Metadata-Version: 1.1
Name: advertools
Version: 0.2.0
Summary: Productivity and analysis tools for online marketing
Home-page: https://github.com/eliasdabbas/advertools
Author: Elias Dabbas
Author-email: eliasdabbas@gmail.com
License: MIT license
Description: advertools: create, scale, and manage online campaigns
        ======================================================
        
        | A digital marketer is a data scientist.
        | Your job is to manage, manipulate, visualize, communicate, understand,
          and make decisions based on data.
        
        You might be doing basic stuff, like copying and pasting text on spread
        sheets, you might be running large scale automated platforms with
        sophisticated algorithms, or somewhere in between. In any case your job
        is all about working with data.
        
        | As a data scientist you don’t spend most of your time producing cool visualizations or finding great insights. The majority of your time is spent wrangling with URLs, figuring out how to stitch together two tables, hoping that the dates, won’t break, without you knowing, or trying to generate the next 124,538 keywords for an upcoming campaign, by the end of the week!
        
        | advertools is a Python package, that can hopefully make that part of your job a little easier.
        
        
        I have a tutorial on DataCamp that demonstrates a real-life example of
        how to use `Python for creating a Search Engine Marketing campaign`_.
        
        I also have an interactive tool based on this package, where you can
        `generate keyword combinations easily`_.
        
        .. image:: app_screen_shot.png
           :width: 600 px
           :align: center
        
        
        Main Uses:
        ~~~~~~~~~~
        
        -  **Generate keywords:** starting from a list of products, and a list
           of words that might make sense together, you can generate a full
           table of many possible combinations and permutations of relevant
           keywords for that product.
           The output is a ready-to-upload table to get you started with
           keywords.
        
        .. code:: python
        
           >>> import advertools as adv
           >>> adv.kw_generate(products=['toyota'],
                               words=['buy', 'price'],
                               match_types=['Exact']).head()
           ...        Campaign Ad Group           Keyword Criterion Type
               0  SEM_Campaign   toyota        toyota buy          Exact
               1  SEM_Campaign   toyota      toyota price          Exact
               2  SEM_Campaign   toyota        buy toyota          Exact
               3  SEM_Campaign   toyota      price toyota          Exact
               4  SEM_Campaign   toyota  toyota buy price          Exact
        
        -  **Create ads:** Two main ways to create text ads, one is from scratch
           (bottom-up) and the other is top down (given a set of product names).
        
        1. From scratch: This is the tradiditional way of writing ads. You have
           a template text, and you want to insert the product name dynamically
           in a certain location. You also want to make sure you are within the
           character limits. For more details, I have a `tutorial on how to
           create multiple text ads from scratch`_.
        
        .. code:: python
        
           >>> ad_create(template='Let\'s count {}',
                         replacements=['one', 'two', 'three'],
                         fallback='one', # in case the total length is greater than max_len
                         max_len=20)
           ["Let's count one", "Let's count two", "Let's count three"]
        
           >>> ad_create('My favorite car is {}', ['Toyota', 'BMW', 'Mercedes', 'Lamborghini'], 'great', 28)
           ['My favorite car is Toyota', 'My favorite car is BMW', 'My favorite car is Mercedes',
           'My favorite car is great'] # 'Lamborghini' was too long, and so was replace by 'great'
        
        2. Top-down approach: Sometimes you need to start with a given a list of
           product names, which you can easily split them into the relevant ad
           slots, taking into consideration the length restrictions imposed by
           the ad platform.
           Imagine having the following list of products, and you want to split
           each into slots of 30, 30, and 80 characters (based on the AdWords
           template):
        
        .. code:: python
        
           >>> products = [
               'Samsung Galaxy S8+ Dual Sim 64GB 4G LTE Orchid Gray',
               'Samsung Galaxy J1 Ace Dual Sim 4GB 3G Wifi White',
               'Samsung Galaxy Note 8 Dual SIM 64GB 6GB RAM 4G LTE Midnight Black',
               'Samsung Galaxy Note 8 Dual SIM 64GB 6GB RAM 4G LTE Orchid Grey'
           ]
           >>> [adv.ad_from_string(p) for p in products]
           ... [['Samsung Galaxy S8+ Dual Sim', '64gb 4g Lte Orchid Gray', '', '', '', ''],
                ['Samsung Galaxy J1 Ace Dual Sim', '4gb 3g Wifi White', '', '', '', ''],
                ['Samsung Galaxy Note 8 Dual Sim', '64gb 6gb Ram 4g Lte Midnight', 'Black', '', '', ''],
                ['Samsung Galaxy Note 8 Dual Sim', '64gb 6gb Ram 4g Lte Orchid', 'Grey', '', '', '']]
        
        | Each ad is split into the respective slots, making sure they contain
          complete words, and that each slot has at most the specific number of
          slots allowed.
        | This can save time when you have thousands of products to create ads
          for.
        
        -  **Analyze word frequency:** Calculate the absolute and weighted
           frequency of words in a collection of documents to uncover hidden
           trends in the data. This is basically answering the question, ‘What
           did we write about vs. what was actually read?’
           Here is a tutorial on DataCamp on `measuring absolute vs weighted
           frequency of words`_.
        
        | The package is still under heavy development, so expect a lot of
          changes.
        | Feedback and suggestions are more than welcomed.
        
        Installation
        ~~~~~~~~~~~~
        
        .. code:: bash
        
           pip install advertools
        
        Conventions
        ~~~~~~~~~~~
        
        Function names mostly start with the object you are working on:
        
        | ``kw_``: for keywords-related functions
        | ``ad_``: for ad-related functions
        | ``url_``: URL tracking and generation
        
        .. _measuring absolute vs weighted frequency of words: https://www.datacamp.com/community/tutorials/absolute-weighted-word-frequency
        
        
        .. _Python for creating a Search Engine Marketing campaign: https://www.datacamp.com/community/tutorials/sem-data-science
        .. _generate keyword combinations easily: https://www.dashboardom.com/advertools
        .. _tutorial on how to create multiple text ads from scratch: https://nbviewer.jupyter.org/github/eliasdabbas/ad_create/blob/master/ad_create.ipynb
        
        =======
        History
        =======
        
        0.1.0 (2018-07-02)
        ------------------
        
        * First release on PyPI.
        
Keywords: advertising marketing search-engine-optimization adwords seo sem bingads keyword-research
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: End Users/Desktop
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
