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SEO for large sites and Excel

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  • 1. SEO for large sites and Excel
    CheeHo Wan
    @cheehowan
  • 2. Table of contents
    Why do this?
    What challenges are there between small and large websites?
    Where does Excel come in?
    How do we do data analysis?
    What data classifications are important?
    Coding
    How to structure data in Excel
    Outputs
    Excel tips
  • 3. Why do this? It looks hard and I have a data analyst
    Inform strategy - Take a data driven approach is important for organisational buy-in and informing your SEO strategy.
    Forecasting – breaking data into bite size pieces
  • 4. Informing strategy- Head vs tail analysis
    Head centric strategy
    Tail centric strategy
    Number of keywords
    Understanding which verticals should take head or tail strategies
  • 5. Why do this? It looks hard and I have a data analyst
    Data latency – SEO has large enough delays without data visibility being an issue
    Breaking problems into tangible chunks enables you to act faster
    Look awesome in front of your work collegues!
    Spot opportunities others can’t see
  • 6. What challenges are there between large and small websites?
    Analysis
    Too much data and keywords!
    Implementation
    Require large scale changes to see traffic growth
    Need to break data into workable chunks
    Tasks need automation
    Changes to site architecture
    Content mashups
    Large scale content writing / UGC
    Modified search - automated
    Domain authority building to win long tail
    Time and resource constraint become an increasing factor in large website SEO
  • 7. Where does EXCEL come in?
    Everywhere!
    Keyword analysis
    Head vs tail
    Trend analysis – customer search patterns
    Back link analysis
    Classifying websites, using filtering to spot opportunities
    Traffic to rankings to links correlation
    Internal link analysis
    Important to turn daily and weekly task into automated process
  • 8. How do we do analysis – love the drill down!
    Total SEO traffic
    Brand SEO
    Head
    Type of page
    Non- brand SEO
    Product
    Tail traffic
    Start wide, then narrow your analysis (don’t get sucked into detailed analysis too quick)
    The only way to do this kind of analysis is to classify your data into smaller chunks
    Site Depth
    Date
  • 9. What data classifications are important for SEO?
    Page type
    Page duration
    Brand
    Product
    % of unique content per page
    Length of content per page
    Date – week, monthly, yearly
    Site depth
    Actionable insights rather than just data for data sake!
  • 10. Example - MAYDAY
    Data analysis
    Symptoms
    Actions
    Drop in traffic on ‘transient pages’
    What inbound link strategies can we apply to stop drop off
    Page type analysis - listing vs item pages
    Pages with inbound links do not lose rank
    Can we create more permanent pages?
    Pages with unique content do not lose traffic
    Can we add more “mashup” content to pages to make them more unique
    Analysis of trade vs private ads, page length, market data
    What internal linking structures can we apply to the website
    Pages with poor internal linking suffer
  • 11. How do I code this into my site?
    Add some JAVASCRIPT to every entry page which classifies pages into different types
    varfuntionality_is_enabled=1;function engine_match(){if(funtionality_is_enabled!=1){return 0}var engines=new Array("google","aolsearch.aol.com","search.aol.com","search.yahoo.com","bing");for(var i=0;i<engines.length;i++){if(document.referrer.length>0&&document.referrer.indexOf(engines[i])!=-1){return 1}}return 0};
    Store the information in a custom variables available in Omniture, Webtrends, Mediaplex, Google analytics
  • 12. Coding…. cont
    s.eVar45="Op:UK:Promo:Flights-morocco-marrakech-“
    pageTracker._setCustomVar(1, "visit type", "prospect", 2)
    DCSext.SEOvariable
    varmpcl = 'h-london---l1-------http://www.gumtree.com/london';
  • 13. How to structure data in Excel
    Excel becomes powerful when you can cross- correlate multiple sets of data
    The key is to get a single view of your data (merge them all on one view
    To do this you will need a combination of VLOOKUP’s, SUMIFS, PIVOTS
    Analytics
    Traffic
    Clear understanding of cause and effect
    Single data set – cross correlate data
    Rankings
    Historic link data
    Date
  • 14. Key tip
    Keep all classifying dimensions as columns
    As opposed to
    Allows you to merge data across multiple data sets and pivot data in any dimension
  • 15. Tip 2: Understand SUMIFS
    Multiple lookup values to merge ranking with traffic data
    SUMIFs must be used when merging data as you have two or more lookup values
    VLOOKUP only allow you to merge one set of data
  • 16. Pivots – what you end up with
  • 17. Typical data outputs
  • 18. Understand YoY trends to predict future behaviour and see opportunities
    What went up and why?
    Can we repeat this trend elsewhere?
  • 19. Head vs Tail Traffic & Conversions
    Does your head deliver against conversion?
  • 20. Informing strategy- Head vs tail analysis
    Head centric strategy
    Tail centric strategy
    Understanding which verticals should take head or tail strategies
  • 21. Tail opportunities
    What are the tail keywords you should focus on – does this correlate to traffic?
  • 22. Example output
    What is the impact on your activities
  • 23. Link back analysis – Majestic data
  • 24. Excel tips
  • 25. Common excel functions
    URL extraction
    Left, mid, right, search
    Errors (#Value,#NA)
    ISNA (), ISERROR() and IF function
    Classification of data
    Sumifs(), VLOOKUP,
    At some point when data sets are too large or formulas are too complex, you will need to use MACROS or ACCESS!
  • 26. Excel ninja shortcuts
    Paste Values - ALT ‘E’ ‘S’ ‘V’
    Paste Formats - ALT ‘E’ ‘S’ ‘T’
    Freeze panes = ALT WF
  • 27. Missing cells in PIVOTS
    Control G
    Click Special, select blanks
    =, UP, CTRL, enter,
  • 28. Questions

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