Click Ventures Startup Metrics Playbook by Summer Interns 2018

Click Ventures Internship Program Summer 2018
Click Ventures’ Startup Metrics Playbook
Created by: Click Ventures summer intern team 2018
(Deal Flow and Portfolio Management)
Click Ventures Deal Flow and Portfolio Management Fellow:
Bhaveshsai Kumar
Emma Fischer
Samuel Choy

Content
I. Product & Customer Metrics
II. Financial Metrics
III. Case Studies: SaaS and Industry Specific
IV. Appendix: Industry Metrics

Product Metrics
I. ARPU/CAC ratios
II. Churn/Retention Rate and Taming your Churn
III. LTV/CAC Ratio
IV. DAU/MAU and Retention Curve
V. Direct Traffic/Organic Traffic
VI. MRR/Gross Churn Rate
VII. Net Promoter Score
VIII. Click Through Rate/Screen Time
IX. Average Follow Up Attempts/User Engagement
X. The Magic Number, Bessemer, & CAC Ratio
XI. Virality (K-Value)

ARPU/ CAC Ratios
- Measures a customer's average contribution to
revenue. A rising level means increasing sales or
greater pricing power
- APRU = Total Revenue/ # of Subscribers
Average Revenue Per User CAC Ratio
ARPU vs CAC Friction Zone
- Chart here
- how much it costs to attract each customer, a
part of broader sales metrics
- Total cost of Sales/# of Customers Acquired
Source: Geckoboard

Churn/Retention Rate and Taming your Churn
Customer Churn/ Retention Rate
- % of customers that stay with you and the
percentage of customers that leave over a given
period
- Very important for SaaS business models
because of their subscription based design
- Churn: (Cs - Ce)/Cs x 100
- Retention: ((Ce – Cn)/Cs) x 100
- Cs= # of customers at the start of a period
- Ce= # of customers at the end of a period
- Cn= # of new customers acquired in that
period
Why taming your churn is important
Hypothetical example:
Month 1:
Existing Customers = 500 customers
New Customers = 50 new customers per month
Churn = 5% per month from your monthly customer
base
At Month 16, you would have reached 75% of your
achievable growth (“The Growth Wall”).
When you tame your churn to 1% but assume the
same growth rate, the same growth wall of 75% will
not be reached until Month 129.
Source: https://www.bonjoro.com/blog/post/what-is-churn-why-does-it-matter

LTV-CAC Ratio
- Is the golden idea of a startup’s profitability levels and its sustainability
- Measures the relationship between the lifetime value of a customer and the cost of acquiring that customer
- Can also act as a barometer for how much or little companies need to spend on CAC measure, like marketing, to stay
ahead of competition
- Ideally want to recover your CAC within first 12 months of spending
-
Source: Investopedia.com
- LTV= GML x (R/(1+D-R))
- Where:
-
- LTV/CAC
- Cons: not the most reliable predictor of future growth,
can easily change
- Crucial for SaaS companies
- What’s the Ideal LTV-CAC ratio?
- Some say it should be 3:1, value of a customer
needs to be 3X higher than acquiring them
- N.B. the ‘ideal’ figure varies from investor to
investors, and

DAU / MAU and Retention Curve
- DAU= number of unique users that engage
with product over 1 day window
- Important because it indicates retention and
growth of user base
- Some us D1, D7, D30 to measure the number
of daily active user levels over the 1st, 7th and
14th days of user retention
- MAU= the number of unique users that engage
with product over 30 day window
Daily Active Users / Monthly Active Users Retention Curve
Bottom line:
DAU / MAU = measures the stickiness of the product
Source: Klipfolio.com
- Data can be used to draw a “retention curve”
- A typical retention curve tends to drop
quickly at first and then level off as growth
steadies
- As the curve flats out, those stayed are your
‘loyal users’ that compensates your churn

Direct Traffic/ Organic Traffic
- Traffic that comes directly from website visits
and not through an intermediary
- Calculated as an absolute value
- Direct traffic benchmarks vary from industry to
industry- with those such as e-commerce
bringing in only 15% of revenue
- SEO (Search Engine Optimizations) are
commonly recommended to boost direct traffic
to the website
Direct Traffic E-commerce traffic breakdown
Organic Traffic
Related Data
- Chart here
- Unpaid traffic from search results and traffic that
comes from intermediaries such as deal sites
- Calculated as an absolute value
Example: Traffic breakdown for different sales models

Gross Churn Rate/ MRR
- % of revenue lost due to cancellation or
downgrades
- Calculates the total lost of a company
- In general, is a reflection of targeting the right
customers and making the right products
increasingly valuable
- High churn rate toxic to any business
- Can be calculated on a chronological basis
(monthly) or in cohorts (groups of people
lumped together for calculation)
- Net Churn: MRR lost- MRR from upsells this
month/ MRR at the beginning of the month
- Gross Churn: MRR lost in a given month/MRR
at the beginning of the month X 100
- MRR= monthly recurring revenue
Net & Gross Churn Rates Appropriate Gross Churn levels
- Out of all the churn levels, gross churn is the
most important
- Some investors believe that the appropriate level
of annual churn at <5%, but then again, not all
SaaS are created equal
- The bottom line is that churn should be ‘tamed’
Source: Geckoboard.com
Example: Typical SaaS Churn

Net Promoter Score
- A management tool that can be used to
evaluate loyalty in a business client relationship
- NPS: % promoters- % detractors
- Score ranges from -100 (all detractors) or +100
(all promoters) based on the question “how
willing are you to submit this service to a
friend”.
- Companies in the consumer good sector tend
to have higher scores (Amazon, etc.).
Companies in the B2C sector use this as a gauge
for customer loyalty and virality
- Pros: index that is easy to calculate and whose
data is based on a single application, very
standardized, easily used as a reference
Net Churn Desired Value
- Simply best to be as high and positive as possible
- Average: +5/+10
- Best Companies: +50/ +80. One of our portfolio
companies has as high as +100 (perfect score)!
Source: Survey Monkey
Methodology
1) Enter all of the survey responses into an
Excel spreadsheet.
2) Now, break down the responses by
Detractors, Passives, and Promoters.
3) Add up the total responses from each group.
4) To get the %, take the group total and divide
it by the total number of survey responses.
5) subtract the % total of Detractors from the %
total of Promoters—this is your NPS score.

Click Through Rate/ Screen Time
- % of clicks that you get per 100 impressions
- [(#clicks)/(#impressions)]*100 = %CTR
- Less biased metrics when compared to total clicks
on an ad, takes into account the # of impressions
- Here is a table of average click through rate across
industries for your reference
Click Through Rate
Screen Time
Average CTR for different Industries
- Measures the navigation behavior of users
including their order of navigation, time spent on
each page, drop off rates per page, etc.
- Allows developers into the minds of users and
refines the products according to their needs
- Information provides opportunities for re-design
that reduce friction, increase engagement, and
create more well defined funnels
Source: https://www.growthpoint.info/adwords-benchmarks/

Average Follow-up Attempts & User Engagement
- Measure of the average number of follow up
attempts to secure a customer
- # of follow up attempts/ # of leads= # of average
follow up attempts
- Pros: allows startups to measure persistence of
sales rep and efficiency of customer contact
- Cons: Higher number of follow ups is not
necessarily positive as customers may be
annoyed/pressured. Adequate time between
follow ups is important and should be measured as
well.
- Benchmark level: Some statistics show 8 attempts
for cold leads is a rational mid-range target but for
a shorter sales cycle or warmer leads (inbound
leads) the number of attempts should naturally be
less.
Average Follow up Attempts User Engagement Actions
- Key actions that users take when using the core
functionality of an app/ website
- Social media: shares, likes, comments
- Pros: clearly shows user engagement and
number of interactions
- N.B. key user engagement doesn’t always mean
greater monetization
Source: Geckoboard

The Magic Number/ Bessemer/ CAC Ratios
- Widely used formula to measure sales efficiency
- Measures output of a year’s worth of revenue
growth for every dollar spent on sales &
marketing
- *Current Quarter’s Revenue- Previous Quarter’s
Revenue) / (Previous Quarter’s Sales and
Marketing Expenses)
The Magic Number CAC Ratio
Bessemer Ratio
- Similar to magic number, but more defined for new
acquisition
- Measures how fast does my gross margin pay for
my customer acquisition costs
- ((Current quarter’s new, signed average contract
value) * Gross Margin)/ (Previous Quarter’s
Customer Acquisition Costs )
- Flips Bessemer’s ratio to create a monthly
payback number
- Previous Quarter’s Acquisition costs/ new
MRR in current quarter * Gross Margin
Source: thesaascfo.com

Virality (K-Value)
- Measures product virality by the number of new
users an existing user generates . This is a good
indicator of company’s growth trajectory
- To complement this metric, you also need to look at
the viral life cycle (how long it takes for friends to
become customers)
- Viral coefficient: average number of invitations
sent exiting user * % conversion rate of invitation
- Value MUST be stronger than 1 to be considered
“viral”
- 1 - 1.2 is good, 1.4 is excellent, 1.7 is
outstanding
- This is different from net promoter score:
- K-Value measures level of customers actually
recommending service
- NPS measures the likelihood of recommending
it
Virality Description Relationship Between User Growth and K
Source: geckoboard.com

Financial Metrics
I. MRR
II. Annual Contract Value/ ARR
III. Breakeven Analysis
IV. Burn Rate/ Cash Flow Forecast
V. Compounded Monthly Growth Rate
VI. Contribution Margin
VII. Gross Margins
VIII.Quick Ratio
IX. Ratio of SAE Ratio/ Revenue Per Employee
X. Runway

MRR
- All recurring revenue normalized into a monthly
amount
- Metrics used with SaaS companies
- Averages all pricing plans and billings into a single
number that can be tracked
- MRR= # of customers * average monthly billable
- Net New MRR= New MRR + Expansion MRR for
existing customers– Churned MRR
Monthly Recurring Revenue Description Some common ways to grow MRR
1. Raise your price
2. Move your free users to paid users
3. Unbundle your features
4. Upsells
5. Increase your lead to conversion rates
6. Play with your pricing strategies: Per-user
pricing (Salesforce, Slack, etc.) vs Metered
Pricing: the more you use the service the more
you pay
Source: https://www.cobloom.com/blog/mrr-hacks-to-increase-your-monthly-recurring-
revenue#5 types of MRR’s to track
- New MRR: New customers
- Expansion MRR: existing customers upgrade
- Reactivation MRR: MRR from previous customers
- Contraction MRR: Lost MRR from existing customers
- Churned MRR: lost MRR from canceled customers

Annual Contract Value/ ARR
- The average annualized revenue per customer
contract.
- Annual contract value / customer acquisition cost
- Shows how long it takes to pay off CAC
- Many successful SaaS companies have built large
businesses with small ACV
- Average value varies between B2B and B2C businesses
Annual Contract Value Annual Contract Value Comparable
- Chart hereAnnual Run Rate (ARR)
- Projects our future revenues for the year assuming no churn. SaaS
companies use this to forecast their topline when minimum contract
duration is 1 year
- Helpful tool to predict long term growth and to visualize the size of a
business
- ARR= (Sales of your last quarter * 4)
Source: Investopedia

Breakeven Analysis
- An analysis that yield the stage at which revenues
equals costs and profit generation begins
- For startups, it is very important to clarify your
startup costs
- Break Even Point (Units)= Fixed Costs/ (Revenue
per unit- Variable cost per unit)
- Break Even Point (sales dollars)= Fixed Costs +
Contribution Margin
- Contribution Margin= Price of Product- Variable
Costs
- If the break even analysis yields too high a number,
need to consider whether or not product is too
expensive
- Ideally conducted before you start a business, but
also useful for business operations and planning
(such as pricing, material, and new product options)
Breakeven Description BEP Graph

Burn Rate/ Cash Flow Forecast
- Measures how quickly cash holdings decrease
- Allows you to forecast when you’ll run out of
money or grow
- Gross burn rate= total amount of cash you’ve
spent each month (add all expenses together)
- Net burn rate= cash out- cash in (or net income
on P&L)
- Needs to be sufficient to take a startup through
15-18 months (your runway)
Burn Rate Public SaaS Burn vs Consumer Publics
Cash Flow Forecast
Related Data
- Chart here
Source: Baremetric.com
- Cash flow forecast should be based upon cash
flow from financing, operations, and investing
- Forecast out as one would any other financial
statement (using benchmarks of other companies
expenses, calculating as a % of revenue)

Compounded Monthly Growth Rate
- Indicator of company profitability & sustainability
- Measure of percentage increase in revenue
(monthly or annual basis)
- Compounded Monthly Growth Rate = (Latest
month/first month)^(# of months)-1
- Factors such as retention rate, legal costs,
marketing techniques, and stage of company need
to be taken into consideration when targeting an
appropriate growth rate
- Benchmark growth rates vary from company to
company, but it is not uncommon among startups
to see CAGR of 50% to 100% in the first 3-5 years
of the startup
Description Growth of small SaaS businesses

Contribution Margin
- Profit per unit without considering fixed costs,
revenue per unit, & variable COGS
- Lets a company see the profitability of its individual
products and evaluate different parts of the business
- Contribution margin= sales price- total variable costs
- Variable costs= materials, labor, or overhead
- Especially important when trying to make pricing
decisions that help the gross margin of a startup
Contribution Margin Contribution Margin Graph
Contribution Ratio
- Contribution ratio= contribution margin/ per unit
sales price
- Can be calculated on a per unit or aggregate basis
- figure will result in a percentage that indicates what
percentage of each dollar of revenue is generated to
cover fixed costs

Gross Margins
- Measures operating profitability
- Gross Profit: Revenue - COGS
- Is a good indicator of variable costs and their
fluctuations
- Expressed as a % of total revenue
Gross Profit
Gross Profit Margin
- Useful for showing a company’s production efficiency
over time
- Gross profit margin= gross profit/ revenue
Subscription growth margins of SaaS

Quick Ratio
- Ratio of gains in revenue vs losses in revenue
- Can give an overall glimpse into how the sales, product, marketing, and CRM teams are
doing as a whole.
- A holistic indicator that measures the company’s success in terms of customer
acquisition and retention
- Quick Ratio in the earlier years of businesses tend to have less reference value
- More applicable to mature companies as young startups typically has very high
with extremely large quick ratios
- Quick ratio becomes more relevant at later stages companies are able to continue
innovating and delivering value to keep churn down
Quick Ratio

SAE Ratio/ Revenue Per Employee
- An efficiency ratio that measures how well a
company is able to manage its non-operating
expenses and generate sales
- Fixed costs in this situation should include no one
off items, only recurring expenses
- SAE ratio = Sales / Administrative Expense
SAE Ratio Description Revenue per employee ratio
- Measures the average revenue generated by each
employee of the company
- Ratio = Revenue/ average number of employees
for period
SAE general levels/ implications Related Data
- Chart here
- The higher the ratio the better, implies better
operating leverage of central functions
- Increasing SAE ratio implies that the company can
generate additional sales with the same fixed
infrastructure
- Low SAE ratio could mean inefficient structure
Source: Geckoboard
Example: Revenue per Employee Ratio across industries

Runway
- The amount of time a company can continue
to run on existing cash without going into the
red
- Dependent on the relevant burn rate
- Having a sustainable cash runway that
matches the founders risk tolerance is key
- Looking at the time between financing
rounds per industry can help founders
understand the typical runway for their
industries
- In Seed to Series A companies, our typical
recommendation is to keep 1 to 1.5 years of
runway when you begin your next round of
financing
Runway Average time lapse between financing rounds
Related Data
- Chart here
- The median lapse between Seed to Series A is
less than the median time lapse between Series
A to B, B to C etc.

Case Studies
I. SaaS Specific Case Study: Groove
II. Industry Specific Case Study: Raw Generation (E-Commerce)

SaaS Featured Case Study: Groove
III. Case Studies

SaaS Case Study: Groove
III. Case Studies
Overview
The Problem
Groove HQ is a SaaS company that offers a no-frills customer support software. It was founded 5 years ago and has gained
traction, with 8,000 paying customers. Groove’s primary target market is early to mid stage startups for whom the
traditional customer support solutions (i.e. Zendesk, Freshdesk) are overly complex and redundant. Like many helpdesks,
Groove offers ticket management, email templates, reply automation, and collaboration functions for CRM reps. It also
provides live chat, customer rating systems, metrics to measure support performance/customer happiness, and
integrations with third party applications
In 2013, Groove was decently successful at acquiring new customers. Nonetheless, it had a monthly churn rate of 4.5%,
which translates into 42% annual churn. Such a churn rate is more than enough to kill a startup: If Groove had 1000
customers at the start of the year, it would need to onboard 420 new customers just to keep its user base and revenue
constant (assuming MRR stays constant). Using the churn figures, it can be calculated that the average customer lifetime
was only 22 months, when compared to 36 months for other SaaS startups with average sales price below $1,000
(InsightSquared, 2016). In addition, as Groove is a B2B SaaS company, it is probable that it has a higher CAC when compared
to startups with B2C SaaS or other business models. With low customer lifetimes, high CAC, and low ARPU (due to its low,
no-frills pricing model), it can be assumed that Groove’s LTV to CAC ratio was not ideal.
Thus, Groove needed to understand why customers were leaving their platform in droves and whether there was a problem
with the product’s core functionality, the value discovery process, or the targeting process of the marketing team.
Source: Cloudinary

SaaS Case Study: Groove
III. Case Studies
Metrics Used
First, Groove sought to identify users that were either having trouble using their service or were not getting any
value from their service. In their research, through a regression analysis of historical data, they identified a few “Red
Flag Metrics” that helped them differentiate between the behavior of users who continued using Groove 30 days
after signing up and users that quit after the same time period.
Initial Session Length
They found that users that stayed after 30 days had an average initial session length of 3 minutes and 18 seconds,
while users which quit after 30 days had an average initial session length of only 35 seconds.
Frequency of Logins
Users which stayed after 30 days logged in to Groove HQ 4.4 times a day on average while users that did not only
logged in 0.3 times a day on average.
Time Spent on Key Tasks
Creating rules on the platform takes 10-30 seconds while the customization of support widgets takes around 2-3
minutes. Groove found that users that churned ended up taking a much longer time to complete said tasks, pointing
to an inability to navigate the software.
Source: Cloudinary

SaaS Case Study: Action 1
III. Case Studies
Using these metrics, Groove better
understood the behavior/traits of a user
likely to churn. They identified users that
displayed such behavior and made efforts
to retain them.
Firstly, they sent this email to users with an
initial session length below 2 minutes.
Source: Cloudinary

SaaS Case Study: Action 2 & 3
III. Case Studies
Action 2 Action 3
Using these metrics, Groove better understood the
behavior/traits of a user likely to churn. They identified users
that displayed such behavior and made efforts to retain them.
Firstly, they sent this email to users with an initial session length
below 2 minutes.
26% of users who received this email responded and of the
users that completed the setup process, 40% were retained
after a 30 day period. Groove then identified users that logged
in less than 2 times in the first 10 days after signing up. These
users were then targeted with the following email
Source: Cloudinary

SaaS Case Study: Action 4
III. Case Studies
Action 4
15% of the targeted users responded to this email and of the respondents, 50% continued using
the platform after the 30 day period Furthermore, Groove hypothesized that users who took more
time to perform key tasks were probably facing problems with the platform. As Groove is a
relatively cheap service, it is possible that these users would rather quit than seek assistance (as
there is not a large subscription cost that they need to recoup). Thus, they sent similar emails to
users that fell in this category.
Source: Cloudinary

SaaS Case Study: Results
III. Case Studies
Results
Groove found that their group of power users sent around 400% more referrals
than their control group. Groove had identified a cohort of customers that they
could leverage not only for marketing but also potential up-sells/cross-sells in the
future due to their loyalty to the platform.
4
3
2
1
10% of users responded and 30% of these respondents were still users after
30 days.
Groove reduced churn by a total of 71%. In the process, they found a number
of key problems with the functionality of their platform, which they later
improved.
Groove targeted the opposite end of their engagement spectrum by
targeting their most active users as promoters for their referral program.

SaaS Case Study: Key Takeaways
III. Case Studies
Key Takeaways
Remember that all churn is not bad as sometimes you will onboard customers that may not derive
much value from your product. Let these customers go. Refer such cases to your sales/marketing
teams so lead quality increases and you do not waste resources acquiring such customers.
4
3
2
1
Metrics is are good for identifying users that are either disinterested in your product or having
problems using it. These metrics can be extremely simplistic (i.e. the number of logins, session
length…etc) or more specific to your product (i.e. time taken to fulfill a specific task, number key
actions performed).
Engage with users who you have identified at risk to churn and provide assistance to them in the value
discovery process. This is especially important if you have free trials/low price points as many customers
would rather give up on your product (see it as a sunk cost) rather than ask for help
Ensure that you continue to improve the user experience for your most loyal power
customers while also leveraging them as resources to gain further traction

Industry Specific Case Study: Raw Generation (E-Commerce)
III. Case Studies

Industry Specific Case Study: Raw Generation (E-Commerce)
III. Case Studies
Overview
The Problem
Founded in 2012, Raw Generation is a pure-organic juice company based in Middletown, NJ. The company is
owned and operated by Jessica Geier, a 30-year-old health coach, and her father, Bill. Raw Generation’s
purpose is to make healthy, raw foods and juices more convenient for the average person to incorporate into
their diet. The juices and smoothies are designed to help customers lose weight in a healthier and more
efficient manner. Like many e- commerce startups, Raw Generation is an exclusively online service that allows
customers greater flexibility by delivering directly to their door. While the company is currently doing well, it
wasn’t always so prosperous
6 months after launching in 2012 the company was facing a critical point. Revenues were having ups and downs,
with no monthly revenue getting above $8000 and growth at a minimal or dismal level. Social media campaigns
and other traditional forms of e-commerce marketing were failing to expand Raw Generation’s consumer base.
Raw Generation came to impasse, but took actions that grew their revenue by 1100% in just two months in mid
2013.
Source: Cloudinary

Ecommerce Case Study: Raw Generation (E-Commerce)
III. Case Studies
Metrics Used
In an effort to improve their operations and profitability, Raw Generation focused on two metrics that
were well known for having large impacts on e-commerce sales: Traffic origination and Retention Rate.
Direct Traffic
Initial efforts to boost revenue growth through increasing direct traffic to the site, primarily through
social media campaigns, proved ineffective in creating new leads. Previous e-commerce market research
have demonstrated the importance on boosting indirect traffic to your company’s website, as it often
makes up the majority of all traffic that comes to a site.
Churn Rate
Raw Generation hoped to decrease their churn rate (increase their retention rate) to promote heavier
interaction with a large and easily addressable market, encouraging greater retention through coupon
and flash offerings.
Source: Cloudinary

Ecommerce Case Study: Actions taken
III. Case Studies
Rebranding Deal Sites and Urgency Marketing
Raw Generation rebranded their product to better fit
trends towards juice cleanses and healthy options in
the drinks industry to reduce their churn.
Through partnering with outside deal sits, they were
able to expand their consumer base, increase their
revenue, and market to high potential customers.
Additionally, by using a marketing strategy marked by
pop-up ads and flash sales, they boosted indirect
traffic to their site.
Source: Cloudinary

Ecommerce Case Study: Results
III. Case Studies
Results
Raw Generation rebranded their product to better fit trends towards juice
cleanses and healthy options in the drinks industry. This rebranding allowed them
to find a better fit amongst customers and reduce churn.
3
2
1
Grew Revenue from $8,000 in May of 2013 to $96,000 in July of 2013, over
1100% growth over a 2 month span
Raw Generation increased their user base by more than 1900 users in under
a 2 month timespan, collecting personal information to use in future
marketing campaigns. Through continuous and heavy marketing outside of
their own page, they managed to boost overall traffic to their site.
Source: Cloudinary

Appendix
I. SaaS specific metrics
II. Ecommerce Specific Metrics
III. Author Recognition

SaaS Specific Statistics
IV. Appendix
General SaaS Statistics
Source: Cloudinary

SaaS Specific Charts & Levels
- Def here
IV. Appendix
Average Monthly Revenue Average Market Cap to Customer Size
KPI Definition /Meaning Related Data
- Chart here
- KPI definition

E- commerce KPI trends
IV. Appendix
- Chart here
Source: Mos.com

Ecommerce Specific Ratios
IV. Appendix
- Chart here
- Chart here
Source: Mos.com

Author Recognition
IV. Appendix
Emma Fischer
3rd Year in the World Bachelor in Business
Program:
University of Southern California
Hong Kong University of Science and
Technology
Bocconi University
Bhaveshsai Kumar
2nd Year in the World Bachelor in Business
Program:
University of Southern California
Hong Kong University of Science and
Technology
Bocconi University
Samuel Choy
MSc Investment and Wealth
Management
Imperial College Business School
BSc Actuarial Science (First-Class
Honours)

Click Ventures Startup Metrics Playbook by Summer Interns 2018

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