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SES presentation by David Hughes who heads up the Performance Insight team at iCrossing in the UK. Presentation focuses on search term research
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Search Term ResearchDavid Hughes
Head of Analytics
Email: [email protected]
Blog: http://connect.icrossing.co.uk
Who am I?0
UK
12UK
120A digital marketing agency with search and social at its core
David Hughes, Head of Analytics
Lead a team responsible for measuring user behaviour on
the web. Work across the whole portfolio of iCrossing
clients including Coca Cola, Toyota, HBOS and Orange
12FTSE 100 clients
120Staff
Global
580Staff
Global
13Offices
We blend SEO, paid search, social media, content, display
advertising, user experience, web development, and
analytics & insight to build connected online marketing
strategies
We create connected brands
I will be mostly talking about…0
Selecting Search Terms
based on value
Search Term research =
Customer Research
Search Term Selection
When we choose Terms on volume only…1
We’re acting like there is no competition!
What’s usually the desired outcome?1
Or maybe:
Unique visitors
Time on Site
Pages viewed
Monetised clicks
Quotes
Engagement
Etc etcEtc etc
We need to build Models1
For this model we need…1
…Search volumes
For this model we need…1 Heat Map showing click through rates
An understanding of where users click(And not just using 2006 AOL data)
For this model we need…1Natural Search Ranking Report
Where we are now(In natural search = rankings)
For this model we need…1
Competition
Technical
Restrictions
Available
1
2
3
A realistic forecast of where we can get to…
Available
optimisation tactics
Timeframes
4
5
6
7
For this model we need…1
Conversion
Rate by
keyword
Basket Value
by Product
keyword
Costs
Finally…1 Profit Margins (by product)
• Often difficult to get
• But half blind without
Can put a £value onto each keyword 1
Forecast Rank
Click Thru Rate
Expected Clicks
Search Volume
=Expected Clicks
Conversion Rate
Basket Value
Profit Margin
=
What does this mean for…Natural Search?1
New Profit =
∑ (sV * CTR (@fR)
x cR * pR * pM) – c – cp)
Where:
sV = search volume
CTR = click though rate
fR = forecast rank
Can optimise the
keywords that
will deliver the fR = forecast rank
cR = conversion rate
pR = product revenue
pM = profit margin
C = cost
Cp = current profit
will deliver the
most additional
profit
Case studies1
4 clients - change in incremental profit vs. picking KWs on search volume
97
%
31
2%
54%57%
Be
ne
fit
Op
tim
al
Sp
en
d
What does this mean for…Paid Search?1
Improves Profits
• Much of paid search management is
achieving the right balance between cost
and benefit; i.e. how can I make the most
profit?
• At any one time there will be optimum
bids on individual keywords and
therefore an optimum spend
Cost
Be
ne
fit
Op
tim
al
Sp
en
d
therefore an optimum spend
• This kind of analysis helps you find that
sweet spot
Customer ReSEARCH
“Link by link, click by click, search is building possibly the most
lasting, ponderous, and significant cultural artifact in the history of
humankind: the Database of Intentions.”
John Battelle
Author of “The Search: How Google And Its
Rivals Rewrote The Rules Of Business And
Transformed Our Culture”
“If you're trying to persuade people to do something, or buy
something, it seems to me you should use their language..”
David Ogilvy
Founder of Ogilvy and Mather
how people search is how they think2
shoes sizes search reflects life
2� Actual
� Search Volume
a Women’s b Men’s
Revealing customers wants and needs2 Discovering pinch points on the customer journey for BAA
Judging demand2 Finding out what music people like…in Brazil
For a Global
Fortune 500
company
Understanding the cultural landscape2 Demand from within Germany for non-German media (e.g. Turkish Ringtones)
Discovering Regional differences2 Variations in how different nationalities describe bathroom items