Logic Based Discounts

Date
January 2023
My Role
Lead Product Designer
Client
Smart Spaces
Project
E2E Journey
THE Opportunity

What I found

Business Problem

Our Product Team noticed that we didn’t have the capability on our website to offer customers logic based discounts or discount stacking because our platform didn’t support it. 

I also noticed current drop off rate from cart to checkout was sitting at almost 40% so a lot of customers weren’t seeing the benefit of proceeding to checkout and were abandoning their cart instead. 

Cart drop off rate before
THE APPROACH

How I fixed it

Hypothesis

I hypothesised that because customers couldn’t see the promotion we had on our products they couldn’t assess the benefit of clicking through to product detail pages. Once on product detail pages customers wouldn’t be able to see these logic based discounts or multiple discounts applicable on the same product either. 

Also once in cart without the total savings being displayed they weren’t feeling rewarded and enjoy the cost benefit of their purchase. For business this could easily negatively affect drop off rates.

Measures of Success

My aim was to provide customers with more transparency over potential savings and therefore greater feelings of contentment after their purchase. The goal for business was to see a reduced cart drop off rate less than 40%.

STEP 1

Journey Map

Customer Journey Map

I began by creating a customer journey map of the existing E2E journey so that I could understand customer expectations and opportunities.

STEP 2

Competitor Analysis

I then conducted a competitor analysis for the three scenarios I had been provided which were:

1. The applicable discount will be applied if a specific defined quantity of a qualifying (Master or Variant) product is added to the cart by the customer.

Example to use: 50% off when you purchase 4 Google Nest Minis

2. Customers belonging to a particular customer group will be eligible for the discounts. The customer group can be defined in SFCC e.g. all customers having an O-Team subscription.

Example to use: 50% off Google Nest Hub for Active Subscriber

3. Customers receive a discount when a target product is in the cart.

Example to use: 20% off an Amazon Echo Dot 4th Gen when there is an Amazon Echo Show 8 in the cart

Competitor analysis
STEP 3

Screen Flow

Screen flows

I then took these three scenarios and mapped out what an E2E journey could look like for each. I was asked to prioritise the Cart and Checkout screens before any of the other screens.

STEP 4

Wireframes

I then looked into some graphical devices which could be applied to the discounts across all scenarios and created some wireframes of the Product Cards for each of the three scenarios. 

The Product Cards were chosen because they were the component where real estate was the most challenging and so if they worked here then they would work everywhere else on the journey.

Wireframes
STEP 5

Designs & Prototype

Cart Designs

At this point I began by first designing the cart designs for the three scenarios. There were multiple use cases for each which had to be considered. 

I then chose one scenario and created an E2E high fidelity prototype to take to my PO and the Product Team for feedback.

STEP 6

Feedback & Approval

After receiving feedback from my peers at Peer Review (our internal feedback session) and my PO I was given approval.

The next step was to meet with the developers to get an estimate of effort. The developers discussed the complexity of each component and created a proof of concept (PoC) where required.

My PO prioritised the components to be built and we held an elaboration session to gather the Acceptance Criteria for each story. 

THE SOLUTION

What I did

While there were a multitude of different designs created for various scenarios and use cases overall I designed:

Final design
Cart drop off rate after

For business the product was a success in that we reached our goal and reduced the cart drop off rate to 33%.

THE CHALLENGES

What I learned

After the project I reflected on the following insights: