Predictive Growth · Customer LTV · Fractional Data Science
Predict your most
profitable customers
with Enterprise-Grade ML.
We bring the regression modeling firepower of $B+ brands to scaling Shopify stores. Science-backed rigor, translated into the strategic signals you need to grow.
Who we serve
Is this
right for you?
Kinetric brings enterprise-level data science to scaling brands — the kind of predictive modeling that used to require a full in-house team. You might be a fit if:
- You're a DTC or e-commerce brand doing $1M–$10M in annual revenue
- You've outgrown Shopify's native reports and need enterprise-level data science — without hiring a full internal data team
- You know some customers are far more valuable than others, but you don't have a systematic way to identify them early
- You want to know which customers are at risk of churning before they go silent — not 90 days after
- You're ready to make acquisition and retention decisions based on predicted customer value, not just past purchase behavior
What we do
Three ways to work together
We don't sell hours. We scope to the depth your data actually requires — nothing more, nothing less.
Predictive LTV & Growth Audit
A regression-based diagnostic of your customer base that identifies the revenue-driving 20%, scores your active customers by churn risk, and maps the behavioral signals that predict whether a new customer will become a repeat buyer. Every technical finding is paired with a plain-language recommendation your team can act on immediately. You walk away with a 90-day predictive growth roadmap — no ongoing commitment required.
- Regression-based customer segment identification
- Churn risk assessment & scoring
- "Revenue Leak" diagnostic
- 90-day predictive growth roadmap
Custom ML Modeling
We build the predictive infrastructure your team can actually use — churn models, LTV scoring engines, and lookalike targeting frameworks — scoped as a fixed-price project with a full handoff. You own every model we build.
- Regression-based churn prediction models
- A/B test decision engines
- Customer lifetime value scoring engine
- High-value customer lookalike & targeting segments
Fractional Data Scientist
Senior data science embedded in your business on a monthly retainer — 10 hours of strategic analysis per month with a direct line to a senior analyst. Built for board-level reporting and making sense of the noise: every engagement produces analysis your leadership team can read and act on in under five minutes. No agency overhead. No junior analysts. No shared queue.
- Monthly cohort & segment performance analysis
- Churn risk monitoring & proactive alerts
- Campaign targeting recommendations
- On-demand predictive modeling
Featured work
Results in practice
From Test Results to Decisions in Minutes
● LiveMost teams wait 3-5 days to interpret A/B test results before leadership can make a call. We built a tool that cuts that to minutes — upload your test data, get a plain-language recommendation any stakeholder can act on immediately.
- Discovered that a personalization feature drove a 47.7% conversion lift for returning customers — but had no effect on new visitors. That single finding changed the rollout from "ship to everyone" to a targeted strategy that protected margin
- Delivers a clear verdict — ship, don't ship, or test further — along with expected revenue impact and who it affects
- Removes the bottleneck between your data team and your decision-makers, so experiments move from results to action in one meeting
Know Which Customers Need Attention — Before They Leave
● In DevelopmentChurn shows up in the data weeks before a cancellation. This dashboard gives your team a single health score per customer so they know exactly where to focus — before a renewal conversation becomes a save attempt.
- Turns a week of manual account research into a 30-second morning briefing — so your team spends time on relationships, not spreadsheets
- Weekly digest automatically flags accounts that dropped into the warning zone, with context on what changed
- QBR-ready in one click — full account history, health trend, and a clear next-best-action without pulling a single report
Our methodology
Science.
Signal.
Strategy.
- Science
- Rigorous regression modeling and mathematical foundations applied to your customer data — no gut feel, no guesswork.
- Signal
- Identifying high-value customer patterns in untamed behavioral data — who your best customers are, and how to find more of them.
- Strategy
- Translating complex model outputs into plain-language recommendations any stakeholder can act on — from Results to Decisions in minutes.
Signal Detection
Longitudinal time-series analysis of your customer base surfaces the behavioral patterns hidden inside your order history. So what: You'll see, in plain English, which early behaviors predict a high-LTV customer — and which predict a one-and-done buyer — before the second purchase ever happens.
Predictive Scoring
Regression-based churn prediction assigns a real probability score to every active customer — not a gut-feel tier, a statistical estimate grounded in your actual data. So what: Your retention team gets a prioritized list of who needs attention and when, not a guess.
Revenue Prescriptions
Incremental lift analysis quantifies the revenue impact of targeting your highest-LTV segments differently — in paid acquisition, retention sequencing, and budget allocation. So what: Every recommendation comes with a dollar estimate and a clear action, not just a direction.
Who we are
About
A focused solo practice — not an agency juggling 30 accounts. Every engagement gets direct senior attention. No junior analysts. No hand-offs. The same person who scopes the work does the work.
Brendan Hoffman
Founder & Lead AnalystDirect analyst for a multi-billion-dollar DTC brand. I build the models that drive $1B+ decisions — regression-based customer targeting, churn prediction, and A/B test infrastructure inside one of the largest DTC brands in the US. Now bringing that same enterprise-grade firepower directly to scaling Shopify brands — without the $150k/year headcount. University of Maryland, Business Analytics & Information Systems.
Get in touch
Let's talk about
your data
Whether you need a one-time audit or an ongoing analytics partner — tell us what you're working with and we'll tell you how we can help.