# How one researcher cut competitive analysis from days to hours with AI Teammates

> Learn how a Quantitative Market Researcher at Asana uses an AI Teammate to perform competitive market analyses with robust research and data sets.

Source: https://asana.com/resources/asana-competitive-market-research-with-ai-teammates

## How one researcher cut competitive analysis from days to hours with AI Teammates

When a competitive tear-down request comes in, Lizzy Munro doesn't start by opening a spreadsheet. First, she needs to understand the landscape: what competitors are offering, how they're positioning it, and where Asana can stand apart. That means combing through competitor websites, analyst reports, and past research, sometimes across eight or more brands, each with 30-plus data points.

Munro, a Quantitative Market Researcher at Asana, had structures and frameworks to help her move as quickly as possible through this work. But still, even with all the proper inputs, it was slow and tedious.

That's because turning raw competitive data into something actionable, accurate, sourced—and nuanced enough—to shape pricing decisions and the product roadmap, requires deep, uninterrupted work. The process used to consume an entire week. Now, thanks to an AI Teammate, she’s got it down to just a few hours.

It used to be my worst nightmare when someone would ask for a competitive tear-down because I knew just how much work that would involve.

## **The work behind a single tear-down**

Lizzy's role is to turn competitive noise into useful insights for a product or marketing team. That means opening competitor websites across a wall of browser tabs and cataloguing features one by one, cross-referencing analyst reports, verifying claims against past research. Every row has to be accurate, sourced, and consistent.

It's not enough to note whether a competitor has a feature. Lizzy also has to capture the nuance: how they've implemented it, what makes their version different, and where the gaps are. Applying that judgment uniformly across dozens of features and multiple competitors takes deep, uninterrupted concentration. Providing a [competitive analysis](https://asana.com/resources/competitive-analysis-example) could stretch across an entire week.

For years, that's how competitive research worked. But AI Teammates have changed what's possible, automating the heaviest parts of the process so researchers like Lizzy can spend their time on the work that actually requires their judgment.

## **How AI Teammates changed the way Lizzy does competitive research**

To move faster, Lizzy built her workflow around a Competitive Market Researcher[AI Teammate](https://asana.com/product/ai/ai-teammates) that works alongside her team inside Asana.

Instead of starting with a blank spreadsheet and a wall of browser tabs, she assigns the AI Teammate a task with the source material from the start—past research, analyst reports, competitor context. From there, the AI Teammate takes on the work of turning that into a structured, sourced competitive analysis.

Here's how it works:

### Step 1: Load it with the right context from the start

Lizzy built the AI Teammate with everything it needs to do the work well: the team's past research, a list of the competitors that matter, and detailed instructions about what good output looks like. She was specific from the beginning, telling the teammate that it wasn't enough to note whether a feature existed. If a competitor implemented something in a way that set the company  apart, she wanted that captured. She also built in checkpoints so the teammate wouldn't get too far ahead without her reviewing the output.

### Step 2: Start with Asana, then move competitor by competitor

Rather than handing the AI Teammate a blank grid and asking it to fill everything in at once, Lizzy started with Asana's own product data. It was territory she knew well enough to catch any missteps. 

Once that foundation was solid, she created a separate task for each competitor, working through them one at a time. Smaller chunks meant fewer errors and made it easier to verify that every claim was sourced. She also gave the teammate explicit permission to edit the [competitive analysis spreadsheet](https://asana.com/templates/competitive-analysis) directly.

### Step 3: Refine until anyone can read it in seconds

The first pass came back dense. The cells had too much detail and more context than a tear-down needs. Lizzy went back and forth with the AI Teammate to strip it down, keeping what made each competitor genuinely different and cutting the rest. The final format is simple: yes or no for standard features, specifics only where they change the story, and category groupings so the whole picture is readable at a glance.

## **From a week of manual work to an hour (or two)**

Using an AI Teammate in Asana, Lizzy Munro reduced competitive tear-down time from multiple days to just an hour or two. The team's Competitive Market Researcher AI Teammate is now shared across the entire quantitative[market research team](https://asana.com/resources/ai-teammates-marketing-roles), and they've started exploring competitors in adjacent categories—work they wouldn't have taken on before because the time investment was too high.

Plus, all of this work lives in Asana including the interaction history, the source material, and the final output. So when, for example, the head of pricing and packaging requests a tear-down, he can follow the task in progress rather than waiting for a finished deliverable. And if someone else wants to deep-dive on a specific competitor, Lizzy points them to the task and they can do their own digging.

AI has reached the point that it can do all of the heavy lifting, which means that my role can be much more about generating the insights, which is really the bit that I enjoy.

## **Research that moves work instead of bottlenecks**

Competitive intelligence has always been about more than collecting data. The value is in knowing what the research actually says, like where a competitor is vulnerable, where Asana can push harder, and what’s coming next. 

That's the work Lizzy got into research to do. Now, with her AI Teammate, it's the work she actually does.

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