Monetization + Pricing

Question 1

What Makes Monetization Hard?

Answer 1

1. Sacred Cows, Monetization decisions should not be touched
2. Fear, Consumer sensitivity to changes
3. Ripple Effects, Monetization is more sensitive than other Growth decisions
4. Stakeholders, Monetization decisions have many stakeholders
5. Massive Lift, Monetization decisions require massive infrastructure lift.

Question 2

Monetization Mistakes & Principles

Answer 2

1. Mistake: Make monetization decisions with only the business view, it is about value (customers) & price (business). Principle: Align monetization strategy with consumers’ perception of value
2. Mistake: Treat monetization as a silo from growth, Monetization is not just the output of growth, but also input Principle: Evaluate the impact of monetization on all elements of growth
3. Mistake: Consider all revenue as good revenue Principle: Account for the cost to acquire and retain revenue
4. Mistake: Look at monetization as just a price Principle: Understand what we charge for, when we charge, the price, and how price scales
5. Mistake: Set-and-forget monetization strategy Principle: Evolve monetization strategy with changing consumers, product and environment
6. Mistake: Use monetization as a short-term growth lever Principle: consider long-term implications of monetization levers

Question 3

Business Hypothesis

Answer 3

1. Use Case
   1.1 Problem, What is the problem we are solving?
   1.2 Persona, Who are we solving that problem for?
   1.3 Alternatives, What are their alternatives to solving that problem?
   1.4 Why, Why do they choose our product over those alternatives? From motivation and differentiation angle
   1.5 Frequency, How often do they have the problem?
2. Monetization Model
   2.1 Scale, how does this price scale with our value metric?
   2.2 What, what features or attributes do customers get from each use case?
   2.3 Amount, For each use case, how much do we charge for the what? We think about this on an average annual revenue per “customer” per use case. Customer is different from user
   2.4 When, For each use case, when do we charge for the what? (Never, Per Transaction, monthly, yearly or every few years)

Question 4

Monetization Triad

Answer 4

Around the Business Hypothesis, we want to consider the consumer view

So we have
1. Consumer view
2. Growth loops
3. Cost of revenue

Our monetization triad changes over time, creating gaps between it and the business hypothesis

We use model strategies to evolve our monetization model, by changing underlying parts of our use case or monetization model.

We can also improve monetization by optimizing, called optimization strategies.

Question 5

Value Metrics

Answer 5

1. Feature Differentiated
2. Usage Value Metric,e.g. Zoom
3. Outcome Value Metric. Thumbtack, per lead

Continuous vs Banded
1. Continuous, per every X (user, editor, minute, mile etc)
2. Between X and Y (users, minutes and subscribers)

Question 6

Model Friction

Answer 6

The elements of our monetization model create friction in our user’s decision to convert, engage, and retain a user case.

2 questions we want to answer
1. How much friction does my monetization model create?
2. Where in my growth model does my monetization model place that friction?

Question 7

Monetization Friction Spectrum

Answer 7

Low Friction <-> High Friction
Scale: Value metrics are easy to measure and predict vs hard to measure and predict. Generically speaking it’s easier to understand outcome-based value metrics over usage-based value metrics.
What: Feature&Attributes Familiar vs Unfamiliar
Amount: Low AARPC vs High AARPC
When: Never(free) vs Transactional and Monthly Recurring vs Annual Recurring vs Multi-Year Upfront

Question 8

Measuring Monetization Output

Answer 8

1. Understand Monetization Outputs, How do I measure the output of my monetization strategy?
2. Analyze High-Level Revenue, How much revenue is our model creating? How much revenue is each of my use cases contributing?
3. Break Renevue Down Into Revenue Equation, What are the key variables of our revenue equation? What are the variables by use case?
4. Analyze New vs Repeat Revenue, How much new and repeat revenue is our model creating? Where is my new and repeat revenue coming from? How quickly are we converting people into new revenue? What is happening to repeat revenue underneath the hood? Is it expanding or contracting?

Question 9

Understanding Revenue Types

Answer 9

1. Bookings, Revenue that a customer has committed to give you
2. Revenue, What we earn in exchange for services provided in a given time period. This is what we mostly care about when we talk about monetization.
3. GMV (Gross Merchandise Value), Total value of transactions that happen through transaction platforms

Question 10

Profitability Metrics

Answer 10

1. Margins, Total revenue - Cost to serve
2. Net Contribution Margins, Total revenue - Cost to serve - cost to acquire
3. Unit Economics, Focusing on a single unit of product, or customer. Uber= Per trip, Figma = Per customer

Question 11

Revenue vs Profitability

Answer 11

Revenue: Critical to building a large company. Most tech companies in the early days are expected to maintain 100% year over year growth, and as they get large, towards the $100 million per year mark, 50% year over year growth.
Profitability: Long-term sustainability

Things to consider when do trade-off between these two
1. Cost to serve, when companies have cost to serve, and relatively low margins, profitability becomes more important
2. Capital Strategy, companies that can raise money at a low cost are more likely to de-prioritize margins and free cash flows in favor of growth.
3. Growth Loops, When companies have a long-term strategy of building Defensibility loops through network effects, scale or brand they deprioritize margins and focus on Growth until they build the needed scale.

Question 12

Analyzing Revenue

Answer 12

1. Choose a Frequency, How often do we want to look at revenue? Daily, Weekly or Monthly?
   1.1 What questions do we want to answer?
   1.2 Who is the consumer of this analysis?
2. Visualize Over time, when comparing, if it is impacted by seasonality, compare the same month not the prior month.
   2.1 How is revenue trending over time?
   2.2 What is our revenue growth rate on a percentage basis?
3. Segment by Use Case, e.g. product usage, category or location

Question 13

Revenue Equation

Answer 13

Revenue = Breadth (Number of paying customers) * Depth ( Total revenue per customer)

Examples
Figma: Revenue = # of Customers * Editors/Customer * Revenue/Editor
Thumbtack: Revenue = # of Pros * # of Leads/Pro * Revenue/Lead
Revenue = # of Customers * # of Projects/Customer * # of Pros Matched/Project * Revenue/Pro Matched

Questions
1. Is our total customer base increasing/decreasing?
2. is the revenue we are getting from each customer increasing/decreasing?
3. If we have multiple dimensions of depth, which dimension is increasing/decreasing?

Question 14

New vs Repeat Revenue

Answer 14

New Revenue: Revenue from Customers that transacted in this time period but have not transacted in a previous time period.
Repeat Revenue: Revenue from Customers that transacted in this time period and have transacted in a previous time period.

Why do we care?
1. Balance, is key to understanding the health of our product
2. Model Strategies, different strategies will impact new vs repeat differently
3. Optimization Strategies, different strategies align differently to new vs repeat

Question 15

New Revenue Creation Cohort - Build Cohorts

Answer 15

Build Cohorts
1. Who, who is in the population of our cohorts? Define the starting point of the User Journey, the activation stage.
2. Time Period, How often do we want to look at the cohorts?
3. Revenue vs Customers, Cumulative vs Non-cumulative. Percentage view. Average Revenue Per Account (ARP[X]) helps us normalize the revenue cohorts as the size of the cohorts change, X = lead, user, etc

Question 16

New Revenue Creation Cohort - Analyze

Answer 16

1. High Level, What are my key metrics, like Time Based Conversion, Time Based ARP[X]?
2. Individual Cohorts, How is new revenue creation trending over time?
3. Segmentation, Are there segments that are performing much better or worse than others?

Question 17

Repeat Revenue Cohort - Build Cohort

Answer 17

The worse your revenue retention, the more new revenue you need to acquire to maintain growth. Leaky bucket concept.

CAC is always going up

Helps us understand how we are retaining dollars over time once we convert someone into a paying customer

1. Who, Who do we include at the start of the cohort? When the first time converting to a paid customer
2. New Revenue, How much new revenue did the cohort of users start with?
3. Time Frequency, What time frequency do we want to look at for the cohorts?
4. Non-Cumulative Revenue, How much revenue is the cohort generating in each time period? % view

Question 18

Repeat Revenue Cohort - Analyze Cohorts

Answer 18

Break down revenue retention cohorts to understand key metrics like net revenue retention

1. High level, is my revenue retention healthy or unhealthy?
   1.1 Time-based Net Revenue Retention
   1.1.1 Influencing Factors
   1.1.1.1 Acquisition Motion, Is your strategy to capture smaller value up front, and expand over time? Or is it to capture more value upfront, and maintain that amount over time?
   1.1.1.2 Company Stage, What stage is your company? What is your forward-looking strategy?
   1.1.1.3 Market Turnover, Does your market have a lot of natural market turnover?
   1.2 Time-based Customer Retention
   1.3 Time-based ARPC
2. Individual Cohorts, how is revenue retention trending over time?
3. Segmentation, Are there segments that are performing better or worse than others?

Question 19

Repeat Revenue Cohort - Define & Analyze States

Answer 19

How repeat revenue can move in a number of different directions, and how that impacts your total repeat revenue

Different States
1. Existing, Dollars transacted in the last time period
2. Expansion, The increase in dollars that customers spent from the previous time period.
3. Contraction, The decrease in dollars that customers spent from the previous time period.
4. Churn
5. Resurrection

4 Steps to Define and Analyze
1. Define Repeat Revenue States
2. High-Level Analysis
2.1 Growth Accounting Bar Chart
2.2 Growth Accounting Line Chart
3. Individual Cohorts
3.1 We can also compare different revenue states from different cohort charts against each other
4. Segmentations

Question 20

Cost of Revenue

Answer 20

1. Acquisition Costs, Increase with number of customers we acquire, but doesn’t scale with revenue from each customer
2. Costs to Serve, Scale with revenue or variables of the revenue equation
3. Fixed Costs, Decrease as you grow but also don’t grow with revenue or the variables of the revenue equation

Question 21

Cost to Serve

Answer 21

Cost Categories
1. Physical Product
2. Logistics
3. Product Dev, & Maintenance
4. Storage & Hosting
5. Customer Support
6. Program & Tooling
7. Partnerships & Integrations

Ways Costs Can Scale
1. Variable, Costs scale in a linear fashion with revenue
2. Semi-Variable, Costs scale non-linearly with revenue but grow as revenue grows
3. Non-Variable, Some costs don’t scale with revenue

Margins = Revenue - Cost to Serve
Margin Percentage = Dollar Margin / Revenue

How are our margins trending over time?
How are margins trending by use cases?

Question 22

Cost to Acquire

Answer 22

Categories of Acquisition Costs
1. Ad Costs
2. Referral Cost
3. People Cost
4. Tooling & Program Cost
5. Misc. Marketing Cost

Net Contribution Margin = Margin - Cost to Acquire

Payback Period
The time our NCM is positive is the payback period

Analyze Payback Period
Health or unhealth?
By cohorts?
By segments

Question 23

Changes to our Monetization Triad

Answer 23

1. Product, Products introduce new features, improve their user experience etc.
2. Market, Competitive landscape changes, market needs evolve
3. Audience, Products expand target audience, enter new geographies etc.
4. Business, Underlying technology evolves, legal and policy changes affect businesses

Question 24

Value Metrics - Survey Methodologies

Answer 24

Ranking Surveys
Pros: Easiest to create and implement
Cons: Difficult to interpret the results and take action
Max-Diff Surveys
Pros: Provides a stronger signal of what users value and don’t value
Cons: Incomplete picture of how users evaluate different options - only understand the best/worst
Conjoint Analysis
Pros: Survey simulates actual behavior so the results are most actionable
Cons: The setup and analysis required are more resource-heavy than other methodologies

Question 25

Value Metric Analysis

Answer 25

1. Define the Scope
   1.1 What creates value for consumers? Look at the Why in our use case map
   1.2 What metrics measure value? Generate proxies for the why
2. Survey Audience
   2.1 Build your Max-Diff Survey
   2.1.1 We typically also want to add a calibration question. This helps us get a sense of how much of the value metric our respondent might consume. E.g. How many leads do you typically get each month?
   2.1.2 (# of times attribute was chosen most - # of times attribute was chosen least) / # of times attribute appear in the set

3 Analyze Results
3.1 Calculate Relative Preference Score
3.2 Analyze Score
3.3 Segment Results
3.3.1 Use Case, What attributes are our use cases created and differentiated on?
3.3.2 Demographics or Firmographics. What are our consumers’ ages, genders or household incomes? What is their company’s size, industry, status?
3.3.3 Geography. Where in the country or world do our consumers live?

Question 26

Willingness to Pay - Survey Methodologies

Answer 26

Van Westendorp
Pros: Anybody can do it even without a lot of customers or users
Cons: All based on survey results versus the actual behavior of the target audience

Conjoint
Pros: Simulates the actual behavior
Cons: Incomplete picture of how users evaluate different options - only understand the best/worst

Live Testing
Pros: Simulates the actual behavior
Cons: Need a significant amount of volume and sophisticated infrastructure to handle and resolve different types of conflicts

Question 27

Analyzing Willingness to Pay

Answer 27

Van Westendorp
At what (monthly) price point does [product] become …
1. Build Survey
1.1 Describe the product
1.2 Define the what (maybe value metrics)
1.3 Willingness to pay question
1.3.1 too expensive that you would never consider purchasing it? [Too Expensive]
1.3.2 starting to become expensive, but you would still consider purchasing it? [Not a Bargain]
1.3.3 a really good deal? [Not Expensive]
1.3.4 too cheap that you question the quality of it? [Too Cheap]

2. Analyze Result
   2.1 Visualize results, what percentage of users think this is [too expensive] at each price point on the X axis? This is a cumulative chart.
   2.2 Analyze overall
   Lower Bound = intersect between Not a Bargain and Too Cheap
   Upper Bound = Too Expensive and Not Expensive
   Optimal Price Point = Not Expensive and Not a Bargain
   2.3 Segmentation

Question 28

Understanding the Consumer View

Answer 28

Scale
Business Hypothesis: How does price scale?
Consumer View: How does value scale for them?
What
Business Hypothesis: What do we charge for?
Consumer View: What features and benefits do they value?
Amount
Business Hypothesis: How much do we charge?
Consumer View: How much are they willing to pay?
When
Business Hypothesis: When do we charge?
Consumer View: When do they want to pay?

Question 29

Model Strategies - Changing Existing Use Cases

Answer 29

1. Value metric strategies, changing how price scales
2. Packaging Strategies, Changing what we charge for
3. Pricing Strategies, Changes in price
4. When Strategies, Changing when we charge

Question 30

Model Strategies - Changing New Use Cases

Answer 30

1. Vertically, Offering the new use case as an additional choice, another price tier for example
2. Horizontally, Introduce a new use case as an add-on for all use cases

Question 31

When Do We Need to Change Existing Use Cases?

Answer 31

1. Consumer view for use case not aligned with business hypothesis
2. Growth loops for use case not enabled by business hypothesis
3. Cost of serving use case not balanced with revenue from use case

Question 32

When Do We Need to Add New Use Cases?

Answer 32

1. Some segments have a different view than the business hypothesis
2. Growth loops for some segments not enabled by business hypothesis
3. The cost of serving some segments is higher than revenue from the business hypothesis
4. Expand the target audience and serve some new personas and problems

Question 33

Value Metric Strategies

Answer 33

Involves changing how our pricing scales:
1. Change from feature differentiated to a value metric (usage or outcome)
1.1 Drives expansion, Products with value metrics can drive expansion more organically than feature differentiated products.
1.2 Minimizes churn, Companies with value metric pricing have lower churn than feature differentiated pricing.
1.3 Value of features is declining, Most competing products in an industry offer similar features, making it harder to differentiate based on just features
1.4 Comfort with lower predictability, since it aligns with their outputs, they are willing to factor in the cost variability.

2. Change our value metric
3. Add more value metrics

Question 34

Value Metric Options

Answer 34

1. Outcome vs Usage, sometimes use usage as a proxy for the outcome. Look at the why in our use case map
2. Continuous vs Banded
3. Single vs Multiple

Question 35

Defining Value Metric Strategy

Answer 35

There are two things we want to understand to set the right value metric.
1. How does value scale for them? (value metric Max-Diff Survey)
1.1 Ideally, the more value a user gets, the more they pay
2. How much are they willing to pay? (Van Wetendorp)

The key question is Does willingness to pay scale with the value metric?
Check Scaling Our Value Metric below

Question 36

Scaling Our Value Metric

Answer 36

1. Calculate Scaled Willingness to Pay
   1.1 Willingness to pay = avg(Not a bargain + Not expensive) from responses Van Westendorp
   1.2 Scaled Willingness to Pay = Willingness to pay * the number of the value metric. E.g. # Landing pages/month * Willingness to pay/page/month
2. Visualize on a Graph
3. Analyze Results
4. Segment Results

Question 37

Packaging Strategies

Answer 37

Involves changing what we charge for in a given use case, whether that is a single feature or combining multiple features into a package

When to use packaging strategies
1. Align with features consumers value, When there are gaps between what features consumers value and what we offer
2. New Feature Development, When we need to understand the right user case and price point to place new features

Packaging Strategies Scenarios
1. Add features to a use case (with or without changing price)
2. Move features between use cases (with or without changing price & Move up or down)

Question 38

Defining Packaging Strategy - Feature Value Analysis

Answer 38

Define the scope
1. What value propositions or benefits do users value?
2. What product features or attributes do users value?
Survey Audience
Build your Max-Diff Survey
Analyze Results
1. Calculate Relative Preference Score
2. Analyze Score
3. Segment

Question 39

Defining Packaging Strategy

Answer 39

1. Setup Matrix
2. Analyze Matrix
   2.1 Don’t overfit this analysis to use cases. Jamming features into the perfect tier can add friction to the decision making process
   2.2 Segment results to avoid underfitting analysis. only looking at the overall results without segmenting will give you an approximate picture.
3. Segment Results

Question 40

Defining Packaging Strategy - Packaging Strategy Matrix

Answer 40

X axis is Relative Preference Score
Y axis is Willingness to Pay
Both from -1 to 1

For the willingness to pay, use the following to steps to convert it to -1 and 1 range
1. Calculate Median WTP
2. For each feature, calculate the absolute deviation
3. The absolute deviation / Median WTP = % deviation

Then plot them into the matrix, we have 4 quadrants
1. Low Value Low Willingness to Pay (Not Valued by Use Case)
1.1 What purpose does this feature serve? Important for setup or activation? Business values it but customers don’t?
2. High Value Low Willingness to Pay (Table Stakes for Use Case)
2.1 Maybe they are available across competition or alternatives for free.
3. Low Value High Willingness to Pay (Add-ons)
3.1 Offer these as add-ons
4. High Value High Willingness to Pay (Expansion Triggers)
4.1 These features offer a great opportunity to differentiate some of our use case.
4.2 We are more likely to see features end up in this quadrant as we segment our results and look different segments value different features differently.

Question 41

Pricing Strategies

Answer 41

This involves changing the amount we charge for an existing use case.

When to use pricing strategies
1. Align pricing with the monetization triad. Change price to align wit consumer view, growth loops or cost of revenue
2. Align pricing with changes to other elements of the monetization model. Change price to align with changing value metric, packaging or when we charge

Increase price or decrease price. Most of the time we need to increase the price. Inflation is one factor. It also depends on whether the increase in depth or decrease in breadth is strong. Vice versus

If there is a trade-off between consumer view and cost, [consumer view tends to win]

Question 42

Pricing Strategies - Visualizing Van Westendorp

Answer 42

Too Cheap > Not a Bargain > Not Expensive > Too Expensive
Lower Bound = intersect between Not a Bargain and Too Cheap
Upper Bound = Too Expensive and Not Expensive
Optimal Price Point = Not Expensive and Not a Bargain

Question 43

When Strategies

Answer 43

1. Free vs Paid
   1.1 Free to paid is rare since consumers who aren’t used to paying for something have very low WTP
   1.2 Paid to free usually happens in response to wider changes in the industry or product
2. Transactional vs Subscription
   2.1 Requires a change in all other elements of the monetization model
   2.2 Industry-wide shifts
3. Term of Subscription

Question 44

Define When Strategies

Answer 44

First, do customers want to play?
1. Are customers willing to pay?
if No, then free
If Yes

We go into Time of Transaction or Recurring?
1. What is their natural frequency of usage?
1.1 Low leads to Transaction
1.2 High leads to Recurring
2. What is the variance in their natural frequency of usage?
2.1 High leads to Transaction
2.2 Low leads to Recurring

If it is Recurring, What is the term of Recurrence?
1. What is the natural frequency of adoption? How often does our audience make a decision about which product to use?
1.1 High leads to Short Term
1.2 Low leads to Long Term
2. How long does it take to form a habit? We want to avoid charging them again before forming a habit
2.1 Less Time leads to Short Term
2.2 More Time leads to Long Term

Question 45

Natural Frequency of Usage

Answer 45

Qualitative Survey
Asking users questions on frequency
1. How often do you face this problem?
2. How often do you use the alternative?

Quantitative Analysis
1. Create a frequency histogram
1.1 Look at a long enough period to identify recurring patterns of usage. E.g if it is weekly, we need at least 1 month of data, if it is monthly, it needs at least 3 months
1.2 How many users are active N days out of that period
2. Analyze frequency
2.1 Look for peaks
3. Analyze variance
3.1 Single spike - low variance
3.2 Uniform Distribution - high variance
3.3 Multiple Spikes - high variance

Question 46

Natural Frequency of Adoption

Answer 46

1. What problem does the product solve for you?
2. When was the last time you had this problem?
3. How did you solve it then?
4. When was the last time you considered [alternatives] to solve this problem?
5. Before you knew about this product, did you ever have this problem before?

Question 47

Time to Form Habit

Answer 47

Qualitative Survey
Asking users open-ended research questions?
1. What do you find most useful about the product?
2. How often do you use the product?
3. When did you feel like the product became an-essential/useful part of your life?
4. How long did it take you to get to this point?

Quantitative Analysis
1. Define the habit moment
1.1 Action, what action do they do
1.2 Frequency, How often do they do it?
1.3 Time Frame, In what time frame do they do it?
1.4 Way to arrive at the habit moment
1.4.1 Qualitative Inputs, When did you feel the product was useful to you? or when did it become essential?
1.4.2 Correlation Analysis, What actions and frequency have a positive correlation to high retention, and a negative correlation to non-retention.
1.4.3 Advanced Analytics, Machine learning algorithms can help us identify where the turning point was
2. Identify successful users
3. Calculate time to habit
3.1 Identify the starting point, user sign up or registers as a user
4. Segmentation

Question 48

Pricing Research Spectrum

Answer 48

Qualitative <-> Quantitative
1. Access to Customer, users and customers are the same group, Low <-> High
2. Audience Reach, Small <-> Large
3. Product Maturity, [Pre-PMF, Mature] <-> Growth, Growth is the best phase to do the quantitative survey
4. Industry Maturity, Mature <-> New
5. Research Question Type, Open-ended <-> Specific
5.1 When an organization wants to understand how many people feel a particular way about some aspect of the product, they are looking to quantify customer sentiment. On the other hand, when an organization is concerned with how people feel about something, or why they feel the way they do about something in the product, the research needs are more qualitative.
5.2 Qualitative research should precede quantitative research

Question 49

Audience Makeup

Answer 49

What are you solving for? Who can answer your questions?
Defensive Play: 100% Existing Customers
New Feature: 80% Existing Customers 20% Prospective Customers
Product Diversification: 50% Existing Customers 50% Prospective Customers
Adjacent Expansion: 20% Existing Customers 80% Prospective Customers
New Market: 100% Prospective Customers

Question 50

How do I select attributes to compare that will produce the most valuable results?

Answer 50

MaxDiff Survey Attributes: Key Considerations
1. Are the attributes comparable? Don’t compare features to categories
2. Do the attributes represent a realistic decision? Don’t ask people to compare attributes that are dependent upon each another
3. Are we asking the audience to compare essential attributes? Don’t compare the product’s core attributes, because users will always need access to them

Question 51

Outsourced vs In-House Surveys

Answer 51

Outsource
Pros:
More Expertise
Less engineering effort
Limited bias
Easier to recruit non-customers
Cons:
More expensive
Make take longer, while still requiring input and management
Less control over data quality and follow-up
More difficult to associate customer profiles into

In-House
Pros:
Less expensive
Usually faster
Can associate customer profile
Cons:
Less expertise
Potentially bias responses
More difficult to recruit outside customers
Internal alignment and effort

Question 52

Model Strategies - Adding New Use Cases - Vertically Vs Horizontally

Answer 52

Vertical
1. When consumers of a single use case segment value the new use case
2. When the value scales the same as existing use cases
3. When a vertical strategy doesn’t increase friction in growth loops
4. When the cost to serve the use case is low

Horizontally
1. When consumers across use case segments value the new use case
2. When the value scales differently from the existing use cases
3. When a vertical strategy adds significant friction in growth loops
4. When cost to serve the use case is high

Question 53

Optimization Objectives

Answer 53

1. Who are we targeting with our optimizations?
2. What will drive revenue growth from these different customers?

Question 54

The Four Customer States

Answer 54

1. Potential Customers
   1.1 Definition, Haven’t transacted yet, but good candidates to be customers
   1.2 Mindset, Curious about value and whether the product is worth the price
   1.3 Uber example, Downloaded app, created account, no first ride
2. Existing Healthy Customers
   2.1 Definition, paying customers who have a healthy engagement with the product
   2.2 Mindset, Already happy with the product, might be wondering about what else the product can solve for me
   2.3 Uber example, User who takes a ride once/twice every week
3. At-Risk Customers
   3.1 Definition, Used to be existing health customers but are now at risk of churning
   3.2 Mindset, Dissatisfied with their experience and might be considering switching to an alternative
   3.3 Uber example, Riders who have given low ratings on two rides in a row
4. Churned Customers
   4.1 Definition, Used to be existing healthy customers but have stopped transacting with us
   4.2 Feel like the product didn’t solve their problem, or that it’s not worth the price, considering alternatives
   4.3 Uber example, User who used to take rides weekly, but hasn’t taken a ride in the past 2 weeks

Question 55

Define and Analyze Customers In Each Customer States

Answer 55

1. How well am I converting users to the target state today?
2. Why have they not converted to the target state already?
3. Which users are candidates for conversion?

Question 56

For Customer States vs Revenue States

Answer 56

Potential Customers: New Revenue
Existing Healthy Customers: Expansion
At-Risk Customers: Existing + Contraction + Churn
Churned Customers: Existing

Question 57

Healthy Customers - Expansion Drivers

Answer 57

1. Who, Customer persona attributes
2. What, Action taken in the product
3. When, External time-based triggers
   3.1 Time of the Year
   3.2 Seasonal Events

Question 58

Healthy Customers - Why Candidates Don’t Expand

Answer 58

1. Awareness, Customers are not aware of the expansion path
2. Value, Customers are aware of the expansion path, but do not see the value
3. Conversion, Customers see the value, but there is too much friction to convert

Question 59

Potential Customers - Conversion Drivers

Answer 59

1. Who, Who are these customers?
2. How, How did we acquire them?
3. What, What did they do before converting?
4. When What time factors drove conversion?

Question 60

At-Risk Customers - Identifying

Answer 60

1. Negative actions, Identify key actions of existing healthy customers that suggest they might be at-risk
2. Negative Direction Of Engagement, Identify declining trend of engagement in existing healthy customers
3. Prediction Model, Build a prediction model that gives each user a score for how likely they are to churn.

Question 61

At-Risk Customers - Reasons

Answer 61

1. Satisfied, Have gotten the needed value from the product, and don’t need it anymore
2. Unsatisfied, Seeking an alternative because the product no longer satisfies their needs
3. Losing Habit, Losing the habit for external reasons

Question 62

Optimization Equation

Answer 62

Perceived Value > Perceived Price + Friction

Perceived Value : The way our users interpret and perceive the value of the target state with respect to the current state

Perceived Price: The way our users understand the price relative to other factors (alternative options, products, use cases)

Friction: Barriers to go from the current state to the target state

Question 63

Transitioning to The Target State

Answer 63

Users need to go through 3 stages
1. Educate, Customers learn how the target state can solve their problems

2. Convert, Customers follow the process of conversion to the target state
3. Activate, Customers establish a habit around the target state

Question 64

Transitioning to The Target State - Educate

Answer 64

A spectrum of required resources and effectiveness
Low Resource <–> High Resource
Low Effectiveness <–> High Effectiveness
Tell < Show < Experience

Tell
In product Message
Educational emails

Show
Explainer videos
Product demos
Case studies

Experience
Free trials
Free credit promos

Question 65

Transitioning to The Target State - Levers for Educate

Answer 65

1. Message, What message do we want to send?
   1.1 Personal Motivation
   1.2 Financial Motivation
   1.3 Social Motivation
2. Channel, What channel do we want to use?
   2.1 Product [Exisiting Healthy]
   2.2 Notifications [Exisiting Healthy]
   2.3 Paid Media [Churned Customers]
   2.4 People [Churned Customers]
3. Timing, When do we want to educate them?
   3.1 Internal Triggers, In the product
   3.1 External Triggers, Events, Holidays, or seasons that influence consumers’s perceived value.

Question 66

Transitioning to The Target State - Convert

Answer 66

Motivational Boosts

Boost and Examples
1. Trust/Credibility/Authority: Trust Seals, Trusted Organizational Affiliations, Press Logos, Trusted Endorsements
2. Social Proof: Testimonials, Reviews, Case Studies, Example Customers
3. Urgency: Deadlines, Countdowns
4. Scarcity: Limited Spots/Availability
5. Belonging: Pictures of Similar People, Popularity Tags
6. Completion: Status Bars, Checklists, Making Something Look Undone

Price Perception Biases
1. Anchoring, Consumers understand price relative to other factors, not as an absolute number
2. Paradox of Choice, When presented with multiple options, consumers find it hard to make a decision
3. Number Biases, round numbers are easier for consumers to understand, and preferred. 4 or 9 are preferred

Question 67

Transitioning to The Target State - Activate

Answer 67

Conversion isn’t the end of the journey. We need to avoid the risk of churning.

Setup Moment -> Aha Moment -> Habit Moment

Question 68

Educate Potential Customers

Answer 68

To move them into healthy existing customers
We need to first understand why they have not convert

1. Awareness: Educate on core value of the paid use case
2. Value: Increase perceived value, decrease perceived price
3. Conversion: Minimize friction of conversion

Optimization Considerations
1. Conversion Motion
1.1 Free to paid (freemium) [Spotify, Slack]
1.2 Direct to paid [Instacart, Uber]
For Direct to Paid
PVpaid > PP + F
For Free to Paid
PVpaid - PVfree > PP + F
2. Acquisition Parameters
2.1 Organic
2.2 Direct
2.3 Paid [LowPVPV]
2.4 Referral [High PV]

Strategies for Educating
High Starting PV can leverage Tell, Show
Low Starting PV can use Experience

Question 69

For Existing Health Customers

Answer 69

1. Deepen revenue from the current use case
2. Move the customer to a higher ARPC use case
3. Add on more use cases

Question 70

Strategies For At-Risk Customers

Answer 70

1. Habit Reinforcement
   1.1 Who: At Risk of losing the habit
   1.2 What: Re-establish the habit with their current use case, focus on the activate step
2. Anti-Conversion Flow
   2.1 Who: Unsatisfied, Losing Habit, on the fence and considering
   2.2 What: Decrease PV, Increase PP, and Friction of churn. Need to balance the friction.
3. Use Case Transition
   3.1 Who: Satisfied, Unsatisfied
   3.2 What: Educate, convert and activate on the new use case

Question 71

Strategies For Churned Customers

Answer 71

1. Resurrect to New Use Case
   1.1 Who: Satisfied, Unsatisfied
   1.2 What: Educate, convert and activate the new use case
2. Involuntary Churn Mitigation
   2.1 Who: Involuntary Churn
   2.2 What: Minimize Product and Payment Friction
3. Reactivation (hardest)
   3.1 Who: Unsatisfied Voluntary
   3.2 What: Educate, convert and activate the new use case

Question 72

Strategies For Churned Customers - Churn Mitigation

Answer 72

2 Reasons
Product Issues
Technical bugs
Getting logged out
Forgetting password

Payment Issues
Expired credit card
Credit limit reached
Address change

Payments failures normally fall into 2 buckets
Soft Decline
Insufficient Funds
Billing address changes
Transaction flagged as fraudulent

Hard Decline
Credit card expired/cancelled
Credit card number updated

For minimizing the soft declines
1. Optimize Retry Cadence
2. Credit Card Processor Rotation
3. Reducing Restriction, Removing verifications to avoid triggering failed payments
4. Optimize Fraud Classification
5. Recurring Flags

For minimizing the hard declines
1. Optimizing Payment Options
2. Account Update Programs
3. Incentivize User Updates

Question 73

Incentives

Answer 73

Any strategy that involves a temporary decrease in model friction, e,g, discounts, promotions, coupon codes, free trials, credits. etc

Question 74

Incentives - Impact on The Monetization Trad

Answer 74

1. Incentives lower the consumer’s view of value, discount fatigue
2. Incentives disable growth loops
3. Incentives make it harder to support the cost of revenue

Question 75

When to Use Incentives

Answer 75

Incentives that Drive Optimization
1. Convert potential customers to existing healthy customers
2. Expand revenue from existing healthy customers
3. Save at-risk customers and make them healthy again
4. Resurrect churned customers back to a healthy state

Question 76

Why is Monetization Testing Hard?

Answer 76

1. Consumer Sensitivity, Testing lower price for a use case might upset current customers
2. Cross Population, Untested consumers might be influenced if they hear about the test, giving murky result.
3. Time, Takes longer to get accurate results, not ideal when decisions need to be made quickly
4. Infrastructure Lift to Test, Testing will require touching multiple parts of the system, make it cumbersome

Question 77

A/B Testing Process

Answer 77

1. Define Scope and Objective
   1.1 What is the change we are testing?
   1.2 Success Metric, What metrics do we think it will impact? also Trade-off metrics, and Secondary Metrics
   1.3 Impact, In which direction and by how much will the metric move?
2. Build the test
   2.1 Define solution and control variations, What are our solution and control variations?
   2.2 User assignment, Which users could we assign to our solution and control variations?
3. Launch the test
   3.1 Timing, When should we run the test?
   3.2 Duration, How long should run the test for?
4. Evaluate Results
   4.1 Implement, Should we implement our test?
   4.2 Don’t Implement, Should we not implement our test and iterate on our solution instead?
   4.3 Investigate Further, Do we need to run the test for longer or do more analysis?

5 Implementing Solution
5.1 Roll Out As-Is, Do we roll out solution variation or do we need to develop further?
5.2 Keep a Holdout Group, Should we keep a holdout group to track long-term effects or should we roll out to 100%. A holdout group is a small control group that is withheld from experiencing the solution once implemented. This provides a reference for how our success metrics and additional outcome metrics would have performed without the solution.
5.3 Managing Existing Users, How do we manage existing customers through this rollout?

Question 78

A/B Testing Process - Metric To Track

Answer 78

Success Metric: Metric we want to move with our solution
Trade-off metrics: Metrics that could be negatively impacted by our solution and affect revenue as a whole
Secondary Metrics: Metrics that validate we are not doing any harm
Leading Indicator: Metrics that give us early signals of long-term impact.

Question 79

A/B Testing Process - Build the Test - Simplifying Solution Variations

Answer 79

1. Painted Door, Feature or product appears to be functioning, but is actually just there to get a user to express intent
2. Wizard of Oz, An automated process is replaced by a manual/thrid-party process temporarily
3. Provisional Test, Breaking down our tests into smaller tests, especially when there are multiple smaller hypotheses/changes in solution
4. Targeted User Release, Instead of rolling out the test to all the users, we target a specific group of users for the test.
   4.1 Solution will be affective for the target audience
   4.2 Solution will not negatively affect other users

Question 80

A/B Testing Process - Build the Test - User Assignment Issues

Answer 80

1. Offline communication (Cross Population)
2. Measuring network effects, NFX
3. Multiple Sessions, same user using different devices

For 1 and 2, we could use Group Based Assignment, create and assign closed groups to solution and control variations

Group Based Assignment
Groups need to be closed to minimize cross-population and measure network effects
Solution and control groups need to be matched to avoid biased results

For Multiple Sessions, we could use
1. Visitor Level Tracking, User cookies to track returning visitors and put them in the variation they were initially assigned to
2. Net New Testing, Only include new users in a specific test and split them between solution and control variations

Question 81

A/B Testing Process - Launch the Test - Timing Consideration

Answer 81

1. Seasonal Variation
2. Internal Promotions, by other teams
3. Product Specific Timing
4. External Market Factor

Question 82

A/B Testing Process - Evaluate the Test

Answer 82

Considering all the metrics we defined before.

Question 83

A/B Testing Process - Managing Existing Users - Grandfather

Answer 83

Grandfathering helps minimize negative experiences and hence churn of existing customers.

How you communicate any change is incredibly important.
1. Message
1.1 What change are we making?
1.2 Why are we making the change?
1.3 Why is the change good for customers?
1.4 What is the best channel for customers to reach out with questions/concerns?
2. Channel
2.1 Not just Blog or Forum only
2.2 Email to customers
2.3 Widely distributed press release
2.4 Personal sales rep call to enterprise value customers

1 Drawbacks to Grandfathering
1.1 Potential Lost Revenue
1.2 Techincal and Resource Costs

1. Should we grandfather or not?
   1.1 Is the revenue loss from churn worth the cost of grandfathering? Potential Revenue Loss > Cost to Grandfather
   Potential Revenue Loss = # of Existing Customers * Revenue per Customer * Probability of Churn

Estimating Probability of Churn
Alternatives & Why of the Use Case
Existing Customer Data, How long have they been with us? How engaged? How have they responded to NPS?
Modeling Impact of Change, Segmentation
Test Results, Provides a good read of how customers will react by comparing the engagement and retention rate of solution and control variations.

Cost to Grandfather
How robust is your infrastructure?
How much technical debt does grandfathering create?

2. How long should we grandfather for?
   2.1 What is the natural churn cycle for our product?
   2.2 How long can we sustain the cost of grandfathering?

How should we transition these customers to a new solution? What can we do to minimize churn? The most common method is to incentivize.