will critchlow - the future of search
TRANSCRIPT
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The Future of Search
And what you should be doing about it right now
Will Critchlow
CEO, Distilled
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1 What’s going on with search?
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Keywords become intentsEverything used to be about matching the words you use to search with words on a web page
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Understand, not just index
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This query really shouldn’t work
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But it does
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See reddit thread for more
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When someone searches for “best”
• From Google Trends
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They probably don’t mean a page that says “best”
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Watch this presentation for more
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“london tube stations”query
Old Query Model
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explicit query
implicit queryiPhone user, on street in London
“london tube stations”New Query Model
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New Query Model
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TIME
TOTA
L SI
GN
AL IN
FOR
MAT
ION
explicit signalimplicit signal
Query Scale
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TIME
TOTA
L SI
GN
AL IN
FOR
MAT
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explicit signalimplicit signal
Query Scale
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TIME
TOTA
L SI
GN
AL IN
FOR
MAT
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explicit signalimplicit signal
Query Scale
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TIME
TOTA
L SI
GN
AL IN
FOR
MAT
ION
explicit signalimplicit signal
Query Scale
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TIME
TOTA
L SI
GN
AL IN
FOR
MAT
ION
explicit signalimplicit signal
Query Scale
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User signals and personalizationThe unexpected power of machine learning at Google
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Vision: Strong AI
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Reality: Weak AI
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Different “algorithms” for different queriesSee Dr. Pete’s presentation
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COMPLEX SYSTEMSEven Google engineersdon’t know why one page ranks above another
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The growth of mobile
You’ve heard all this before
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The iPod revolutionized an industry
Source: Business Insider
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The iPhone makes it look slow
Source: Business Insider
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Then came the iPad
Source: Business Insider
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Wow. Android.
Source: Business Insider
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And it keeps going
Source: Business Insider
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Source: Benedict Evans
The point is social is mobile
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So content marketing is mobile
Source: Recent B2B Distilled campaign
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Let’s look at a viral loop
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Sees something cool. Shares it.
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Bunch of people see it.
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At least some think it’s cool.
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If on average more than 1 new share happens each time it is shared, then it is “viral” (k > 1)
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What if it sucks on mobile?
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It sucks for more than half
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Half as many share it
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k has to be twice as big to achieve virality
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This isn’t about disappointing 10%…or even 50% of mobile visitors
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It’s the difference between……getting a couple thousand visitors and getting millions
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2 Practical tips and tactics to succeed
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Don’t build things differently.Build different things.
What does content marketing look like “mobile first”?
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This is a creative piece we made
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This view is probably more important
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Quick tip:Right-click → inspect element.Click on mobile icon.
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Mobile emulation
You can choose a device and speed filters, try out touch responses and more
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Example
Remember this piece?
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It was made in 2012 so this isn’t so bad
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The answer is not a responsive animation
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No. Probably still not the answer
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• Simple
• Unexpected
• Concrete
• Credible
• Emotional
• Stories
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• Simple
• Unexpected
• Concrete
• Credible
• Emotional
• Suitable - for your medium
• Stories
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• Simple
• Unexpected
• Concrete
• Credible
• Emotional
• Suitable - for mobile
• Stories
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And how do we attack machine learning?Let’s make the users happy in order to make the algorithms happy
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a) Tips from conversion rate optimizationLet’s make the users happy in order to make the algorithms happy
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Optimize for what would happen if you did rank
Do I click? Do I like what I see?
Do I get what I want?
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#1
#2
#3
#4
#5
#1
#2
Your site
#4
#5
A B
It’s possible Google is testing user happiness directly
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Even if Google isn’t testing this directlyThese are the signals that Google is optimizing for
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‘Traditional’ CRO A/B testing is user oriented
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CRO process
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DiscoveryFinding out what people like and dislike is often the most important part, and doesn’t have to be aimed at “conversions”
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Test against each of these stages
Do I click? Do I like what I see?
Do I get what I want?
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Note: what makes users happy may not please Google
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b) A/B testing for GoogleWithout breaching their guidelines
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Check out this post from Pinterest’s engineering blog
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SEO A/B testing page oriented
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Consider typical traffic data
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Read Ben Estes’ blog post for more
We can extract:
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Seasonality...
We can extract:
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...and trend
We can extract:
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Then we can make forecasts(Dotted line = forecast, blue area = confidence interval)
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We can detect anomaliesWe use this on our client-only ops platform to spot unexpected changes
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Forecast is correct
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It’s hard to make these kinds of changes:
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But there are real benefits
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1 Optimise for actual Google preferences(rather than guessing how Google will interpret user preferences)
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2 Avoid wide scale losses from unsuccessful tests
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One more thing…
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One more thing…
We have an early private beta of a product to do SEO split testing. Contact me if you’re interested
