Optimising Seeks ad design through experimentation

I led the redesign of Seeks ad products on the product selection page, experimenting with different design variants in order to drive a 5.3% increase in yield (+$3M of incremental revenue) through only design optimisations.

I led the redesign of Seeks ad products on the product selection page, experimenting with different design variants in order to drive a 5.3% increase in yield (+$3M of incremental revenue) through only design optimisations.

Timeline

Timeline

2 weeks (research & design)

Responsibilities

Responsibilities

Research, visual design

Role

Role

Lead Designer, Manager

The successful design variant increased yield by 5.3%

The successful variant increased yield by 5.3%

problems

Seeks long-standing ad product design had resulted in users exhibiting 'auto-pilot' behaviour

Based on prior research and analytics, users were continually defaulting to the least expensive product option, not considering other, higher-value products that may better meet their need. We classified this as 'auto pilot behaviour', which was characterised by:

Based on prior research and analytics, users were continually defaulting to the least expensive product option, not considering other, higher-value products that may better meet their need. We classified this as 'auto pilot behaviour', which was characterised by:

Low adoption of higher-value products

Low adoption of higher-value products

Adoption metrics for performance and premium products hadn't changed despite extensive experimentation to improve the inclusions and pricing.

Low understanding of features

Low understanding of features

Over 50% of SME users interviewed in past research stated they didn't have clear performance expectations for any of Seeks products.

Low time on page

Low time on page

Metrics indicated that users were just defaulting to the cheapest product without considered higher-value, better fit alternatives for their hiring needs.

The current state experience (control group)

The current state experience (control group)

opportunity

How can we capture user attention to communicate value and break users selection 'inertia'?

Our teams ingoing hypothesis was that we could be doing a significant amount more to drive our users to consider higher-value products. We had the constraint of only utilising the existing data points and features available in the current experience, but with flexibility to re-structure their presentation altogether.

Goals

Goals

  • 5% increase in performance ad adoption

  • Increase consideration of higher value products by 15%

Metrics to measure

Metrics to measure

  • Ad mix (percentage of different product types purchased)

  • Time on spend on selection page per user

process

Breaking down the problem, quickly & succinctly

Unpacking existing behaviour

Unpacking existing behaviour

Through cross-functional workshops as well as 8 qualitative research sessions run over 2 days, we landed on 3 key themes that were driving the observed behaviour.

Existing ad selection design

Unoptimised hierarchy of information

Unoptimised hierarchy of information

The current design emphasised price and the product name title, which was encouraging users to make a purchase desicion based on price and not the value received.

The current design emphasised price and the product name title, which was encouraging users to make a purchase desicion based on price and not the value received.

No laddering of value

No laddering of value

It was unclear to users what they could expect from actually selecting a product. Feature information was positioned below CTA, leading to difficulty comparing product features and inclusions.

It was unclear to users what they could expect from actually selecting a product. Feature information was positioned below CTA, leading to difficulty comparing product features and inclusions.

Unclear use case for selection

Unclear use case for selection

Current designs made it difficult for users to understand why they should pick a particular ad over another with similar terminology being used across products causing confusion.

Current designs made it difficult for users to understand why they should pick a particular ad over another with similar terminology being used across products causing confusion.

Existing ad selection design

Explorations

Explorations

Next I focused on a fast and structured exploration looking at numerous different approaches to design existing ad content in a way that clearly communicated value and resonated with users.

Existing ad selection design

Design explorations

Final designs

Different approaches to communicating value

Ensuring differentiation across variants

Ensuring differentiation across variants

A key part of preparing for on-platform experimentation was ensuring both variants were clearly differentiated. I emphasising different elements within the product hierarchy across both variants to ensure we could understand specifically what moved the metrics.

Variant 1: Targeted tagline, simplified layout

By emphasising value through a simpler title (explaining how the product will meet the hirers need) and by teasing additional inclusions we will encourage more interaction of comparison of products, therefore increasing awareness of higher value products

Variant 2: Strong visuals, display inclusions and exclusions

Prominent visualisations will allow for stronger, more salient communication of value. Showing exclusions would also help in articulating what a user is missing by not considering higher value products.

Results

Relevance and simplicity best resonated with users

We had some exciting results with Variant 1 increasing performance ad adoption by 5.2% and time on page by 20% per visit. This outcome was a fantastic demonstration of the power of user-centred thinking, and has meant the team can isolate specific changes like hierarchy, composition and copy and directly point to their impact on business success.

Control

Yield: Baseline
Time on page: Baseline
Conversion: Baseline

Variant 1

Yield: +5.3%
Time on page: 20% increase
Conversion: Steady

Variant 2

Yield: +1.7%
Time on page: 10% increase
Conversion: Steady