Data is king! Get ready to understand how a successful analytics team can empower managers from product, marketing, and other areas to make effective, data-driven decisions.
Louis Cialdella, a data scientist at ZipRecruiter, shared some case studies and successful strategies that he has used at ZipRecruiter as well as previous experiences. The purpose of this data talk was to enlighten people on how to make sure that analysts can successfully partner with other departments and get them the information they need to do great things.
Ad Monetization Products with SoundCloud's Product ManagerProduct School
JoriBell, Product Manager at SoundCloud, talked about her experiences bringing monetization products to SoundCloud and how to introduce seemingly "questionable" product features to a larger organization. In her talk she focused on soft skills related to stakeholder management and communications as well as hard skills to highlight processes and tools that aid in gaining support from a broader, international company like SoundCloud.
Measure Your Way to Success by Sephora's former Dir. of ProductProduct School
Product management is about creating change. Metrics are the guideposts that help us ensure that the changes we make are leading to the results we want. They let us forecast, provide early warning signals, and create incentives for action.
In this talk Meghan Cochran talked about designing good metrics, gaining alignment among a broad range of stakeholders, and communicating progress effectively. She discussed the trade-offs of looking at rates & ratios vs absolute numbers, and talked about funnels, cohorts, and other fascinating and exciting measures of success.
Why Big and Small Data Is Important by Google's Product ManagerProduct School
In this talk, Dan McClary, a Product Manager at Google, walked through the importance of using data to drive product decisions, as well as how to quickly pull together an architecture using free tools to help grow a product effort from market analysis to live data capture and data-driven product decisions. We also played a rousing game of Breakout.
Intro to Artificial Intelligence w/ Target's Director of PMProduct School
Given that Machine Learning (ML) is on every product enthusiast’s mind, this talk gave a broad view of the investment landscape for future innovation. Director of Product Management at Target, Aarthi Srinivasan, talked about macro AI themes & trends, how you can build your AI team and how to create a ML backed product vision.
Additionally, this talk armed the attendees with enough information to create your Point of View (POV) on how to incorporate AI into your business.
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.
Product in Online Advertising with LinkedIn's Senior Product ManagerProduct School
Linda Leung, Senipr Product Manager at LinkedIn, talked about product management and online advertising. Whether you like ads or not, online advertising is still the lifeblood of the internet. Every consumer internet business at some point asks itself, should we be putting an ad on this page? Linda discussed the basics of online advertising, what a monetization PM focuses on, and what separates the winners from losers in the industry.
How Data Influences Product by Capna Intellectual VP of ProductProduct School
Elay Carmon, former Senior Product Manager at Yelp, told the story of his experiences launching Eat24. He talked about about how no product launch is exactly the same, and that each experience is a lesson to learn from.
He dove into questions and answers that stimulate from Yelp to Eat 24 and how the On Demand food industry is rapidly expanding.
How to Become a Versatile Product Manager by Google's PMProduct School
The pace of change in technology products is accelerating. As you build out your Swiss army knife of Product Manager skills, one key asset is an ability to be able to adapt to different types of products. Large companies look to hire generalist product managers who can navigate across product areas with ease. Some startups pivot from focusing on the consumer to becoming a B2B product. Are you prepared to be the versatile Product Manager that can be effective, no matter what?
In this session, Siddharth Bhai from Google took a look at three types of products, and discussed their distinct needs and strategies to succeed as a Product Manager in each:
Enterprise (Eg. Infrastructure/Deployment/IT)
Consumer (Eg. Apps/Websites)
Business (Eg. Sales/Marketing/Finance)
Ad Monetization Products with SoundCloud's Product ManagerProduct School
JoriBell, Product Manager at SoundCloud, talked about her experiences bringing monetization products to SoundCloud and how to introduce seemingly "questionable" product features to a larger organization. In her talk she focused on soft skills related to stakeholder management and communications as well as hard skills to highlight processes and tools that aid in gaining support from a broader, international company like SoundCloud.
Measure Your Way to Success by Sephora's former Dir. of ProductProduct School
Product management is about creating change. Metrics are the guideposts that help us ensure that the changes we make are leading to the results we want. They let us forecast, provide early warning signals, and create incentives for action.
In this talk Meghan Cochran talked about designing good metrics, gaining alignment among a broad range of stakeholders, and communicating progress effectively. She discussed the trade-offs of looking at rates & ratios vs absolute numbers, and talked about funnels, cohorts, and other fascinating and exciting measures of success.
Why Big and Small Data Is Important by Google's Product ManagerProduct School
In this talk, Dan McClary, a Product Manager at Google, walked through the importance of using data to drive product decisions, as well as how to quickly pull together an architecture using free tools to help grow a product effort from market analysis to live data capture and data-driven product decisions. We also played a rousing game of Breakout.
Intro to Artificial Intelligence w/ Target's Director of PMProduct School
Given that Machine Learning (ML) is on every product enthusiast’s mind, this talk gave a broad view of the investment landscape for future innovation. Director of Product Management at Target, Aarthi Srinivasan, talked about macro AI themes & trends, how you can build your AI team and how to create a ML backed product vision.
Additionally, this talk armed the attendees with enough information to create your Point of View (POV) on how to incorporate AI into your business.
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.
Product in Online Advertising with LinkedIn's Senior Product ManagerProduct School
Linda Leung, Senipr Product Manager at LinkedIn, talked about product management and online advertising. Whether you like ads or not, online advertising is still the lifeblood of the internet. Every consumer internet business at some point asks itself, should we be putting an ad on this page? Linda discussed the basics of online advertising, what a monetization PM focuses on, and what separates the winners from losers in the industry.
How Data Influences Product by Capna Intellectual VP of ProductProduct School
Elay Carmon, former Senior Product Manager at Yelp, told the story of his experiences launching Eat24. He talked about about how no product launch is exactly the same, and that each experience is a lesson to learn from.
He dove into questions and answers that stimulate from Yelp to Eat 24 and how the On Demand food industry is rapidly expanding.
How to Become a Versatile Product Manager by Google's PMProduct School
The pace of change in technology products is accelerating. As you build out your Swiss army knife of Product Manager skills, one key asset is an ability to be able to adapt to different types of products. Large companies look to hire generalist product managers who can navigate across product areas with ease. Some startups pivot from focusing on the consumer to becoming a B2B product. Are you prepared to be the versatile Product Manager that can be effective, no matter what?
In this session, Siddharth Bhai from Google took a look at three types of products, and discussed their distinct needs and strategies to succeed as a Product Manager in each:
Enterprise (Eg. Infrastructure/Deployment/IT)
Consumer (Eg. Apps/Websites)
Business (Eg. Sales/Marketing/Finance)
How to Disrupt Digital Product Cultures by LearnVest VP of ProductProduct School
A big part of product management success is bringing various cultures together from people, process, and innovation. Vivek Bedi from LearnVest hosted the product and technology digital teams from Northwestern Mutual and LearnVest as they discussed over the past two years how they have brought two cultures together to come up with a bold, brave, yet balanced "third" culture.
The new culture is one of taking risks, being ok with failing, and focused on innovation while keeping focus on being at the center of clients' financial lives.
Intro to A/B Testing by Spark Networks former Sr. Product ManagerProduct School
Alex Alwan from Spark Networks talked about how to use A/B testing to figure out the best product and marketing strategies for your business. He discussed how to adopt a culture of testing everything from website copy to engagement emails to Facebook ads, and how to learn through a real SaaS product experiment.
Intro to Data Analytics with EA's Director of ProductProduct School
Building an analytics strategy is crucial for every product manager. How do you build and implement an effective product analytics strategy that quantifies and drives product success and iteration? Director of Product at Electronic Arts, Bertram Chan, talked about how data analytics is no longer a luxury, its a competitive and integral need for Product Managers. He also discussed ways to understand not only who your users are but how they behave.
How Clorox Experiments Across Brands to Turn Visitors into ConsumersOptimizely
As more brands focus on digital marketing and Direct-to-Consumer strategies, experimentation can help them efficiently increase consumer engagement. At Clorox, a data-driven experimentation strategy helps them leverage insights across multiple brands.
Watch the on-demand webinar to learn:
- How Clorox gathers insights from omnichannel experimentation to turn visitors into consumers
- Clorox’s experimentation strategy including how an experiment to remove price friction helped their conversion rate optimization
- The process behind creating “Ways of Working” for experimentation programs across Clorox’s Direct-to-Consumer (DTC) brands
Growth Product Management w/ WeWork's Digital Growth Team PMProduct School
In tech, everyone is always talking about growth - but what does that actually mean and how do you make it happen? The PM for the Digital Growth team at WeWork, Drew Howard, gave an overview of what a growth PM does, what kind of tactics they focus on and how they measure results.
He talked about what some important growth channels to be aware of for any product are, if "growth hacking" is a real thing or a terrible buzzphrase and how you can tell if you're really driving growth for your product.
What Are the Basics of Product Manager Interviews by Google PMProduct School
Ankit walked through an intro to the Product Manager role, the skills needed, and how the role differs between small and large companies. He wrapped up with some advice that's helped him in his Product Manager interviews over the years.
He gave a structured approach to thinking about what a Product Manager actually does (structured, meaning no "top 10" lists) and what are the skills you need to do well as a Product Manager.
Data Driven Growth Hacks with ListenFirst Media's Senior PMProduct School
Ross Sclafani from ListenFirst Media discussed growth hacking, its role in product management and how to use to data drive growth hacking in your organization as Product Manager.
He also talked about what Growth Hacking is and how to interpret Data for Growth Hacking.
Product Management Ethics in A.I. by Yammer's former Dir. of ProductProduct School
From maximizing the crave-ability of food additives to notification addiction, Product Managers have a profound impact on society. In the not too distant future, a number of those Product decisions will be delivered by artificial intelligence. In this talk, we discussed ethical lessons from the history of Product Management and how we can learn from them to build ethical AI.
Former Director of Product at Yammer also talked about how to understand data quality, biases, and potential impacts, and learn what your self-driving car will do when it encounters The Trolley Problem.
Pivotal Tech Talk - Using data to inform product decisions (22.10.14)Marc Abraham
Why is important to use data to inform product decisions? How can you best use data as part of the product lifecycle? This talk about the role that data can play in informing decisions (and answering questions) at different stages of the product lifecycle.
How to Combine Retail and Product Technology by Gilt.com Sr. PMProduct School
It's no surprise that retail is undergoing structural transformations with the onset of e-commerce. What roles could product managers play to support the brick-and-mortar businesses of tomorrow?
Sophia Huang, Senior Product Manager at Gilt.com, talked about the challenges and opportunities operating in a post-merger startup environment, and how technology can draw out the best of the physical and digital worlds.
Zillow + Optimizely: Building the Bridge to $20 Billion RevenueOptimizely
Join Jason Tabert, Senior CRO Marketing Specialist, and learn how Zillow is using Optimizely’s experimentation, personalization and integrations to help grow their revenue to $20 billion by helping their customers cross the real estate chasm from despair to delight.
With Nicole Forsgren, VP of Strategy and Research at GitHub
Now more than ever, technology matters. Long before COVID-19 made remote work the norm, digital products were driving value and disruption for organizations. But delivering software safely remained a debate: For years, we thought slow meant more stable code and releases… even though we kept seeing fire drills and suffering through weeks-long releases.
The best, most innovative organizations have realized that it's possible to release code -- in ways that are safer, more stable, and more reliable while providing insights into what users value and need. Nicole Forsgren, author of "Accelerate" and leading software development and DevOps researcher will share insights on what teams can do to improve their software delivery as well as stories from organizations that have seen the benefits of these practices.
Selling people on the idea that analytics can be a catalyst for creative freedom isn't easy. We have been doing analytics in the "creative" environment of a communications agency for a while and whenever analytics and creative are thrown in the mix together the natural instinct is a right brain, left brain power struggle. Happily, we have found ways for analytics to help partner with the creative teams and the sparks created are usually bigger and richer ideas.
Introduction to Machine Learning with Azure & DatabricksCCG
Join CCG and Microsoft for a hands-on demonstration of Azure’s machine learning capabilities. During the workshop, we will:
- Hold a Machine Learning 101 session to explain what machine learning is and how it fits in the analytics landscape
- Demonstrate Azure Databricks’ capabilities for building custom machine learning models
- Take a tour of the Azure Machine Learning’s capabilities for MLOps, Automated Machine Learning, and code-free Machine Learning
By the end of the workshop, you’ll have the tools you need to begin your own journey to AI.
How to Disrupt Digital Product Cultures by LearnVest VP of ProductProduct School
A big part of product management success is bringing various cultures together from people, process, and innovation. Vivek Bedi from LearnVest hosted the product and technology digital teams from Northwestern Mutual and LearnVest as they discussed over the past two years how they have brought two cultures together to come up with a bold, brave, yet balanced "third" culture.
The new culture is one of taking risks, being ok with failing, and focused on innovation while keeping focus on being at the center of clients' financial lives.
Intro to A/B Testing by Spark Networks former Sr. Product ManagerProduct School
Alex Alwan from Spark Networks talked about how to use A/B testing to figure out the best product and marketing strategies for your business. He discussed how to adopt a culture of testing everything from website copy to engagement emails to Facebook ads, and how to learn through a real SaaS product experiment.
Intro to Data Analytics with EA's Director of ProductProduct School
Building an analytics strategy is crucial for every product manager. How do you build and implement an effective product analytics strategy that quantifies and drives product success and iteration? Director of Product at Electronic Arts, Bertram Chan, talked about how data analytics is no longer a luxury, its a competitive and integral need for Product Managers. He also discussed ways to understand not only who your users are but how they behave.
How Clorox Experiments Across Brands to Turn Visitors into ConsumersOptimizely
As more brands focus on digital marketing and Direct-to-Consumer strategies, experimentation can help them efficiently increase consumer engagement. At Clorox, a data-driven experimentation strategy helps them leverage insights across multiple brands.
Watch the on-demand webinar to learn:
- How Clorox gathers insights from omnichannel experimentation to turn visitors into consumers
- Clorox’s experimentation strategy including how an experiment to remove price friction helped their conversion rate optimization
- The process behind creating “Ways of Working” for experimentation programs across Clorox’s Direct-to-Consumer (DTC) brands
Growth Product Management w/ WeWork's Digital Growth Team PMProduct School
In tech, everyone is always talking about growth - but what does that actually mean and how do you make it happen? The PM for the Digital Growth team at WeWork, Drew Howard, gave an overview of what a growth PM does, what kind of tactics they focus on and how they measure results.
He talked about what some important growth channels to be aware of for any product are, if "growth hacking" is a real thing or a terrible buzzphrase and how you can tell if you're really driving growth for your product.
What Are the Basics of Product Manager Interviews by Google PMProduct School
Ankit walked through an intro to the Product Manager role, the skills needed, and how the role differs between small and large companies. He wrapped up with some advice that's helped him in his Product Manager interviews over the years.
He gave a structured approach to thinking about what a Product Manager actually does (structured, meaning no "top 10" lists) and what are the skills you need to do well as a Product Manager.
Data Driven Growth Hacks with ListenFirst Media's Senior PMProduct School
Ross Sclafani from ListenFirst Media discussed growth hacking, its role in product management and how to use to data drive growth hacking in your organization as Product Manager.
He also talked about what Growth Hacking is and how to interpret Data for Growth Hacking.
Product Management Ethics in A.I. by Yammer's former Dir. of ProductProduct School
From maximizing the crave-ability of food additives to notification addiction, Product Managers have a profound impact on society. In the not too distant future, a number of those Product decisions will be delivered by artificial intelligence. In this talk, we discussed ethical lessons from the history of Product Management and how we can learn from them to build ethical AI.
Former Director of Product at Yammer also talked about how to understand data quality, biases, and potential impacts, and learn what your self-driving car will do when it encounters The Trolley Problem.
Pivotal Tech Talk - Using data to inform product decisions (22.10.14)Marc Abraham
Why is important to use data to inform product decisions? How can you best use data as part of the product lifecycle? This talk about the role that data can play in informing decisions (and answering questions) at different stages of the product lifecycle.
How to Combine Retail and Product Technology by Gilt.com Sr. PMProduct School
It's no surprise that retail is undergoing structural transformations with the onset of e-commerce. What roles could product managers play to support the brick-and-mortar businesses of tomorrow?
Sophia Huang, Senior Product Manager at Gilt.com, talked about the challenges and opportunities operating in a post-merger startup environment, and how technology can draw out the best of the physical and digital worlds.
Zillow + Optimizely: Building the Bridge to $20 Billion RevenueOptimizely
Join Jason Tabert, Senior CRO Marketing Specialist, and learn how Zillow is using Optimizely’s experimentation, personalization and integrations to help grow their revenue to $20 billion by helping their customers cross the real estate chasm from despair to delight.
With Nicole Forsgren, VP of Strategy and Research at GitHub
Now more than ever, technology matters. Long before COVID-19 made remote work the norm, digital products were driving value and disruption for organizations. But delivering software safely remained a debate: For years, we thought slow meant more stable code and releases… even though we kept seeing fire drills and suffering through weeks-long releases.
The best, most innovative organizations have realized that it's possible to release code -- in ways that are safer, more stable, and more reliable while providing insights into what users value and need. Nicole Forsgren, author of "Accelerate" and leading software development and DevOps researcher will share insights on what teams can do to improve their software delivery as well as stories from organizations that have seen the benefits of these practices.
Selling people on the idea that analytics can be a catalyst for creative freedom isn't easy. We have been doing analytics in the "creative" environment of a communications agency for a while and whenever analytics and creative are thrown in the mix together the natural instinct is a right brain, left brain power struggle. Happily, we have found ways for analytics to help partner with the creative teams and the sparks created are usually bigger and richer ideas.
Introduction to Machine Learning with Azure & DatabricksCCG
Join CCG and Microsoft for a hands-on demonstration of Azure’s machine learning capabilities. During the workshop, we will:
- Hold a Machine Learning 101 session to explain what machine learning is and how it fits in the analytics landscape
- Demonstrate Azure Databricks’ capabilities for building custom machine learning models
- Take a tour of the Azure Machine Learning’s capabilities for MLOps, Automated Machine Learning, and code-free Machine Learning
By the end of the workshop, you’ll have the tools you need to begin your own journey to AI.
Brent Summers, Director of Marketing at Digital Telepathy Using Data and Design toDrive Your Business June 25, 2015
Data is All Around You 1
Quantitative Data Sales Reports Data is All Around
Quantitative Data Application Performance Data Data is All Around You Quantitative Data Search Engine Optimization Data is All Around
Quantitative Web Analytics Data is All Around You
Qualitative Data Customer Surveys Data is All Around You Qualitative Data Customer Interviews Data is All Around You Get more info at: goo.gl/Jeol7v
Qualitative Data Personas Data is All Around You Get more info at: goo.gl/UW8mgQ
Observation Heat Mapping & Scroll Mapping Data is All Around You Observation User Behavior Data is All Around You
Data Already 
 Informs Design 2
A/B Testing Optimize for conversions. Data Already Informs Design
Eye Tracking People read in F-Shaped Pa erns Data Already Informs Design
Eye Tracking People look where people look. Data Already Informs Design h
Vertical Rhythm There’s a reason paper is ruled. Data Already Informs Design
Color Psychology What does your brand color say about your business?
The Golden Ratio 1.618 —
Consider the Entire 
 User Journey 3
Identify the Friction Evaluate sentiment/friction at each stage of the user journey. Consider the Entire User Journey
Designing for
 Business Objectives 4
Identify the Friction Where can you make the biggest impact? Designing for Business Objectives
User Journey Consideration
Landing Pages Incremental improvements can drive exponential results.
Be er Social Sharing Social sharing + content performance insights.
Animations Scroll is the new click.
Change Language Try different value proposition, calls to action, etc.
Change Layout Use behavior patterns to drive decisions.
User Journey Conversion: The act of purchasing a product or service through self service or a sales process.
Content Marketing Share knowledge to establish trust. Onboarding Step-by-step walkthroughs for new users.
Get the First Click Break through psychological barriers. User Journey Retention: Post-purchase. Activities that drive further product engagement, adoption and upgrades. Designing for Business Objectives
Reduce cognitive load: hide data until a user requests it.
Simplify your user interface for experienced users
Testimonials “Who doesn’t love social proof?” - Brent Summers
Prioritizing Your Backlog
Keep Track of Experiments Practical Advice Use a formula to assess which experiments to do first.
Sample Experiments Which of these experiments should be implemented Paid conversions
What does the data tell you? Identify where can design make the biggest impact.
Rounding Out the Process Your implementation method is unique. Measure the results. Repeat.
Measuring Success 6
Good Design is Great for Business Design lead firms out-perform the S&P 500 by 228%. Measuring Success
Machine Learning for Business - Eight Best Practices for Getting StartedBhupesh Chaurasia
Though the term machine learning has become very visible in
the popular press over the past few years—making it appear to be the newest shiny object—the technology has actually been
in use for decades. In fact, machine learning algorithms such as decision trees are already in use by many organizations for predictive analytics.
Giving Organisations new capabilities to ask the right business questions 1.7OReillyStrata
This presentation takes the seminal work structured analytic techniques work pioneered within US intelligence, and proposes adaptions and simplifications for use within commercial enterprises
In the fast-changing world of corporate recruiting, it’s important to be aware of and prepared for the problems and opportunities that you will soon face. In short, because it’s “better to be prepared than surprised”, both recruiting and hiring managers must find a way to be “proactive” in planning for these upcoming events, rather than being “reactive”. The most effective way to identify trends and to predict upcoming recruiting issues is through the use of analytics and predictive metrics This advanced webinar will be led by long time ERE.net author and global metrics expert Dr. John Sullivan. He will guide you through the goals, the action steps and the best emerging corporate practices in predictive recruiting metrics.
BA is used to gain insights that inform business decisions and can be used to automate and optimize business processes. Data-driven companies treat their data as a corporate asset and leverage it for a competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business, and an organizational commitment to data-driven decision-making.
Business analytics examples
Business analytics techniques break down into two main areas. The first is basic business intelligence. This involves examining historical data to get a sense of how a business department, team or staff member performed over a particular time. This is a mature practice that most enterprises are fairly accomplished at using.
Machine Learning with Azure and Databricks Virtual WorkshopCCG
Join CCG and Microsoft for a hands-on demonstration of Azure’s machine learning capabilities. During the workshop, we will:
- Hold a Machine Learning 101 session to explain what machine learning is and how it fits in the analytics landscape
- Demonstrate Azure Databricks’ capabilities for building custom machine learning models
- Take a tour of the Azure Machine Learning’s capabilities for MLOps, Automated Machine Learning, and code-free Machine Learning
By the end of the workshop, you’ll have the tools you need to begin your own journey to AI.
The Softer Skills Analysts need to make an impactPaul Laughlin
25 min presentation given at London Business School, to the OR Society's Analytics Network. Summarising Laughlin Consultancy's 9 step model of Softer Skills for Analysts.
Better Living Through Analytics - Louis Cialdella Product SchoolLouis Cialdella
What does a successful partnership between product and analytics teams look like? What can analysts do to ensure a successful partnership with other teams? Some strategies and tips from my work at ZipRecruiter.
Business is running ever faster—generating, collecting and using increas-ing volumes of data about every aspect of the interactions between sup-pliers, manufacturers, retailers and customers. Within these mountains of data are seams of gold—patterns of behavior that can be interpreted, classified and analyzed to allow predictions of real value. Which treat-ment is likely to be most effective for this patient? What can we offer that this particular customer is more likely to buy? Can we identify if that transaction is fraudulent before the sale is closed?
Data Science for Business Managers - An intro to ROI for predictive analyticsAkin Osman Kazakci
This module addresses critical business aspects related to launching a predictive analytics project. How to establish the relationship with business KPIs is discussed. A notion of data hunt, for planning & acquiring external data for better predictions is introduced. Model quality and it's role for ROI of data and prediction tasks are explained. The module is concluded with a glimpse on how collaborative data challenges can improve predictive model quality in no time.
Webinar How PMs Use AI to 10X Their Productivity by Product School EiR.pdfProduct School
Explore AI tools hands-on and smoothly integrate them into your work routine. This practical experience is here to empower you, offering insights into the mindset of successful Product Managers. Learn the skills to become a more effective Product Manager.
Main Takeaways:
Hands-On AI Integration:
Learn practical strategies for integrating AI tools into your workflow effectively.
Mindset Insights for Success:
Gain valuable insights into the mindset of successful Product Managers, unlocking the secrets to their achievements.
Skill Empowerment for Growth:
Acquire essential skills that empower your evolution toward becoming a more effective and impactful Product Manager.
Webinar: Using GenAI for Increasing Productivity in PM by Amazon PM LeaderProduct School
In this webinar, you will learn how AI can take work off your plate, allowing you to focus on deep thinking or critical work. Cut out the drudge work in Product Management and get more out of your day.
Learnings:
Improve workflows that are high frequency - "manual tasks"
Increase the quality of output that has high importance - "brainy tasks"
Put GenAI to work today
Unlocking High-Performance Product Teams by former Meta Global PMMProduct School
Main Takeaways:
- High-Performing Team Dynamics: You’ll gain insights into fostering high-performance teamwork.
- Unveiling Team Personas: You’ll learn about different personas in the team and how to foster these differences.
- Decoding the Team Needs x Productivity Equation: You’ll learn about different team needs and how they correlate with engagement and productivity.
Remote sensing and monitoring are changing the mining industry for the better. These are providing innovative solutions to long-standing challenges. Those related to exploration, extraction, and overall environmental management by mining technology companies Odisha. These technologies make use of satellite imaging, aerial photography and sensors to collect data that might be inaccessible or from hazardous locations. With the use of this technology, mining operations are becoming increasingly efficient. Let us gain more insight into the key aspects associated with remote sensing and monitoring when it comes to mining.
What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
Attending a job Interview for B1 and B2 Englsih learnersErika906060
It is a sample of an interview for a business english class for pre-intermediate and intermediate english students with emphasis on the speking ability.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
Accpac to QuickBooks Conversion Navigating the Transition with Online Account...PaulBryant58
This article provides a comprehensive guide on how to
effectively manage the convert Accpac to QuickBooks , with a particular focus on utilizing online accounting services to streamline the process.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
Explore our most comprehensive guide on lookback analysis at SafePaaS, covering access governance and how it can transform modern ERP audits. Browse now!
Buy Verified PayPal Account | Buy Google 5 Star Reviewsusawebmarket
Buy Verified PayPal Account
Looking to buy verified PayPal accounts? Discover 7 expert tips for safely purchasing a verified PayPal account in 2024. Ensure security and reliability for your transactions.
PayPal Services Features-
🟢 Email Access
🟢 Bank Added
🟢 Card Verified
🟢 Full SSN Provided
🟢 Phone Number Access
🟢 Driving License Copy
🟢 Fasted Delivery
Client Satisfaction is Our First priority. Our services is very appropriate to buy. We assume that the first-rate way to purchase our offerings is to order on the website. If you have any worry in our cooperation usually You can order us on Skype or Telegram.
24/7 Hours Reply/Please Contact
usawebmarketEmail: support@usawebmarket.com
Skype: usawebmarket
Telegram: @usawebmarket
WhatsApp: +1(218) 203-5951
USA WEB MARKET is the Best Verified PayPal, Payoneer, Cash App, Skrill, Neteller, Stripe Account and SEO, SMM Service provider.100%Satisfection granted.100% replacement Granted.
Enterprise Excellence is Inclusive Excellence.pdfKaiNexus
Enterprise excellence and inclusive excellence are closely linked, and real-world challenges have shown that both are essential to the success of any organization. To achieve enterprise excellence, organizations must focus on improving their operations and processes while creating an inclusive environment that engages everyone. In this interactive session, the facilitator will highlight commonly established business practices and how they limit our ability to engage everyone every day. More importantly, though, participants will likely gain increased awareness of what we can do differently to maximize enterprise excellence through deliberate inclusion.
What is Enterprise Excellence?
Enterprise Excellence is a holistic approach that's aimed at achieving world-class performance across all aspects of the organization.
What might I learn?
A way to engage all in creating Inclusive Excellence. Lessons from the US military and their parallels to the story of Harry Potter. How belt systems and CI teams can destroy inclusive practices. How leadership language invites people to the party. There are three things leaders can do to engage everyone every day: maximizing psychological safety to create environments where folks learn, contribute, and challenge the status quo.
Who might benefit? Anyone and everyone leading folks from the shop floor to top floor.
Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.
"𝑩𝑬𝑮𝑼𝑵 𝑾𝑰𝑻𝑯 𝑻𝑱 𝑰𝑺 𝑯𝑨𝑳𝑭 𝑫𝑶𝑵𝑬"
𝐓𝐉 𝐂𝐨𝐦𝐬 (𝐓𝐉 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬) is a professional event agency that includes experts in the event-organizing market in Vietnam, Korea, and ASEAN countries. We provide unlimited types of events from Music concerts, Fan meetings, and Culture festivals to Corporate events, Internal company events, Golf tournaments, MICE events, and Exhibitions.
𝐓𝐉 𝐂𝐨𝐦𝐬 provides unlimited package services including such as Event organizing, Event planning, Event production, Manpower, PR marketing, Design 2D/3D, VIP protocols, Interpreter agency, etc.
Sports events - Golf competitions/billiards competitions/company sports events: dynamic and challenging
⭐ 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐝 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬:
➢ 2024 BAEKHYUN [Lonsdaleite] IN HO CHI MINH
➢ SUPER JUNIOR-L.S.S. THE SHOW : Th3ee Guys in HO CHI MINH
➢FreenBecky 1st Fan Meeting in Vietnam
➢CHILDREN ART EXHIBITION 2024: BEYOND BARRIERS
➢ WOW K-Music Festival 2023
➢ Winner [CROSS] Tour in HCM
➢ Super Show 9 in HCM with Super Junior
➢ HCMC - Gyeongsangbuk-do Culture and Tourism Festival
➢ Korean Vietnam Partnership - Fair with LG
➢ Korean President visits Samsung Electronics R&D Center
➢ Vietnam Food Expo with Lotte Wellfood
"𝐄𝐯𝐞𝐫𝐲 𝐞𝐯𝐞𝐧𝐭 𝐢𝐬 𝐚 𝐬𝐭𝐨𝐫𝐲, 𝐚 𝐬𝐩𝐞𝐜𝐢𝐚𝐥 𝐣𝐨𝐮𝐫𝐧𝐞𝐲. 𝐖𝐞 𝐚𝐥𝐰𝐚𝐲𝐬 𝐛𝐞𝐥𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 𝐬𝐡𝐨𝐫𝐭𝐥𝐲 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐚 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐨𝐮𝐫 𝐬𝐭𝐨𝐫𝐢𝐞𝐬."
5. 5
Today’s topics
About me and ZipRecruiter
What does the analytics team do? What are our projects like?
Strategies for successful partnerships
Some things I wish I knew when I started
7. 7
About Me
Columbia University - Computer Science and Machine Learning
Worked at startups in New York, work on the credit risk analytics system at JP
Morgan
Currently a data scientist on the analytics team at ZipRecruiter
8. 8
ZipRecruiter
Short version: We help people find jobs
Employers post jobs, we help them find qualified candidates
#1 job search app on iPhone!
Located in Santa Monica
We’re hiring! For analytics and product positions - Resumes to
louisc@ziprecruiter.com
9. 9
Some challenges we face at ZipRecruiter
How can we match employers with jobseekers in a way that benefits both?
Who should we market our service to?
How can we improve our user experience?
How can we guard against fraud on our platform?
10. 1
0
What we do and how we do it
Analytics at ZipRecruiter
11. 1
1
The Role of analytics at ZipRecruiter
Help business stakeholders make data driven decisions
Other departments have domain knowledge and problems to solve, we
supply statistical skills
Define metrics
Answer vague business questions with well-defined data analysis
13. 1
3
ZipRecruiter’s Analytics team
Follows the “centralized” model
Independent department which provides data and statistical analysis
Advisory capacity - help other teams understand their data and figure out
which decisions will benefit them the most
14. 1
4
ZipRecruiter’s Analytics team
Follows the “centralized” model
Pros:
Makes it easy to build up institutional knowledge
Can build and share analytics tools
Independent incentive structure
Cons:
Requires skilled analytics-specific leadership
Further from domain experts
My opinion: Given the rapidly changing state of industrial analytics, pros outweigh
cons
16. 1
6
Analytics can help make great products
Product managers have vision, and data analysis can help advise on the best
way to execute it
Two main ways:
Product Optimization:
Example: A/B testing different user experiences
Machine intelligence Integration:
Example: Making recommendations to users, dynamic pricing, fraud
detection
17. 1
7
Successful partnerships
A balancing act:
Product people are incentivized
to do cool things as fast as
they reasonably can
Analytics people incentivized to
be rigorous and careful
Pragmatism vs rigor
Fast vs slow
18. 1
8
Analytics projects
It helps to understand how an analytics project is structured
For a data-driven project to succeed, we need to:
Collect the data
Run experiments, look at historical data, etc
Analyze the data
Build a model, extract insights, etc
19. 1
9
Analytics projects
What insight will
be extracted?
What information
will the model give
us?
What mechanism
collects the data?
Where will it be
stored and
accessed?
What is the
question we want
to answer?
What data will be
used?
What modelling
approach will be
used?
What software will
be used?
Data Collection
Data Analysis
Design Implementation
20. 2
0
Analytics projects
Some anti-patterns:
“Crunch these numbers for me”
Analysts need context
“Do some data stuff with all our historical data”
Analysts benefit from a clear product vision
“We ran this experiment, what does it tell you”
If an analyst did not help design the experiment, the data may not
be useful
22. 2
2
A typical request
ZipRecruiter has a free trial for our employer subscription product
During the free trial, employers post jobs and get applications
If we knew how the number of applications related to the conversion rate, we
could design our experience to improve this
How can we understand the relationship between number of
applications per job and likelihood of conversion?
23. 2
3
A first look
We have historical examples of how many applications/job were received, as
well as whether or not a user converted
We could compare the response counts of the convert/non-convert groups
to describe the data
But this doesn’t allow us to make predictions - what we want is a model!
24. 2
4
Understanding our data
We have a few years of historical data about:
Hundreds of thousands of free trials
How many jobs each one posted, which jobs received applications
Whether or not they converted
Geographic and industry information
Our model will need to relate the features (geo/industry info, number of
applications) to the output (conversion event)
25. 2
5
Error bars
Just specifying the expected value of the conversion rate at each response
count can give a false impression of precision
We want to quantify our uncertainty
Solution: Add confidence intervals to estimates (via bootstrap)
26. 2
6
Analytics projects
Can we produce a
curve defining the
FT conversion vs
response
relationship?
The data used is
collected in our
SQL (Redshift)
database
What is the
relationship
between FT
conversion and
responses?
Use historical data
Model: Logistic
regression
Software: SQL
and Python
Data Collection
Data Analysis
Design Implementation
27. 2
7
The result
The curve which describes the
relationship between application
count and conversion
Can use this to optimize the free trial
give our customers the best
experience (for example, tuning
the length of time the trial lasts)
29. 2
9
Uncertainty is the only certainty
Analytics helps us understand where there is uncertainty, but it usually can’t
be brought to zero
Nate Silver: “[Some forecasters] see uncertainty as the enemy...this tends to
leave us less prepared when a deluge hits.”
Analysts deal with uncertainty by mitigating it where possible, and
communicating it where not possible
Use confidence intervals and similar techniques, which provide best/worst
cases
30. 3
0
Don’t be afraid to experiment
Experiments have become common in the industry (A/B tests)
But there is a cost associated with running them - when should we run them?
Answer - whenever possible!
Product can often get great insight by running an experiment
Analytics can often provide much more definitive results and mitigate
uncertainty as much as possible
31. 3
1
Understand Everyone’s Incentives
Analysts should report revenue/profit/cost impact, dollars and cents
Product folks can help by making it clear what needle you want to move,
even if it’s a big picture metric
Analysts are responsible for translating their findings into a language that a
business user can use for decision making
32. 3
2
Understand the choices, make a recommendation
Try and help people make data driven decisions by understanding the
choices they want to evaluate
Product - present the strategies you are considering
Analytics - focus on making specific recommendations, rather than simply
conveying the results of number crunching
33. 3
3
Focus on the small picture
It’s tempting to totally overhaul a system and replace it with DEEP
LEARNING THE BIG DATA
But big overhauls are risky
At each step in modelling, you may make bad assumptions - rolling out
incremental improvements allows you to check these assumptions
When trying to improve a process, don’t overhaul it from the very beginning -
start with small improvements to the existing method
34. 3
4
Summary
● ZipRecruiter’s centralized analytics team model has a lot of
advantages
● Analytics + Product = 😊
● Uncertainty is part of the process, but we can do a lot to mitigate it
and communicate it clearly
35. 3
5
About my work? About ZipRecruiter? About working in data science?
Q & A
37. Part-time Product Management Courses in
Silicon Valley, New York, Los Angeles, and
Orange County
www.productschool.com
Editor's Notes
When you checked in tonight, you got an email inviting you to join our slack community
In that community, we have 12k product people who have come through different companies like google, facebook, uber
Sharing information about events, job offers from our partner companies, and valuable online content
Please check your email and join - it’s free
Opening remarks:
Good evening
Hope you’re doing well
Name, rank, serial number
Thanks for inviting meEvangelizing for the ZipRecruiter analytics model - the industry is figuring itself outQuestions at the end, pleaseWho is in the audience? Analysts? Product? Marketing or Finance?
Go over the analytics at ziprecruiter - it’s a good model
Talk about how to avoid friction, which can show up even when everyone is acting in good faith
Context is important
Background is more engineering than stats
Experience at a small company was good to learn about poorly-defined problems, experience at JPMC was good to learn about scale
ZipRecruiter is a little of both
Fast growing, founded in 2010
Major player in the employment/recruiting space
Raised millions of dollars in funding
Great place to work!
The experience needs to be good for both employers and jobseekers, but finding good matches is hard, as tinder users know
Analytics support is also needed to determine strategy for marketing and product
We can improve operations by automating fraud detection
Gatekeepers of statistical decisions making
Work with everyone
Know what is and is not feasible
Organizations do analytics differently
Sometimes analysts are “embedded”
Sometimes they are independent advisors which are separated
Early and mid-stage companies are still often figuring this out! The structure can change too
Up next:
How can analytics and product work together? Avoid friction?
Data scientist, not a tech talk, one equation
How can analytics help? What does a successful partnership look like?
Analysis can reveal what the best product decisions are from multiple alternatives
Automating analysis can lead to efficiency gains and product improvements
It’s not a consulting gig, it’s a partnership! Both teams should trust and support each otherThis is related to incentives:
For product, the key is a successful, on-time, on-budget shipment of something that people like. A project manager can afford to be wrong and iterate quickly.
For analytics, the key is applying the right techniques to reliably get correct answers. An analyst would rather be slow but cautiously correct
For the partnership to be successful, both sides need to respect the goals of the other!
If we have a roadmap for the project, we can figure out who needs to be involved at each step
Not having a clear division of responsibility leads to confusion and stepping on toes
Analysts care about all of these, product only needs to care about the left side of the line.
If we have a roadmap for the project, we can figure out who needs to be involved at each step
This is a parable about partnership
This demonstrates, I think, the success of our model
The conversion rate at N responses is not exactly 30.4532324234234%
Remember: Analysts care about all of these, product only needs to care about the left side of the line.
Product needs to help us understand:
What data we can use
What the specific problem is
What the metric they want to move is
If the proposed model (curve) would be useful
Tribal knowledge of the organization
There are no known best practices - but I think these are pretty good
Each of these has two sides - what product can do, and what analytics can do
Story: Case study about - avoid presenting estimates as iron-clad facts
Your users need to understand the best case and the worst case in your forecasts
A/B tests are part of the industrial practice
In my experience, they are worth the investment
ZipRecruiter - system for launching, tracking, analyzing A/B tests has paid off a lot
New analysts often tend to give detailed technical reports - that goes in the appendix
No one cares about your damned P-values
This goes hand-in-hand with the last one - it’s about supporting decision making, not doing statistics for its own sake
Story: Scammer detection - initial improvement leading to bigger wins - easier to manage than a full overhaul involving so many people