Test your next big product decision before you make it.
Lexsis lets you simulate the outcomes of a reformulation, a pricing change, or a new SKU against your real customer signals before you commit a single dollar of budget.
Most product decisions are educated guesses. They don't have to be.
You're sitting on a big call. Should you add a new ingredient to address the complaints you've been seeing? Launch a lower-price SKU to stop leaking price-sensitive customers to a competitor? Expand to retail before your DTC base is fully profitable?
The instinct is to gut-check it with the team, pull whatever data is available, and commit. Six months later you find out if you were right.
Lexsis changes the sequencing. Before you commit, you run the simulation. You see which customer segments stand to benefit, which ones are indifferent, what the projected churn impact looks like if you do nothing, and what it looks like if you do.
You still make the call. You just make it with the outcome already modeled.
Three decisions where simulation changes everything.
Reformulation decisions
You're seeing consistent signals around a product attribute like texture, taste, ingredient tolerance, or efficacy. Before you commission R&D, Lexsis models the impact: which segments are driving the complaint? What share of your total base does this affect? What is the projected retention improvement if the attribute is fixed, and the projected churn acceleration if a competitor launches with it first? You go into the reformulation conversation with a business case, not a hunch.
Pricing decisions
Price sensitivity looks the same in aggregate. It isn't. Lexsis breaks down which customer segments churned citing price, in which acquisition channels, against which competitors. Before you launch a mid-tier SKU, you know exactly which markets and cohorts it needs to serve, and which ones just need better value communication, not a cheaper product.
Channel and expansion decisions
Retail expansion looks like growth. Sometimes it's brand dilution. Lexsis models the downstream signal impact of a retail rollout: does review quality hold? Does DTC churn accelerate as retail customers substitute? What does your brand NPS look like in 90 days if the retail experience doesn't match the DTC promise? You see it before it happens.
See a simulation in action
Get a walkthrough of how Lexsis models outcomes before you commit.
The cost of skipping the simulation.
The average major product mis-decision costs a CPG brand $2.4M per year in reformulation costs, re-launch spend, recovered customer acquisition, and brand repair.
The window from signal to strategic response for most brands is 6 to 8 weeks. During that time, customers are forming opinions, leaving reviews, and switching to alternatives.
Lexsis compresses that window to under 48 hours and lets you test the response before committing. Not because your instincts are wrong, but because the signals in your customer data will tell you things your instincts can't.
“73% of customer signals never reach the decision-makers who could act on them.”
“$2.4M: the average annual cost of a major product mis-decision for a CPG brand.”
“Lexsis compresses signal-to-decision from 6 to 8 weeks to under 48 hours.”
Your next product decision is already in your customer data.
Lexsis surfaces it, models it, and gives your team the confidence to commit or the evidence to wait.