If you've determined that virality is worth pursuing, you need to understand the four main types of viral loops and their characteristics.

Word-of-Mouth Virality: The Brand-Driven Loop

What it is: Users love your product so much they naturally tell others about it.

Characteristics:

• Ramp-up time: Moderate (improves as product improves)
• Ceiling potential: Moderate
• Control level: Indirect (function of product quality and brand)

Word-of-mouth is fundamentally a trailing result of core product value. It gets better as your product gets better, but you have less direct control over it. The implementation strategy is primarily building the best product possible—which is why everyone is pursuing some form of virality even if not explicitly.

Best for:

• Apps that solve painful, visible problems
• Products with clear, measurable outcomes
• Brands people feel good about using

Examples:

• Notion: Users share templates and workflows because it makes them look organized and productive
• Duolingo: The owl mascot and streak features are memorable enough that users naturally mention their language learning
• Netflix: Their witty social media and culture makes subscribers want to share and engage with the brand

The brands that win word-of-mouth make every touchpoint remarkable. When Netflix writes a cease and desist letter that goes viral because it's hilarious, they're turning legal communications into brand advocacy moments.

Messaging like that could convert users—and even prospects—into brand advocates. Netflix subscribers who get the references and inside jokes will delight in the connections they feel.

Pull Virality: The Network-Driven Loop

What it is: Your product becomes more valuable when users invite others to join them, so they actively pull people in.

Characteristics:

• Ramp-up time: Medium (requires product-market fit)
• Ceiling potential: High
• Control level: High (you can optimize invitation flows)

Note: Pull virality often co-occurs with network effects (where the product gets better with more users), but they're not the same thing. Network effects increase product value; pull virality is the acquisition mechanism.

Best for:

• Social apps and platforms
• Messaging and communication tools
• Collaborative work products
• Any app where having friends/colleagues makes it better

Examples:

• Slack: You invite your team because the product only works when everyone's on it
• Figma: Designers invite stakeholders to comment on designs
• Venmo: You add friends so you can easily split bills and send money
• MarkUp lets you leave comments on design mockups. In order to leave feedback on a design, you have to use MarkUp.
• Spotify users can create playlists of their favorite songs, then share them with friends or anyone else who might be interested.

The key insight: Users pull others in because they need them to participate to get full value from the product.

Push Virality: The Content-Exposure Loop

What it is: Normal product usage naturally exposes your brand to potential customers.

Characteristics:

• Ramp-up time: Long (requires exceptional product-market fit)
• Ceiling potential: Highest
• Control level: Medium (you can optimize shareability)

Push virality has the steepest growth curve once it hits critical mass, but it takes longest to develop. Users need to be creating and sharing content that others want to see. Our virality flywheels also serve as content flywheels. Any model where users are generating content (whether distributed by users or the company) is a form of virality and content.

Best for:

• Apps that create shareable content
• Products with visible outputs
• Services with public-facing elements

Example: Electric scooters and Segway

Two similar products had very different virality paths.

The launch of Segway in 2001 was centered on word-of-mouth virality: getting people to talk about the product as a way to build anticipation. Everyone was talking and writing about the incredible invention that would be coming to market soon. It would be “revolutionary,” Jeff Bezos said. “As significant as the personal computer,” Steve Jobs said.

The problem was that no one actually knew what the product was. They just knew who the inventor was (the millionaire Dean Kamen) and that Harvard Business School Press had already acquired a book about it for a quarter million dollars. The Harvard editors didn’t even know what the product was.

That could have all been great. Except that when the product actually debuted, the response was a collective huh? It wasn’t a game changer. It was a mall cop transporter. The Segway flopped. Hard.

Compare that to electric scooters. Those emerged on the market more gradually. City-dwellers started using them to get around, with urban centers like San Francisco and San Antonio acquiring thousands of them to improve sustainable transportation options.

As more people used electric scooters along city streets, they gained visibility through push virality. They demonstrated their usefulness in action. Global revenue for the electric scooter market grew 9.8% from 2020 to 2021, with sales expected to triple between 2021 and 2031.

The takeaway: Push virality works—but only if your product has core value and solid market fit.

Electric scooters offer a clear value—they’re an easy, affordable way to get around—and they fit in a market that cares about reducing emissions. At Segway, on the other hand, the marketing team couldn’t validate product-market fit because they couldn’t tell anyone what the product was!

In fact, core product value and product-market fit are essential for all virality types. If users don’t love your product, they won’t pull others into it. They won’t talk about it. And they won’t recommend it to their friends no matter the incentive (unless they don’t really like those friends).

Everything goes back to your product. And the value users get from it.

Other Examples:

• TikTok: Every video shared to other platforms exposes the TikTok watermark
• Canva: "Made with Canva" watermarks on free designs
• VSCO: Edited photos shared to other social platforms often drive people to ask "what filter is that?"

This is often a nice-to-have rather than essential. Don't force it if it doesn't fit naturally.

Incentivized Virality: The Reward-Driven Loop

What it is: Users refer others in exchange for rewards (credits, discounts, premium features).

Characteristics:

• Ramp-up time: Fast (immediate motivation)
• Ceiling potential: Lowest (network effects fade quickly)
• Control level: Highest (you set the incentives)

Critical insight: Incentives don't create virality. They amplify existing sharing behavior.

Incentivized virality works when ALL three conditions are met:

1. Users already have some desire to share (social or utility capital)
2. The referral action connects to your product's core value
3. The reward aligns with what users actually want

Best for:

• Apps with clear economic value
• Services where word-of-mouth needs a "nudge"
• Products with strong unit economics that can afford rewards

Examples:

• Cash App: Cash rewards for referrals make sense for a money app
• Spotify: Free Premium months for referrals reduce churn and align with user value
• Dropbox: Extra storage rewards connected directly to the core product benefit

Budget considerations: Your target customer acquisition cost (CAC) is the maximum incentive you can afford. If your target CAC is $30, you could offer a $30 discount on their monthly subscription or $15 to both the referrer and referee. Use the target CAC you calculated in your Growth and Guardrails module as your ceiling.

Managing referral fraud: Users will try to game the system, but your risk varies based on what you reward:

Higher risk (TOFU rewards): Paying for signups, downloads, or free trial starts. Easy to fake with disposable emails or fake accounts.

Lower risk (BOFU rewards): Paying only when referred users become paying customers or complete meaningful actions. Harder to fake and aligns with your business goals.

Common mistakes:

• Generic rewards that don't match your product (Amazon gift cards for a meditation app)
• Pushing referrals before users understand your value
• Complex rules that confuse users
• Rewarding top-of-funnel actions instead of meaningful conversions

Most successful incentive programs build on top of existing organic sharing behavior.