The product team had spent six months building our most requested feature. Customers had been asking for it for years. Support tickets referenced it constantly. Sales said it would unlock enterprise deals.
We launched it with full fanfare: blog post, email campaign, in-app announcement, sales training, the works.
Two weeks later, I checked the adoption numbers.
8% of active users had even tried it.
Not "adopted it regularly." Not "found it valuable." Just... opened it. Clicked on it once. 8%.
The product team was devastated. "Why did we spend six months building something nobody wants?"
But that wasn't the problem. Users did want it—they'd been requesting it for years. The problem was simpler and more frustrating:
Most users didn't know it existed.
This is the harsh reality of feature launches: Shipping a feature and getting users to adopt it are completely different challenges.
The Launch Illusion
Here's what we did for the launch:
Pre-launch:
- Built the feature over 6 months
- Beta tested with 20 customers
- Prepared documentation and help articles
- Trained support team
- Briefed sales team
Launch day:
- Published blog post announcement
- Sent email to all users
- Added in-app banner
- Posted on social media
- Created walkthrough video
By all conventional standards, this was a good launch. Coordinated. Multi-channel. Clear communication.
So why did only 8% of users try it?
I dug into the data to understand what happened to our launch communications:
Blog post: 1,200 views (our active user base was 15,000) Launch email: 18% open rate, 3% click-through In-app banner: Dismissed by 94% of users within 2 seconds Walkthrough video: 340 views
Even our best-performing channel (the blog post) only reached 8% of our user base.
The uncomfortable truth: Most users never saw the announcement. And the ones who did mostly ignored it.
We'd spent 6 months building the feature and 2 weeks planning the launch. We'd spent zero time thinking about what happens after launch day.
Launch creates awareness. Adoption requires ongoing education, prompts, and friction removal.
We treated launch like a one-time event. It needed to be an ongoing campaign.
Why Users Ignore New Features
I interviewed 30 users who hadn't tried the new feature. I expected to hear: "Didn't need it" or "Didn't see the value."
What I actually heard:
"Oh, you launched that? I must have missed the announcement."
"I saw the email but was in the middle of something. Meant to check it out later but forgot."
"I don't usually read product update emails. Too many emails already."
"I saw the banner but assumed it was an ad for something premium I'd have to pay for."
"I didn't realize it solved [their specific problem]. The announcement made it sound like it was for different use cases."
Only 2 of the 30 users said they didn't need the feature. The other 28 either didn't know it existed or didn't understand how it applied to their specific workflow.
This wasn't a product problem. It was a product marketing problem.
We'd assumed: "If we announce it, users will see it and try it."
Reality: Users are busy, distracted, and don't pay attention to product announcements unless you make it impossible to miss AND make the value immediately obvious.
The Real Feature Adoption Playbook
After watching our launch flop, I built a new playbook for feature adoption. The next feature we launched using this playbook hit 42% adoption in the first 30 days.
Here's what changed:
Pre-Launch: Identify Target Users
Instead of launching to everyone at once, we identified which users would get the most value from the feature.
We segmented users by:
- Current behavior patterns (which workflows they use)
- Problems they'd reported to support
- Account attributes (company size, industry, plan level)
For our failed feature, the target users were: accounts with 5+ team members who were currently using Feature X but manually doing the job that our new feature automated.
We identified 2,400 users (16% of our base) who fit this profile.
Instead of announcing to all 15,000 users, we focused adoption efforts on the 2,400 who would get immediate value.
Launch: Value-First Messaging
Our original launch email subject line: "Introducing [Feature Name]"
Our new approach: "Stop manually [doing task]—we just automated it"
Old messaging focused on the feature. New messaging focused on the problem it solved.
Old email body: "We're excited to announce [Feature Name], a new capability that lets you [technical description of what it does]..."
New email body: "If you've ever spent 30 minutes manually [doing task], we just saved you that time. Here's how..."
The difference: Old version told users what we built. New version told users what problem they could now stop having.
Open rate on the new email: 47% (vs. 18% on original launch email) Click-through rate: 24% (vs. 3% on original launch email)
Post-Launch: Contextual In-App Prompts
The in-app banner we used for the first launch was generic: "New Feature: Try [Feature Name]"
It appeared on every page. Users dismissed it immediately because it interrupted what they were doing.
New approach: Contextual prompts that appear only when relevant.
We placed prompts:
Location 1: In the exact workflow where users were manually doing the task our feature automated
Timing: Right after they completed the manual task
Message: "You just spent 15 minutes on [task]. Want to automate this in 1 click?"
Location 2: On the results page where users would benefit from the new feature's output
Message: "See that data? You can now [do new thing] with it using [Feature Name]. Want to try?"
These contextual prompts had 10x higher engagement than generic banners because they appeared at the moment of maximum relevance.
Ongoing: Weekly Adoption Campaigns
Instead of treating launch as a one-week event, we ran a 6-week adoption campaign:
Week 1: Email announcement to target segment Week 2: Webinar showing real use cases Week 3: Case study from beta customer who got results Week 4: In-app tutorial series (3 short lessons) Week 5: "Office hours" where users could ask questions Week 6: Email showcasing results: "500 customers have saved 1,000+ hours using [Feature]. Here's how..."
Each week reinforced the message through a different channel and angle.
By week 6, adoption had climbed from 8% to 42% among target users.
Measurement: Adoption Funnel, Not Just Usage
We started tracking adoption as a funnel, not a binary metric:
- Awareness: User saw announcement (measured by email opens, banner impressions)
- Interest: User clicked to learn more (measured by help doc views, video views)
- Trial: User tried the feature once (measured by first-time use)
- Adoption: User used it 3+ times in 30 days (measured by repeat usage)
- Habit: User uses it weekly (measured by sustained usage)
For our failed launch:
- 35% reached Awareness
- 12% reached Interest
- 8% reached Trial
- 3% reached Adoption
- 1% reached Habit
We were losing users at every stage of the funnel.
This helped us identify where to focus efforts. The biggest drop-off was Awareness → Interest (23 percentage points), which told us our messaging wasn't compelling enough.
Iteration: Listen to Why Users Don't Adopt
I interviewed users at each stage of the funnel to understand why they dropped off:
Users who saw announcement but didn't click (Awareness → Interest): "I didn't understand how it applied to my workflow" "The announcement made it sound complicated" "I thought it was for enterprise customers only"
Users who clicked but didn't try (Interest → Trial): "The setup looked complicated" "I wasn't sure what data I needed to prepare" "I planned to try it later but forgot"
Users who tried once but didn't adopt (Trial → Adoption): "It didn't work how I expected" "Results weren't better than my current method" "Too many steps to get value"
Each piece of feedback pointed to specific fixes:
- Messaging clarification
- Simplified setup flow
- Better onboarding for first-time use
- Faster time-to-value
We iterated on the feature and the adoption campaign based on this feedback.
What We Changed About Feature Launches
The failed launch taught us that launch ≠ adoption. Now we approach feature launches completely differently:
We Define Success as Adoption, Not Announcement
Old success metric: Did we announce it on launch day? New success metric: What percentage of target users are using it regularly 60 days after launch?
Launch day is just the beginning. Real success is sustained usage.
We Segment Target Users Before Launch
Old approach: Launch to everyone simultaneously New approach: Identify the users who will get the most value and focus adoption efforts on them first
Once we hit 40%+ adoption with the target segment, we expand to broader audiences.
We Run Adoption Campaigns, Not Launch Events
Old approach: Big announcement on launch day, then move on New approach: 6-week campaign with weekly touchpoints, education, and prompts
Adoption requires repetition. Most users need to see the message 5-7 times before they try something new.
We Use Contextual Prompts, Not Generic Banners
Old approach: In-app banner on every page saying "New feature available!" New approach: Contextual prompts that appear in the exact workflow where the feature adds value
Context drives adoption. Generic announcements get dismissed.
We Measure and Optimize the Adoption Funnel
Old approach: Track "% of users who tried it" as a single metric New approach: Track Awareness → Interest → Trial → Adoption → Habit as a funnel
This shows exactly where users are dropping off and what to fix.
The Features That Get Adopted vs. The Ones That Don't
After launching 12 features over two years, I've noticed patterns in which features get adopted and which don't:
Features with high adoption (40%+ within 60 days):
- Solve a visible, frequent pain point
- Deliver value in the existing workflow (no context switching)
- Have fast time-to-value (can see results in <5 minutes)
- Are discoverable at the moment of need
Features with low adoption (<15% after 60 days):
- Solve edge case problems most users don't have
- Require leaving current workflow to access
- Have slow time-to-value (need setup or data accumulation)
- Are only discoverable if users read announcement emails
The harsh lesson: You can't marketing your way to high adoption of a poorly designed feature.
If the feature requires users to change their workflow, learn a new interface, and wait days for value, no amount of promotion will drive adoption.
Good product marketing can 3x feature adoption. But it can't fix fundamental product design issues.
Before investing in adoption campaigns, ask:
- Does this feature solve a problem users have frequently?
- Can users access it without leaving their current workflow?
- Can they get value in under 5 minutes?
- Will they discover it at the moment they need it?
If the answer to any of those is "no," fix the product design before investing in promotion.
The Uncomfortable Truth About Feature Launches
Most product teams celebrate shipping. They treat launch as the finish line.
Launch is the starting line.
Shipping a feature means you've built the capability. Getting users to adopt it is a separate challenge that requires ongoing effort.
The gap between shipping and adoption is where most features die.
Teams ship features, send one announcement email, then move on to building the next thing. Three months later, they're surprised that nobody uses the feature they worked so hard to build.
What doesn't work:
- One-time launch announcements
- Generic in-app banners
- Assuming users read product update emails
- Treating launch as a one-day event
What works:
- 6-week adoption campaigns with weekly touchpoints
- Contextual in-app prompts at moment of need
- Value-first messaging focused on problems solved
- Segmented rollout to target users who need it most
- Adoption funnel measurement showing where users drop off
The teams that drive feature adoption:
- Define success as sustained usage, not announcement
- Identify target users and focus adoption efforts on them
- Run multi-week campaigns, not one-day launches
- Use contextual prompts in the workflow, not generic banners
- Measure adoption funnel and iterate based on drop-off points
The teams with low feature adoption:
- Treat launch as a one-time event
- Send announcement to everyone without segmentation
- Use generic "new feature available!" messaging
- Only measure "did users try it once?"
- Move on to next feature without optimizing adoption
I was on the second team until a feature I spent six months on launched to 8% adoption.
Now I spend as much time planning the adoption campaign as I do planning the launch.
Because a feature that ships but doesn't get adopted might as well not exist.