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.
Simulate reformulation decisions.
Before you commission R&D, model the impact against your real customer signals.
Identify complaint drivers
See which segments are driving complaints around texture, taste, ingredient tolerance, or efficacy,and how much of your base they represent.
Model retention impact
Project the retention improvement if the attribute is fixed, and the churn acceleration if a competitor launches with it first.
Build the business case
Go into the reformulation conversation with a data-backed case,not a hunch. Know the numbers before you commit the budget.
Simulate pricing decisions.
Price sensitivity looks the same in aggregate. It isn't.
Segment-level price sensitivity
Break down which customer segments churned citing price, in which acquisition channels, and against which competitors.
Test before you launch
Before launching a mid-tier SKU, know exactly which markets and cohorts it needs to serve,and which ones just need better value communication.
Avoid mispricing risk
A cheaper product isn't always the answer. See whether the signal is price, value perception, or competitive positioning before you commit.
Simulate channel and expansion decisions.
Retail expansion looks like growth. Sometimes it's brand dilution.
Model downstream signals
See whether review quality holds after a retail rollout, or whether the retail experience dilutes brand perception.
Predict DTC cannibalization
Understand if DTC churn accelerates as retail customers substitute,before it shows up in your quarterly numbers.
Forecast brand health
Project what your brand NPS looks like in 90 days if the retail experience doesn't match the DTC promise.
“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.”
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.
See a simulation in action
Get a walkthrough of how Lexsis models outcomes before you commit.
Your next growth 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.