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Lessons from redesigning
LinkedIn Search
Kumaresh Pattabiraman (@kumareshp)
Senior Product Manager, LinkedIn
May 16, 2014
2012
The Search Page
•
5B queries a year
One of the top visited pages on LinkedIn
Why fix it?
• Selling us short – Discoverability
 LinkedIn has more to offer than just people search, but
the other verticals don’t get discovered enough
• Inflexible - Not easy to iterate
 Each search vertical is built on a different stack with low
leverage across verticals
• Design cadence with the rest of the site
 Search verticals look completely different from each
other, and LinkedIn is doing a site-wide redesign
March 15, 2012
Product Review
New design: Unified Search
Product Goals
 Engagement from Search
(Page Views & Actions driven
from search)
 Searchers per vertical
 Dead-end searches
 Revenue from search
1 year later
March 25, 2013
5% Public Launch
Early Results
 Engagement from Search
(Page Views & Actions)
 Searchers per vertical
 Dead-end searches
 Revenue from search
What changed?
100+ things
Change 1: The Vertical Selector
Before Unified Search
Searcher gets control of what
they are searching for
(People, Jobs, Companies,
Groups)
Unified Search
We remove the vertical selector
Change 2: Intent detector
Before Unified Search
Searcher specifies intent
explicitly
Unified Search
We algorithmically predict the
searcher’s intent
Query: “marketing”
?
Change 3: Buttons
Before Unified Search
Big blue Action buttons
Unified Search
Small gray CTAs
Vote
What change do you think impacted
engagement the most?
 Vertical Selector
 Intent Detector
 Gray vs Blue buttons
To find out… We ran controlled A/B tests
Control
Default search box with no
vertical selector
Treatments
Vertical selector
Ghost text changes
We prioritized what to test... ruthlessly
And measured the isolated impact of major changes
Metrics
A/B tests
We optimized for speed of learning
• Quick experimental iterations designed to
answer the most burning questions
• Design -> Spec -> Dev -> QA -> Prod in
~1 week.
We identified and ramped the winning
changes
And either iterated on or killed the losing
ones
3 months and ~30 experiments later
June 25, 2013: 100% en-US Launch
And we eventually rolled out Unified Search
100% worldwide over the following 3 months…
Results
 Engagement from Search
(Page Views & Actions)
 Searchers per vertical
 Dead-end searches
 Revenue from search
What did we learn?
#1: Have opportunity analysis drive goal setting
Was an X% increase in searchers per vertical a realistic goal?
eg: How much of search traffic can we realistically expect to
distribute from people to other verticals with unified search?
Opportunity unclear? Test the waters - Quickly
Example of a test we ran within one dev quarter:
Structured suggestions to clarify user’s vertical intent
#2: Importance of controlled experimentation
• To understand the isolated impact of each
major change
• Especially so when you are changing
something working well
• Even when the combination of changes is
a huge net win (so we know what led to
the win)
• Often mistaken with going after
“incremental” wins - Disruptive changes
can be executed incrementally and can be
tested in a controlled fashion
Google: Thousands of search experiments per year
Bing: Search Quality α Experimental velocity
“You have to kiss a lot of frogs to find one
prince. So how can you find your prince
faster? By finding more frogs and kissing
them faster and faster.”
Mike Moran
Do It Wrong Quickly: How the Web Changes the Old
Marketing Rules, 2007
#3: Agility in a crisis
Product launches after 1 year in development.
Metrics drop.
Panic sets.
All hands on deck.
Huge number of (emotional) people involved.
Huge number of options.
Behind schedule on ramp.
The clock is ticking.
Often the time for drastic measures…
And yet, it is important to be agile. We made controlled changes,
executing quickly and taking rational decisions based on data
Organizational alignment critical to pull this off…
• Product/Design: Micro-prioritization, mini-specs for
experiments with clear hypotheses
• Web-dev/Apps: Time-box efforts, limited scope (eg:
launch test in a subset of locales or browsers)
• Relevance: Practical hand-tuned approaches
• Analytics: A/B dashboards and custom analysis
• QA: Minimal QA automation & more manual checks
until test succeeds
• SRE/Ops: Frequent deployments
3 Key Takeaways
• Analyze opportunity & test the waters
early, quickly, cheaply
• Control your biggest changes to
understand isolated impact
• Stay agile when things go wrong
Thanks!
Questions/Comments? @kumareshp

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Lessons from redesigning LinkedIn Search

  • 1. Lessons from redesigning LinkedIn Search Kumaresh Pattabiraman (@kumareshp) Senior Product Manager, LinkedIn May 16, 2014
  • 4. 5B queries a year One of the top visited pages on LinkedIn
  • 5. Why fix it? • Selling us short – Discoverability  LinkedIn has more to offer than just people search, but the other verticals don’t get discovered enough • Inflexible - Not easy to iterate  Each search vertical is built on a different stack with low leverage across verticals • Design cadence with the rest of the site  Search verticals look completely different from each other, and LinkedIn is doing a site-wide redesign
  • 8. Product Goals  Engagement from Search (Page Views & Actions driven from search)  Searchers per vertical  Dead-end searches  Revenue from search
  • 9. 1 year later March 25, 2013 5% Public Launch
  • 10. Early Results  Engagement from Search (Page Views & Actions)  Searchers per vertical  Dead-end searches  Revenue from search
  • 13. Change 1: The Vertical Selector Before Unified Search Searcher gets control of what they are searching for (People, Jobs, Companies, Groups) Unified Search We remove the vertical selector
  • 14. Change 2: Intent detector Before Unified Search Searcher specifies intent explicitly Unified Search We algorithmically predict the searcher’s intent Query: “marketing” ?
  • 15. Change 3: Buttons Before Unified Search Big blue Action buttons Unified Search Small gray CTAs
  • 16. Vote What change do you think impacted engagement the most?  Vertical Selector  Intent Detector  Gray vs Blue buttons
  • 17. To find out… We ran controlled A/B tests Control Default search box with no vertical selector Treatments Vertical selector Ghost text changes
  • 18. We prioritized what to test... ruthlessly
  • 19. And measured the isolated impact of major changes Metrics A/B tests
  • 20. We optimized for speed of learning • Quick experimental iterations designed to answer the most burning questions • Design -> Spec -> Dev -> QA -> Prod in ~1 week. We identified and ramped the winning changes And either iterated on or killed the losing ones
  • 21. 3 months and ~30 experiments later June 25, 2013: 100% en-US Launch And we eventually rolled out Unified Search 100% worldwide over the following 3 months…
  • 22. Results  Engagement from Search (Page Views & Actions)  Searchers per vertical  Dead-end searches  Revenue from search
  • 23. What did we learn?
  • 24. #1: Have opportunity analysis drive goal setting Was an X% increase in searchers per vertical a realistic goal? eg: How much of search traffic can we realistically expect to distribute from people to other verticals with unified search?
  • 25. Opportunity unclear? Test the waters - Quickly Example of a test we ran within one dev quarter: Structured suggestions to clarify user’s vertical intent
  • 26. #2: Importance of controlled experimentation • To understand the isolated impact of each major change • Especially so when you are changing something working well • Even when the combination of changes is a huge net win (so we know what led to the win) • Often mistaken with going after “incremental” wins - Disruptive changes can be executed incrementally and can be tested in a controlled fashion
  • 27. Google: Thousands of search experiments per year
  • 28. Bing: Search Quality α Experimental velocity
  • 29. “You have to kiss a lot of frogs to find one prince. So how can you find your prince faster? By finding more frogs and kissing them faster and faster.” Mike Moran Do It Wrong Quickly: How the Web Changes the Old Marketing Rules, 2007
  • 30. #3: Agility in a crisis Product launches after 1 year in development. Metrics drop. Panic sets. All hands on deck. Huge number of (emotional) people involved. Huge number of options. Behind schedule on ramp. The clock is ticking. Often the time for drastic measures… And yet, it is important to be agile. We made controlled changes, executing quickly and taking rational decisions based on data
  • 31. Organizational alignment critical to pull this off… • Product/Design: Micro-prioritization, mini-specs for experiments with clear hypotheses • Web-dev/Apps: Time-box efforts, limited scope (eg: launch test in a subset of locales or browsers) • Relevance: Practical hand-tuned approaches • Analytics: A/B dashboards and custom analysis • QA: Minimal QA automation & more manual checks until test succeeds • SRE/Ops: Frequent deployments
  • 32. 3 Key Takeaways • Analyze opportunity & test the waters early, quickly, cheaply • Control your biggest changes to understand isolated impact • Stay agile when things go wrong

Editor's Notes

  1. 5B Searches a day among most popular pages on site. Everything looks great. Why fix it?
  2. Kevin: Any high level data to support this?
  3. What is a product review… Execs – How are products developed and deployed here? What is the role of a product manager?
  4. Talk about features of unified search… Explain a use-case. Voice-over how this helps.
  5. Define engagement… (Page views, Actions) Not showing numbers. +20% actions +10% page views > +100% searchers (remove) -20% dead-ends
  6. Num Eng, Des, people… 5% of site traffic…
  7. History… personal take… Day 1… Not showing numbers -14% actions -6% page views -1% searchers +10% dead-ends -$X revenue
  8. Talk through this…
  9. 3 major changes…
  10. Expand CTA
  11. Guess the biggest driver that turned things around, from this list of three
  12. You can run multiple, not just conflict with each other… as a reason for why we need infrastructure for it… conceptually simple – but infra needs to support it… experimentation platform… take advantage.. Simplification of architecture.. Not only did people differ on this but they had strong reasons, backed by strong intuition…\
  13. Explain the process…
  14. Blurred – Readable… Show 3
  15. +10% actions +2% page views Flat on searchers and dead-ends +$X weekly ad revenue
  16. Climax – story telling – Positioning unified search…
  17. Platform a requirement for product changes. Talk about unified search as a platform…
  18. How do you get a team that is used to building a product with a 1 year time-frame in mind to suddenly be iterative and experimental? What hypotheses are worth testing? How much effort do you put into a particular test… What makes a test a good test… Take slide from Kohavi’s talk Frogs and faster… from management…