Freemium and Virality for Startups

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FREEMIUM AND VIRALITY FOR STARTUPS

Freemium

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Why study Freemium?

Pricing is tricky...how should we think about the Freemium pricing model?

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People say stuff

“As for me, all I know is that I know nothing”

“Don’t rely on buzzwords - think through the problem

Socrates

The Psychology of Free

• “Zero as emotional hot button - source of irrational excitement” - theLindt/Kisses experiment

• Free removes the psychological barrier of the downside(automatically make us think that there’s no risk involved althoughthere might be)

• The Penny Gap - it is much harder to get someone to pay the firstpenny than to upgrade them from a penny to 20 cents.

The Economics of Free

In economic theory - a software product is an experience good -

a product or service where product characteristics such as quality or price are difficult to observe in advance, but these characteristics can be ascertained upon consumption.

“The fact was that Dropbox was offering a product that people didn’t know they needed until they tried”

Shapiro - “Optimal Pricing of Experience Goods”

Quality underestimated Contribution to current profit

Favorable quality information - augments future demand= +

“The seller can mitigate the problems of skeptical consumers by using a low introductory price, and it is optimal to do so. The seller's optimal policy consists of a low introductory price followed by a higher price which is maintained forever.”

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How Freemium worked for LinkedIn

Premium Subscriptions. Revenue from our premium subscriptions is derived primarily from online sales of our Business, Business Plus and Executive subscription products. These products provide our members, acting as individuals or on behalf of their enterprises or professional organizations, with access to more tools and features than our free membership, including enhanced search results, enhanced communication capability, improved organizational functionality and priority customer support.0

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HR servicesAdvertisingPremium

How Freemium worked for Dropbox

Broken Economics - LTV of $99 on $300 CAC led to focus on Freemium + strong referral program

A framework to think through freemium

Direct Revenue from free users

(Advertising, selling data)

Promotional value from free users

Inherent value to other users

Value added to other users

No value added to other users

Virality

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They are telling you only a part of the story...

Word of mouth?

The 8 types of virality - inherent

WhatsappBest kind of virality. Users invite other users because this is the only way they can use the product. Causes very strong network effects.

The 8 types of virality - collaborative

Users invite other users because they want to collaborate with them. In this case - the product is still useful as a stand alone.

The 8 types of virality - communication

Riding a communication channel with a digital signature. Every message that is sent is spreading the work about the product.

The 8 types of virality - incentivized

Users invite other users because of an incentive. In Dropbox’s case - extra space. For Gilt - $25.

The 8 types of virality - embedded

Works well for content websites / products. Creating a “widget” that can be embedded in other websites and helps spread the word.

The 8 types of virality - signature

Great for products that are used off site (Kampyle, Uservoice). In this case there’s a logo signature that promotes the product. This will many times be removed for paying users.

The 8 types of virality - social

“Riding” a social network can lead to exponential growth. Users are spreading the word by simply using the application. Their activities are broadcasted to the whole social graph (think Zynga, Spotify, Pinterest)

The 8 types of virality - pure word of mouth

Sometimes, when the product is special or adds a lot of value, there’s a pure word of mouth effect. This was very strong in the early days of Groupon (especially since it started locally).

The formula

There’s a clear formula for virality with which you can calculate the viral effect.

The two important parameters are:K - Viral Coefficient. How many new users each user brings?p - Cycle Time. How long does it take a user to bring in new users?

You can then calculate how many users you will have in time t given the users in time 0.