The 10x Product Launch

A stage-based product launch strategy that prioritizes the right risks.

You’ve painstakingly defined and built an MVP through 100+ customer interviews. You’ve collected thousands of emails from potential prospects through a teaser page. You’re ready to launch. But…

The engineer in you is worried about some real technical risks. You’re pushing the envelope using a new type of database — is the database partitioned correctly? Will it scale? Should you wait and run more tests first?

The marketer in you is worried about your pricing and positioning — can you justify charging for your MVP? Are you delivering enough value? Have you picked the right price? Maybe you should wait to add a few more features or defer charging to later?

A popular solution is launching as a “private beta,” — allowing you to incrementally roll out your product, keep early customer expectations at bay, and defer the pricing question under the guise of gaining more learning first. While this approach certainly appeases our inner fears, it is often the cop-out approach.

The purpose of the MVP is to get your product in front of customers to start the process of learning, but not all learning is equal. You need to prioritize learning about the riskiest parts of your product first.

For most products, technical risk ain’t what’s riskiest.

Launching a new product can be daunting because you have to simultaneously juggle multiple products, customer, and market risks. I’ve been fielding some of these tradeoffs lately with the upcoming launch of a new SaaS product — USERcycle, and devised the following 10x launch plan.

The 10x Product Launch Plan

Here’s the general idea:

10X Launch

Like the “private beta”, the 10x launch uses a staged rollout. But unlike the private beta, it completely avoids any connotations around “being in beta.” You must demonstrate strong product conviction and be ready to rigorously test those convictions from day one.

Additionally, the staged rollouts use a logarithmic step function (10x) that prioritizes risk at each stage.

What is the right prioritization of risk?

The Lean Canvas below charts the path I use for systematically tackling the three types of risks:

Product Risk — Getting the product right

1. First, make sure you have a problem worth solving.
2. Then define the smallest possible solution (MVP).
3. Build and validate your MVP at a small scale (demonstrate UVP).
4. Then verify it at a large scale.

Customer Risk — Building a path to customers

1. First, identify who has the pain.
2. Then narrow down to early adopters who want your product now.
3. It’s okay to start with outbound channels.
4. But gradually build/develop scalable inbound channels — the earlier, the better.

Market Risk — Building a viable business

1. Identify competition through existing alternatives and pick a price for your solution.
2. Test pricing first by measuring what customers say (verbal commitments).
3. Then, by what they do.
4. Optimize your cost structure to make the business model work.

Putting 10x in Action

Stage 1: Use interviews to recruit ten early adopter customers

  1. Use problem interviews to find a problem worth solving and identify your prototypical early adopter.
  2. Put up a “problem focussed” teaser page and collect email addresses.
  3. Use solution interviews to define your MVP and recruit your first 10 “early adopter” customers (not users) — they pay you from day one. If you nail the right problem, this shouldn’t be difficult. Make a bold promise, keep pricing simple, and back it up with a high-touch concierge MVP model and/or money-back guarantee.
  4. Build your MVP and validate that it delivers on your Unique Value Proposition.

What’s happening here?

  • The first objective is finding motivated early adopters, not on-the-fence users.
  • Early adopters are as visionary as you but from the problem perspective.
  • Customer interviews are a great way to qualify early adopters.
  • Plan on talking to 100 prospects to find the right ten early adopters.
  • Starting with just ten customers defers technical risk for testing market risk.
  • The first key metrics are activation, retention (and revenue).

Stage 2: Use an email list to find the next 100 customers

  1. Use your ten early adopters to help find the next batch of customers (they pay you too).
  2. Supplement the rest by setting up more solution interviews using your email list.
  3. Collect customer testimonials / case studies.
  4. Start building a marketing website.

What’s happening here?

  • Exercise full AARRR user lifecycle (adding referral) to validate compelling UVP.
  • Test early channels for user acquisition.
  • Use refined positioning and social proof to build a compelling marketing website.
  • Plan on 1,000 person email list to yield 100 customers.

Stage 3: Use a marketing website to acquire the next 1,000 customers

  1. Use your marketing website to sign-up users.
  2. Use your learning to define multiple pricing plans, including a freemium option if one makes sense.
  3. Manage the full user lifecycle from visitor to sign-up to paid.

What’s happening here?

  • Strong early adopter testimonials should help drive latter-stage customers.
  • Usage patterns of existing customers help define optimal pricing plans.
  • Move towards a more automated self-serve model.
  • Start tackling scaling risks.

Stage 4: Build your engine of growth for the next 10,000 customers

  1. Start testing other customer acquisition channels.
  2. Optimize cost structure.
  3. Optimize the AARRR funnel.

What’s happening here?

  • Product/Market Fit
  • Shift from finding a plan that works to accelerating that plan

Why 10x works?

Maximize learning (about what’s riskiest) per unit time.
You don’t need a lot of users to learn. Just a few good customers.
If you can’t convert a prospect in a 20 minute face-to-face meeting, it’s much harder to convert an unaware visitor in 8 seconds on your landing page.
Pricing is not only part of the product but defines your customers.
Start building a path to customers from day one — start direct to maximize learning before automating.

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