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SEO for large sites and ExcelChee Ho Wan@cheehowan
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
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
Informing strategy- Head vs tail analysis
• Understanding which verticals should take head or tail strategies
Tail centric strategy
Head centric strategy
Number of keywords
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
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 architectureContent mashups
Large scale content writing / UGC
Modified search - automatedDomain authority building to win long tail
Time and resource constraint become an increasing factor in large website SEO
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
How do we do analysis – love the drill down!
• 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
Total SEO traffic
HeadType of page
ProductTail traffic
Brand SEO
Non- brand SEO
Site Depth
Date
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!
Example - MAYDAY
Symptoms
Drop in traffic on ‘transient pages’
Pages with inbound links do not lose rank
Pages with poor internal linking suffer
What inbound link strategies can we apply to stop drop off
Can we create more permanent pages?
Pages with unique content do not lose traffic
Actions
Can we add more “mashup” content to pages to make them more unique
What internal linking structures can we apply to the website
Analysis of trade vs private ads, page length, market data
Page type analysis - listing vs item pages
Data analysis
How do I code this into my site?
• Add some JAVASCRIPT to every entry page which classifies pages into different types– var funtionality_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
Coding…. cont
s.eVar45="Op:UK:Promo:Flights-morocco-marrakech-“
pageTracker._setCustomVar(1, "visit type", "prospect", 2)
DCSext.SEOvariable
var mpcl = 'h-london---l1-------http://www.gumtree.com/london';
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
Rankings
Date
Single data set – cross correlate data
Historic link data
Clear understanding of cause and effect
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
Tip 2: Understand SUMIFS
• 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
Multiple lookup values to merge ranking with traffic data
Pivots – what you end up with
Typical data outputs
Understand YoY trends to predict future behaviour and see opportunities
What went up and why?Can we repeat this trend elsewhere?
Head vs Tail Traffic & Conversions
• Does your head deliver against conversion?
15%
85%
SEO Traffic
Head Tail
39%
61%
SEO Conversions
Head Tail
Informing strategy- Head vs tail analysis
• Understanding which verticals should take head or tail strategies
Tail centric strategy
Head centric strategy
Tail opportunities
• What are the tail keywords you should focus on – does this correlate to traffic?
x dea
lsx u
k
x pay
as yo
u gox p
rice
x contra
ct
x sim
free
best x
deals
buy xx p
ayg
x contra
ctsx b
uyx d
eal
chea
p x
x pay
monthly
pay as
you go
x
chea
pest x
x for s
ale x0
500
1,000
1,500
2,000
2,500
3,000
3,500
Average Search Volumes
Keywords (where x = [Make][Model])
Example output
• What is the impact on your activities
Link back analysis – Majestic data
Excel tips
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!
Excel ninja shortcuts
• Paste Values - ALT ‘E’ ‘S’ ‘V’• Paste Formats - ALT ‘E’ ‘S’ ‘T’• Freeze panes = ALT WF
Missing cells in PIVOTS
• Control G– Click Special, select
blanks– =, UP, CTRL, enter,
Questions