This document discusses revenue models, pricing strategies, and enterprise valuation. It begins with an overview of Dave Parker's background and credentials. It then covers key aspects of building a business model including creating value through products/services, delivering value via revenue models, pricing, marketing and sales. Revenue models discussed include fee for service, commerce, subscription, metered service, and others. The document provides examples and metrics for evaluating different models. It also reviews pricing mechanics, marketing strategies, and factors that influence enterprise valuation such as revenue multiples.

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Revenue Models, Pricing,
& Enterprise Value
Dave Parker
www.DKParker.com
@DaveParkerSEA

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Agenda
¤ About Dave
¤ Business model breakdown
¤ Identify Key Inputs, Identify Unit Economics
¤ Choose primary/secondary revenue models
¤ Marketing and Sales
¤ Pricing Mechanics
¤ Enterprise Value

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About Dave
¤ 5X founder, raised $12M, exited $85M
¤ Former SVP Programs at UP Global (Startup Weekend)
sold to Techstars
¤ Author – ”Trajectory: Startup–Ideation to Product Market
Fit” shipping 3/2021
¤ 2X VC and occasional Angel
¤ 11 transactions – 9 sell side, 2 buy side now with NextPath
Advisors

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Creating Value:
Product or Service,
Market, Team
Delivering
Value: Pricing,
Marketing &
Sales, Rev
Model
Capturing
Value
Reasonable to
Exceptional
Returns
Business Model Breakdown

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Creating Value
¤ Product or Service
¤ Cost to Build – Team
¤ Engineering
¤ Design
¤ Hosting
¤ Manufacturing
¤ Cost to Support

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Delivering Value
¤ Revenue Model – how you monetize
¤ Pricing
¤ Cost of Selling
¤ Marketing Methods and Spend
¤ Sales Models
¤ Business Development

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Capturing Value
¤ The outcome:
¤ Topline Revenue
¤ Gross Margins
¤ Net Profit

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Two Views of Your Startup

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How to Monetize Your Startup:
Revenue Models

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The Data
¤ 2654 companies from Crunchbase
¤ 5+ year tracking
¤ Creates massive impact on valuation
¤ Surprises
¤ Seed 1-10
¤ Combinations models
¤ * on short time from Seed to A
¤ Failures
¤ Wayback Machine
¤ >80% lacked clear CTA and Value Prop

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1. Fee for Service
¤ Example: Consulting Services company
¤ Use: B2B & B2C
¤ Key Metrics
¤ Project Revenue
¤ Cost of delivering (usually time)
¤ Gross Margin
¤ Services are hard to scale because they require people
to deliver including Restaurant, Contractors, etc.
¤ Services include markup on cost of goods sold

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2. Commerce
¤ Example: Amazon, AmazonSupply
¤ Use: B2C & B2B
¤ Key Metrics:
¤ Wholesale or cost of goods sold
¤ Average Margin %
¤ Average Basket
¤ Commerce – Physical Goods- Wholesale, cost of goods,
retail, average margin, physical good
¤ Notes: Can mature into marketplace

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3. Subscription
¤ Example: Salesforce , Box, Spotify
¤ Use: B2C & B2B
¤ Key Metrics
¤ Average Revenue Per User (ARPU)
¤ Conversion ratio – e.g. trial to purchase
¤ Churn
¤ Challenges: MVP won’t be enough to be Kick Ass Product
¤ Notes: Highest multiple, forecastable revenue

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4. Metered Servcie
¤ Example: AWS, Splunk, Azure
¤ Use: Favors B2B
¤ Key Metrics
¤ Average Revenue Per User (ARPU)
¤ Usage growth over time
¤ Churn
¤ Challenges: infrastructure required at launch
¤ Notes: Highest multiple, forecastable revenue

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5. Transaction Fees/Rental
¤ Example: 99Designs, KickStarter, Elance, Chugg
¤ Use: B2C & B2B
¤ Key Metrics
¤ Average transaction revenue
¤ Fee % per transaction
¤ Number of transactions
¤ Challenges: Margins are small (15%), need efficiency
¤ Notes: Don’t start too low

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6. Productize a Service
¤ Your offerings is generally complex and requires services
to deploy
¤ Gross margin on Services >35%
¤ Product development comes with services
¤ Use: B2C & B2B
¤ Examples: Moz, service company convert to tools.
¤ Challenges – difficult to make the transition away from
services

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7. Combinations
¤ Combinations business models happen for two reasons
¤ You don’t know which model is right
¤ At scale you can expand revenue sources
¤ Examples: Hardware sensors + software services to create
data analytics
¤ Challenges – most require scale or at least traction
¤ Mature faster

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8. Marketplaces
¤ Example: eBay, Alibaba
¤ Use: B2C & B2B
¤ Key Metrics
¤ Average Transaction Amount
¤ Number of Monthly Transactions
¤ Commission %
¤ Challenges: two sided market places require you start
with one side, value to seller & Product market fit (x2)
¤ Notes: critical mass or marketplace required

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9. Lead Generation
¤ Example: Mint.com, AllStarDirectories, NetQuote
¤ Use: B2C & B2B
¤ Key Metrics
¤ Cost to generate traffic
¤ % conversion of form data
¤ Price per lead
¤ Challenges: Highly competitive, barrier of entry is low
¤ Notes: Conversion rates average 0.06%

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10. Gaming
¤ Example: King.com/Candy Crush
¤ Use: B2C Only
¤ Key Metrics:
¤ Downloads
¤ % play
¤ Average in app purchase
¤ Challenges – tends to be “hit driven business”
¤ Notes: use in first 21 days is a predictor of success

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11. Advertising/Search
¤ Example: Google, Facebook
¤ Use: B2B – advertisers pay, users are free
¤ Key Metrics
¤ Traffic
¤ Click
¤ Avg. revenue/click
¤ Challenges – Scale, need >1M uniques/month to
consider the option

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12. New Media
¤ Example: SnapChat, WhatsApp
¤ Use: B2C only
¤ Key Metrics:
¤ K-Factor (Viral Co-efficient)
¤ Network effect of inviting others to join
¤ Challenges – K-Factor is hard. Little revenue until scale
¤ Notes: Everyone wants to! Not happening in B2B
¤ No revenue acutally required

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13. Big Data
¤ Examples: PatientsLikeMe
¤ Use: B2B
¤ Key Metrics:
¤ Per API Call
¤ Per record pricing
¤ Frequency/recency
¤ To monetize data, you need to have the data in
advance or massive cash

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14. Licensing
¤ Example: Think Microsoft office license or server license –
before subscription. Content Licensing
¤ Use: B2B
¤ Key Metrics:
¤ Duration of license
¤ Upgrades & maintenance (20-25% annually)
¤ Use can be based on vertical market or geography

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Revenue Models– Primary/Secondary
1. Fee for Service
2. Commerce
3. Subscription
4. Metered Service
5. Transaction Fee/Rental
6. Productize a Service
7. Combinations
8. Marketplace
9. Lead Generation
10.Gaming
11.Advertising/Search
12.New Media
13.Big Data
14.Licensing

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Pricing

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Ultimately pricing needs to cover
¤ Cost of Customer Acquisition
¤ Cost of Delivering
¤ Margin (Profits and Returns)
¤ Lifetime Value (LTV) is calculated at 12 or actual
¤ Pricing is not an afterthought
¤ 10, 100, 1000 customers

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Pricing Mechanics

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Cost Based
¤ Pay Rate
¤ Bill Rate
¤ Gross Margin

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Value Based
¤ What the market will bear

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Value Based
¤ Range
¤ Product maturity
¤ Jobs to be done framework

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Pricing Tiers
¤ Pricing should be appropriate for the stage/type of
customer
¤ Usage based
¤ User based
¤ Balance friction, easy to start
¤ With cost of sales, minimum user size

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Hubspot Example

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Competitive Analysis
¤ Use the Wayback Machine – Internet Archive
¤ Know the Market
¤ Price changes over time
¤ Service/Product Offerings
¤ Terms – duration, contract length

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Hubspot Example

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Hubspot example

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A/B Testing
¤ Have a hypothesis – what will you test?
¤ Hide current pricing on site
¤ Traffic to landing pages
¤ Unbounce or other
¤ Squeeze Page – only CTA is buy

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Promotions
¤ Freemium
¤ Time based
¤ Early Adopter based
¤ Percentage Discount
¤ Grandfather early users

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Common Errors
¤ Setting your pricing too low
¤ Freemium is a marketing method, not a price
¤ Too Opaque of a price will frustrate customers
¤ “Knowing the answer” vs testing
¤ Positioning as “me too” – just like my competitors but less
¤ Same price for all customers
¤ Free for Life!

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Marketing – Finding the right
customers

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Marketing – Finding Customers
¤ Messaging/Value Proposition
¤ Does it resonate with the target customer segment
¤ They are the hero of the story
¤ Is it repeatable?
¤ Strategy
¤ Outbound first
¤ Inbound second

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Unit Economic Terms
¤ State your hypothesis
¤ CAC – customer acquisition cost
¤ LTV – lifetime value
¤ ARPU – average revenue per user
¤ ACV – annual contract value
¤ Churn – customers that leave monthly
¤ Net Negative Churn – increase in annual contract value
¤ Time to Close – in days
¤ Customer engagement – time on site, in app

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Organic
Search
Paid
Search
Word
of
Mouth
Sales
Calls
PR
Miracles!
Time
to
Close
Month
1
Month
2
Month
3
Month
4
$
Spen
d
#
Conv
#
Conv
#
MRR
Time

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Marketing Channels
¤ Paid Search
¤ Organic Search
¤ Word of mouth
¤ Sales calls
¤ Public Relations
¤ Affiliate
¤ Email marketing
¤ Social

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Marketing Qualified Leads
¤ Define qualified vs list
¤ Suspects
¤ Prospects
¤ Qualified Prospects

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Sales Qualified Leads
¤ Hand off to Sales
¤ Identify steps to close
¤ Number of calls

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Time to Close
¤ Lead attribution
¤ Source time
¤ Compressing or Expanding
¤ Trend by source

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Tracking
¤ Data allows you to know where to double
down and where to hold back
¤ Conversion ratios

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Sales – capturing value creation

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How will they buy?
¤ Web Direct – place the order to buy on the web
¤ Direct – outbound sales, inside/outside
¤ Indirect/Channel – fulfills demand, doesn’t generate
¤ Retail – BestBuy, etc

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Sales Model Hypothesis
Known
Market
Unknown
Market
Low
Price
Point
High
Price
Point
Known
Search
Words
Unknown
Search
words
Web Direct ✔ ✔ ✔
Direct ✔ ✔ ✔ ✔ ✔
Indirect ✔ ✔ ✔
Retail

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Enterprise Value

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Enterprise Value
¤ Multiple of revenue or EBITDA for mature companies
¤ TTM
¤ Profit (sometimes)
¤ Other Factors
¤ TAM size – Tesla
¤ Nascent market/customer segment – AirBnB
¤ Growth rate %
¤ Viral Coefficient – B2C only
¤ Churn or net negative churn
¤ Customer concentration is a negative

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Enterprise Value Examples
Advertising/Search
Google 8.4X, FB 8.79
Only work at Scale
Metered Service Microsoft* – subscription + metered (Azure) 12.02
Subscription
Netflix – 9.82
8-12X Revenue, if predictable future twelve vs.
TTM
Transaction Fee
eBay – 4.33
4-6X Revenue
Services Revenue
Consulting, unless is shortens other revenue sales
cycle. .75-1.5X Revenues
*Bigco data is blended revenues