ayyaaz

/aɪ'æz/

ayyaaz

/aɪ'æz/

My Process

In a nutshell.

 

The Online Journey

Put simply, my UX process is evidence-based and data-driven:

  1. Gather evidence
  2. Make decisions based on that evidence
  3. Validate those decisions

These activities are conducted iteratively, in 'test and learn' cycles, and there are many techniques for gathering and validating evidence (qual and quan).

The Offline Journey

Focusing on why the product is used: the motivations and triggers. This part of the user's journey is where technology meets behavioural psychology.

Many of the decisions that the user makes, in their offline journey, are emotionally driven. If your product can find an emotional trigger to align with, it can achieve user engagement on a much deeper level.

This part of my role overlaps with marketing, but then UX is all about collaboration.

Clients I have worked with

Brands Brands Brands Brands Brands Brands Brands Brands Brands Brands

Projects

An insight into my process and the techniques I use to make design decisions.

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"Capture" project for James and James Fulfilment

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Experian EBC project

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Viking Direct project

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J&J website

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"Share checker" and "fidelity" prototypes

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Experian VMC project

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UX Skill Set

User journeys

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Information architecture and content strategy

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Wireframes

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Interaction design

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UI and visual design

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Design guidelines for UX, UI and CSS

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Mock-ups and coded prototyping

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Mobile UX

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User stories

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Google analytics

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A/B Testing

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Personae

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Card sorting

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Usability testing

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User interviews

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User task based analysis

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Quantitative analysis: Visitor stats and usage analysis

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Leveraging heat maps and visitor session recordings

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Competitor site/application analysis

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Interviews with stakeholders

Interviews with business stakeholders to ensure that business goals and objectives are crystallised and prioritised

Interviews with customers

Interviews with customer facing/focused departments such as call centres, support staff, and sales & marketing

Analysing metrics

Click through rate, conversion, average transaction value, bounce rate, dropout rate