Universal Help Module

CASE STUDY 1

ROLES

Lead Designer/Architect, Researcher

DELIVERABLES

Competitive Analysis, Brainstorming Workshops, Early Concepts, Mind Mapping, Wireframes, Prototypes, Usability Testing, User Stories

COLLABORATION

Business Stakeholders, Sales Specialists, Support Agents, Product Management, Engineering, QA, Data Science, Analytics, Program Management, Content Strategy, Research, Visual Design

TIME LINE

2019 - 2021

Goal

Autodesk is a leader in 3D Design, Engineering and Entertainment Software. Its mission is to empower innovators around the world to design and make solutions in the architecture, engineering, constructions, product design, manufacturing, and media & entertainment world.

In 2016, Autodesk switched to a SaaS model which meant that customers started transitioning from purchasing through resellers to directly purchasing products online. This changed what customers started to expect from Autodesk - more direct & immediate customer service. In addition, Autodesk keeps growing and expanding its suite of products and platforms, so consistency of design and interaction also became a priority.

Problem

We were hearing from customers via site surveys & green button feedback channels that finding help was very frustrating.

  • No consistent way to get help

  • No direct paths to help

  • Inconsistent contact options

  • Pass from agent to agent

“Provide a support number or a live chat feature”

"Extremely confusing website - getting help was impossible"

"Why do I have to jump through hoops and spend hours trying to find someone to help me”

Approach

Combine self-help, guided help and human help to get the customer to the right answer with minimum effort.

Provide consistent access to contextual and customer-aware help at every point in the customer journey.

Teamwork

This project was the first of its kind to cross many different organizations for alignment and implementation.

Discovery

Top Pain Points

  • Evaluated a year’s worth of case data from various touch points to establish high level issue types and topics.

  • Led workshops with stakeholders to align on top pain points to prioritize for e-commerce and post-purchase support.

Complex Business Rules

  • Helped stakeholders document a matrix of business rules based on customer’s subscription type and user role. Engineers then coded these rules into the help application so that customers got the contact options they are entitled to.

Agent Ecosystem

  • Sales and support agents are skilled based on topics across the customer lifecycle, the product a user has and the language they speak. I facilitated workshops with agents to try and help simplify the skill categories to reduce overlap and make it easier to guide customers to the right agent.

Design Principles

I crafted key principles rooted in research to guide the design of the Universal Help application. These were referred back to for more informed decision making and negotiating design trade-offs during roadmap planning and feature prioritization.

Design

MVP

Universal Help was a lightweight, guided experience for help with buying, trying and troubleshooting Autodesk products. Machine learning algorithms were used in specific flows for better issue classification and agent routing. MVP was deployed on 5 product center pages in the US dotcom site.

THREE PARTS

There are 3 aspects to Universal Help.

  1. Issue classification - what users need help with collected via decision tree of topics or by collecting their question

  2. Self-help - curated links to articles, short answers, dynamic links if question was captured, and Watson-based workflows

  3. Human help - variety of options for customers to choose from to connect with an agent, such as phone, chat, case, etc

ISSUE CLASSIFICATION

The primary way for users to narrow down their issue is to go through a decision tree of topic selection. I worked with data science and content strategy teams came up with several versions of this tree based on case data. Then I partnered with our lead researcher to test wording and organization with customers to ensure the topic names resonated with them.

We learnt from foundational research that customers prefer typing in their question. In a few specific branches, we piloted machine learning enhanced search where users could type in their question to receive more specific answers.

SELF-HELP SOLUTIONS

For branches with topic selection, users see 2-6 curated links (which lead to articles on the Knowledge Network) or short answers which are presented in the help tool. I worked extensively with content strategy to identify the links and answers to be shown while also providing guidance on styling and layout.

In branches where users entered a question, they see dynamic recommended links to knowledge articles (intelligent links). I worked with the search platform team to understand the technology enough to help users enter better questions and helped fine tune how the results are displayed.

We also included a virtual agent workflow that offers step by step guidance for finding a download, from a previous project I had worked on.

ALWAYS A WAY OUT

I included ways for customers to exit the decision tree or virtual agent workflow so the user can change course, if needed, and doesn’t feel trapped. At any point in the flow, the user can jump back up to the home screen, track back to previous steps or use an escape hatch to talk to a human agent.

HUMAN HELP & SIGN IN

While self-service is what users primarily seek, there are always urgent situations or complex issues where they prefer connecting with a human.

By asking the user to sign in we are able to look up their account and serve up personalized contact options based on their subscription type or product. We recognize if users are already signed and do not ask again, and make sure that we utilize their account information for their benefit only.

In the places where they typed in a question, we use machine learning to classify their question and route them to the right support team.

VARIETY OF HUMAN CONTACT OPTIONS

Human help options are all offered in a compact way all in one place. We offer you ways to chat with a human agent, schedule a call at a time that’s convenient to you, give you a phone number depending on your subscription type, or allow you to submit your question via email. And pretty soon, you will also see a call back option so you don’t have to wait in line over the phone and for those purchasing questions, we will also be providing chat with a sales expert.

User Research

I formulated research goals and worked closely with the Research team in evaluating various aspects of the experience.

We used Treejack and First click studies in testing the decision tree of topics. A key insight was that the initial selection is extremely important so having fewer topics upfront and displaying a short description helps them choose the right path.

Results & Reflection

  • While engagement with the ““?” icon is consistent month over month, it is overall lower than expected < 1% dotcom visitors)

  • 75% of customers who engage with the app click on at least one article or contact an agent

  • Visits to dotcom that had interaction with the help module resulted in 5% higher cart additions and almost 2% higher number of orders placed

“I really like how this is laid out… live chat, schedule a call, create a case….because sometimes you have to go through menu after menu after menu and it just drives you crazy to do it. This is actually very nice.”

— Customer with a Standard Subscription

Expansion of Platform: Broader - Deeper - Smarter

After the first 6 months, the modular, extensible Universal Help platform was expanded to cover more use cases in more languages across multiple web properties.

  • Localization: Universal Help was deployed on all global dotcom sites (>1000 pages) and adapted to 30+ countries with geo-specific content. The UI was translated to the local language but in some cases the articles themselves were in one of 10 Visitors saw article titles in their language but often times the articles themselves were in English and the agents they were connected to did not speak their language. So I designed appropriate ways to help transition users from local language to English, in addition to help identify country-specific content needs.

  • Account Management Portal: The help app was embedded in the customer’s Account recognized the authenticated customer right away and guided to help with their downloads, installation and user management activities. It was also embedded within Fusion product to offer customers a quick way to chat with an agent.

  • Contact Support: Full page website version of the application helped customers to find the quickest path to post-purchase and contact Autodesk Support

  • In-Product Support: Embedded inside Fusion that increased resolution time by 20%

  • Pop-up nudge: Drove awareness around benefits of using the new module - increased engagement by 15%

Account Management Portal

Contact Support website

Fusion in-product