Everest Ventures Group, 2024–2026

From waitlist signups to product activation

I helped drive 100K+ signups to our prelaunch waitlist. A month or two after soft launch, fewer than 1K people were active in the product itself, and every campaign cost engineering time. I proposed moving acquisition into the product through partner startups. Testnet grew to about 40K users, and launch brought 10K+ users transacting with real money, with about 90% of acquired users coming through partners.

Product
Marketplace where professionals earn from their knowledge
Stage
Private beta to launch, 1–2 months after soft launch
Team
6-person non-engineering team
My role
Growth Marketing Manager, reporting to the founder
<1K → ~40K

users in the product, before the switch vs. testnet

2–3K

average daily active users on testnet, peaking at ~6K

10K+

users after launch, transacting with real money

~90%

of acquired users came through 10 partner startups

100K+ people signed up. Under 1K were active in the product.

I had helped drive signups to the prelaunch waitlist, a dashboard built separately from the product. A month or two after soft launch, activity was still concentrated on that dashboard. In the product, where it mattered, fewer than 1K people were active: answering questions on the free core flow, the first step toward paid use.

Engineering was already stretched, and every new campaign needed it to build custom tasks. The challenge wasn’t acquiring more users. It was attracting high-intent users who would actually use the product, quickly, without acquisition overhead growing with every campaign.

Where campaigns ran

Custom prelaunch waitlist

  1. Promotional campaign
  2. Custom campaign tasks
  3. Registrations
Engineering work, every campaign
Signups didn’t turn into use
Where value is created

The product

Usage below expectationsEngineering time spent on campaigns was time not spent here.

So I proposed moving acquisition into the product itself.

Instead of asking people to complete promotional tasks for a future product, we would give them a relevant reason to try the real one immediately.

The founder had backed the waitlist approach. I brought him the conversion data with an alternative, and the numbers made the case. I conceptualized and set up the first campaign within 1–2 days.

Use the product itself as the acquisition experience, instead of building separate infrastructure to attract signups.

Old approachWhat I proposed
Who we reachA broad audienceUsers of partner startups on the same platform, already active and spending
Where people landA waitlist for a future productThe real product
Built per campaignCustom tasks, by engineeringNo custom tasks: existing features
What we learnRegistration countsReal usage and product feedback

  • Why partner startups

    Partners were consumer startups on the same blockchain platform, Berachain, so their users already held assets there and could try us in one step. Like SaaS companies serving each other’s customers.

  • The evidence behind it

    Participation patterns and spending signals suggested earlier campaigns reached a broader audience than the product needed.

  • The bet

    People try a new product more readily when their first interaction is about a topic they already care about.

Each campaign turned a conversation a community was already having into a question answered in the product.

Example: Yeet community members were debating why they had permanently destroyed valuable digital collectibles. That debate became a rewarded question in the product, so taking part meant using it. It was our first partner campaign: seven days, December 16–22, 2024, including picking the winner and distributing the reward. It drew 80+ participants.

  1. 1Yeet Discordbefore the campaign

    Why would anyone burn their own NFT?

    A recurring conversation and running joke in the community

  2. 2In the productofficial account, Dec 16, 2024

    “Why did you burn your NFT?”

    10K YEET to the best answer

  3. 3In the producta participant’s answer

    “My dog threatened to push me off a building if I didn’t burn it.”

Original answer posted in the product by basic_de…: an ASCII drawing of someone throwing an NFT off a building, captioned “Just burn it yeetard”, “I heard Yeet NFTs are deflationary & will accrue value…”, and “My dog threatened to push me off a building if I didn’t burn it”
  1. The conversation. The topic already existed; we gave it somewhere to go.
  2. The question. Answering meant using the product’s core feature.
  3. The answers. One of 80+ participants, answering in the community’s own voice.

Public record of the campaign on X: announcement (Dec 16, 2024), mid-campaign update (Dec 18), finale (Dec 19). The answer is quoted from an original screenshot (view original); the conversation and question are transcribed from the campaign.

Because no custom builds were needed, the model ran across 10 partner startups, and each cycle got faster.

Reusing the concept cut setup from 1–2 days to about one. Participation data also showed most people joined in the first days of that first seven-day campaign with Yeet, so I proposed an active run of two days. Participation in the next campaign was similar or slightly higher.

Changed for each partner

  • Communityrelationships set up with the founders
  • Topic or task
  • Rewardlow-cost rewards

Stayed the same every time

  • Existing product features
  • Participation inside the product
  • Feedback to the product team

Format 1: Community recognition

Rewards tailored to a community, earned through tasks completed in the product.

Format 2: Interest-driven questions

Rewarded questions drawn from conversations already happening in the community.

From under 1K active users to 40K on testnet and 10K+ with real money.

  1. Prelaunch100K+

    waitlist signups

    Activity on the dashboard, not the product
  2. Soft launch, before the switch<1K

    active in the product

  3. Testnet, practice money~40K

    users

    2–3K average DAU, peak ~6K
  4. Mainnet launch, real money10K+

    users

~90% of acquired users came through partner campaigns, which ran throughout testnet and launch alongside other launch activity. Stages use different measures (signups, users, daily actives), not one cohort.

Delivered

  • Into the productcampaigns ran on existing features, without custom prelaunch builds
  • 10 partner startupson two reusable campaign formats
  • 1–2 days → ~1 daysetup per campaign, by reusing the concept
  • 2-day active runafter most joins came in the first days of a 7-day campaign

Observed

  • ~90% of acquired userscame through partner collaborations
  • 80+ participantsin the Yeet campaign; ~60% revisited or logged in within 1–2 weeks
  • Real feedbackbugs and usability issues found by real users

Approximate internal figures and project observations, not audited data.

Not shown here

  • Paid conversion (a separate case study)
  • Long-term retention
  • Repeat core-product use
  • Engineering hours or cost saved

What I owned, and who I worked with.

I did

  • Spotted the signups-without-usage problem and proposed the shift
  • Developed the activation concepts, participation mechanics and messaging, and ran execution for both formats
  • Found the campaign-length pattern and pitched the 2-day window

With

  • FoundersHelped establish the partner relationships.
  • EngineeringBuilt and owned the platform the campaigns ran on.

What I’d do from day one

Measure the activation that matters, not the signup count.

Here that meant answering questions on the free core flow: the action that helps users and leads toward revenue. Counting waitlist signups hid weak activation until after soft launch.

Growth isn’t just about acquiring more users. It’s about creating meaningful product activity relative to the resources required.

What happened next. The partner model ran through the first product’s private beta and launch. The company later pivoted to a second product and eventually shut down; this case covers the first product’s acquisition phase.

Measurement note. Signup, user, DAU, acquisition-share, participation and revisit figures are approximate, from internal figures and observations during the project. Underlying records aren’t available for independent verification, and the campaign comparison was not a controlled experiment.