In case you missed my presentation or you are interested in the resources which helped me to learn Python - here are all my slides.

1. SLIDESHARE.NET/BGOERLER
BRINGING THE FUN BACK TO SEO
WITH PYTHON
BENJAMIN GÖRLER // AYIMA //
@ayima

2. BRACE YOURSELVES
INFORMATION OVERLOAD
IS COMING!

3. 48000
50000
52000
54000
56000
58000
60000
62000
2000 2002 2004 2006 2008 2010 2012 2014 2016
Total number of pubs in the UK
Source: BBC (2018)

4. 48000
50000
52000
54000
56000
58000
60000
62000
2000 2002 2004 2006 2008 2010 2012 2014 2016
Total number of pubs in the UK
v9.0
v10.0
v11.0
v12.0
v14.0
v15.0
v16.0
Source: BBC (2018)

5. YOU SPEND 4 HOURS PER WEEK USING EXCEL

6. 16 HOURS PER MONTH

7. ~ 100 HOURS PER YEAR

8. WHAT IF I TOLD YOU
YOU’RE WASTING YOUR TIME

9. Python To The Rescue
What is Python?
● Easy to learn programming language
● Runs on any device
Why Python?
● Steep, but quick learning curve
● Almost unlimited use cases
● Tons of resources provided by a massive online community
● You can use it without actually ‘speaking’ any Python
● It’s scalable!
● Cause it’s fun!

10. WHY SHOULD I BOTHER TO LEARN IT?

11. You already possess an essential skill!
1 x 8 + 1 = 9
12 x 8 + 2 = 98
123 x 8 + 3 = 987
1234 x 8 + 4 = 9876
12345 x 8 + 5 = 98765
123456 x 8 + 6 = 987654
1234567 x 8 + 7 = ??????? Spot the pattern

12. Problem Pattern Python
Solving Problems with Python

13. Scenario #1
Site crawl of
5 Million
URLS

14. https://www.screwfix.com/c/decorating/paint/c
at850142#category=cat850142&brand=dulux
Analysing URL parameters

15. & {word} =
Pattern

16. The Excel Way #1
• Opening the crawl 10 mins
• Filtering and cleaning the data 15 mins
• Performing VLOOKUPs 10 mins
• Analysing the data 30 mins
= 1 hour in total

17. The Python Way

18. python paramsfinder.py -i crawl.csv -o output.csv
The Python Way
Evoke python Script name
input argument output argument
input file output file

19. python paramsfinder.py -i crawl.csv -o output.csv
The Python Way
Parameter Occurrences Example
&brand= 11,655
https://www.screwfix.com/c/decorating/paint/cat8501
42#category=cat850142&brand=dulux_trade
&colour= 24,182
https://www.screwfix.com/c/decorating/paint/cat8501
42#category=cat850142&colour=white
&price= 144,693
https://www.screwfix.com/c/decorating/paint/cat8501
42#category=cat850142&colour=white&price=5.0&pric
e_to=25.0

20. Digestible Data
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
Paint
Parameters By Category
brand colour price

21. Time Spent Using Python
1
2
3
4
Developing the script 20 mins
Entering the command 10 secs
Opening the crawl 5 secs
Running the script 15 secs
~ 20 mins in total

22. HOW MANY FRIDAY PINTS COULD I HAVE HAD?

23. Let’s ask Google

24. Success Metric
10 Minutes =

25. Success

26. Scenario #2: Keyword Reporting

27. Raw Data Export From Third Party Tool
Keyword Monthly Traffic Rank Ranking URL
bags 9,500 1 https://www.asos.com/women/bags-purses/cat/?cid=8730
hoodies 3,100 1 https://www.asos.com/men/hoodies-sweatshirts/cat/?cid=5668
jumpsuit 13,500 5 https://www.asos.com/women/jumpsuits-playsuits/cat/?cid=7618

28. Categorise keywords automagically
Dresses Jeans Jumper Shoes Accessories
wedding guest dresses boyfriend jeans mens turtleneck loafers for men wallet
maternity dress black skinny jeans half zip jumper flip flops belt
party dress mom jeans jumper dress espadrille wedges hat
burgundy grey ripped jeans cropped jumper sandals mens scarf

29. Pattern #1
https://www.asos.com
/women -> Women
/dresses -> Dresses

30. The Excel Way #2
• Filtering and cleaning the data 20 mins
• Developing formulas 120 mins
• Categorising the data 90 mins
4 hours in total

31. python analyse-kw.py -i keywords.csv -o analysis.csv
The Python Way #2
1
2
3
4
Developing the script 60 mins
Entering the command 10 secs
Opening the keyword export 5 secs
Running the script 5 secs

32. 72%
28%
Monthly Traffic
Women Men

33. Reporting Made Simple
4.3
2.5 3.5 4.55.4
3.9
7.5
2.8
8.2
2.0
18.0
5.0
This Month Last Month Last Year
Avg. Rank Department
Shoes Dresses Jeans Accessories
Page 1
Page 2

34. Success

35. You Can Potentially
Automate Everything
With Python
Facet
Optimisation
Reporting
Keyword
Research
Internal Linking
Analysis
Redirect
Hops
Ad
Campaigns

37. Today
● Set up the
Python
environment
● Learn about
Command Line
Interface (CLI)
● Run your first
script!
In a Week
● Support some
workflows with
existing scripts
● Tweak scripts for
own scenarios
In a Month
● Write custom
scripts
● Query data from
various sources
● Automate
reporting
Start Saving Time Today

38. Useful resources
Prerequisites
• Command Line
(Windows)
• Terminal (Mac)
• Python
Environment
Using Python
• Python tutorial
• Online
community
• Ayima’s blog

39. Contact
Benjamin Görler
benjamin@ayima.com