Agenda [1/2]Recap
Analytics frameworks
Startup stages
Empathy
Stickiness
Virality
Revenue
Scale
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Agenda [2/2]
Start the development of proposed work
Analysis of a commercial game regarding:
Balancing + Monitoring
http://www.di.ubi.pt/~palmeida/Balanceamento_Jogos_15_16/Balanceamento_Jogos_15_16.htm
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RecapFundamentals: Lean Startups (Strategic) + Agile (Operational)
Business Model: Intro + Canvas
Intro to Digital Product Metrics
Types (Quali vs. Quanti, Vanity vs. Actionable, etc.)
Analysis techniques (A/B Testing, Segmentation, etc.)
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Analytics frameworks
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IntroThere’s a myriad of factors that define which metrics to watch, but we mostly it relies on:
Business model type
Startup stage
Some authors defines a set of categories to organize this task
Frameworks
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Analytics frameworksHelp understand startups functioning in terms of:
Lifecycle
Grow
Find market
Costumer acquisition
Revenue streams
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Pirate Metrics - AARRR
Created by Dave McClure, startup investor and founder of business accelerator 500 startups
Its name comes from a acronym for Acquisition, Activation, Retention, Revenue and Referral (AARRR)
A user generates value not only from revenue, but also from referral and content creation
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Pirate Metrics - AARRR
Lean Analytics (Croll & Yoskovitz, 2013)9
Dave McClure - Pirate Metrics
http://developers.magmic.com/metrics-track-mobile-game/10
Engines of growthCreated by Eric Ries, author of Lean Startup
Startup growth comes from the works of 3 engines:
Sticky
Virality
Paid
Each is associated with specific KPIs (key process indicator)
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Engines of growthSticky engine: focused in user engagement
Returning active users
Key metrics: costumer retention, churn rates and usage frequency
Secondary metrics: time since last visit, click-through rate (email, notifications)
Examples: Game notifications, email reminder, Ads, etc.
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Engines of growthVirality engine: focused in user virality
Users bringing other users
Key metrics: viral coefficient
Secondary metrics: Viral cycle time, number of connected accounts, number of invitations, number of answered invitation
Examples: Facebook Connect, invite users to speed progression (Farm Ville), etc.
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Engines of growthPaid engine: focused in user monetization
Key metrics: Costumer lifetime value / costumer acquisition cost
Caution: focusing on receiving money before sustainability (stickiness and virality) is dangerous
Examples: number of subscriptions, inventory availability, etc.
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Lean Canvas
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Lean CanvasLean Canvas was created by Ash Maurya (detailed last class)
It can be interpreted as a current snapshot of your game / product
Hypothesis and Results
Its lightness should be used to provide dynamism to strategic decisions
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Lean Canvas
Video: https://vimeo.com/39687297 Lean Analytics (Croll & Yoskovitz, 2013)17
Startup stages
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Startup stagesIt is usually hard to have a specific "hard number” metric telling which stage a startup is at or should be do next
Lean Analytics authors created a five stage gate model to help that out
Empathy; Stickiness; Virality; Revenue and Scale
Draws some aspects of models presented previously and puts emphasis on metrics for transitioning
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EmpathyIt is the time to get into your user’s head
Discover and validate a problem/idea/need
Qualitative data is key in this stage
Observe patterns that emerge
Methodology is extremely important
Tools, methods => Collect, analyse and report data
Avoid bias and unwanted effects
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EmpathyDecouple problem from solution:
Painful enough?
Enough people care?
Are they trying to solve it themselves?
What it takes to make them aware of the problem?
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EmpathyPrepare for interviews
Face to face
Neutral location
Have a script (Ash Maurya’s Running Lean)
Set the stage: put the interviewee in the right frame of mind
Segment: collect demographics
Problem context: tell the story
Test the problem: rank problems and others that might come up with
Test the solution: how do they solve it today
Ask for something: schedule a solution interview and refer other people
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Empathy
Choose an approach
Convergent: some specific problems to be ranked
Divergent: diving into a more broad problem space
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Empathy
How do I know if I have found the right problem?
The metric here is Pain (or Fun)
Ideally, results from your interview should be scored
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Empathy
Did the interviewee ranked the problems presented?26
Empathy
Is the interviewee actively trying to solve the problems (or already did so)?27
Empathy
Was the interviewee engaged and focused throughout the interview?28
Empathy
Did she agree on a follow with you (possibly with a solution)?29
Empathy
Did she refer other people for you to interview?30
Empathy
Did she offer to pay you for the solution?31
EmpathyAt TechStars, LikeBright founders were asked to talk to 100 women to understand better their “problem"
Frustrations on dating
Report
Used Mechanical Turk from Amazon and Google Voice
$2 per interview and got 100 responses in 4 hours
This gave a better understanding and insights of their problem and had the company accepted
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Empathy - SummaryGoal: identify a need that people want to pay at scale.
Conduct qualitative, exploratory discussions early on
Finding the right questions, scale to more quantitative surveys, reach more people
Use existing tools to collect data and simulate your solution
Balsamiq, Google Docs, Twitter, Linkedin, etc.
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Empathy - Moving to next stage
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StickinessOnce the problem is known and realistic, start build something
Iterate your MVP: methodical work
Improve core metrics
Avoid premature scaling
The goal at this stage is retention.
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StickinessPrioritise features according to the following:
Develop estimates on why things will be better with that feature
Measure the impacts (metrics), avoid scope creep
Estimate time to develop vs. expected results
Usability: avoid complexity
Anticipate risks: technical and user response
Level of innovation: it is allowed to bake big bets on this stage
User voice: listen (carefully), take deeper look to their actions.
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StickinessPrioritise features according to the following:
Develop estimates on why things will be better with that feature
Measure the impacts (metrics), avoid scope creep
Estimate time to develop vs. expected results
Usability: avoid complexity
Anticipate risks: technical and user response
Level of innovation: it is allowed to bake big bets on this stage
User voice: listen (carefully), take deeper look to their actions.Problem-solution canvas: weekly reality-check tool
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Stickiness
Problem-solution canvas: weekly reality-check tool38
StickinessSimple tool for conducting focused surveys for a small group
First iteration of the product required that respondents first signed-up and then answered the questions
Problem: low response rate: 10-25%
Test: What if the user is already considered signed up if they answer a question?
They prioritised this feature (based on email) instead of building a mobile version
Stickiness
10-25% 70-90%
Stickiness - Moving to next stage
Are people using the product as expected?
What is an active user?
What is current percentage? Can this be higher?
Evaluate product roadmap against presented criteria
Evaluate user complaints
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ViralityStands for the phase that users shares your product with other users
There are three types
Inherent: function of use
GDocs: share documents
Artificial: stimulated through reward
Dropbox: Space Race
Word-of-mouth: natural, happens from users exchange of experience
Blog post, Influentials, Spontaneous media, etc.
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Virality
Most important metric: Viral coefficient
It is obtained by combining (multiplying):
Invitation rate: number of invites sent / number of users
Acceptance rate: number of signups / number of invites
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Virality
Second most important metric: Viral cycle time
Time taken for a user to invite another one
It can make a huge difference when combined with viral coefficient
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ViralityLeading indicator
Social engagement (links to friends)
Content creation (post, share, likes)
Return frequency (days since last visit, time on site, etc.)
Tied to part of a business model (revenue, daily traffic, etc.)
Come early on user lifecycle: increase data points
Early extrapolation = Sooner prediction
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Virality
Circle of Moms
"Being a mom" was a leading indicator of engagement.
Facebook / Linkedin
Friends suggestion / invitation early in user lifecycle leads to higher spreadability
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ViralityTimehop is a startup focused on recalling/reposting previous posts from social networks.
They already had an extremely engaged audience: 40-50% emails open rate
It was needed to go viral
Through pixel tracking on emails: 50% of emails were on iOS
As email is no inherently sharable, led them to develop an iOS version of their app
Virality - Moving to next stage
Which types of virality are you employing?
What is your viral coefficient? Is it enough to sustain business growth?
What is viral cycle time? Can it be speed up?
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RevenueThis stage is focused in making money
After showing you are solving a real problem and the solution is sticky and viral
Charging up-front ≠ Focusing on revenue and margins
Most startups spend sometime until being self-sustainable
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RevenueRevenue per costumer is a better metric than raw revenue
Clearer perspective and actionable
Other important metrics:
Ad revenue
Conversion rate
Shopping cart size
Subscription
Costumer lifetime value
Costumer acquisition cost
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RevenueGoal: “more stuff to more people for more money more often more efficiently”
Focus on your strength:
Selling physical, per-transaction cost: focus on more efficiently
High viral: more people for every dollar
Loyal costumer: buy more often
One-time big ticket: more money for each purchase
Recurring: more stuff through higher-capacity packages
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RevenueCostumer lifetime value > Costumer acquisition cost
Oversimplified math: delay between acquiring and paying costumers
Balance between:
Investment
Amount spent on costumer acquisition each month
Revenue brought from each user per month
Churn rate
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RevenuePivoting
Changing part of a product and its business model in order to fit a new market.
If business model is not working: avoid the urge to build more features
It might be easier to change a market (target users) than a product
But it is difficult anyway53
Revenueparse.ly is focused on giving some tools for publishers in order to track their metrics
Their first product was a reader for end user
An extremely engaging product and earned really good media attention
All the metrics were fine, except one, revenue.
"They love, but they don’t pay.”
They built an entirely new product, using part of the knowledge and architecture from the past
This new offering uses a trial mode (one month)
Revenue - Moving to next stage
Breakeven on variable costs:
Costumer revenue > costumer acquisition + delivering service
Time to costumer breakeven
Investment made by the company until a user pays itself
EBITDA Breakeven
Ignores large investments and previous debts
Hibernation Breakeven
No new marketing is spent, only minimum
Lights on, servicing existing costumers, word of mouth, no new features
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Scale
Represents a stage for wider audience, new market entrance
A product/service can stand on its own
High order metrics come into play
Channels, regions and marketing campaigns
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ScaleRepresents a stage for wider audience, new market entrance
A product/service can stand on its own
High order metrics come into play
Channels, regions and marketing campaigns
Compensation, API traffic, channel relationship and competitors
Efficiency vs. Differentiation: reduce cost vs. increase margins
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Scale
Strategy, tactics and implementation must be aligned regarding their goals
It might be harder to innovate at this stage
“Big company” feelings
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