Using SuperAnalyst to Turn Competitor Signals Into Decision-Ready Intelligence

A competitor announces a new product. An expert call raises a question about customer priorities. A field team member asks how to respond to a claim they are hearing in the market. These signals rarely live in isolation or arrive in a neat sequence, and not all of them warrant immediate attention. But you have to be able to make a quick decision on what to go deeper on, what your stakeholders will care about, and most importantly, what will actually affect your ability to be competitive in the market.

For me, the challenging part about competitive intelligence (CI) isn’t about how I can collect more information or how best to summarize it. The biggest challenge is how I can quickly and definitively decide what matters, what is noise vs. signal, and what should be brought up in product, go-to-market, or customer conversations.

SuperAnalyst is the always-on agent designed for my workflows in competitive intelligence. It acts as an extension of my team by continuously monitoring competitor signals, building battlecards, and delivering cited, auditable outputs.

What Competitive Intelligence Means at AlphaSense

I joined AlphaSense in June 2025 as the first member of the competitive intelligence team, which meant I was in charge of collecting, distilling, and surfacing relevant information to the right people in a market that is shifting every week. But with innovation and a fast-changing industry comes more noise.

My job is to quiet the noise and amplify the signal so AlphaSense employees can stay current on the competitors, markets, and use cases customers care about most when they evaluate solutions like ours. It also means producing work people can trust and act on, not just collecting information as an FYI.

How I Use SuperAnalyst for Competitive Intelligence

With SuperAnalyst, I can move through all those questions at once. Instead of asking only, “What did this competitor announce?”, I can frame the work around the decisions I need to make:

• Where is this company strongest?
• Where are there gaps compared with AlphaSense?
• Which recent changes matter to our buyers?
• How should a seller position AlphaSense for a particular use case?

For my competitive enablement work, I call on a SuperAnalyst skill I created called Sales Enablement CI Dashboard Skill, which builds a cited, interactive competitor dashboard for any company. By looking at the competitor through the lens of its own competitors, I can assess how the competitor has positioned itself in the market. I built it to fill a gap in my workflow: Information about competitor products, releases, and updates was scattered across sources and lacked broader context about competitive positioning.

SuperAnalyst transforms market research into interactive, fully cited battlecards. I can quickly evaluate competitive positioning, drill down into core strengths, gaps, and objection handling, and instantly click through to verify the exact source text. This turns a simple summary into an actionable sales enablement asset that yields dependable, auditable guidance I can trust.

Now, I can easily see prioritized differentiators, vulnerabilities, suggested battlecard updates, objection handling, and talk-tracks related to these updates — all in one clean and interactive view. SuperAnalyst points to the exact competitor I want to know more about, and it automatically knows how to get me the right answer. Instead of asking me to provide the competitive set or assuming the set is always the same, SuperAnalyst always starts at the company level, researches recent developments in the market universe, and builds the most current competitor set.

SuperAnalyst digs deeper from there, identifying relevant competitors and organizing the findings into data for sales enablement: a scorecard, battlecards, head-to-head positioning, buyer-specific messaging, recent activity, recommended enablement actions, and evidence gaps.

Once I’m happy with the results, I use the updates to refresh individual battlecards, share them with the field, and watch for signals that could affect seller guidance and potentially warrant a larger field-wide update. The dashboard helps me distinguish between a change that belongs in one competitor’s battlecard and one that should be shared across the team.

And with SuperAnalyst’s persistent memory, I know that my work compounds across sessions: It keeps the project history, workflows, analytical logic, and my instructions, so I don’t have to rebuild the context and instructions each time. This means I can keep the materials our sellers rely on relevant with minimal effort. Before SuperAnalyst, updating those materials could take me up to a week of work.

Seeing the memory in action is something that still impresses me. Last month, I spoke with our product marketing team to discuss a theme we’d noticed across recent deals. I put the takeaways of our discussion into a separate SuperAnalyst thread to help me research this specific competitor’s capability and folded that into my dashboard to keep a pulse on this development. SuperAnalyst pulled from expert transcripts, broker research, and our own internal content to build my ad-hoc request, as well as a repeatable monitor on my current CI dashboard.

Without my prompting, it flagged a phrase in our existing battlecard that conflicted with newer data. Our internal battlecard called out a weakness for that competitor when newer data, made available since that battlecard was published, indicated that the competitor had made decent strides to fill the gap.

That’s where I had to decipher the noise vs. signal. SuperAnalyst was able to flag the conflicting evidence, but ultimately, I have context that SuperAnalyst doesn’t yet have — like insights shared with me over coffee, or things I heard at a conference that never made it into my notes.

That’s why it’s ultimately up to me to judge what those pieces of evidence and gaps mean for the seller and the decision at hand. That’s the shift AI has enabled in my work: less manual stitching, more time interpreting the signal and deciding what to do with it.

The Value Lies in the Interpretation

Before SuperAnalyst, I used to spend my time stitching together outputs across Generative Search queries, then copying and checking them against the battlecard by hand to make sure it was up to date. I ran Workflow Agents, but still had to copy and paste their outputs into a PowerPoint. Now, SuperAnalyst does that work for me automatically and hands me ready-to-use battlecards and an HTML dashboard.

And the more I use SuperAnalyst, the more it learns about my needs. Now, it does more than just answering my initial query. It surfaces competitors and perspectives I didn’t think to ask about, color-coding the results so I can see what changed from the previous version. And with custom skills like Sales Battlecard, Competitor Integration Depth, and Claim-by-Claim Compare Page Pressure Test, I’ve become a better CI practitioner and a better teammate because I can proactively share up-to-date insights with my team.

SuperAnalyst Understands the Workflow, Not Just the Query

SuperAnalyst has changed the way I work completely. It advances an entire workflow; all I have to do is ask my initial question, and it now has enough context and understanding of my job to provide me with a real deliverable I can use. I still own the judgment, but now I can better apply that judgment in a way that ensures I can support the teams that rely on our intelligence.

Want to try it on your own work? Log in to AlphaSense and start exploring how SuperAnalyst can accelerate your workflows or sign up for a free trial.