bmw buy          Exact          Buy
1  SEM_Campaign      Bmw          bmw buy         Phrase          Buy
2  SEM_Campaign      Bmw        +bmw +buy          Broad          Buy
3  SEM_Campaign      Bmw  bmw second hand          Exact  Second Hand
4  SEM_Campaign      Bmw  bmw second hand         Phrase  Second Hand

>>> kw_df.tail()
        Campaign Ad Group                    Keyword Criterion Type           Labels
SEM_Campaign   Toyota     second hand toyota buy         Phrase  Second Hand;Buy
SEM_Campaign   Toyota  +second hand +toyota +buy          Broad  Second Hand;Buy
SEM_Campaign   Toyota     second hand buy toyota          Exact  Second Hand;Buy
SEM_Campaign   Toyota     second hand buy toyota         Phrase  Second Hand;Buy
SEM_Campaign   Toyota  +second hand +buy +toyota          Broad  Second Hand;Buy

Sometimes you want to retain capitalization and keep it as it as is in the "Ad Group" column. This is especially important for consistency with ads DataFrames for easier integration between the two. Set capitalize_adgroups=False to keep capitalization the same:

>>> adv.kw_generate(['SEO'], ['services', 'provider'], capitalize_adgroups=False).head()
       Campaign Ad Group         Keyword Criterion Type    Labels
SEM_Campaign      SEO    SEO services          Exact  Services
SEM_Campaign      SEO    SEO services         Phrase  Services
SEM_Campaign      SEO  +SEO +services          Broad  Services
SEM_Campaign      SEO    SEO provider          Exact  Provider
SEM_Campaign      SEO    SEO provider         Phrase  Provider

kw_modified(words)[source]

Return words in modified broad match.

Parameters: words (list) -- list of strings
Returns formatted: words in modified broad match type

>>> keywords = ['learn guitar', 'guitar courses', 'guitar tutor']
>>> kw_modified(keywords)
['+learn +guitar', '+guitar +courses', '+guitar +tutor']

kw_neg_broad(words)[source]

Return words in negative broad match.

Parameters: words (list) -- list of strings
Returns formatted: words in negative broad match type

>>> keywords = ['learn guitar', 'guitar courses', 'guitar tutor']
>>> kw_neg_broad(keywords)
['-learn guitar', '-guitar courses', '-guitar tutor']

kw_neg_exact(words)[source]

Return words in negative exact match.

Parameters: words (list) -- list of strings
Returns formatted: words in negative exact match type

>>> keywords = ['learn guitar', 'guitar courses', 'guitar tutor']
>>> kw_neg_exact(keywords)
['-[learn guitar]', '-[guitar courses]', '-[guitar tutor]']

kw_neg_phrase(words)[source]

Return words in negative phrase match.

Parameters: words (list) -- list of strings
Returns formatted: words in negative phrase match type

>>> keywords = ['learn guitar', 'guitar courses', 'guitar tutor']
>>> kw_neg_phrase(keywords)
['-"learn guitar"', '-"guitar courses"', '-"guitar tutor"']

kw_phrase(words)[source]

Return words in phrase match.

Parameters: words (list) -- list of strings
Returns formatted: words in phrase match type

>>> keywords = ['learn guitar', 'guitar courses', 'guitar tutor']
>>> kw_phrase(keywords)
['"learn guitar"', '"guitar courses"', '"guitar tutor"']