0→1 · ADOPTION · MOBILE + WEB
Winning Back Users Who’d Already Given Up on the Product
COMPANY
CINC · Real Geeks
ROLE
Lead Designer
EXPERTISE
Design Sprint Facilitation · UX Research · UX/UI Design
YEAR
2026
8 → 291 unique users calling in the first 12 days after launch
3,400+ calls in under two weeks
Users who had paid for third-party tools came back
The hardest product to fix isn’t one nobody has tried. It’s one people tried and gave up on.
The dialer is the most important tool in a real estate agent’s day. Leads become appointments through conversations, and every conversation starts with a dial. It should have been the most-used feature in the app. Instead, people went out of their way to avoid it.
It ran on a single line, couldn’t record or summarize calls, and dropped close to a third of its connections. On smaller phones it hid its own Start Dialer button, and once the call modal was dismissed, there was no way to bring it back. So users did what people always do with a tool that fights them: they stopped using it. They called from desktop, from their personal phones, or paid out of pocket for Dialpad.
The product technically existed. In users’ real workflows, it didn’t. That made this a 0→1 problem, not a refresh: design the version people would choose for the first time.
Winning back a user who has written you off is a different problem than improving something they like. There’s no benefit of the doubt.
The brief:
“How might we optimize the web and mobile dialer to increase productivity, reduce friction in lead engagement, and use modern dialing technology to drive better connection outcomes?”
The tension I designed against:
Rebuild enough trust that people would open the dialer again
Without adding a relearning curve for those who had stuck with it
While making calling feel fast and reliable, not one more thing that might freeze mid-call
The insight underneath it all: people weren’t avoiding the dialer because they didn’t want to call. Calling is how they get paid. They avoided it because it made the most repeated moment of their day harder than picking up their own phone.
I ran this as a design sprint, built to earn the right to design before drawing a screen.
1. Separate assumptions from evidence
A product with near-zero adoption collects many theories about why. I brought the team’s theories into the open and had everyone vote, so we wouldn’t redesign on beliefs nobody had tested.
2. Turn the riskiest assumptions into research
I converted them into eight research areas, each with its own interview questions. That aimed our conversations at what we were least sure of, not what we already believed.
3. Talk to the people who use it daily
I interviewed three users across every role that touches the tool. Different comfort with tech, different workflows, but same product.
What I learned
Adoption was a trust problem, not a feature gap. No one was asking for one missing button. They had quietly routed around the tool entirely.
No recording or AI summary on mobile removed most of the value. The thing brokers wanted most for coaching and follow-up was the one thing mobile couldn’t do.
Unreliability had broken confidence. Freezes and failed connections taught users not to trust it with a live lead.
The workflow fell off a cliff after each call. There was nowhere to log an outcome or take notes.
Building a call list was hard, especially on a phone, on the go.
People wanted to move between desktop and mobile without losing their place.
I reframed the findings from the user’s point of view and had the team prioritize. A long pile of complaints became a short list worth solving.
The problems
The goals
I defined what winning would look like, short and long term, so the design had a target beyond “make it nicer.”
The risks
I also mapped how this could fail.
The biggest risk was never technical. It was shipping real improvements that burned-out users still refused to try, or solving the wrong problems. Both pointed to the same answer: let research, not instinct, decide what got built.
Solution Sketches
Lightning demos surfaced proven patterns from the tools users had switched to. Then I sketched fast and wide with Crazy 8s, pushing past obvious answers toward an AI-assisted dialer: an activation flow, a live call screen with recording, a post-call summary, and a queue built for working a list.
I split the work into two user story maps, Single Dial and Mass Dial. Calling one person and working through a list of a hundred are different jobs and shouldn’t share one screen.
Every decision traced back to something a user told me.
1. Bring call recording and AI summaries to mobile. Signal: the most-voted mobile gap (12 votes), and the reason one user had left for Dialpad. Decision: make recording and post-call summaries core features on mobile, with a consent step when a call starts. Tradeoff: the consent step adds a beat of friction to a flow I was speeding up. It’s legally required, and handled well, it helps rebuild trust.
2. Make the dialer reachable from anywhere. Signal: “not available in all locations” (10 votes), and the top assumption that users need to call from anywhere in the platform. Decision: the dialer appears wherever a contact lives, instead of in one corner of the app. Tradeoff: more surfaces to design and maintain, but it’s the difference between a tool users hunt for and one that meets them where they are.
3. Add a wrap-up step between calls. Signal: “difficult to add notes and actions between calls” (6 votes), plus a call modal that couldn’t be reopened once dismissed. Decision: a post-call step that captures the outcome, notes, and next action before the next dial, and a queue that holds your place. Tradeoff: a deliberate pause at the end of each call. Skipping that step is exactly how leads used to slip through.
4. Treat mobile as a continuation of desktop. Signal: the top-voted assumption (7 votes) was that users want to switch devices without breaking stride. Decision: design mobile as a true continuation of desktop, not a stripped-down version. Tradeoff: it raises the bar for feature parity, but parity was the point. Users left mobile because it felt like a downgrade.
5. Make it obvious to find and start. Signal: the Start Dialer button was hidden on smaller phones. Decision: a clear entry point and an activation flow that shows users where they are. Tradeoff: it spends prime screen space on one action. For the tool that runs the user’s day, that’s the right call.
From Research to Delivery
A successful redesign needed more than a better interface. The team had to address the reasons users abandoned the product while preserving the workflows that existing users already knew.
I led the design process, translating research findings into prioritized workflows, interaction patterns, and high-fidelity designs. Working alongside product managers, engineers, and stakeholders, I helped align the experience around two distinct needs: making individual calls quickly and working through larger call lists without losing context.
The biggest design challenge was balancing speed with functionality. Recording, AI summaries, call dispositioning, and cross-device continuity all added value, but they also introduced complexity. Each decision needed to support the user's primary goal: completing calls efficiently and confidently.
Rather than treating individual features as separate improvements, I designed them as parts of one connected experience. The goal was to give users a workflow they could trust from the first call through the last.
The flows are organized around the two jobs research separated, Single Dial and Mass Dial. Each screen answers a specific signal from users.
The redesigned dialer launched on September 2, with adoption as the primary measure of success.
In the 12 days before launch, only 8 unique users placed calls through the iOS mobile dialer.
In the first 12 days after launch:
192 unique users placed calls through the redesigned iOS dialer, compared with just 8 before launch.
99 additional users placed calls through Android.
291 unique mobile users placed more than 3,400 calls across both platforms.
The iOS comparison alone represented a 24x increase in unique callers over the equivalent 12-day period.
For a product users had actively avoided, the early adoption was an encouraging signal. The redesign addressed more than discoverability. It made the calling experience useful enough for people to try again.
The next measure of success would be whether that adoption translated into sustained usage, more efficient workflows, and better calling outcomes over time.
When a product has been abandoned, more features won’t win people back. Trust will. That means finding the specific reasons people left and fixing those first. The team had plenty of theories about why adoption had died. Research turned them into a ranked, defensible list, and the design targeted the real reasons users left rather than the ones we assumed.