In today's rapidly evolving utility landscape, artificial intelligence  presents unprecedented opportunities to transform customer engagement strategies. However, as UX professionals in the energy and utilities sector, it's crucial to implement these technologies thoughtfully, balancing automation with the human touch that customers still expect and value.

‍

‍

Understanding AI's Role in Customer Engagement

‍

The energy and utilities sector faces unique challenges: managing peak demand periods, addressing complex billing inquiries, and communicating effectively during outages. AI can help address these challenges by:

‍

• Managing routine inquiries at scale: Chatbots and virtual assistants can handle common questions about billing, service disruptions, or energy-saving tips, freeing human agents for more complex issues.
  ‍
• Personalizing customer communications: AI can analyze consumption patterns to deliver tailored energy-saving recommendations or alert customers to unusual usage.
  ‍
• Streamlining service processes: Smart algorithms can help schedule maintenance visits or process service changes more efficiently.

‍

‍

Finding the Right Balance: AI and Human Interaction

‍

While AI offers significant advantages, implementation requires careful consideration of when and how to deploy these technologies:

‍

Where AI Excels:

‍

• Initial customer triage: Directing customers to the right department or information resource
  ‍
• Data analysis and pattern recognition: Identifying trends in customer behavior or service issues
  ‍
• Content creation foundations: Generating initial drafts of communications or documentation
  ‍
• 24/7 basic support: Providing answers to straightforward questions outside business hours

‍

‍

Where Human Expertise Remains Essential:

‍

• Complex problem resolution: Addressing unique or multifaceted customer issues
  ‍
• Emotional intelligence: Handling sensitive situations with empathy and understanding
  ‍
• Content refinement: Adding nuance, brand voice, and industry expertise to AI-generated content
  ‍
• Strategic decision-making: Determining how customer engagement should evolve

‍

‍

Implementation Best Practices for UX Professionals

‍

As you consider integrating AI into your customer engagement strategy, keep these guidelines in mind:

‍

1. Start with clear objectives: Define specific goals for your AI implementation, whether it's reducing wait times, improving self-service options, or enhancing personalization.
   ‍
2. Design transparent AI interactions: Customers should understand when they're interacting with AI versus a human agent. This transparency builds trust and sets appropriate expectations.
   ‍
3. Create seamless handoffs: When an AI system needs to transfer a customer to a human agent, ensure the transition is smooth and context is preserved.
   ‍
4. Continuously refine AI models: Use feedback from both customers and employees to improve your AI systems over time, addressing gaps in knowledge or performance.
   ‍
5. Measure both efficiency and effectiveness: Track not just cost savings or time metrics but also customer satisfaction and resolution quality.

‍

‍

Leveraging Optimal for AI-Enhanced Customer Engagement

‍

Optimal's user insights platform can be instrumental in ensuring your AI implementation truly meets customer needs:

‍

Tree Testing

‍

Before implementing AI-powered self-service options, use Tree Testing to validate your information architecture:

‍

• Test whether customers can intuitively navigate through AI chatbot decision trees
  ‍
• Identify where users expect to find specific information or services
  ‍
• Optimize the pathways customers use to reach solutions, reducing frustration and abandonment

‍

‍

Card Sorting

‍

When determining which tasks should be handled by AI versus human agents:

‍

• Conduct open or closed card sorting exercises to understand how customers naturally categorize different service requests
  ‍
• Discover which functions customers feel comfortable entrusting to automated systems
  ‍
• Group related features logically to create intuitive AI-powered interfaces that align with customer mental models

‍

‍

First-Click Testing

‍

For AI-enhanced customer portals and apps:

‍

• Test whether customers can quickly identify where to begin tasks in your digital interfaces
  ‍
• Validate that AI-suggested actions are clearly visible and understood
  ‍
• Ensure critical functions remain discoverable even as AI features are introduced

‍

‍

Surveys

‍

Gather crucial insights about customer comfort with AI:

‍

• Measure sentiment toward AI-powered versus human-provided services
  ‍
• Identify specific areas where customers prefer human interaction
  ‍
• Collect demographic data to understand varying preferences across customer segments

‍

‍

Qualitative Insights

‍

During the ongoing refinement of your AI systems:

‍

• Capture qualitative observations during user testing sessions with AI interfaces
  ‍
• Tag and categorize recurring themes in customer feedback
  ‍
• Identify patterns that reveal opportunities to improve AI-human handoffs

‍

‍

Prototype Testing

‍

When developing AI-powered customer interfaces for utilities:

‍

• Test early-stage prototypes of AI chatbots and virtual assistants to validate conversation flows before investing in full development
  ‍
• Capture video recordings of users interacting with prototype AI systems to identify moments of confusion during critical utility tasks like outage reporting or bill inquiries
  ‍
• Import wireframes or mockups of AI-enhanced customer portals from Figma to test user interactions with energy usage dashboards, bill payment flows, and outage reporting features

‍

‍

Looking Forward

‍

As AI capabilities continue to evolve, the most successful utility companies will be those that thoughtfully integrate these technologies into their customer engagement strategies. The goal isn't to replace human interaction but to enhance it, using AI to handle routine tasks while enabling your team to focus on delivering exceptional service where human expertise, creativity, and empathy matter most.

‍

By taking a balanced approach to AI implementation, supported by robust UX research tools like those offered by Optimal, UX professionals in the energy and utilities sector can create more responsive, personalized, and efficient customer experiences that meet the needs of today's consumers while preserving the human connection that remains essential to building lasting customer relationships.

‍

Big things are happening in 2024! 🎉

‍

We’re undergoing a huge transformation in 2024 to deliver more value for our customers with exciting new products like prototype testing, features like video recording, upgrading our survey tool, introducing AI, and improving how we support large organizations and multiple teams managing their accounts. These new products and features mean we need to update our pricing plans to continue innovating and providing top-tier UX research tools for our customers now and in the future.

‍

Say hello to our new pricing plans  👋🏽

‍

Starting July 22, 2024, we’ll be introducing new plans—Individual and Individual+—and updating our Team and Enterprise plans. We’ve reduced the price to join Optimal from $249 a month on the Pro plan to $129 on the new Individual plan. This reduction will help make our tools more accessible for people to do research and includes two months free on the individual annual plan, too.

‍

We’ll be discontinuing some of our current plans, including Starter, Pro, and Pay per Study, and letting customers know about the changes that will affect their account via email and in information on the plans page in the app.

‍

Prototype testing is just around the corner 🛣️ 🥳

‍

The newest edition to the Optimal platform  is  days away, and will be available to use on the Individual+, Team and Enterprise plans from early August.  Prototype testing will allow you to quickly test designs with users throughout the design process, to help inform decisions so you can build on with confidence.  You’ll be able to build your own prototype from scratch using images or screenshots or import a prototype directly from Figma. Keep an eye out in app for this new exciting addition.

‍

What is session replay?

‍

Session replay allows you to record participants completing a card sort without the need for plug-ins or integrations. This great new feature captures the participant's interactions and creates a recording for each participant completing the card sort that you can view in your own time. It’s a great way to identify where users may have struggled to categorize information to correlate with the insights you find in your data.  

‍

Watch the video 📹 👀

‍

How does session replay work?

‍

• Session replay interacts with a study and nothing else. It does not include audio or face recording in the first release, but we’re working on it for the future.
  
• There is no set-up or plug-in required; you control the use of screen replay in the card sort settings.  
  
• For enterprise customers, the account admin will be required to turn this feature on for teams to access.
  
• Session replay is currently only available on card sort, but it’s coming soon to other study types.

‍

Help article 🩼

‍
Guide to using session replay

‍

How do you activate session replay?

‍

To activate session replay, create a card sort or open an existing card sort that has not yet been launched. Click on ‘set up,’ then ‘settings’; here, you will see the option to turn on session replay for your card sort. This feature will be off by default, and you must turn it on for each card study.

‍

‍

How do I view a session replay?

‍

To view a session replay of a card sort, go to Results > Participants > Select a participant > Session replay. 

‍

I can't see session replay in the card sort settings 👀

‍

If this is the case, you will need to reach out to your organization's account admin to ask for this to be activated at an organizational level. It’s really easy for session replay to be enabled or disabled by the organization admin just by navigating to Settings > Features > Session Replay, where it can be toggled on/off. 

As information professionals, we work with the “stuff” of information in our everyday work. We search for information, we spend time analyzing and synthesizing it, and we carefully create and structure it. Whether you elicit information from users and stakeholders, explore large data sets, design ‘journeys’ or interfaces, or create information architectures, understanding the information you are using and creating as information can help you do your work better.

‍

Kat King, Business Intelligence Analyst at the University of Michigan Library, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, about understanding exactly what information is, and where it is, in our work.

‍

In her talk, Kat uses simple examples to teach you to “see” the information around you and understand what makes something “information” in the context of working as a human to accomplish something.

‍

Kat King bio 🎤

‍

Kat King is an Information Architect interested in language, meaning, and the things we make. She currently works as a Business Intelligence Analyst for the University of Michigan Library.

‍

Contact Details:

‍

Email: Katalogofchaos@gmail.com

‍

Where is the information? 📍🗺️

‍

Information theory can be dense and jargon-filled, and discussions in academic texts can feel divorced from the practice of actually working with information. We’re all told that information architecture is much more than website navigation. So, what is it? IA has a reputation for being difficult to understand, and in her talk, Kat attempts to help us understand what it is, where the information is, and what is it that we’re doing when we use IA methods.

‍

Kat defines IA as “the practice of ensuring ontological alignment”. ‘Ontological’ relates to concepts, categories, properties, and relationships. ‘Alignment’ means arrangements into appropriate relative positions. Therefore, information architecture is “the practice of ensuring concepts, categories and their properties and relationships are arranged into appropriate relative positions.”

‍

To align information then, you need to begin by sorting it into concepts and categories, which is difficult because information can sometimes be “slippery and abstract”. Kat argues this is the real reason that IA is sometimes hard to wrap our heads around. So, getting to the heart of the question, what is information? 

‍

Kat defines information as “a patterned relationship between differences that reduces uncertainty”. The key word here is ‘differences’. The trick to understanding and taming information is to identify what is different about sets of information. The next trick is to identify consistencies between these differences.

‍

This can be a little confusing, so Kat uses the example of picking fruit. We tend to use color (the difference) to identify when fruit is ripe and sweet. We know for a fact that, at some point, the fruit will be at its sweetest and, while there is a scientific way of identifying this point, we have to use the information we have at our disposal instead i.e. the colour of the fruit. The skin of the fruit in this example is like an interface - allowing a flow of information from the fruit’s ripening process to our eyes.

‍

Information categories 🧺🧺🧺

‍

The relationship between the information described in the fruit example can be split into two categories. “Information 1” is a factual, objective description of when the fruit is ripe (i.e. the science of why the fruit is the color that it is right now), whereas our subjective observation, based on color, is “Information 2”.

‍

• Information 1: Matter and energy, and their properties and interactions i.e. the laws of physics and universal truth or rules

‍

Information 1 poses challenges for us because we have a narrow range of perception, attention, and aggregation, which means we, as humans, can’t possibly understand the laws of nature just by observing. We have evolved to be simple, efficient observers of what is important to us. In other words, we don’t need to understand everything in order to get things right. We see patterns and generalize. Going back to the fruit example – we only need to know the color of ripe fruit, not the exact chemistry of why it is ripe.

‍

• Information 2: This is Information 1 that is given meaning by humans. This is done via processing semantic information, or “differences and structures that create meaning for people”.

‍

We use semantic information by processing concepts, patterns, categories, mental models, and even language as inputs to form our understanding. As social animals, we tend to reinforce general ‘truths’ about things because we’re constantly cooperating using shared information. General ‘truths’ are good enough.

‍

Kat uses the following interaction to demonstrate the interplay of different information.

‍

• Person 1: If the raspberries look good, can you get some for me?
• Person 2: How can tell is they’re good?
• Person 1: Get the ones that are the most red.

‍

In this interaction, the different pieces of information can be broken down by category:

‍

• Semantic information = Words and concepts
• Information 1 = Meaningful signs
• Information 2 = Perceptible differences
• Real life information = Raspberries

‍

Using our ability to communicate and understand concepts (words “red”, “good”, and “raspberries”) helps us to understand Information 2 (processing the words and concepts to understand that a red berry is good”), which aligns with Information 1 (the evolutionary science and ongoing consistency of red/ripe berries being sweet) that helps us decide when processing all of this information.

‍

So, now that we understand a little more about information, how does this influence our roles as designers?

‍

Why it matters 👀

‍

Thanks to our individual lived experiences, people have many different inputs/concepts about things. However, Kat points out that we’re pretty good at navigating these different concepts/inputs.

‍

Take conversations, for example. Conversations are our way of getting a “live” alignment of information. If we’re not on the same page we can ask each other questions to ensure we’re communicating semantic information accurately. 

‍

When we start to think about technology and digital products, the interfaces that we design and code become the information that is being transmitted, rather than words in a conversation. The design and presentation become semantic information structures, helping someone to understand the information we’re putting forward. This highlights the importance of aligning the interface (structure and semantic information) and the users' ontology (concepts and categories). For the interface to work, IA practitioners and designers need to know what most people understand to be true when they interact with information, concepts, and categories. 

‍

We need to find some sort of stability that means that most users can understand what they need to do to achieve a goal or make a decision. To do this, we need to find common ground between the semantic information (that might vary between users) so that users can have successful Information 2 style interactions (i.e. absorbing and understanding the concepts presented by the interface).

‍

To wrap up, let’s remind ourselves that information architecture is “the practice of ensuring concepts, categories and their properties and relations are arranged into appropriate and relevant positions”. As IA practitioners and designers, it’s our job to ensure that concepts and categories are arranged in structures that can be understood by the nuance of shared human understanding and semantic information – not just in some physical diagram.

‍

We need to present stable, local structures that help to reduce uncertainty at the moment of interaction. If we don’t, the information flow breaks and we aren’t reducing uncertainty; instead, we create confusion and disappointing user interactions with our digital products. Making sure we present information correctly is important (and difficult!) for the success of our products – and for better or worse, it’s the work of information architecture! 

‍

‍

At Optimal Workshop, we're dedicated to building the best user research platform to empower you with the tools to better understand your customers and create intuitive digital experiences. We're thrilled to announce some game-changing updates and new products that are on the horizon to help elevate the way you gather insights and keep customers at the heart of everything you do. 

‍

What’s new…

‍

Integration with Figma 🚀

‍

Last month, we joined forces with design powerhouse Figma to launch our integration. You can import images from Figma into Chalkmark (our click-testing tool) in just a few clicks, streamlining your workflows and getting insights to make decisions based on data not hunches and opinions.  

‍

What’s coming next…

‍

Session Replays 🧑‍💻

‍

With session replay you can focus on other tasks while Optimal Workshop automatically captures card sort sessions for you to watch in your own time.  Gain valuable insights into how participants engage and interpret a card sort without the hassle of running moderated sessions. The first iteration of session replays captures the study interactions, and will not include audio or face recording, but this is something we are exploring for future iterations. Session replays will be available in tree testing and click-testing later in 2024.  

‍

Reframer Transcripts 🔍

‍

Say goodbye to juggling note-taking and hello to more efficient ways of working with Transcripts! We're continuing to add more capability to Reframer, our qualitative research tool, to now include the importing of interview transcripts. Save time, reduce human errors and oversights by importing transcripts, tagging and analyzing observations all within Reframer. We’re committed to build on transcripts with video and audio transcription capability in the future,  we’ll keep you in the loop and when to expect those releases. 

‍

Prototype testing 🧪

‍

The team is fizzing to be working on a new Prototype testing product designed to expand your research methods and help test prototypes easily from the Optimal Workshop platform. Testing prototypes early and often is an important step in the design process, saving you time and money before you invest too heavily in the build. We are working with customers and on delivering the first iteration of this exciting new product. Stay tuned for Prototypes coming in the second quarter of 2024.   

‍

Workspaces 🎉

‍

Making Optimal Workshop easier for large organizations to manage teams and collaborate more effectively on projects is a big focus for 2024. Workspaces are the first step towards empowering organizations to better manage multiple teams with projects. Projects will allow greater flexibility on who can see what, encouraging working in the open and collaboration alongside the ability to make projects private. The privacy feature is available on Enterprise plans.

‍

Questions upgrade❓

‍

Our survey product Questions is in for a glow up in 2024 💅. The team are enjoying working with customers, collecting and reviewing feedback on how to improve Questions and will be sharing more on this in the coming months. 

‍

Help us build a better Optimal Workshop

We are looking for new customers to join our research panel to help influence product development. From time to time, you’ll be invited to join us for interviews or surveys, and you’ll be rewarded for your time with a thank-you gift.  If you’d like to join the team, email product@optimalworkshop.com

We’re excited to share some new features and product updates that we've rolled out lately and what’s coming up next.

‍

What's new…

‍

Speeding up task analysis in Treejack 🚤

‍

Customer feedback and research have shown that users analyse results in Treejack in a task-by-task manner. To better support this way of working, we’ve updated Treejack results to ensure the success and directness of each task are easier to compare with the new Task overview tab in Results.  This new visualisation is available in Results > Overview> Task overview section in Optimal Workshop.

‍

‍

Aggregate path views 

‍

We have also introduced the aggregate paths view in the Paths tab (it used to only be visible via the compare tasks button). This allows users to more easily see what the popular paths are for each task and how much each successful path was used (or not). 

‍

Over the next few months, we’ll continue working through our results tabs to update them to a task-by-task view and highlight insights at a task level. 

‍

Improving the quality of participant recruitment

‍

We’re continuing work to improve the quality of participants recruited in Optimal Workshop. Our latest release involves eliminating all participants that rush through a Treejack study.  We’ve analysed years of participants to get a good idea of what ‘rushing’ means, and we can now identify these ‘speeders’ and remove them from our participant pools. We have also removed the limit in-app for replacement participants across all study types, and released updates to immediately eliminate poor quality participants from custom orders. 

‍

Help guide: How to replace study participants in-app

‍

What’s next:

‍

• Identifying participants that rush through other tools and remove from participant pools.
• Build more automated flagging and behaviours to eliminate other behaviours that indicate poor-quality participants.
• Continued monitoring and analysis to ensure high participant quality.

‍

Templates are here 🙌 

‍

We are excited to announce our first six project templates are now available. Templates have been created with industry experts to give you the confidence to quickly launch studies and back your results to make data-driven decisions.   These ready-made templates give you a headstart on your research by providing you with the right range of study types and when to use them. 

‍

Where will they live?

‍

Templates are accessible in the app from the Dashboard > Browse Templates. From the ‘templates menu’ select a template that matches your use case for example ‘I need to organise content into categories’ and get going faster than before. You can edit and customise the templates to suit your research goals. 

‍

More templates from our community

‍

This is just the beginning of our template journey and while we continue to build up our collection we’d love your input too. If there are templates that you regularly use and think the community could benefit from we’d love to hear from you. Email us at product@optimalworkshop.com.

‍

What’s coming up…

‍

Optimal Academy 🎓

‍

The Optimal Academy is due to launch in later this month.  The Academy will provide education that enables our customers to get started faster with our tools and elevate their knowledge of all things Information Architecture and UX. 

‍

The first courses available will be a series of Optimal Workshop tool-based lessons, including best practice study setup analysis and recruitment.  You can expect to see more exclusive content and courses from industry experts and institutions on a diverse range of topics continuing to drop in 2023 and 2024.

‍

Enterprise team features

‍

We’re committed to making things easier for our team customers, particularly on the administration side of our product. Our product team have begun discovery on improving our administration features, and have had a lot of great customer feedback to help shape up the opportunities. We are aiming to make improvements to this area of the product later this year.