Improve communication
between Brands &
Appbrew with AI
Case Study at
Appbrew
Outcome
New process addresses 100% issues & reduces micro-issues by 50%.
Introduction
What Appbrew Does
The company makes mobile apps for D2C Brands using Shopify. Appbrew has built & currently running apps for 200+ D2C Brands.
Appbrew opens another sales channel for Brands using Shopify
Who are the Users
Appbrew targets Shopify Brands looking for another channel to improve revenue, retention, conversion etc.
inside a Shopify Brand
brand goals
more revenue & loyalty
brand identity & web parity
integration management
decision-making users
founders
brand owners
growth marketers
execution-only users
brand designers
shopify developers
What I worked on
My job was to understand the product priorities & problem space well enough from the user insights gathered by the team, to design the most effective workflow for Brands and their desired outcomes.
Team Members
Co-Founder (CTO)
Product Manager
Engineers
The Product
How the App connects to the Product
Every Brand on Shopify goes through an onboarding process to setup their App and go live, after which Brands manage their App directly on the Product – a web-based low-code app builder.
2 stages to build & manage apps
What's relevant for this project
As soon as the customer lands on the product, Help & Updates is available at the bottom-right across all pages, except on the AI-Assisstant Milo.
The Problem
How Appbrew & Brands maintain their apps
After going live, Appbrew & Brand are constantly in touch to resolve bugs & improve the app's shopping experience with new features.
issues Brands want to solve
bugs & tech glitches
custom design updates
integration setup & maintain
manage app store submissions
feature requests
updates & alerts by Appbrew
new features or integrations
critical compliance alerts
proactive fixes & improvements
best practices & strategies
operational status
How communication worked before design
Docs & newsletters were the most reliable methods to reach Brands. But, Brands still have to troubleshoot themselves, only when not reaching out via chat groups & regular calls for manual resolution.
Reliable channels are slow, while fast channels are unreliable.
What problems Brands were facing
Problem
Manual issue management is prone to human errors.
Problem
Context parity requires a lot of communication and is slow.
Problem
Generic newsletters don't always reach the right users.
Problem
No way to scale personalised alerts, updates & insights.
The Solution
PHASE I
How problems were addressed
The main goal is to streamline all communication on one channel for both – issues Brands report & updates Appbrew delivers.
The fastest possible ways prioritised to cover all necessary use cases.
Solution
One portal for Brands to connect with Appbrew for all types of problems.
Solution
One portal to send all central updates & critical alerts to all Brands using the product.
PHASE II
How problems were addressed again
The main goal was to use AI for a proactive & contextual help & news portals, bypassing complex logic or human support.
Portals built on the product are the most compatible with Brand context.
Solution
Chat to troubleshoot problems before raising support request.
Solution
Add Brand context for tailored response-resolution & alerts.
What constraints exist
Constraint
Low bandwidth for a custom solution, leading to delayed AI context integration.
Constraint
Human support has to be connected, as a necessity for complex problems.
Constraint
Project went live with old design system (showcasing new UI on this page).
Final Design
PHASE I
Portal Access
Given the global nature of help & news, a product-wide placement is used, following the common web-app practice.
Help & Updates Portals
A similar popup design used for both portals, despite the difference in approach & content.
PHASE II
Access to AI
With Milo active, placement of AI-led Help is rethought to better integrate with Milo & signal a familiar functionality.
Help with Milo
With complete control over the experience, the capability of the portal can be highlighted better.
Solving Issues
The internal workflows setup during Phase I are used by Milo to address all problems that may arise appropriately.
Outcome
PHASE I
What Changed
Outcome
No missed issues raised by Brands with Pylon's built in management
Outcome
Reduced compliance or system issues, with proactive alerts right next to help
Outcome
Higher reported discovery & usage of new features highlighted via Updates
Outcome
Support team's workload reduced drastically, allowing faster & higher resolutions
PHASE II
What Changed
Outcome
Milo addresses 75% of routine queries, replacing manual support for those cases
Outcome
Issues resolved for Brands within an hour, instead of days by raising support requests
Outcome
Milo helps not only understand issues, but also plan & strategise solutions
What to Improve
Up Next
Milo-led proactive insights, strategies or automated actions
Up Next
Personalised industry-relevant recommendations
Up Next
Maintain memory across all past chat threads
Up Next
Milo "humanised" like an Appbrew member.