Linked Helper
/ Tandraft
How customer language became a product strategy and a landing page for controlled personalization.
The design problem
Linked Helper combines AI messages, custom variables and conditional logic. The challenge was to explain that depth without making the first interaction feel complex.
I worked from the assignment and supplied research materials to develop the positioning, information architecture, content and responsive landing-page prototype. The central question: how can people scale outreach while retaining control of each message?
- My role
- Research synthesis, product strategy, UX architecture, content design, UI and prototyping.
- Inputs
- Assignment brief, product documentation, review dataset, search snapshot and competitor sources.
- Deliverables
- Research presentation, messaging framework and interactive EN/RU landing page.
- Status
- Independent concept. No client launch or measured business impact is claimed.
What the evidence showed
The detailed thematic review covers 768 G2 reviews: Linked Helper (142), Waalaxy (528) and Expandi (98). The broader competitor comparison uses a different cohort of 1,445 reviews across seven products.
- Ease and clarity · 343/768
- 44.7%
- Time saved · 132/768
- 17.2%
- Personalization · 92/768
- 12.0%
- Complexity and learning · 72/768
- 9.4%
Share of the 768-review cohort. One review can match several themes. This is secondary research using a supplied dataset, not interviews, a representative market survey or a causal study. The two cohorts and their coding are not interchangeable.
Method, sources and limitationsFrom evidence to design
- Make control the value proposition
- The reviews describe both useful flexibility and a learning curve.
- Design decision: Position the concept around personalization people can control, rather than an inventory of AI features.
- Explain the mechanism through decisions
- A user needs to know which context is used, what happens when it is missing and who checks the result.
- Design decision: Structure the demonstration around data, rules, a draft and human review. Show a fallback example alongside the rule.
- Place reassurance before the next commitment
- The first campaign and the activation of a trial license are different steps.
- Design decision: Make the trial path explicit, explain what happens after the CTA and define a separate first-campaign success event.
What was built
An interactive landing-page concept and a complete, linked research presentation. The prototype lets visitors compare personalization modes and example recipients, inspect fallback logic and see the review step.
My product-design contribution is the traceable connection between evidence, positioning, page structure and interface behavior. The result is a testable design proposal; higher conversion or reply rates have not been demonstrated.
What I would validate next
Before calling the concept successful, I would test the assumptions it depends on:
- Comprehension: can a new visitor explain the personalization mechanism and the human-review step?
- Usability: can people choose context, understand a missing-data fallback and locate draft review?
- Activation: track the path from landing-page visit to trial start and first campaign, with clear event definitions.
- Business impact: measure against a baseline; use a controlled experiment where traffic permits.