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Metrics

Transcript: What you measure, changes behavior! The Solution Balance Point The Problem Occupant Gains Multiplicty of Metrics, Tools and Methods Traditional Wisdom Abandoned Fossil Fuels Enable Freedom From Constraints End of Cheap Fossil Fuels & Carbon Emissions Sustainability Demands New Metrics and Analytics Balance Point Solar Gains Rethinking Design Process Evidence Based Design Sustainable Systems Dashboard Database Analytics Data Representation Architecture Solar Gains Climate Metrics IES Simulation Metrics Solar Gains EUI - Energy Use Intensity Performance Metrics Solar Gains Solar Gains Ken Hall A.I.A., CSBA, LEED AP Director of Sustainable Design Systems Design Metrics Evidence Based Design Solar Gains WUI - Water Use Intensity Resource Metrics Solar Gains CUI - Carbon Use Intensity Heat Losses http://www.gensler.com Solar Gains Solar Gains

Metrics

Transcript: Growth Date 1 By Lilit Dallakyan Armenia Startup Academy Business Metrics & Models STOP Lying to Yourself Verify the meaning of words, and you will save the mankind from half of their delusions. We Are All Liars data startups failures Rene Descartes Case Study Airbnb Photography - Growth Within Growth Rules of Rules of Good Matric A Good Matric Is Comparative Understandable Ratio or Rate (usually) Behavior Changing 5 Things to Keep in 5 Things to keep in 1 1. Qualitative VS Quantitative WHY? What? How Much? 2 2. Vanity VS Actionable 8 Vanity Metrics to Watch Out For # hits # visits # unique visitors # followers/friends/likes time on site # emails collected # downloads # people # page views Stickiness DAU/MAU=50% # new visitors Actual engagement Retention (after register) Launch rate } 3 3. Exploratory VS Reporting Things we know don't know we know we don't know we know we don't know facts questions intuition exploration Initially a facebook app: Circle of Friends 10 million users in 1 year BUT Too few actual users 50% longer messages 115% attached pitures 110% deep conversations 60% accept app invites 75% click on notifications 180% click on news feed items 50% more engaged 4 4. Leading VS Lagging 5 5. Correlated VS Cousal Good for predictions 10,000 1,000 100 10 1 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Great for changes Ice-cream sales People drowning FIND the Right Metric for Right Now ONE Matric that Matters The OMTM 4 Reasons Why 1. Answers the most important questions 4 Reasons WHY 3. Forces to draw a line in the sand 4. Focuses the entire company 2. Inspires a culture of experimentation MOZ less KPIs Net Adds Daily SaaS company New Free Trials Yesterday 7-day Net Add Average Pirate Metrics Retention Referral Revenue Activation Acquisition Users find you Users interact with you Users stay with you Users recommend you Users pay you Pirate Metrics Relevant Metrics Acquisition Activation Retention Revenue Referral Traffic, search results, cost of acquisition Enrollments, signups, subscriptions Engagement, time from last visit, churns CLV, conversion rate, shopping cart size Invites sent, viral cycle time, viral coefficient And expect it to change :) Define OMTM for your startup DECIDE What Business You're in 6 Business Models 1 Web-based retailer E-COMMERCE Acquisition mode Hybrid mode Loyalty mode <40% 40%-60% >60% Repurchase Rate <15% 15%-30% >30% 1 Year 90 Days Conversion Rate - % of visitors who buy sth. Useful Metrics Cost of Customer Acquisition - money spent to get smb. to buy sth. Revenue Per Customer - lifetime value of a customer 2 SaaS Software as a Service Churn - % of customers who leave in a given time period Engagement - % of customers who use your product daily Conversion - % of users who become paying customers upgrade to a higer-paying 3 FREE MOBILE APP Active Users - % of users who use the product on a daily or monthly basis: DAU and MAU Time to First Purchase - time after activation it takes users to make a purchase Virality - the average number of users a user invites 4 MEDIA SITE Audience & Churn - # of visitors and their loyality Ad Inventory - # of impressions that can be monetized Content/Ad Balance - max overall performance 5 USER-GENERATED CONTENT Content Creation - % of visitors who interact with the contect in some way (create, rate) Notification Effectiveness - % of users who act when told by push, email, etc. Content Sharng & Virality - the way contetnt is shared and its effect on growth 6 6 TWO-SIDED MARKETPLACES Buyer & Seller Growth - rate at which you're adding new buyers and sellers Inventory Growth - rate at which sellers are adding new listings (consider also completeness) Search Effectiveness - what buyers are searching for, & wather it matches your inventory You can't improve it unless you measure it! Contact me: lilitdallakyan3@gmail.com Thank you!

Metrics

Transcript: There are different ways to measure length, the U.S. Customary System and the Metric System. Metrics are used almost everywhere else in the world. Metric System There are four main units of the metric system. These units are millimeters (mm), centimeters (cm), meters (m), and kilometers (km). Two tools that can be used to measure metric length are... 1. Meter Sticks 2. Metric Rulers A Way To Remember A way to remember about how long each unit is to think of an object about that distance. 1. mm - about the thickness of a dime 1. cm - about the width of your fingernail 1. m - about the height of a desk 1. km - about the distance of 10 football fields. Metric Conversion Metrics are very easy to convert between units, unlike the U.S. system. Since metrics are based on 's all you have to do is convert! Thanks for watching my Prezi! Remembering 0.74 m Length height of a table 1 cm = 10 mm 1 m = 100 cm 1 km = 1,000 m Length is a way to measure distance Different Ways 740 mm 74 cm 0.00074 km 40 cm height of a computer Try It Length 400mm 0.4m 0.0004km Let's try converting units. By ; Kiyan Bhalla

Metrics

Transcript: Research Product PHONE DATA PRIVACY, SECURITY AND AGE Shelley Allen - D16129049 John Smith - C13553167 Kieva McLaughlin - C13752131 Objective 100% H4: Concerns regarding phone data is dependent on age H5: Concerns relating virtual home assistants and data is dependent on age H6: Age influences how much a person is willing to spend on a home assistant H7: Ownership of a virtual home assistant is dependent on age Virtual home assistants Amazon Echo, Google Home, Apple Homepod, and Microsoft Invoke Price Cloud based application H4 1. Listening 2. Camera 3. Drop-in The Sample Data Analysis VHA DATA PRIVACY, SECURITY AND AGE Research Product Objectives Methodology Conclusions and Recommendations Conclusions Research Objectives Recommendations Methodology H2 Hypotheses The Questionnaire Attitudes towards virtual home assistants Privacy Concerns Security Concerns 15 questions Question types 5 minutes Pilot survey Introduction Coding and data analysis SPSS T- test Hypothesis Tests VHA AWARENESS AND COLLEGE EDUCATION AMOUNT WILLING TO SPEND ON VHA AND AGE John, Shelley & Kieva H1 VHA DATA PRIVACY, SECURITY AND GENDER VHA OWNERSHIP AND AGE H7 4. Recording 5. Hacking 6. Advertising H5 Virtual Home Assistants PHONE DATA PRIVACY, SECURITY AND GENDER H1: Concerns relating to phone data security and privacy is dependent on gender H2: Data privacy and security concerns relating to virtual home assistants is dependent on gender H3: Awareness of virtual home assistants is related to college education H3 18-50+ years old General population Social networking sites 62 respondents H6 To determine consumers attitudes towards the use of virtual home assistants Privacy

METRICS

Transcript: GIFT OFFICER METRICS AND ANALYTICS APRIL 2018 Understanding the system Buying into the system Creating a better team Predicting results Improving time management Better portfolio management Forecasting and planning Finding the motivation that works for you Evaluating tactics Closing larger gifts Closing more major gifts WHAT'S THE POINT? BE BETTER FUNDRAISERS BY: THINGS YOU CAN CONTROL THINGS YOU CAN CONTROL MEETINGS SUBSTANTIAL INTERACTIONS OUTREACH EFFORTS HOW DOES THIS HELP? MONTHLY PROGRESS FY ACTIVITY PROJECTIONS OUTREACH EFFECTIVENESS MAKING THE RIGHT KIND OF PROGRESS A CLOSER LOOK TOP 30 TOP 30 DISCOVERY PORTFOLIO MANAGEMENT AND WHERE CAN WE TAKE THIS? (Meetings/Sub. Int. per Accepted Opportunity) x (# of Goal Accepted Opportunities) = Meetings/Sub. Int. GOAL Planning Examples (7.33) x (15) = 110 Meeting GOAL (12) / (27%) = 44 DISCO Meeting GOAL (# of New Prospects to ID ) / (DISCO Positive Conversion Rate ) = DISCO Meeting GOAL (# Closed Opps/Asks ) / (Opp. Acceptance Rate) = # Asks GOALs (15 ) / (49%) = 30 Asks GOAL (# Meetings ) / (Meeting Acceptance Rate) = # Meeting Requests GOALs (110 ) / (37%) = 297 Meeting Requests GOAL (# DISCO Meetings ) / (DISCO Acceptance Rate) = # DISCO Requests GOALs (44 ) / (29.5%) = 149 DISCO Requests GOAL (9.77) x (15) = 147 Sub. Int. GOAL THINGS YOU CAN'T CONTROL OPPORTUNITIES AND ASKS PROGRESS HOW DOES THIS HELP?

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Metrics

Transcript: What's new How we measure LIFR SKUs are segmented according to 2 parameters R3M L2 BIAS STOCK JOURNAL 2.0 L2 BIAS Launch updates Simplify the Complex For Everyone SEGMENTATION 2.0 ROLLING 3 MTHS ERROR (R3M) % or # SKUs OFF TARGET L2 BIAS New scorecard Which is the SKU value of last 12 months of Sales or FC? %/# SKU OFF TARGET (stock journal 2.0, executive summary, FC accuracy) Twice per week VALUE Main improvements L2 BIAS It’s the metric valid to calculate the only official target to measure FC accuracy: Upcoming How it works SKU highlights, root causes, std status, back orders, escalation level, shortage analysis 3 In 1 Report REPORTS Monthly R3M Last update comparison Extedend time horizon information PARAMETERS How we're measured % SKU OFF TARGET METRICS Pre-read analysis DP Global standard for measuring forecast error SEGMENTATION 2.0 WHAT DOES IT CHANGE? METRICS Weekly DP Sharepoint How much is Customer satisfied from a supply perspective? REPORTS Under or Over Forecast? PARAMETERS R3M VOLATILITY Is this SKU easy to FC? YES NO LOW VOLATILITY HIGH VOLATILITY

Metrics

Transcript: Reships & Delays YOY 61% Improvement YOY 90% Improvement Thank you for your attention!