where growth meets causal inference analysis
Every product manager, every analyst, every data scientist knows the feeling. It’s the ghost in the machine, the question that haunts every growth meeting:
“We see the drop-off. We have the funnel charts. But where, in this entire user journey, is the one change that will actually make the LTV curve bend upwards?”
Meet Maya, our PM. It’s Monday morning. The air in the conference room is thick with the smell of stale coffee and unspoken pressure. On the screen is the slide everyone dreads: “60-Day LTV: Flat for Q3.” The analyst nervously scrolls through a labyrinth of dashboards. The data scientist, buried in a Jupyter notebook, mutters, “Just give me one more week to let the model converge.” And the engineering lead just wants to know which fire to put out first.
Funnels show us where we lose users. Dashboards tell us what the conversion rate is. But when you only have the budget for one smart move, picking where to place your bet feels less like data-driven strategy and more like a spin of the roulette wheel.
Maya needs a decision. Not in two weeks, after another costly A/B test. Today.
This is the story of how Allye transforms that messy, high-stakes guesswork into a clear, ranked-to-win battle plan. All without writing a single line of Python.
In our mobile productivity app, the path to an active user is a treacherous, four-step journey.
Our 60-day Lifetime Value (LTV) is stubbornly stuck at $12.3. We’re bleeding potential, but we don’t know which of these four gates is the bottleneck strangling our growth.
The traditional playbook? Ship four different A/B tests—one for each gate—and pray. Wait weeks for the p-value to dip below 0.05, all while confounding variables muddy the waters. Was it the new marketing campaign? The holiday season? The fact that Android users outnumbered iOS users this week? The causal story becomes a tangled mess.
You know the scene. The 11 PM Slack notification that everyone dreads: “Test is still underpowered. Can we extend for another week?”
Engineering lets out a collective groan. Marketing loses momentum. And Maya’s beautifully crafted roadmap slips, yet again, to the right.
Allye makes advanced causal analysis easy for everyone on your team—no code required. Here’s how you can quickly identify which step in your funnel will drive the biggest LTV growth:
*(Duplicating a node is a single click. Your canvas stays clean, your mind stays clear.)
Propensity Score Matching — One dropdown per column. The heavy lifting happens in seconds, not sprints.
Causal Forest — This isn't just a tree. It's a treasure map. Hover to see where the gold is buried.
Transform — Various handy nodes for flexible data transformation.
Allye condenses weeks of analysis into a single、no-nonsense table:
Hover over any bar and Allye surfaces the CATE. For Android users aged 18-24、the tutorial overhaul is worth a jaw-dropping +$4.17 per head. Maya now knows not just what to tackle、but who will benefit most.
The analysis you just read about isn't magic — it's what happens when powerful analytics become truly accessible.
Stop wrestling with tedious code and start exploring your data at the speed of thought.