This document discusses using data to guide product development. It recommends analyzing user data and key performance indicators to identify features that correlate with retention. The document advocates continually running A/B tests to evaluate potential product features, noting tests should be fast to implement with minimal impact and visible results. Failure of tests is acceptable as getting results now is better than waiting.
Product lessons from the launch of Unified Search, a massive redesign of LinkedIn's search experience, presented at the Stanford Graduate School of Business High Tech Club on May 16, 2014
In this talk I presented a ratio analysis approach to measuring agile performance we use at Bookmate. It is invariant to story size and story point value. We measure productivity as a ratio of estimated committed & done effort to all resources available, further it cascades down as a product of accuracy, ability to ship, ability to plan and resource utilisation.
This is a presentation showing the practical techniques that helped us build a mobile site, iPhone app and website in 8 weeks. I cover User Centred Design techniques, testing services, performance and cross channel benefits of the approach we took.
Google Flight is a flight aggregator and search tool that shows the routes and fares offered by almost all major airlines around the world. It is one of the best tools for finding cheap flights.Visit site - https://cheap-discount-flights.com/
Google has made its biggest algorithm update in years. Called Hummingbird the update was announced at Google's 15th birthday bash. In this presentation we explain how Hummingbird affects search
Analyzing search engine results pages(SERPs) All over the worldsAnil Sah
Truly,
“Search was Big Data before there was Big Data”
Search has always been concerned with
extremely large datasets, and
statistical analysis of those sets, both for indexing (i.e. large scale batch processing) as well as at query-time (i.e. high speed real-time processing).
Billion-document databases have existed in search engines for decades.
Search has always lacked is a good, inclusive framework. Do we have that framework now? No. But we have the vision of the framework, and it lives on Big Data.But what would we do with such a framework?
Things like:
Link Counting / Page Rank / Anchor Text / Popularity
Were too hard, too expensive, and too unreliable to be used except in complex, hand-crafted implementations.
These are all techniques using external references to improve search relevancy.
Link counting uses inbound links into a document (i.e. links from other documents) to boost relevancy.
Google's "PageRank" has the same goal, but is mathematically more sophisticated.
"Anchor text" can influence relevancy by taking into account how other people reference your document.
Popularity boosts documents that are known to be more popular based on how often those documents are clicked
These algorithms become more than just possible; they are a natural evolution. After all, Google invented Map/Reduce specifically to handle Page Rank calculations for Google.com.
Because of the lack of an appropriate framework that all of this incredibly valuable external data is underused in most search implementations.
Search Engine Results Pages (SERP) : Pages displayed by search engines in response to a query by a searcher.
Main component of the SERP :listing of results that are returned by the search engine in response to a keyword query,
Pages may also contain other results such as advertisements.
Two general types:
Organic search (i.e., retrieved by the search engine's algorithm)
Sponsored search (i.e., advertisements)
Several pages in response to a single search query, Due to the huge number of items that are available.
What kind of pages are viewed as high quality?
Which factors influence high-quality and low-quality ratings (SUPER important, as these factors may be similar to how Google measures page quality for SERP rankings)
Organic SERP listings are the natural listings generated by search engines based on a series of metrics that determines their relevance to the searched term.
Webpages that score well on a search engine's algorithmic test show in this list
1. Count: the number of times that the domain appeared in the searches that we made.
2. Mean: the mean (average) rank of each of the domains.
3. Coverage: the count divided by the number of queries.
Total appearances: the number of times the domain appeared in SERPs (top 10)
Coverage: total appearances divided by the total queries (shown as a percentage)
Average position (rank)of each of the domains
Product lessons from the launch of Unified Search, a massive redesign of LinkedIn's search experience, presented at the Stanford Graduate School of Business High Tech Club on May 16, 2014
In this talk I presented a ratio analysis approach to measuring agile performance we use at Bookmate. It is invariant to story size and story point value. We measure productivity as a ratio of estimated committed & done effort to all resources available, further it cascades down as a product of accuracy, ability to ship, ability to plan and resource utilisation.
This is a presentation showing the practical techniques that helped us build a mobile site, iPhone app and website in 8 weeks. I cover User Centred Design techniques, testing services, performance and cross channel benefits of the approach we took.
Google Flight is a flight aggregator and search tool that shows the routes and fares offered by almost all major airlines around the world. It is one of the best tools for finding cheap flights.Visit site - https://cheap-discount-flights.com/
Google has made its biggest algorithm update in years. Called Hummingbird the update was announced at Google's 15th birthday bash. In this presentation we explain how Hummingbird affects search
Analyzing search engine results pages(SERPs) All over the worldsAnil Sah
Truly,
“Search was Big Data before there was Big Data”
Search has always been concerned with
extremely large datasets, and
statistical analysis of those sets, both for indexing (i.e. large scale batch processing) as well as at query-time (i.e. high speed real-time processing).
Billion-document databases have existed in search engines for decades.
Search has always lacked is a good, inclusive framework. Do we have that framework now? No. But we have the vision of the framework, and it lives on Big Data.But what would we do with such a framework?
Things like:
Link Counting / Page Rank / Anchor Text / Popularity
Were too hard, too expensive, and too unreliable to be used except in complex, hand-crafted implementations.
These are all techniques using external references to improve search relevancy.
Link counting uses inbound links into a document (i.e. links from other documents) to boost relevancy.
Google's "PageRank" has the same goal, but is mathematically more sophisticated.
"Anchor text" can influence relevancy by taking into account how other people reference your document.
Popularity boosts documents that are known to be more popular based on how often those documents are clicked
These algorithms become more than just possible; they are a natural evolution. After all, Google invented Map/Reduce specifically to handle Page Rank calculations for Google.com.
Because of the lack of an appropriate framework that all of this incredibly valuable external data is underused in most search implementations.
Search Engine Results Pages (SERP) : Pages displayed by search engines in response to a query by a searcher.
Main component of the SERP :listing of results that are returned by the search engine in response to a keyword query,
Pages may also contain other results such as advertisements.
Two general types:
Organic search (i.e., retrieved by the search engine's algorithm)
Sponsored search (i.e., advertisements)
Several pages in response to a single search query, Due to the huge number of items that are available.
What kind of pages are viewed as high quality?
Which factors influence high-quality and low-quality ratings (SUPER important, as these factors may be similar to how Google measures page quality for SERP rankings)
Organic SERP listings are the natural listings generated by search engines based on a series of metrics that determines their relevance to the searched term.
Webpages that score well on a search engine's algorithmic test show in this list
1. Count: the number of times that the domain appeared in the searches that we made.
2. Mean: the mean (average) rank of each of the domains.
3. Coverage: the count divided by the number of queries.
Total appearances: the number of times the domain appeared in SERPs (top 10)
Coverage: total appearances divided by the total queries (shown as a percentage)
Average position (rank)of each of the domains
Using Lean Principles to Manage the Data Value ChainMario Faria
Creating and managing a data office is not an easy task. The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined.
Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful.
This session delivered for the Data Quality Pro Summit explores how it can be done.
Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
Data and experimentation is becoming core of product development in todays world. In this talk I will talk about what I learned from building various products, why data and experimentation matter when building products used by millions of users. The talk will also touch on how we at Customator plan to make it easy for any one to follow a data driven product development approach.
Venue : NUS School of Computing Seminar
Big data is changing the way people within organizations work together. It is creating a culture in which business and IT leaders must join forces to realize value from all data. Insights from big data can enable all employees to make better decisions—deepening customer engagement, optimizing operations, preventing threats and fraud, and capitalizing on new sources of revenue. But escalating demand for insights requires a fundamentally new approach to strategy, architecture, tools and practices.
This presentation was given as a guest lecture in Laurel Hart's Spring 2011 Masters progra course for Corporate and Organizational Communications in the NYU school of continuing studies by Amy Sample Ward. Learn more at http://amysampleward.org
Agile and data driven product development oleh Dhiku VP Product KMK OnlineRein Mahatma
Di webinar ini Dhiku akan membawakan materi seputar tips product management, bagaimana proses membangun product digital dengan agile dan data driven. Dimulai dari memahami kebutuhan user, melakukan usability testing, menganalisa data, melakukan prioritas fitur dan perencanaan product roadmap, incremental deployment ke user, sampai evaluasi data untuk pengembangan product yang lebih baik.
Oleh http://www.startupbisnis.com dan http://www.codepolitan.com
Modernizing Architecture for a Complete Data StrategyCloudera, Inc.
Data is the future of business. Either take advantage of it, or get surpassed by those who do.
In this webinar, Ovum's Tony Baer discusses the importance of building a modern data strategy that ensures your journey with Apache Hadoop and big data is a successful one. Together, we'll walk through how to build a plan for long-term success while realizing short-term gains, including:
How to pinpoint the business goals that matter most
How to assess your strengths and weaknesses to meet those goals
How to build a thoughtful approach that ensures your initiatives succeed
Developing a Data Strategy -- A Guide For Business Leadersibi
Data is one of our most valuable assets -- yet we rarely understand how to incorporate it into our business plans. This presentation provides an introduction to data strategy for business leaders and points to more resources.
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
Mozilla Foundation Metrics - presentation to engineersJohn Schneider
@rossbruniges and I talked with our fellow Mozilla Foundation engineers and development teams about getting the data for building a data driven operation using statsd, graphite, geckoboard, google analytics, and newrelic.
Report on A/B title testing of educational videos and materials for small business owners and entrepreneurs. Goal is finding the best way to help the owner start and grow the business.
Using Lean Principles to Manage the Data Value ChainMario Faria
Creating and managing a data office is not an easy task. The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined.
Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful.
This session delivered for the Data Quality Pro Summit explores how it can be done.
Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
Data and experimentation is becoming core of product development in todays world. In this talk I will talk about what I learned from building various products, why data and experimentation matter when building products used by millions of users. The talk will also touch on how we at Customator plan to make it easy for any one to follow a data driven product development approach.
Venue : NUS School of Computing Seminar
Big data is changing the way people within organizations work together. It is creating a culture in which business and IT leaders must join forces to realize value from all data. Insights from big data can enable all employees to make better decisions—deepening customer engagement, optimizing operations, preventing threats and fraud, and capitalizing on new sources of revenue. But escalating demand for insights requires a fundamentally new approach to strategy, architecture, tools and practices.
This presentation was given as a guest lecture in Laurel Hart's Spring 2011 Masters progra course for Corporate and Organizational Communications in the NYU school of continuing studies by Amy Sample Ward. Learn more at http://amysampleward.org
Agile and data driven product development oleh Dhiku VP Product KMK OnlineRein Mahatma
Di webinar ini Dhiku akan membawakan materi seputar tips product management, bagaimana proses membangun product digital dengan agile dan data driven. Dimulai dari memahami kebutuhan user, melakukan usability testing, menganalisa data, melakukan prioritas fitur dan perencanaan product roadmap, incremental deployment ke user, sampai evaluasi data untuk pengembangan product yang lebih baik.
Oleh http://www.startupbisnis.com dan http://www.codepolitan.com
Modernizing Architecture for a Complete Data StrategyCloudera, Inc.
Data is the future of business. Either take advantage of it, or get surpassed by those who do.
In this webinar, Ovum's Tony Baer discusses the importance of building a modern data strategy that ensures your journey with Apache Hadoop and big data is a successful one. Together, we'll walk through how to build a plan for long-term success while realizing short-term gains, including:
How to pinpoint the business goals that matter most
How to assess your strengths and weaknesses to meet those goals
How to build a thoughtful approach that ensures your initiatives succeed
Developing a Data Strategy -- A Guide For Business Leadersibi
Data is one of our most valuable assets -- yet we rarely understand how to incorporate it into our business plans. This presentation provides an introduction to data strategy for business leaders and points to more resources.
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
Mozilla Foundation Metrics - presentation to engineersJohn Schneider
@rossbruniges and I talked with our fellow Mozilla Foundation engineers and development teams about getting the data for building a data driven operation using statsd, graphite, geckoboard, google analytics, and newrelic.
Report on A/B title testing of educational videos and materials for small business owners and entrepreneurs. Goal is finding the best way to help the owner start and grow the business.
Anatomy of Search Relevance: From Data To ActionSaïd Radhouani
Relevance denotes how well a search result satisfies the user information need. In addition to the search engine components (i.e., indexer and query parser), there are many other components that impact relevance. e.g., user understanding , data optimization, domain knowledge, etc. Improving relevance remains the main and most challenging goal of each search engine. Indeed, relevance can be subjective, therefore hard to measure and to improve. In this talk, Saïd will demystify the concept of relevance by defining its main components. For each component, he will present the technology enablers, the data, and processes that are required in order to measure and improve relevance. In this talk, attendees will learn how to provide a relevant user experience and track it over time.
Data-Driven Software Testing: The New, Lean Approach to QualityTechWell
The Internet of Things and always connected devices are generating exabytes of user data and device telemetry. Organizations worldwide are leveraging this data for new products and new business insights, but this data is also fundamentally changing how organizations drive, assess, and improve product quality. Testers have traditionally relied on test results, but, with additional data sources now available to testers, the testers’ ability to process these is expanding like never before. Data-driven quality (DDQ) strategies such as Testing in Production (TiP) are essential tools for most testers. But the questions are: How do you implement these strategies to benefit your specific product? How do you convert testers into data scientists? How do A/B testing, continuous delivery, and creating products from service components drive us to a leaner and better approach to quality? Ken Johnston answers these questions and more in this insightful session.
October 2013 - Public legal education (PLE) is increasingly delivered online. This webinar will look at how to leverage a number of free or low-cost online tools (including Google Analytics and iPerceptions surveys) to acquire data to measure your impact and align with your key performance indicators or KPIs.
Other tools that will be discussed include online user testing tools and what metrics matter when it comes social media evaluation.
Intro to Data Analytics with Oscar's Director of ProductProduct School
The Director of Product at Oscar, Vasudev Vadlamudi, went over key types of quantitative analysis that B2C product managers use on the job including: funnels, cohorts, and a/b testing. For each one he looked into when and why they are used, and used examples.
We are a US based cross platform mobile applications development company, emphasizing on the latest mobile apps.
We have extensive expertise in developing highly interactive mobile applications & utility development that are extremely functional. We create value-added mobile apps on various platforms as per your specific needs.
Smarter search drives value to your business. Delivering search that matches users to the right content is what you care about. But organizations often get stuck getting there. It turns out that you need quite a number of very different ingredients to deliver tremendous search. It can make your head spin! To help you think through where your team is on its road to smarter search, Pugh introduces the maturity model used by OpenSource Connections and walks you through a very concrete method to inventory needed skills and translate that into search roles for your team. He shows how to measure your capabilities in key areas of search to drive better ROI from search.
Woj takes you on a journey to demystify the art and science of Search Engine Optimisation. Explore the true facts about SEO, the history of Google and other search engines and what the current landscape looks like.
Arm yourself with valuable tips on production & writing for search engines as well as Woj’s indispensable do-and-don’t best practice guide so you can leave the session ready to take action!
Intuit - How to Scale Your Experimentation ProgramOptimizely
Here’s the playbook Intuit uses to increase its experimentation velocity — even when they face traffic limitations.
Mike Loveridge is not new to running experimentation teams. Before Intuit, he built out programs at Ancestry.com, GE, Humana, and CheapOair. He's an expert at making experimentation work at high velocity, even in traffic-challenged situations.
In this webinar, Mike Loveridge shared his best practices for making CRO work at high velocity, key lessons from scaling multiple teams, and why he's bullish on the future of "test and learn".
Tips for Choosing A New College Planning TechnologyCyndy McDonald
Looking for a new college planning tool? How do you go about comparing different tools? What questions should you be asking? What should you be looking out for? With the news this week about the closure of GuidedPath, many people will be looking for new software solutions. Join Cyndy McDonald and Katie Andersen for a discussion on how to compare software platforms, and what some of the significant differences are in the platforms on the market.
Webinar - SEO for Beginners: Simple Steps for Nonprofits and Libraries - 2016...TechSoup
SEO – search engine optimization – is the practice of improving, and promoting a website in order to increase the number of visitors the site receives from search engines. The majority of traffic to your organization or library website may come from the three major search engines - Google, Yahoo, and Bing.
In this free webinar with Whole Whale, learn some basic SEO tips for beginners to help your organization's site and content rank higher and be found more consistently, helping you grow your reach and supporters.
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Takeaways:
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-- Link-building basics to increase traffic
-- Understanding the on-page and off-page principles of the algorithm
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8. Competitor analysis
• Sitemaps are an amazing resource
• Google - “site:competitor.com“
• OpenSiteExplorer, can be used to find links and any growth
tactics being used
• graph.facebook.com/<app_id> can give you monthly Facebook
actives for FB connected apps
• API’s
11. Pick a single KPI
• Easily understood
• Provides focus and align the team
• Represent the core of the product, and usually isn’t uniques
Mixcloud - Listener minutes / 28 days
AirBnb - Nights stayed / 28 days
Eventbrite - Tickets Booked / 28 days
SendGrid - Mail Sent / 28 days
12. Dashboards
• Distribute information amongst the team
• Make trends observable
• Give the team a solid understanding in
top level metrics
• We’re big fans of graphite and grafana
• Alert on changes
15. User accounting
Site A Site B
Active Users 1000 1000
Born +800 +100
Die -100 0
Sleep -300 -50
Awaken +100 +450
Next Period’s Active Users 1500 1500
26. What facts do we know about our users?
• What information did they give us? name, email, Facebook?
• Do they use mobile web/desktop/iOS/Android?
• Do they have email notifications enabled?
• Which core features have they used and to what degree?
• Which features did they miss?
• What was their last interaction with the service?
• Where did they come from? (Referrer)
• Do they use competitor products?
27.
28. Evaluating potential product features
• Do we have the resources to build it?
• How many users will the feature be relevant to?
• How frequently will they interact with it?
• What is the conversion rate against our primary goal?
35. AB testing
• Continually run AATests
• Requirements
- Fast to implement, a single line of code
- Negligible cost to product performance, including SEO
- Results need to be available to the entire team
• Tools
- Django Experiments (we wrote it)
- A/Bingo (Ruby on Rails)
- Optimizely
- Google Website Optimizer