Omniconvert

Omniconvert is the straightforward solution for eCommerce experimentation 

Our suite:

Explore 
- real-time web personalization (based on weather, geolocation, cookie and behavior data, etc)
- A/B testing using an advanced WYSIWYG editor
- triggered mobile and desktop interactions (exit-intent technology, on-load, on-scroll or on-click)
- surveys with branching logic that you can easily build in order to get strong insights about specific segments of visitors (new, returning, sleepy, lost, VIP, etc)

Pulse
- NPS monitoring
- real-time alerts based on NPS + RFM segment
- advanced NLP analysis of customer feedback

Reveal: 
- Advanced customer segmentation 
- Customer analytics - CLV, retention, cohorts, etc
- Audience Builder - target customers based on their NPS, RFM, product, category, time since the last order, city, etc

Orgo.space

Investor

Omniconvert CVO Academy

There's a shift going on in the entire retail industry: from products to customers and from acquisition to retention. 
To be able to make the shift, companies have to understand the customer behavior and the jobs that their products are being hired for by their customers. 

Amazon makes a great job on this aspect: they manage to keep 9 out of 10 customers coming back and buy again. 
Customer lifetime value should be the north star metric for any eCommerce company willing to thrive.

Together with 8 great minds in the digital eCommerce and marketing arena, I am starting an online academy to help companies understand and improve customer lifetime value. 
It is a serious endeavor - for the first course, we condensed all our knowledge about customer lifetime value into >100 lessons.

In a world where 3rd party cookies are becoming irrelevant, becoming an expert in a field that’s just shaping up will be an unfair advantage for you and your company. 

Working in an email marketing, CRO, or PPC agency? This is going to give you huge leverage: you will be able to actually know what’s going on with your eCommerce customers better than they do. 

Leader of a retailer willing to nail digital transformation? Don’t neglect this: the main reason that you’re in the digital transformation is to become customer-centric and adapt to the new market conditions. 
How can you do that, if your team has outdated knowledge?

Founder & Course Instructor

Pintilie Broker de Asigurare

Business development
Marketing strategy
Innovation

Marketing Manager

Co-founder

Etcetera

Owner

Sover Optica Shops

Sales Trainer

BNet Computers

Co-owner

Sover Optica

Key Account Manager

Delta RFI

Weekly radio-show producer, just for fun: getting in touch with thousands of ears might be delightful:)

Radio-Show Producer

Founder at Omniconvert: I help retailers increase their Customer Lifetime Value and Conversion Rate with our advanced solutions

I help eCommerce brands and retailers unlock growth by leveraging CRO & CLV! 

I’m the founder of Omniconvert, where we empower eCommerce players like Patagonia, Shiseido or Tempur make progress through experimentation & AB testing 

After 18 years in eCommerce, here are three significant achievements that brought me here:

➔ My first eCommerce company started with just $700 and went on to become the largest online car insurance player in Romania, thanks to the principles of Conversion Rate Optimization (CRO) and Customer Lifetime Value (CLV).

➔ After realizing the game-changing potential of Conversion Rate Optimization I launched OmniConvert, a growth experimentation suite for eCommerce companies, where >1K eCommerce companies ran >60K experiments 

➔ My team helped >800 eCommerce companies like Patagonia, Sephora, and Max Mara run experiments to improve their conversions and CLV

I’ve finally put all my experience in one place and wrote a best-selling book: The CLV Revolution - a practical guide with actionable insights to leverage the power of customer research, CX, and experimentation to improve the Customer Lifetime Value in eCommerce. 

Currently, we're developing the first AI-powered CRO audit in collaboration with 100 leading experts from the CRO community, with the goal of establishing the global CRO standard for eCommerce

✉️ Let’s connect! DM me to chat about AI in CRO, CX, CLV, or experimentation, or reach me at valentin [@] omniconvert [.] com

Happy Birthday, Romania!

May your next experiments have solid hypotheses!

Valentin Radu

Omniconvert: we help companies grow with AI / AB testing

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This is a very dangerous lie: 
"Good work speaks for itself."

It doesn’t.
I spent years building in silence. 
I thought if I just kept my head down and grinded, the market would notice. 
But here is the hard truth: If you don’t use your voice, the market files you in the wrong folder: "Ignore"
And when the moment comes, they won’t think of you.

My journey wasn't a straight line to the boardroom.
Event 1: Humble beginnings in Bucharest ->
Event 2: 2h in a butcher shop when I was 15 -> 
Learned that life can get real ->
Event 3: Traded time for money without creating leverage
Event 4: Scraped together $700 to launch my first eCommerce business. Learned by doing. I stumbled. I got back up.

But the real unlock didn't come from better code or more ads. 
It came when I stopped guessing and started listening. 
I took customer insights and turned them into experiments.

For years, I hid behind the label "Builder, not Speaker." 
That label kept me small. 
So, I rewrote the pact with myself.
I decided to share the scars. 
To teach what I know. 
To challenge the status quo gently but firmly.

Now, my folder in the market is clear:
I help companies stop guessing using our tech + services. 
I turn data and customer behavior into experiments that lifts 3 things:
1. Conversion Rate
2. Customer Lifetime Value (CLV)
3. NPS

That’s it. No "growth hacking." 
No shiny tactics.
CLV is the compass.
Experiments are the engine.
Customer Truth is the fuel.
I poured this methodology into my book, The CLV Revolution, and I built it into our software.
Today, there are 2 years since I launched my book. 
One of the hardest, yet best projects of my life so far.

The takeaway?
Your voice is not vanity. It is the index tag in people’s minds. 
If you don’t write it, they will write it for you, and they’ll probably get it wrong.
I’m choosing to write mine.
So when you are ready to turn data into experiments that actually move the needle? 
You know exactly where to find me.

omniconvert

marketizator

cvo-academy-by-omniconvert

JSESSIONID

LinkedIn Login, Sign in | LinkedIn

li_at

Talks about #clv, #cro, #cvo, #nps, and #ecommerce

Retail is about to be disrupted. 
Experimentation is about to be disrupted.
Massively.
As pretty much anything else on this planet.
Figure this:
We are moving from disconnected human silos to a unified, Agentic AI ecosystem.

The manager's brain is the bottleneck. 
The data flood:
- competitor ad spend
- real-time sentiment
- pricing
- competitor ads & offers
- stock availability
Is too vast for manual analysis. 
Old-school "If-This-Then-That" logic is dead; it’s too slow and rigid for shrinking margins.

The Solution: An autonomous, self-learning engine.

Input (Total Recall): 
Ingests everything: from Shopify customer data to unstructured reviews to competitor stock levels.
Process (The Brain):
 AI Agents don’t just analyze; they hypothesize. They predict impact, rank experiments, and decide the next move.
Action (The Hands): 
The system auto-adjusts levers, swapping creative, changing pricing, or triggering SMS, without waiting for approval.
The Mandate: 
Experiment everywhere. The goal isn't to be "right" once, but to test constantly at machine speed.

The Shift: 
The E-commerce leader is no longer a "doer" pulling levers, but a Supervisor auditing the machine’s logic.

See you there!

I have lived 45 years and still haven't cracked this code. 
At least I know that you owe this to yourself:
Avoid sameness from all your heart! 

"It's a hell of a responsibility to be yourself. It's much easier to be somebody else, or nobody at all" - saw this in a recent movie with G Clooney. 
Actually a pretty good one, btw.

But I don't want to talk about any movie.
I want to talk about differentiation.

Many companies are drowning in a sea of sameness.

They claim to be data-driven, but all they do is over-invest in "performance" traffic & ads, neglecting the other 2 levers: conversion & retention. 
Or ignoring that they don't have a brand, but a logo.

We have done the same, for too many years.

We 've built a CRO / experimentation tool. 
Until Google Optimize ate our dinner.
That's when we realized it: we have to over-deliver.
300 interviews later, found out that retention rate is massively important.

Built a customer insights & analytics tool to create more value. 
Than, Google Optimize got sunset. 

Now, 2 years after a very intense marathon, our tool is among the Leaders in the AB testing category.

Why? 
Because we offer way different than any AB testing tool in the eCommerce landscape:
> AI diagnose tools for their UX, data, user sentiment 
> Specialized for profit, not vanity metrics: CLV-focused
> Segment and understand their customers
> Monitor CX & NPS
> Get quali insights
> Proper Support: we're small enough to care.

And this is only the beginning: we are cooking something truly disruptive in Q1! 

Follow me to stay up to date!

I got into the SaaS with a lot of stupid ideas in my head.
And made a ton of mistakes.

That’s why, I am trying to spare fellow entrepreneurs from making the same ones - tomorrow at Tekpon AI 

For the first 3 years, I thought I was a genius for building features. If churn was high? Code a new feature. If leads were low? Code a new feature.

I was treating every business problem like a nail, and "Product Engineering" was my only hammer. 

The result? 
I built a spaghetti-code monster and walked straight into the Red Ocean (see image #2). 
High supply. 
Incredibly high CAC. 
Low close rates.

It cost me $1M and a painful round of layoffs to learn the difference between Product Engineering and GTM Engineering.

In my upcoming presentation, I’m sharing the unfiltered playbook. No fluff, just the scars and the system.

We will cover:
1. The $1M Mistake: Why hiring more sales reps before you nail a system is suicide. 

2. PMF vs. CMF: Why Product-Market Fit means nothing without Channel-Market Fit. 

3. How to nail GTM these days - out step by step process

Come for the scars. Leave with a system.

Who’s ready to get out of the Red Ocean? 👇

68% of visitors never reach the cart page. That's why most Shopify store owners can't barely break even on their ads. 

The problem has nothing to do with your products, but with your promise.
Your promise doesn't connect to their struggle.

Why is this an issue? Because nowadays it's way too expensive to acquire customers. As a Shopify store owner, you compete with everything on your clients' feeds:
- The newest pair of Nike's 
- The upcoming Apple AirPods 
- The latest Patagonia jacket

You compete with cute cats, the threat of AI wiping your job, a new robot from Elon Musk, etc. Pretty much, everything in people's feeds. That means it's very very very hard to break even with ads anymore.

Most Shopify store owners believe they should add more to their pages. 

That's wrong! 

The most important thing is not to add more, but to remove the friction.

There are 5 main friction points you need to be aware of:

1. The Hero Zone

This is the most important section because it's the hook that says to your customer, "I understand your struggle, and I'm gonna solve it with my product."

On mobile, it's even more important because your customers only have an 800-pixel screen, and they should see something that is big enough, compelling, and punchy enough so people will stick around and buy.

2. The Uncertainty Gap

This issue occurs when you don't provide sufficient clarity, and your solution doesn't address their problem.

To fix this problem, simply ask your existing customers what their pain was and how they would describe your solution.

3. The Trust Void

People don't trust you. You're a stranger. You've just grabbed their click and they are there for a few milliseconds.

They need to see social proof and other success stories, they need a money-back guarantee, they need real reasons to buy, and they expect answers to all of their questions.

4. The Decision Maze

When people visit your online store, you "throw a lot of things at them."
And very often you end up wasting a click because you don't make the job very simple.

To fix this mistake, you need to do one very simple thing: buy something from your own website. If the process is complicated for you, it will likely be the same for your customers.

5. The Mobile Experience

70% of traffic is on mobile devices. Most shop owners leave it to chance and waste a lot of money on traffic and ads, forgetting that most of their revenue comes from these small devices.

So make sure your website is easy to navigate and offers instant gratification with every button your visitors press.

This is what's going to set you apart from the other 95% of your competitors.

If you want to test these friction points on your Shopify store, here you go:
AB test on 50K free users every month:  

https://lnkd.in/dr9QcKPg

CRO isn’t broken, the incentives are. 
We’ve turned rigorous experimentation into a stage show that rewards loud wins, cherry‑picked stats, and “lift” that never hits the P&L.

I wrote about the CRO disinformation circus: why vanity testing thrives, how weak hypotheses and bad math poison decisions, and what it takes to rebuild trust with customer research, proper stats, and a CLV compass. 

If the goal isn’t profitable growth, it’s theater.

If you’re done with “+40% CVR” posts that don’t move margin, this is for you. 
I break down the traps, the incentives behind them, and a practical path back to evidence and outcomes.

Read the whole guide here : https://bit.ly/CRO-circus

I'm Valentin. I write (almost) daily about growing eCommerce companies through data, experimentation, and deep customer insights.
If you want to scale smarter, click that bell button on my profile.

The CRO Disinformation Guide

Becoming a CRO Strategist in 6 months?
It hinges on your definition of "effective."
Entry-level role: 
Yes, you can master the basics. 
You can learn A/B testing principles, identify obvious friction points, and land that first gig. You can run tests.

Mature driver of growth: No. 
That takes time.
True strategy isn't just about changing button colors; it is about mastering the invisible work that actually moves the needle:
Data Integrity & Anomaly Detection: 
It’s not just reading reports; it’s spotting when the data is lying. Is that dip in conversion a seasonality issue, a broken tracking pixel, or a genuine UX failure?

The "What" meets the "Why" (Quant + Qual): 
Anyone can look at GA4. A strategist knows how to overlay hard numbers with customer sentiment (surveys, heatmaps) to generate insights that actually predict behavior.

Navigating the "Office Politics": 
This is the unspoken killer of experimentation. You need to know who to leverage—Product, Dev, Legal—to speed up the process. A strategist knows how to get buy-in and clear the road so the testing velocity doesn't stall.

Quick wins in your role: Absolutely. You can start optimizing conversion flows today.
Use tools like Omniconvert Explore to get developer-free A/B/n testing.
Bridge the gap between strategy and execution.

Consult our CRO Benchmark to access over 60 tailored experiment ideas based on real industry data.

The Verdict: Choose your path.
Go beyond the basics:
Diving into cohort analysis, RFM for CLV, and advanced organizational navigation, our CVO Academy covers the deep work.

Set clear, measurable goals. Be damn sure that you are realistic about the dedication. 
CRO reliably creates value, but you have to prove it with real wins.

Can you become a CRO strategist in 6 months?

In 2010, I was that frustrated eCommerce marketer: 

Staring at Google Analytics at 2 a.m., trying to figure out why our CAC was climbing and our conversion was stuck. 

Every change I asked for took weeks. 
The devs were annoyed. I was losing sleep. 
So I hacked a way to change the site without waiting. 
That hack became the ancestor of Omniconvert.
Fast-forward. 

We went up against the big, well-funded players. 
They had billboards; we had scars and customer calls. 

When Optimizely raised a monster round, our CPCs exploded overnight. 

I remember seeing bids jump from around a dollar to north of $40, feeling like we’d been priced out of our own category. 

That day forced a decision: we can’t win on noise, so we’ll win on outcomes.
We doubled down on three things:

1. Evidence over ego: every feature earns its place through real experiments and real revenue impact.

2. CLV over vanity: optimize journeys that compound, not just pages that spike.

3. Partner over vendor: fast, human support, and hands-on onboarding so teams actually ship tests.

That’s why today, real users share that Omniconvert Explore is the tool they enjoy using more than the well-funded alternatives. 
Not because we’re louder, but because it’s easier to get to a clean hypothesis, target the right segment, launch without code, and learn fast. 

And when they get stuck, a human shows up.

I started with $20K and a pain I couldn’t ignore. 

The product you see today is just that pain, polished by 70k+ experiments and thousands of conversations with people like you who need momentum, not marketing. 

If you’re in the eCommerce arena, we built this for you.

Most eCommerce leaders chase the "next big thing."
I've talked with over 300. 
The common pain after Black Friday?
High CAC / Low ROAS.
They ignore the cheapest growth lever: conversion.

Ignoring feedback and just tracking spend, is a mistake. 
Understanding "why" they';re not buying? 
That's gold.

Predictable growth comes from experiments.
It’s about learning users. Solving problems with tests.
Use specialized tools. 
Dedicate a team. 
Change behavior. 
Boost revenue.

Think "dopamine loop" in your customer journey.
What small wins make it irresistible?
One team learned from surveys that customers forgot discount codes. 
Their fix? 
Auto-apply first-time discount at checkout.
Faster. 
Cheaper than a redesign.
Fix fundamental UX first. Clear navigation. Shipping clarity. That's low-hanging fruit.

Data-driven companies win. 
Especially fast-scaling ones.

They run strong growth experiments:
Iterative learning + evidence-based decisions

Most eCommerce audits miss growth. They give generic advice. We believe in precision.

Our AI CRO audit cuts deeper. It assigns a "CRO Index Score"

Black Friday = Pretty charts on Linkedin

Here’s why you shouldn’t trust inflated “+X% conversion” claims:

1. No baseline, no truth. 
+47% vs what? 
From 0.8% to 1.2% on 2k sessions is noise, not a business shift.

2. Cherry-picked windows. 
Two great days in a 14-day buying cycle can look like a “winner,” then regress.

3. Wrong denominator. 
“Conversion” on clicks, add-to-carts, or micro-signups isn’t revenue per visitor or net margin.

4. Survivorship bias. 
You see wins; you don’t see the 9 losing tests that were never posted.

5. Misattribution. 
New LP gets credit while price cuts, email pushes, or seasonality did the heavy lifting.

6. Vanity vs actionable. 
Followers, views, CTRs feel good; repeat rate, AOV, RPV, and CLV pay the bills.

7. Hard to reproduce “hacks.” 
If the uplift can’t be replicated on new traffic or cohorts, it’s a lucky strike.

What to demand before believing any uplift:
Baseline and sample size, split, runtime, statistical confidence, and the buying cycle length.

Primary KPIs: revenue per visitor, checkout completion, refund rate, and net margin after returns.

Cohort view: first product bought, device, channel. 
Did it lift second purchase rate?

Reproducibility: rerun on a fresh audience and show stability across weeks. 

Operator’s rule: if it doesn’t move revenue per visitor, repeat rate, or margin, it’s theater. 
Test, measure, then talk.

I'm Valentin. I write (almost) daily about growing eCommerce companies through data, experimentation, and deep customer insights.
If you want to scale smarter, click that bell button on my profile.

Discounts are a tax on being lazy.

But worse than that, most discounts are unvalidated experiments.
Too many companies treat pricing like a guessing game. 

They slap a "20% OFF" sticker on a product without calculating the break-even point or the long-term damage to the brand. They panic, slash prices, and they hope volume fixes the margin leak.
It rarely does.

I learned this the hard way back when I ran an online car insurance business.

The biggest player in the market entered our category. 
We discovered the segment of truck drivers: a tricky, high-intent, extremely lucrative, but incredibly price-sensitive segment. 
We quickly realized that if you use discounts as a blunt instrument, you bleed money.

So, we started using discounts as a scalpel.

Here is exactly how we did it:

We used real-time rate calculations and competitive syncing. 
Every hour, we pulled fresh competitor benchmarks and recalculated the break-even point. 
We used the "Uneven Nudge." 
Before showing the price, we had a loader in which we articulated our points of difference + testimonials.
We didn't matched the blanket 15% off like our competitors. 

We surfaced a tiny, specific incentive at checkout: 7% for 10 minutes.

And we only did it when the math said the contribution margin was still safe:
- higher discounts for larger AOVs ; lower for lower AOVs

We managed to offer discounts from 7 to 18% (for larger AOVs) 

The result?
We hit the sweet spot. 
We protected our contribution margin because our baseline price was smart. But we also spiked conversion because that odd, contextual discount tipped the fence-sitters without dragging the whole customer base into a "wait-for-a-deal" mindset.

Whenever we experimented with wider, rounder discounts (like a standard 10% or 15%), our margins eroded and customers started waiting for the next sale.

The lesson is burned in:
Stop guessing. 
If you don't know your exact break-even on a discounted unit, you aren't selling; you're gambling.
Get weird with the numbers. 
A 10% discount feels arbitrary. 
A 7% discount feels like you sharpened your pencil, did the math, and cut the price to the absolute bone to help them out.
Fix the story. 
Use precision to close the deal, but use storytelling to make the discount unnecessary in the first place.
Discounts shouldn't be a tax. 
They should be a calculated ongoing experiment.

There are the 4 phases of Agentic eCommerce:

Phase 1: Assisted ops with behavior‑linked creatives & websites

What happens: 
AI generates copy, images, and video variants from product feeds and on‑site behavior signals (views, recency, cart status). 
Creatives adjust headlines/CTAs to match intent and stage, then test automatically. 

Threats: 
Creative sameness and weak hypotheses; privacy/compliance gaps when tying creatives to individual behavior; data noise that misguides automation. 

Phase 2: Predictive personalization using geo‑sentiment

What happens: 
Models blend first‑party behavior with geo‑located sentiment from public reviews to adapt offers, social proof, and messaging by city/region. 
Positive local sentiment boosts urgency; negative themes trigger objection‑handling creatives. Location rules respect consent. 

Threats: 
bias from dirty or unrepresentative sentiment data; overfitting to short‑term CVR at the expense of CLV; consent and transparency risks with location data. 

Phase 3: Autonomous experimentation + price/creative coupling

What happens: 
Systems auto‑spin creatives and page layouts, then coordinate them with competitor price feeds and margin floors. If a rival drops price, AI shifts from discounting to value‑led creatives or bundles, staying within guardrails to protect contribution margin. 

Threats: 
black‑box decisions you can’t justify; price wars from naive competitor‑matching; test pollution and false positives without governance. 
Set minimum margin floors, document logic. 

Phase 4: Journey orchestration for CLV

What happens: 
AI aligns acquisition, onsite UX, pricing, and retention. Creatives adapt in real time by cohort, inventory, and geo performance; pricing varies by rules while offers stay transparent. Success optimized to contribution margin and CLV, not just CVR. 

Threats: 
stack brittleness and vendor lock‑in; misaligned incentives between teams; ethics and trust if pricing or nudges feel unfair. Keep human oversight, clear price logic, and CLV guardrails. 

How managers win:
Anchor to CLV and margin floors; prohibit reckless price‑matching. 

Clean first‑party data and segment by behavior; use consented geo only. 
Feed creatives with real behavior and local sentiment, then test for lift, not volume. 

Standardize experimentation quality and document decision logic to keep humans in control

It all started with a sour taste:

CAC was climbing, ROAS shrinking, talent scarce, and managers too swamped to prove what everyone already knew: eCommerce sites were leaking money. 

Still, only a fraction of eCommerce companies are running experiments.

So I started to call. 
One call, then ten, then one hundred and twenty conversations with CROs, agencies, product leads, and ecommerce leaders. 
The story was the same:
“I don’t have time to run audits.”
 “I can’t win budget without competitive proof.”
 “I need a fast, objective way to open CRO deals.”

So we rallied the community.

120 plus experts, 300 criteria, a voting group that acted like open-source CRO. 

We defined what “CRO-ready” actually means across UX, PDP and checkout friction, accessibility, data tracking hygiene, speed, and trust signals.

Then we built the engine.
An AI model that scores, ranks, and turns leaks into a prioritized backlog with AB testing ideas that make sense.

The beta punched us in the face with a negative NPS, so we rebuilt it, hardened everything, and added accessibility, tracking hygiene, and finally, BrandFeel: voice-of-customer intelligence that explains the why behind the user behavior.

Now the AI CRO benchmark gives teams something they’ve badly needed: high-leverage points. 

3450 eCommerce websites later, I want to hear from you:

How do you think the future of eCommerce will look?
Comment your prediction.

The top 10 most upvoted answers will each get 5 free credits for AI CRO audits they can use for ecommerce websites.

Your turn:

We have to stop building the Pedestal. 
We need to start training the Monkey.

There is a famous mental model from Google X’s Astro Teller regarding innovation. 
If your goal is to get a monkey to recite Shakespeare while standing on a pedestal, which task do you tackle first?

Times are tough for eCommerce. 
High competition + High CAC = Thin margins.

Most people build the pedestal. 
Why? 
Because it’s easy. 
It feels like progress. 
You can show your boss a shiny new pedestal and say, “Look! 
We’re halfway there!”

But if you can’t train the monkey, the pedestal is useless.

In eCommerce growth, we are guilty of building pedestals. 
We build shiny dashboards, tweak the website with some A/B tests, waste a ton on media. 
But we are ignoring the "Monkey": the impossible, messy, critical task of making sense of the noise.

The Hard Truth: The Human Brain Cannot Cope with all this data.
We are drowning in signals. 

To run truly impactful, evidence-based experiments, we need to synthesize a chaotic web of inputs that no human team can process manually:

❶ Consumer & User Behavior: What are they doing on-site and off-site?
❷ Sentiment Analysis: How do they feel about the brand?
❸ Competitor Intelligence: Real-time offers, stock availability, pricing wars, and their entire Ad Library.
❹ Product Data: Product assortment, sales velocity, and returns data.
❺ UX & Messaging: What copy resonates? What flows cause friction?

Our Current Mission at Omniconvert: Training the Data Monkey

We are shifting our focus from the pedestal (the easy wins) to the monkey (the hard data engineering).

We are building an engine capable of ingesting all of this at once.
The goal isn't just "more data."
It is better data + better evidence-based analysis.

We don't want to run more experiments. 
We want to run the right experiments.

To do this, we're starting to assembly the building blocks for eCommerce growth into a unified growth machine:
AI CRO audit - gets UX & data insights from the website & GA4
Brandfeel.ai - provides user sentiment & competitive landscape analysis 
Reveal - ingests customer cohorts & product anomalies into the AI processing layer
Explore - empowers companies to run experimentation on web or mobile apps.

By letting technology handle the correlation of thousands of variables, we free up our human strategists to do what they do best: be creative.

We are done polishing the pedestal. 
DM me if you want to be among the first ones to see it in action.

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