GrowthFactor Agent
One sentence in. An absurd amount of analysis out
GrowthFactor Agent works inside GrowthFactor, right alongside your deal pipeline. Ask it to rank your deals, flag cannibalization, compare finalists, write the committee memo — or model a brand-new market from any set of addresses. Trade zones, revenue forecasts, demographics, and foot traffic, with the reasoning behind every recommendation.
How It Works
From pipeline to shortlist in one prompt.
Open the agent from your deal dashboard. Ask a question in plain English. It pulls data across every deal in your pipeline and gives you a ranked answer with the data behind it.
Ask your pipeline a question
Type a natural-language question from the deal dashboard. "Which 3 of my 11 deals in Review should move to LOI?" The agent understands your pipeline stages, deal context, and portfolio.
Agent pulls data across every deal
Scoring, demographics, cannibalization, foot traffic — the agent runs 20+ API calls in parallel across your entire pipeline. What takes an analyst an hour takes the agent 30 seconds.
Get a ranked recommendation
A scored shortlist with clear reasoning. Not just which deals to advance — which to pass on and why. Cannibalization overlaps, demographic mismatches, and portfolio conflicts surfaced automatically.
Conversational Intelligence
One conversation. Start to finish.
The agent keeps context across follow-ups. Start with a broad pipeline question, drill into a specific deal, then ask it to write the memo. No re-entering data. No starting over.
“Which 3 of my 11 deals should move to LOI?”
Ranked shortlist with scores, demographics fit, and cannibalization risk for every deal.
“Dig deeper on Okeechobee Blvd. What are the risks?”
Risk analysis comparing the candidate against your best-performing existing store.
“Write me a recommendation for the investment committee.”
A clean paragraph with specific data points, ready to copy into an email or slide deck.
“Model 5 new stores in Dallas — how do they cannibalize each other?”
Revenue forecasts, trade zones, and mutual cannibalization across the whole candidate set — add or drop sites and the plan updates.
Each follow-up builds on the previous context. No re-entering data, no switching tabs, no starting over.
What You Can Do
Every pipeline question, answered.
The agent has full context on your deals, scores, portfolio, and org criteria. Ask it anything you'd ask your best analyst.
Rank and prioritize deals
"Which of my Review deals should move to LOI?" The agent scores, compares, and ranks every deal against your criteria — then tells you which ones deserve your time.
Flag cannibalization risks
The agent checks every candidate against your existing portfolio. If a new site overlaps 20–30% with a current store, you'll catch it before the LOI.
Deep-dive on a single deal
"What are the risks on Okeechobee Blvd? How does it compare to our best-performing store?" Follow up in the same conversation. The agent already has context on every deal.
Generate committee deliverables
"Write me a one-paragraph recommendation I can send to the investment committee." The agent already has the data, the scores, and the reasoning. The output is the deliverable.
Spot patterns across the pipeline
Cluster effects, demographic skews, market concentration — patterns that only surface when you look at the full pipeline together, not deal by deal.
Compare against the existing portfolio
"How does this site stack up against our top 10 performers?" The agent benchmarks candidates against stores you already operate, with matched demographics and trade zone analysis.
New · Market Planning
Plan an entire market, not just one deal.
Give the agent a market and a set of addresses — your pipeline deals or brand-new candidates you're just exploring. It draws trade zones, forecasts revenue, models how the candidates cannibalize each other, and scores demographic fit. Add or drop sites and the plan updates — a committee-ready market plan in minutes.
Bring any addresses
Pipeline deals or net-new candidates you're just kicking around — model a hypothetical store set before you commit a dollar.
Revenue, forecast per site
Projected revenue for every candidate in the plan, with the trade zone and demographics behind it.
Cannibalization across the set
See how five proposed Dallas stores eat into each other — not just into the stores you already run.
Foot traffic and fit, ranked
Annual visits, year-over-year trend, and demographic fit for every pin, ranked across the market.
Why This Matters
The bottleneck is the evaluation, not the data.
Your team evaluates deals one at a time. Click in, read the scores, check cannibalization, compare in their heads, write the memo. An hour per deal, minimum. The agent does the same work across every deal in your pipeline simultaneously.
One hour becomes two minutes
Eleven deals evaluated, ranked, and explained in a single prompt. The agent doesn't get faster per deal — it evaluates all of them at once.
Patterns that surface at the portfolio level
Evaluating deals individually hides portfolio-level patterns. Across the full pipeline, the agent surfaced that most Boston-area deals had 20–30% cannibalization against an existing store — the kind of finding that only appears when you look at everything together.
From analysis to action in the same conversation
Evaluate the pipeline, drill into a finalist, write the committee recommendation — without opening a new tab or re-entering context. The output is the deliverable.
2 min
Eleven deals ranked from one prompt
10+
Candidate sites modeled in one market plan
Zero
New tools to learn — it's already in GrowthFactor
FAQ
Common questions
See the agent work your pipeline
We'll run the agent on a live deal pipeline. Not a canned demo — real deals, real scores, real recommendations.