## 🏢 Company overview

Attest is a startup that helps researchers and marketeers have confidence in every decision with quick, insightful consumer research. The platform brings together a flexible survey builder, large panel audience, data quality controls and results analytics tools into a single experience allowing researchers to get quick answers to their pressing questions.

## 🤔 Problem statement

Customers could technically run a single market brand tracker (a way of measuring your brands' performance in a market) on Attest, however, it was a series of single surveys that they then had to analyse in excel. Their Job To Be Done is to track their key brand metrics, and their specific problem with our current solution is they cannot see the difference in brand awareness metrics over time.

This was a key problem space for Attest with a sizeable amount of Net ARR and churn risk attached to it.

## 👥 Users

Marketing managers at growing startups. They have some experience with research/ data tools but not much. Their key job to be done is understanding if their marketing strategy is correct via brand awareness and other metrics. 

## 🌟 Goal

Create a product for single market brand trackers will allow marketers to easily see the difference in their key brand metrics over time and will therefore be more likely to use Attest for their brand tracker going forward (renew their subscription).

**OKR:**

**Objective**: Grow the number of customers running end-to-end legitimate multi-survey research through the new product 

**Key Result:** Increase the number of organisations using\* Trackers from 7 > 40 by the end of Q2

## ⚙️ Process

### 🕵️ Discovery

We began the project in late 2020 with a cross-functional workshop designed to challenge the paradigms of how Attest currently works. At the time our survey model looked something like this:

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F341cba0a-1fea-48ca-aba2-692b9a6b8735.png?alt=media&token=155902b5-a0de-4dc0-ab14-3a7574063aba","id":"341cba0a-1fea-48ca-aba2-692b9a6b8735","width":529,"height":120,"filename":"image_(6).png","type":"image/png","caption":"","border":false}]}
```

This worked effectively for one-time research objectives but when our users wanted to measure changes over time it required this process to be repeated and then the results merged: 

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F50a32eaf-5a30-4c59-a25f-39a571f50ac0.png?alt=media&token=05be55d7-d52c-4e24-9d66-cf5ae29dfd7f","id":"50a32eaf-5a30-4c59-a25f-39a571f50ac0","width":724,"height":249,"filename":"image_(7).png","type":"image/png","caption":"","border":false}]}
```

The smallest and easiest change that we could make was to give users tools to make this comparison easier. We had run a few experiments in this space which had met with limited success but ultimately had been complicated and limiting for users to use since the surveys didn't 'know' about each other. The data wasn't always comparable or comparing correctly.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F50d99ee3-fb6f-4519-97ac-b136cfbb5598.png?alt=media&token=7dfcd33a-7923-4210-8f4e-f214e0e775a2","id":"50d99ee3-fb6f-4519-97ac-b136cfbb5598","width":3584,"height":2240,"filename":"Screenshot 2021-09-19 at 14.23.08.png","type":"image/png","caption":"An early attempt at 'merging' survey results","border":false},{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F08c8756b-ba2c-4418-8d74-d69c9a08013f.png?alt=media&token=298bc92b-c4de-4566-b4dd-28ebf257acaf","id":"08c8756b-ba2c-4418-8d74-d69c9a08013f","width":3584,"height":2240,"filename":"Screenshot 2021-09-19 at 14.23.25.png","type":"image/png","caption":"An early experement to create comparison graphs from data","border":false}]}
```

So we spent a week reworking the system model. If there were no rules what would we do?

We began by mapping all the objects in the system, their relationships and the data they contained. With this info in front of us we rearranged the objects, debated the relationships and built on each other's ideas until we settled on a new model: 

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2Fa6fb6b64-970c-4ce2-ac1b-e500b9d94d1f.png?alt=media&token=ca6cdadd-1846-4674-9944-5e2f057a9f3a","id":"a6fb6b64-970c-4ce2-ac1b-e500b9d94d1f","width":683,"height":249,"filename":"image22.png","type":"image/png","caption":"","border":false}]}
```

There would be one survey that could be sent off to collect results multiple times (or have multiple 'dips') that would all feedback into. We tested this model against multiple use cases beyond the scope of what we were looking to build to ensure it would scale (how would this work for multiple markets? What about different languages?) and once we felt confident it would work set about creating concept experiences and evaluating them.

### 🧪 Research

With our model set, we set out to evaluate and build a solution. We began by mapping the entire experience in one story map. We used this to divide up the stories between those we felt were must-haves in the MVP experience and those that were less essential.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F904b2a09-487f-4acb-9552-2011317b02cb.jpg?alt=media&token=7b1117e3-6d40-43bd-a67c-32369de9e08d","id":"904b2a09-487f-4acb-9552-2011317b02cb","width":2513,"height":1591,"filename":"Insights Discovery.jpg","type":"image/jpeg","caption":"","border":false}]}
```

With our rough scope identified we collected our assumptions, questions and hypotheses for the project. These included: 

* We assume that by importing old surveys, we are making the solution immediately valuable to existing brand tracking users.

* We assume that users will not need to make changes to their survey after sending the first dip

* We assume that for single market trackers, users won't need to filter out waves on the Trends page

* We assume that a default pot is sufficient for use

 We prioritised these and created a series to research plans to gather insight and build confidence in our concepts. At the time our customer contact was limited so we structured each session to understand customer expectations in a given space of the experience and then asking them to complete a series of tasks in a prototype. These would often be early Figma click though prototypes but at later stages, we began introducing early versions of the code to better understand how customers interacted with real data.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F07c2664c-f543-402d-962a-851de98feaff.png?alt=media&token=8aeca9e1-2272-4a4f-a1c9-c90ac192a854","id":"07c2664c-f543-402d-962a-851de98feaff","width":1440,"height":899,"filename":"trends v2.png","type":"image/png","caption":"A later iteration of the trends experence","border":false},{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F75fb7028-3b8e-493c-a418-5bae93769bd0.png?alt=media&token=47fa9c3c-2ac5-4c9a-98e9-46c732054401","id":"75fb7028-3b8e-493c-a418-5bae93769bd0","width":932,"height":583,"filename":"trendsv1.png","type":"image/png","caption":"An early design for the 'Trends' experence ","border":false},{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F3e0a0e7d-9434-4838-a7a3-c18a55fb2c2f.png?alt=media&token=9f4bc60b-3556-4e4e-a748-16c70e2f07f0","id":"3e0a0e7d-9434-4838-a7a3-c18a55fb2c2f","width":932,"height":583,"filename":"wavesv1.png","type":"image/png","caption":"Early design for a page showing all the times you have sent a survey","border":false}]}
```

We learned a large amount about the usability of our solution but also three key things about its value:

1\. Editing between Dips/waves/Sends was crucial. Customers would often adjust their survey over the first few times they sent it to iron out any inconstant or less useful data.

2\. Not all questions suited a line graph. Some customers sent trackers yearly leading to smaller data samples and some just preferred a bar graph view.

3\. That customers need a full range of questions visualised for the solution to be useful.

### 💡 Solution

**Trends** 

Trends would be the core of our solution. Here customers would be able to view the results of each send of a survey on a visual graph. They could switch between line or bar graphs depending on the question and user. Each graphs data could be filtered out based on specific demographic filters and show or hide responses depending on what the users wanted to compare. 

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F0e7c672c-0e4b-4744-a74b-2296165c62de.png?alt=media&token=ef78006c-3edf-4c2f-9b42-da91c78f0306","id":"0e7c672c-0e4b-4744-a74b-2296165c62de","width":3584,"height":2240,"filename":"Screenshot 2021-09-19 at 16.13.18.png","type":"image/png","caption":"The trends page included a simple overview of your current and next survey send","border":false},{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F6bd5cea0-4e61-4778-963e-e7727570162a.png?alt=media&token=23affba4-a5c0-40e6-86c3-8871d4f120e0","id":"6bd5cea0-4e61-4778-963e-e7727570162a","width":3584,"height":2240,"filename":"Screenshot 2021-09-19 at 16.13.29.png","type":"image/png","caption":"An example of a multi-choice question visualised as a bar graph with two surveys data","border":false},{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F8cba5153-a199-4359-8899-7ba4c709ea87.png?alt=media&token=80109e40-175c-45de-9f93-f8c088e0d620","id":"8cba5153-a199-4359-8899-7ba4c709ea87","width":3584,"height":2240,"filename":"Screenshot 2021-09-19 at 16.13.36.png","type":"image/png","caption":"An example of a multi-choice question visualised as a line graph with two surveys data","border":false}]}
```

**Results**

Customers could view the results of individual surveys in the traditional results view. They could switch between each send and export the data to diffrent formats.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2F22f83a26-0053-4556-bf95-9bc1da7b247e.png?alt=media&token=02c0d15b-324f-40ba-81f5-becc7fb89cfe","id":"22f83a26-0053-4556-bf95-9bc1da7b247e","width":3584,"height":2240,"filename":"Screenshot 2021-09-19 at 16.18.28.png","type":"image/png","caption":"","border":false}]}
```

**Edits**

Our initial experience only allowed users to send an exact copy of the original survey to the same audience. We had learned from our research that in more than a few cases this was too limiting and didn't allow for refinement of a tracker. So we spent some time building in a editing experience allowing customers to add new questions, delete questions and make limited changes to exiting questions content.  

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2F8fBpcHbqC3WfQhGToJrJ%2Fe107d677-b16c-45d1-acd2-35369a246225.png?alt=media&token=3ac4bd97-a7f0-400d-b0a0-b058defd32e4","id":"e107d677-b16c-45d1-acd2-35369a246225","width":3584,"height":2240,"filename":"Screenshot 2021-09-19 at 16.13.51.png","type":"image/png","caption":"","border":false}]}
```

## ✨ Outcomes and lessons 

### 👍 Validation

With our initial beta release we invited a core group of 7 customers. On full release we currently have 45 total Trackers created, 5 more than we originally targeted.

Customers responded very positively to the new feature:

> Big shout out of course to whole trends squad as this functionality has made Jasper's brand tracker even more business critical than it was has added a great amount of value.

> I just showed some of the new releases to a key contact at Sainsburys. Trackers was really well received as they had shared a frustration with the challenges around comparing pre/post campaign surveys and mentioned that this could help unlock them during more trend work with us.

### 🤓 What I learned

The importance of braking down big problems vertical slices of the experience. We did this well during the project but absolutely could have done it better.

Trackers

**Description**: Solve a significant pain point for our customers by creating a new system to orchestrate the circumstances that certain questions are shown to respondents.

**Goal**: Better serve a crucial use case, prevent churn, increase adoption and close a competitive gap.

**Years**: 2021-2022

**Role**: Product designer

(Responsible for leading the project end to end: from digging into each facet of the experience, fully understanding customer needs and defining the scope of releases with engineering and Product)

## **Sneak peek:**

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F112d3832-8bce-4ed7-a928-8cad6d9698d3.png?alt=media&token=c62b2c68-2104-4151-9fe5-1b986d135e5a","id":"112d3832-8bce-4ed7-a928-8cad6d9698d3","width":2160,"height":1408,"filename":"case1.png","type":"image/png","caption":"","border":false}]}
```

## **Intro**

### **Realising the problem**

Researchers often need to configure surveys with multiple queries to identify weaknesses in their product, brand or proposal. Attest's initial feature was “Routes,” an effort to facilitate the creation of diverging paths in surveys.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F6827121e-f8b4-4062-9d89-466dda8e8261.png?alt=media&token=0c2f816b-dfcc-4b11-a3fc-9256fb6d7a79","id":"6827121e-f8b4-4062-9d89-466dda8e8261","width":3436,"height":2240,"filename":"Image.png","type":"image/png","caption":"","border":false}]}
```

This approach was very visual, putting approachability at its core and hiding the underlying logic of the survey flow. Customers could craft each question, link them up dependent on the answer selected and launch the survey.

Many customers appreciated this approach but, with time, we found out that for many others, instead of making things easier, it made them more complicated - too much of the logic was hidden behind this simple visual linking.

Through a series of customer interviews, we found that many customers begin their survey creation process by planning out their questions, order, and conditions in a text document.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F58cb58da-3b14-41cf-a36a-b9d2a611f103.png?alt=media&token=e58605b6-d6ab-4038-b854-6739c1d9263c","id":"58cb58da-3b14-41cf-a36a-b9d2a611f103","width":2160,"height":1408,"filename":"Case2.png","type":"image/png","caption":"","border":false}]}
```

We understood that customers were growing increasingly frustrated with the restrictive, linear route structure of traditional surveys. The lack of ability to ask a question early, and follow up later created bias and required users to spend hours attempting to craft a survey which was effective and structurally sound. This often resulted in ‘broken’ surveys which caused adoption issues and resulted in higher churn rates.

### **Learning and understanding**

In order to get a broad understanding of the problem, we decided to take in lots of diverse inputs to guide our thinking:

* We directly interviewed a small number of customers to build a better picture of their needs when creating paths in their survey.

* We looked through past feedback from our existing customers which helped us to better understand their needs, and the scale of that needs.

* We had multiple conversations with our internal Customer Research Team (internal research experts who support customers with their research objectives).

* We played with dozens of logic builders such as Intercom Series, Apple Shortcuts, Mixpanel Cohorts and many more, trying to understand what makes all of those tools great.

* We signed up for dozens of competing products to get a glimpse of what works in their solution and what doesn't.

Through this process, we discovered there was a spectrum of problems customers had with the current system of Routes.

* Give a series of questions based on multiple answers to a multiple-choice question

* Display questions later in the survey based on earlier answers

* Logic-based on answers that were not selected by the respondent

* Targeting behaviour based on multiple answers across multiple questions

## **Exploring concepts** 

In parallel I started to disambiguate the vision behind this feature: what's the opportunity, how it roughly could work and how it would fit into the overall Attest system. 

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F3b4e8793-6ad4-4f47-9177-db40d8bc4f88.png?alt=media&token=8feddfdc-ae95-4e22-a30a-4b727a2c5e23","id":"3b4e8793-6ad4-4f47-9177-db40d8bc4f88","width":2160,"height":1408,"filename":"Case 3.png","type":"image/png","caption":"","border":false}]}
```

As I worked on ideas, I made some assumptions that needed testing before we moved forward. To get feedback from a group of customers, I whipped up two prototypes in Figma. We got an idea of how customers wanted more complex logic, but we realized a more ‘realistic’ approach was needed for real feedback. So, to really understand user needs, we set up a plan to create something more tangible.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2Fc8a77249-33a2-4d9c-80b1-c9e79b7ead9a.gif?alt=media&token=96ce4d55-86ac-4d9b-b89b-bd88d8d08ad0","id":"c8a77249-33a2-4d9c-80b1-c9e79b7ead9a","width":800,"height":501,"filename":"AnimatedImage.gif","type":"image/gif","caption":"","border":false}]}
```

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F622a9c04-52cd-4b20-a9f5-6c8e1971cd3a.gif?alt=media&token=c40b81e7-6d8d-4730-92dc-b8a6ed4ceb22","id":"622a9c04-52cd-4b20-a9f5-6c8e1971cd3a","width":800,"height":496,"filename":"CleanShot 2022-10-30 at 1.28.03.gif","type":"image/gif","caption":"","border":false}]}
```

I partnered with a frontend engineer to create a throwaway prototype for our Display logic concept. Once we had a proof of concept ready, we tested it with a handful of customers to get their feedback.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2Fe80b2028-3ea1-425a-8e96-242427a9d6c1.png?alt=media&token=b3230b98-8211-4153-bfe8-967b9068c529","id":"e80b2028-3ea1-425a-8e96-242427a9d6c1","width":1834,"height":1214,"filename":"Cord-3.png","type":"image/png","caption":"","border":false}]}
```

As a result of our efforts, we discovered additional use cases, needs, and confusion that had been previously overlooked.

## **Finalising designs**

Finally, having done all the things above, I moved on to exploring all the gnarly system, UX, Interactions and visual design problems.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2Fb9cf44fc-ba87-4d04-809d-0f2aa956bb40.png?alt=media&token=4716005c-0f2a-4008-9d3a-7b97e111331b","id":"b9cf44fc-ba87-4d04-809d-0f2aa956bb40","width":2160,"height":2267,"filename":"Cover4.png","type":"image/png","caption":"","border":false}]}
```

## **Initial release**

We made our first release of Display logic in late 2021. Due to the technical complexity of this work we kept the first release scope as small as possible. This meant initially cutting some customer needs, staggering those as follow-up releases. To help us understand which needs to work on next I set up a Buy a Feature research exercise. In this exercise, each feature is given a description and a price (that reflected its development complexity). Participants are given 'money' to spend on features they want. They would only have enough money to buy a little over half of the features. We would monitor what they bought first, and what they left behind if they chose many 'cheap' features or a few 'expensive' features.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F4fed838d-78e4-448d-8b3a-0ab8e595e3c4.png?alt=media&token=d0c9a1f0-1685-4a3c-baa3-faf4d69f1efe","id":"4fed838d-78e4-448d-8b3a-0ab8e595e3c4","width":3584,"height":1924,"filename":"BuyAFeature.png","type":"image/png","caption":"","border":false}]}
```

I ran this exercise with a selection of internal research experts and customers to build a picture of what were the most important iterations. With this information, I set up a story map detailing the order we would release and the requirements for each. 

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F07629b62-9a20-482d-9e2e-ab924ab7918e.png?alt=media&token=23df04cc-f310-470a-bed8-bd5725dce0fd","id":"07629b62-9a20-482d-9e2e-ab924ab7918e","width":3356,"height":1546,"filename":"StoryMap.png","type":"image/png","caption":"","border":false}]}
```

This approach was useful in keeping us aligned as a team, surfacing the dependencies and leading to a rapid series of releases building on our initial work.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F77ddfe04-6106-4569-b53c-598cc4b4678e.gif?alt=media&token=a36991a1-4917-4674-84ec-cc27237745e9","id":"77ddfe04-6106-4569-b53c-598cc4b4678e","width":800,"height":502,"filename":"Demo1.gif","type":"image/gif","caption":"","border":false}]}
```

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F05aaa33b-282c-4059-a258-84a9b95bb5c7.gif?alt=media&token=a8c10b0a-dc92-46d5-b9cd-72b15ec8d48b","id":"05aaa33b-282c-4059-a258-84a9b95bb5c7","width":800,"height":502,"filename":"Demo2.gif","type":"image/gif","caption":"","border":false}]}
```

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F59bbf874-8dca-44c5-a78d-f176dbe42cce.gif?alt=media&token=f97b8415-813d-4b27-b137-7a41a0a4bcde","id":"59bbf874-8dca-44c5-a78d-f176dbe42cce","width":800,"height":502,"filename":"Demo3.gif","type":"image/gif","caption":"","border":false}]}
```

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2FnnOUHD7OcDgzwRraRteBr0rp3un1%2FlNLBGQu5u3rTmgoq1A04%2F548614ef-7069-4894-9aba-7838a07f10fa.gif?alt=media&token=099afcdd-4427-4c15-b27d-f610c0113bb8","id":"548614ef-7069-4894-9aba-7838a07f10fa","width":800,"height":502,"filename":"Demo4.gif","type":"image/gif","caption":"","border":false}]}
```

## **Measuring success**

This addition to our survey creation system unlocked a range of customer needs and exceeded our adoption aim of 30% of customers in the following quarter. It also positively increased our adoption and has unlocked new possibility's for the future of the product. Most importantly the early feedback has been overwhelmingly positive.

Question display logic (2021-2022)

Looking for my next role as a Product Designer. If you think we might be a good fit I’d love to chat! 

Product designer

Survey editor flexability

Building on-brand, quality and consistent web properties at scale is hard. It’s even harder when you have many businesses with varying audiences who all sit under one master brand. Success requires more than another redesign and a vague set of brand guidelines. This was the challenge we faced at Octopus. We needed a strong foundation. Our solution: Deepsea design system.

Deepsea design system

Solve a significant pain point for our customers by creating a new system to orchestrate the circumstances that certain questions are shown to respondents.

The focus of my work here is on presenting complex financial products in a simple, usable way. 
* Lead design and research in agile squads across multiple product areas shipping projects of varied scope.
* Projects included creating a new way for customers to track survey results over time and creating complex logic tools for survey creation.
* Lead work on the company design system and applying our brand refresh.

Senior Product Designer

Product Designer

The focus of my work here is on presenting complex financial products in a simple, usable way. 
* Led design on an organisation-wide design system 
* Led design on internal investment data management tools 
* Facilitated workshops with key stakeholders
* Assisted in creating a design career progression system

* Design and oversite of the user experience for the client's website and chatbot applications, from conception to launch. 
* UX lead on the website learning and optimization program.

UX Architect

• Woking on a 3-week sprint with the small intern team to create a mobile-only vision piece for a client in the banking sector. 
• Competing with the five intern teams around the world, our team was selected to pitch our design directly to the client in New York and was selected as the winning design.
• Worked with the cross-functional design team on projects across a broad range of clients.

Ben Shelford

2022

2021