Building Trust in AI Design

ditto is an AI-powered marketing assistant for small businesses and agencies. I co-founded it in 2023 and was its only designer until I left in 2025. My job was shaping how users experienced the product's core promise: let the AI handle your marketing content, and trust that it'll sound like you.

The second half of that promise was the hard part. Most of what I designed at ditto, from the first screen to the pricing page, was about getting people to trust it.

The Challenge

AI-generated content is only useful if people publish it. Marketing professionals clear that bar easily: they treat AI output as a draft and edit freely. Small business owners are harder to win. Their brand voice is personal. A post that sounds slightly off feels like a misrepresentation of who they are.

ditto also did most of its work automatically, which is a strange thing to onboard someone into. With so little for the user to actually do, the risk was that they'd feel like spectators, never sure whether the AI understood their brand. The experience had to prove that it did, without turning into a lecture.

Research & Discovery

I interviewed five participants: three marketing professionals and two small business owners. It's a small group, but the split between the two held up in every round of testing afterwards.

Marketing professionals were comfortable with AI-generated drafts as a starting point. They evaluated output critically and edited freely.

Small business owners were emotionally invested in their brand voice. They were sceptical that AI could capture their nuance, and needed reassurance before they'd engage.

The small business owners didn't object to AI. They objected to anything that might misrepresent their business, and they wanted ditto to prove itself before they gave it any work. So the design shows value first and asks for effort later.

Research insights, user segment comparison

Design Approach

Brand analysis as the trust foundation

An early product decision was having ditto analyse each user's existing marketing materials to learn their brand voice. I put that analysis on screen instead of running it silently, so users could see ditto learning about their business before it wrote anything.

Our first usability test backed that up. When our beta user saw ditto's first output, she hadn't expected it to sound so much like her business. We saw the same reaction from every business we onboarded afterwards. Once people said some version of "that sounds like me", they stopped being sceptical, so I designed the rest of the product to get them there as early as possible.

Onboarding that shows before it asks

The first version of onboarding asked users to connect accounts and fill in details upfront. Research kept telling us small business owners, especially solo ones, have no patience for setup. Every form field that came before a result felt like a cost. So I rebuilt the flow to get users to their first real campaign and pushed everything else later.

Three decisions shaped the redesign:

Background AI processing. While users moved through the steps, ditto analysed their materials behind the scenes, so they never had to sit through that part of setup.

The tutorial is the product. Rather than explaining ditto, onboarding walked users through creating a real campaign. The tutorial and the first result were the same thing.

Minimal, contextual UI. Each step showed only what that step needed, so new users were never presented with a wall of options.

Onboarding step-by-step flow

Testing cut it down further. We assumed users would want to see everything the AI had generated at once. In usability sessions, a few strong examples worked better than a long list, so I cut the volume and led with the best samples.

Control without friction

Even users who liked the output still needed small edits: a specific product, a current promotion, details the AI couldn't know. I designed a preview panel with three options: edit it, regenerate it, or publish it as-is.

The regenerate button came from watching people use it. Some found editing more work than starting over, and one click got them to something they were happy with faster.

Context preview panel with edit, regenerate, and publish options

Pricing that doesn't spend the trust

Subscription tiers were as much a UX problem as a business one. AI processing costs varied a lot by model, so I matched each task to the cheapest model that did it well, then defined tiers around content quantity and type. The free tier gave one high-quality pillar piece per week plus three social posts. Users nearing their limits saw a small prompt about the next tier. I left out countdown banners and anything else that felt like pressure, because it would have undone what the onboarding had built.

For the same reason, ditto used predefined flows instead of an open-ended chatbot. A chatbot would have demoed better. Predefined flows gave consistent output, and that's what our users cared about.

Subscription tier design

Designing with the engineer in the room

My co-founder was also our only developer, and every design I made was negotiated against two constraints he owned: what was feasible to build, and what it would cost to run. Those negotiations were frequent and sometimes blunt. Designs I believed in died because the AI processing behind them was too expensive, or because the build was more complex than a two-person company could carry.

I learned to bring cost and feasibility in early instead of defending finished mockups. Some of the product's best decisions came out of arguments I didn't want to have at first, including the model-to-task matching and the predefined flows.

Results

When I left in 2025, ditto had 8 businesses actively using it. Four of them had been running their content through it for months, publishing what it wrote week after week. Our first beta user, the one from that first usability test, was still publishing ditto's output directly to her social media a year on.

Ahead of its seed round, ditto received an independent $10M valuation. The product experience was part of that, though I can't say how much.

Key Learnings

No amount of reassuring copy did what that first accurate output did. Anything that delayed it (account connections, configuration, explanations) gave the user another reason to doubt.

The two groups needed different things. Marketing professionals went straight to editing. Small business owners wouldn't touch the output until they'd seen ditto get their brand right, so leading with the brand analysis mattered most for them.