Increase LTV after
the first order.

I help Shopify subscription brands get more new customers to buy again, stay subscribed longer, try the right next product, and leave more proof. I do that by installing my own software-backed LTV system behind the customer path.

Book a 30-minute call

How I get there

Find the best customer path.

I identify your highest-LTV customers, what they bought first and next, how fast they bought again, which offers brought them in, and which actions made them more valuable.

Build the customer value data layer.

My system shows which customers become more valuable and where others fall off:

90-day repeat revenue per new customer
30, 60, 90, and 180-day contribution LTV
Second order rate and time to second order
Subscription retention by charge number
First-product, offer, channel, and discount quality
Refunds, margin, and buying paths by customer segment

Install the systems that move customers along that path.

The exact build depends on what your brand needs most. It can include:

Customer portal improvements for subscriptions, swaps, skips, saves, and product education
Review and UGC loops across Judge.me, Trustpilot, photo reviews, and social posts
Product discovery paths based on what high-LTV customers buy next
Customer credits and incentives for actions that grow the business, not just generic discounts
Subscription save flows, pre-cancel interventions, and recovery paths

Turn it into an operating rhythm.

The work becomes clear decisions your team can use, not another dashboard to ignore:

Opportunity roadmap by impact, confidence, effort, speed, and risk
Execution briefs for email, SMS, paid media, support, product, and dev teams
Experiment tracking so the team knows what changed and what actually moved
Monthly LTV report: what improved, what got worse, and what to fix next

Who this is for

Shopify subscription brands where the first purchase is not the whole business.

You sell on Shopify and depend on customers buying again, staying subscribed, trying other products, or creating proof.
You have enough customers that small LTV changes are worth real money.
You already have a team or agency for daily execution, but the customer path after the first order still feels underbuilt.
You want better infrastructure behind customer value, not another dashboard no one opens.

How I work

I start by finding your highest-LTV customers and the path they took. Then I build toward that path.
I install my system and playbooks directly. Your team or agency can still own day-to-day creative, campaigns, and channel execution.
I keep the work tied to repeat revenue per new customer, subscription retention, contribution LTV, margin, refunds, and behavior after the first order.

The simplest fit is setup plus ongoing support: install the system, establish the reads, then keep improving the customer path as the data shows what gets people to buy again, stay subscribed, and become more valuable.

Who I am

I'm Piotr. I've worked on ecommerce growth since 2016, starting as a freelance developer building landing pages and fixing other agencies' work, then founding Carybit, a CRO agency, in 2022.

This is founder-led work, not a handoff to a junior team. I built the software, data layer, and playbooks I install, then stay close to the work as it starts changing the customer path.

Through Carybit I ran CRO programs for multiple ecommerce brands at $100M+ in annual revenue. The agency side is sunset. The quiz-funnel software I built there still serves paying ecommerce customers today.

Before any of that, I played professional tennis for 12 years. Not a credential for advising on growth, but it's where my standards came from.

Why I build this way:

A builder's view of LTV.

Most growth work stops at recommendations. My background is software, CRO, and Shopify implementation. I have built the pages, tools, and systems myself, so I know what can actually change the customer path after the first order and what will turn into busywork.

Real depth on AI, not the hype version.

Most operators selling "AI workflows" in DTC don't have the technical foundations. I'm a developer who's worked through the actual material, including Karpathy's ML and LLM lectures end-to-end. I can tell you which AI workflows will actually move your business and which are half-baked.

I read outside DTC on purpose.

Most growth and CRO advice stays inside DTC, with customer psychology reduced to surface tricks (urgency, scarcity, social proof). I work from frameworks and research outside that bubble: hospitality (Unreasonable Hospitality, Ritz-Carlton's excellence model) and customer psychology (Cialdini on influence, Kahneman on decision-making, Schwartz on awareness levels). I bring them in when they fit.

What I believe

Higher LTV comes from doing hundreds of small things excellently. No single move sustains long-term growth. The brands that scale commit to excellence at every touchpoint: product, copy, customer service, onboarding, retention.
Negative word of mouth is 10x more viral than positive. Rising CAC with stable CPMs is often a reputation signal. People who would have bought are choosing not to because of something they read or heard. Reputation and consistency are long-term risk mitigation.
Your best customers already show the path. The highest-LTV customers usually have patterns in common: what they bought first, what they bought next, how fast they came back, and which actions they took along the way.