The powerful functionality that is available for brands to utilise across the Partnerize platform is somewhat hindered by the existing interface. How could we improve the usability of this feature and what metrics could be surfaced to enhance —rather than hinder— workflows? I lead the redesign of this project.


The purpose of insights is to provide an area for brands to monitor and make business decisions based on data and trends surfaced across their campaigns. The frustration caused by the general usability of this area often lead users to task failure, and ultimately pushed them to consider other platforms. Partnerize identified the potential of insights and added the project to the roadmap, allowing us to research further and improve how insightful data can be consumed and used to their advantage.

As the Design Lead, I worked closely with product managers, data science, engineering, and most crucially, the end-users, to focus on delivering a feature that serves their needs.


We conducted research to build an understanding of the current usage of insights, and what we could do to improve it. We also looked for opportunities to completely change the current feature, including its extension out to partners and its potential inclusion (from a data perspective) into the marketplace.

A study on competitors showed that our insights feature was lagging behind in almost every aspect - we needed to catch up or we would lose to the competition.

Although brands have access to attribution data and timeframes between initial click and associated conversions within the existing interface, we recieved feedback that the interface was unclear, and in turn, made it difficult to analyse without switching to analytical reports and downloading files. We then looked at the metrics that fit within the scope of the project, this included;

  • In-channel attribution - partner interactions, partner summary, sale by sale click path, average touchpoints
  • Conversion/Product Analysis - Trending products, click to conversion, conversion rate analysis
  • Partner Analysis - League table, cost of sale/ROAS
  • Customer behaviour - Purchasing patterns, repeat business

These metrics supported different use cases, for example, brands who wanted to compare partners within a campaign, create split commissions, and to be informed of any changes to cost, partner performance and trends.


The insights feature should provide tremendous value to affiliate marketing efforts, and as the Partnerize platform has the ability to track and surface more data in comparison to competitors we saw this as an opportunity to keep brands from leaving. We prioritised a few key metrics that would add the most value and would be feasible in the time allocated to the project, this included:

  • Attribution analysis — to provide visibility of conversion attribution and partner interactions over time.
  • Conversion analysis — to show the origin and causes of clicks and conversions.
  • Partner analysis — to show partner performance ranked over time.


The aim of the project was to provide high level, actionable data at a glance, with the ability to dig deeper into more granular data points. Improving the presentation of data could solve key use cases for clients using insights to make data-driven business decisions.

The existing interface consisted of a tabbed view, using icons without descriptions or labels to split nine metrics into sections, which caused confusion and a lot of clicking around. I initially looked at introducing cards to provide a glimpse of what has happened on a campaign over a chosen period as an entryway to dig deeper into each data point, but ultimately I proposed adding subsections to the new sidebar for quick access to each section, reducing clicks and presenting as much information as possible per metric, except for filtering and clicking into partner profiles etc, to dig deeper. This approach is particularly useful for us as it gives us the ability to add/ remove sections within the menu for certain users/ access rights and MVP based on constraints and phasing. This approach is also useful for brands as it provides quick and easy access to key data points.

Data visualisation

One of the big pieces of data we had to work with was partner attribution - the interactions involved before a conversion takes place.

I looked at ways to visualise the relationship between partners and how many times they were an initiator, contributor or converter in the path leading to conversion.

I created an interactive Sankey diagram that changes according to chosen filters, that displays partners within any of the attribution roles and how many times they took a particular role when conversions took place for a campaign over the chosen date range.

Attribution analysis is particularly useful for brands to view partner performance across campaigns to learn which partners drive most conversions and assign credit to specific partners.

This information can be downloaded and viewed in table format.

Verification process

As part of the design process, we gather internal and external validation before producing final mockups ready for production. We usually like to select five external candidates. We selected brands who are heavy users of insights to demo prototypes and asked the following questions;

How important is the insights feature to you on a scale from 1 to 10?
1 being not important and 10 being very important.

Using the same measurement, how often do you see yourself/others in your organisation using this feature?

What kind of affect do you see this having on your program in terms of sales, commissions etc?
Measurement: Positive | Neutral | Negative

What kind of affect do you see this having on the management of your program (time, learning etc)?
Measurement: Positive | Neutral | Negative

With the feedback we received during the verification process, it was clear that we were delivering on user needs.


This was a really exciting and fun project to work on as it provides real value, involved a lot of research, and detailed interaction work. However, shifting priorities and resourcing issues delayed the launch of this feature. Still, I learned some important takeaways from this project related to product and business processes.

How to adapt to changing requirements
New timelines, resourcing issues, and reprioritisation meant the scope of the project was constantly changing. I had to adapt to those changes and still deliver the best design in time with tight deadlines.

Always fight for design and user requirements
I had to work under very strict technical constraints, but I still fight for what I believe is essential to having a good user experience.

Don’t overpromise and underdeliver
I learned how to define a true MVP vs. something that is simply not usable and therefore not shippable.

Choosing what we won’t do
There were many great use cases and metrics we could tackle when we iterate, however, they were unrealistic to deliver when we could provide real value with the metrics we looked at.

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