So what is Viva Insights?
Pretty good question.
In large enterprises, data analysts often grapple with complex business intelligence tools to spot overwork trends, improve team collaboration, and create a better work environment.
Viva Insights is one of the pioneering tools in this space, a platform aimed at improving organizational effectiveness and employee well-being through data-driven insights.
Many analysts struggle with the tool’s complexity, often feeling overwhelmed by numerous cogs to run a simple query. This called for something big, something game-changing.
An opportunity to work on the bleeding edge technology
Copilot is here, and the world is taken up by a storm.
Copilot is Microsoft’s rendition of GPT, but unlike the sea of GPT toys out there, both the M365 suite and the Viva suite are products used by billions. If anyone had a chance to make an asteroid-sized dent, it’s us.
With this weight in our shoulders, the Insights team set out to figure out how could we leverage generative AI technologies, to streamline the query-building experience, reduce cognitive load, and empower analysts to make more data-informed decisions with confidence.
Clearing the fog
So, what’s plaguing the current experience?
Analysts in our platform can run queries, which allow them to generate reports that inform productivity and well-being strategies across the organization.
Traditionally, analysts navigate numerous dropdowns and filters manually, which can be time-consuming and overwhelming. By integrating Copilot, we envisioned enabling analysts to simply write what they want to understand, with the system offering relevant metrics, filters, and guidance instantly.
Our current custom query builder has majorly 3 steps involved.
1. Selecting Metrics
Metrics are criteria which are used to measure productivity and wellbeing.
2. Applying Filters
This allows us to narrow down the employees to run the query for.
3. Selecting Attributes
Attributes are data fields of these employees who are being measured.
Diving deep into how a query is run
Because the best course of action is always to put your user’s shoes, or something like that.
The analyst’s journey involves multiple steps, often creating friction, from defining queries and selecting metrics to applying filters and viewing results across separate tools.
Analysis Paralysis
With hundreds of metrics and attributes, both new and experienced analysts can feel overwhelmed. The lack of contextual cues or suggestions compounds complexity, increasing time to completion.
Lack of Guidance
Documentation is helpful but external. Without integrated support, analysts must rely on memory or guesswork to select suitable metrics and filters.
Steerability & Trust
Without transparency or rationale for metric suggestions, analysts hesitate to trust automated recommendations.
Siloed Experience
Once queries are set, results open in separate visualization tools (e.g., Power BI). Switching between systems disrupts focus, slowing down analysis and insight generation.
What about our competition?
You oughta learn from what others do better.
A competitive analysis of AI-driven analytics assistants and query-building experiences across industry leaders:
1. IBM Watson Analytics Assistant
Watson offers chat-based analytics with contextual suggestions and citations, aiding trust. However, it can feel too “wizard-like,” sometimes oversimplifying advanced analytics steps.
2. Qlik Insight Bot
Qlik provides integrated chat-based insights and can connect to Slack. Its visualizations and homepage metrics help users track trends, but its suggestions often remain surface-level without deep reasoning.
3. Tableau Pulse (Einstein AI)
Tableau’s integrated AI insights within dashboards highlight anomalies and provide “Explore further” prompts. Users appreciate seeing parameters selected and understanding the “why” behind recommendations, though initial setup can be complex.
| Feature | IBM Watson Analytics | Qlik Sense | Tableau Pulse |
|---|---|---|---|
| Entry Point | Chat bar in the bottom right | Button on top navigation | Data visualization in homepage |
| Experience Type | Chatbot | Modal immersive experience | Immersive full-screen experience |
| Unique Capabilities | Uses citations for answers; contextual information. | 3rd Party integrations; visual tracking metrics. | Deeper analysis; selected parameters; data visualizations. |
Scratching up concepts
A look at the different routes that we can take.
Copilot experience guidelines showcases 3 different types of ways a Copilot can be represented. Depending on your product requirements, you choose what’s best for your users.
Immersive
Whole knowledge-based focus
Assistive
In-app focus
Embedded
Single-entity focus
So what do we choose?
It was crucial that we pursue all avenues, because its an entirely new paradigm for our users and we wanted to validate what’s best for them. So we built concepts for all of them.
1. Assistive experience
This is the standard experience for any Copilot experience, as it provides the context of the page that you are working on, and it provides intelligent suggestions accordingly.
Starting off
Suggestions on what the Copilot can do.
References on every answer
AI should be built on trust, and Copilot relies on this trust from the user. The analyst can see where each and every suggestion is coming from.
Metric and filter suggestions
Upon asking a question, the Copilot will suggest the right metrics and filters for the query, making it easier to run in one single click.
Visualisations
Every query has data to represent for their organization. It was only natural that Copilot have the ability to showcase beautiful visualizations before running a query to preview what they can derieve from it.
2. Embedded experience
A more seamless approach would be to make Copilot more natural in terms of experience, where it assists in the flow of work. Anyone who’s already deep into the product need not have to learn new ways to utilize Copilot as its already baked into the process.
Metric suggestions
The metric flyout (which is also very similar to the Attribute flyout) was one of the obvious choices for an embedded Copilot, since these metrics control what they query shape up to be. The analyst can type in the query that they want and the Copilot will suggest the right metrics to add to the query.
Building from context
One of the more quirkier ideas that I had was to build from the Query name and description with a click of a button. This would drive users to name and describe their Query better as well. The problem was Analysts rarely choose a different name than the default one and almost never add a description to their queries.
3. Immersive experience
A full-page Copilot had a lot of potential too, which could give generative and realtime insights of one's organization.
The Copilot home
This page can be accessed directly from the Viva Insights homepage by clicking on the side navbar, or better yet, by scrolling down the homepage to access it (inspired by the Bing Copilot <3). It provides quick suggestions on what they can run and ask to the Copilot, similar to the sidecar experience.
Generative Insights
This is the most captivating section for the Copilot, where it progressively generates insights about the Analysts organization. The more queries Analysts ran, the better these predictions and suggestions got.
Better representation of data
While it was a novel idea to show the visualisations in the Sidecar experience, it's best seen in a bigger viewport. The immersive experience is the perfect canvas for data representation nerds.
Validating with our customers
Because who better to ask than someone who’s well versed with our product.
To ensure our approach aligned with real-world needs, we engaged with the Viva Customer Connection Program, hosting a session that included 74 participants from a wide range of global organizations. Our goal was to validate Copilot’s value, exploring how analysts of varying experience levels perceived its potential to streamline query building and assist with broader analytical tasks.
We wanted to validate 3 major things.
1
How effectively can Copilot guide analysts through complex query-building tasks?
2
Can it suggest relevant metrics and filters to streamline analysis?
3
Are these designs aligned with their preferred interaction methods?
Some of our customers included
Some key highlights of the interviews
Copilot was seen as especially valuable for less experienced analysts, enabling them to overcome the steep learning curve of Viva Insights and navigate the tool more efficiently.
Participants stressed the importance of Copilot identifying analytical blind spots, offering a comprehensive range of metric recommendations rather than just obvious or top-performing ones.
Customers emphasized the need for greater visibility into metric calculation methods and better customization options including creating custom metrics tailored to their organization.
Beyond query building, users sought help from Copilot in summarizing query results effectively, especially for presenting complex analyses to stakeholders.
“This has a potential of building complex queries much easier and more efficient. Instead of adding metrics one by one, it simplifies the process, saving time and effort.”
“Copilot is incredibly helpful in identifying relevant metrics, but I’d love to see it uncover potential blind spots in the language used. Validating the most important metrics while comparing them to other potential ones is crucial, and I think this feature would add significant value.”
“I think its gonna be really useful in getting kind of through the learning curve a lot quicker!”
The final designs
What got shipped out finally.
The customer feedback proved to be very crucial to the direction that we took. The final product that we shipped included a multitude of features which were deemed essential by our customers.
Homepage Discoverability
It was crucial that we showcase the Copilot in the homepage, so that users can easily discover it. The feature discovery card was the just the perfect opportunity for this. Apart from this, we also added an FRE experience, which is standard across Microsoft for all Copilots in our product line.
The sidecar
As the Analyst lands in the Create Analysis page, they are greeted with the Copilot and how it can help them. The analyst can ask their query and the Copilot will pick the right query to run in a fraction of a minute.
The query builder
The Copilot simplifies query building by bringing all essential information into a single, easy-to-use side panel. Analysts can hover over any metric to instantly see its definition, removing confusion. It combines the 5-step query process, the Viva Insights glossary, and the reasoning behind each query type into one seamless experience, making it faster and easier to build and understand queries.
Some final thoughts
And maybe some of my learnings
This experience gave me a real taste of the wild world of enterprise challenges and showed me just how crucial user-centered design is in complicated ecosystems. Juggling time zones felt like competing in an Olympic event for communication skills, but it taught me how to stay clear and connected. With a mix of careful planning and some good old trial and error, we kept things moving. I would like to believe that embracing setbacks and every twist and turn made me a stronger, more resilient designer. All in all, it was a crazy, but rewarding ride!