Concept Creative

Concept Creative

Concept Creative gives back to the open-source community by sharing our tools and expertise.

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Open-Source Tools and Projects

One part literature and one part software, our tools help us make better decisions on the web.

Ngrams

Analyze search terms and identify those words and phrases that are most important.

> python analyze.py --help
usage: analyze.py [-h] [--skip-lines SKIP_LINES] [--drop-lines DROP_LINES]
                  [--column COLUMN] [--weight WEIGHT]
                  [--ngram-size NGRAM_SIZE] [--display DISPLAY]
                  filename

Ngram Analyzer

positional arguments:
  filename

optional arguments:
  -h, --help            show this help message and exit
  --skip-lines SKIP_LINES
                        number of lines to skip at the start of the file
  --drop-lines DROP_LINES
                        number of lines to drop at the end of the file
  --column COLUMN       name of the search term column
  --weight WEIGHT       name of the column by which to weight terms
  --ngram-size NGRAM_SIZE
                        size of the ngram
  --display DISPLAY     number of ngrams to display

Backlinks

What link directories are most important? Use Google and SeoMoz to answer that question.

Though it can be complex to automate the process, the results are well worth it:

  1. Identify the competition. You can do this manually from your own research or automate the process by querying search engines.
  2. Identify backlinks to the competition. Our system uses the OpenSiteExplorer SeoMoz API.
  3. Cross-reference those backlinks to identify which sites are linking to your competitors.

Rather than listen to so-called experts in SEO, this process tells you which link directories matter most. The results will surprise you!

Wordsegment

Parsingwordswithoutspacesishard, but domain names work like that. This is such an important problem that the Director of Research at Google published a billion-word corpus to help us out.

Installing WordSegment is simple with pip:

> pip install wordsegment

You can access documentation in the interpreter with Python’s built-in help function:

>>> import wordsegment
>>> help(wordsegment)

In your own Python programs, you’ll mostly want to use segment to divide a phrase into a list of its parts:

>>> from wordsegment import segment
>>> segment('thisisatest')
['this', 'is', 'a', 'test']

WordSegment also provides a command-line interface for batch processing. This interface accepts two arguments: in-file and out-file. Lines from in-file are segmented iteratively, joined by a space, and written to out-file. Input and output default to stdin and stdout respectively.

> echo thisisatest | python -m wordsegment
this is a test

Autocomplete

Web search auto-complete can tell you a lot about what people are looking for.

This project also includes notes on how to visualize the search queries in clusters.

usage: crawl_google_autocomplete.py [-h] [--query QUERY] [--prefix PREFIX]
                                    [--include INCLUDE] [--exclude EXCLUDE]
                                    filename

Crawl Google Auto-Complete Query

positional arguments:
  filename

optional arguments:
  -h, --help         show this help message and exit
  --query QUERY
  --prefix PREFIX
  --include INCLUDE
  --exclude EXCLUDE

Adstats

Wish you could visualize ad variation by day? Use even more tools to slice and dice your data.

> python analyze.py --help
usage: analyze.py [-h] [--adwords ADWORDS] [--adsense ADSENSE]
                  [--print-col-names] [--interactive]

Ad Network Statistics

optional arguments:
  -h, --help         show this help message and exit
  --adwords ADWORDS  path to Google Adwords csv report
  --adsense ADSENSE  path to Google Adsense csv report
  --print-col-names
  --interactive

Askbot

Our most ambitious project yet. Question and answer deployed to the financial industry.

As this is a work in progress, more details are forthcoming.