Conversion Optimization in Khmelnytskyi: A/B Tests That Deliver ROI
I am Oleksandr Filyuk, 15+ years and 130+ product projects. I lift conversion on 7th Kilometre wholesalers' B2B portals, Podillia retail DTC e-commerce and agritech platforms through GA4, Hotjar, A/B tests and the HEART framework — no inflated cases, only honest unit economics.
35%average conversion increase
500+A/B tests conducted
2.5xaverage optimization ROI
100+Satisfied clients worldwide
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Tell me about your website, current conversion, and business goals — I'll prepare a preliminary analysis
Free conversion audit
I'll analyze your site and show the main customer drop-off points with growth potential estimate
Conversion growth
We implement changes, test hypotheses, and record measurable growth in your metrics
Types of Conversion Optimization
I increase your website conversion based on data and testing
🧪
A/B testing
Comparative testing of page variants, buttons, texts and forms to determine the best performer.
📄
Landing page optimization
Improving landing page conversion: headlines, CTAs, structure, social proof.
📈
Sales funnel optimization
Analysis and elimination of customer drop-off points at every stage from first visit to purchase.
🎨
UX interface optimization
Improving website or app usability based on user behavior data.
📝
Form optimization
Reducing form abandonment rate: simplification, validation, progress bar, autofill.
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User behavior analysis
Heatmaps, session recordings, scroll-maps to understand how users interact with the site.
Work Process
1
Current Conversion Audit
I analyze current conversion metrics, sales funnel, traffic sources, and user behavior to establish a baseline.
2
User Behavior Analysis
I study heatmaps, session recordings, scroll maps, and click analytics to understand real interaction patterns.
3
Hypothesis Formation
Based on data, I create a prioritized list of conversion improvement hypotheses, estimating each one's potential impact.
4
Variant Design
I develop alternative versions of pages and interface elements to test the formed hypotheses.
5
A/B Testing
I run controlled A/B tests with statistically significant samples to verify each hypothesis.
6
Implementation & Iteration
I implement winning variants, analyze results, and launch a new optimization cycle for continuous growth.
Pricing
Choose the optimal package for your project
Basic
Express Consultation
One-time 2-hour session
$300$400What's included:
- Preliminary site/product analysis
- 2-hour video call
- Current situation analysis
- Main UX issues overview
- Basic competitor analysis (3 companies)
- Conversion improvement recommendations
- Current design assessment
- Mobile version analysis
- Page speed check
- SEO recommendations
- Sales funnel overview
- Task prioritization
- Consultation recording
- Short action checklist (PDF)
- Chat support for 7 days after consultation
Results in 1 day
Optimal
Deep Audit
Comprehensive analysis in 1 week
$800$1000What's included:
- Full UX audit of website/app
- Analytics analysis (GA4, Hotjar)
- Competitor analysis (5-7 companies)
- Target audience analysis
- User behavior research
- Step-by-step conversion funnel analysis
- Forms and CTA elements audit
- Responsiveness check on 5+ devices
- Content strategy analysis
- SEO audit (technical + content)
- Speed and Core Web Vitals analysis
- Detailed report with screenshots (PDF, 30+ pages)
- Step-by-step change roadmap
- Results presentation (2 hours)
- Prioritization by business impact
- Chat support for 14 days
- 1 additional consultation after implementation
Most popular
Premium
Strategic Partner
1 month collaboration
$2000$2500What's included:
- Everything from the Deep Audit package
- Full digital strategy development
- Product strategy and positioning
- Detailed competitor analysis (10+ companies)
- Customer Journey Map development
- Key page prototypes creation
- A/B test plan for conversion optimization
- Content marketing strategy
- Process automation recommendations
- Technical infrastructure audit
- Business model and unit economics analysis
- Presentation for team/investors
- 4 strategic sessions of 1.5 hours each
- Weekly check-ins throughout the month
- Help with specs for developers/designers
- Implementation monitoring
- Post-implementation results analysis
- Chat support for 30 days
- Priority access to future consultations
- 20% discount on my development services
Maximum results
Frequently Asked Questions
Answers to the most popular questions
The standard cycle is 12-16 weeks. The first 2-3 weeks are a deep audit: GA4 event model, Hotjar/FullStory setup, AARRR funnel analysis by ICP segment. Next 1-2 weeks for user discovery interviews and shaping the hypothesis backlog. The remaining time is A/B-test sprints of 2-3 weeks each. First results appear by week 4-6, multiplier ROI effect by month 3-4. I never promise "+50% in a week" — that is marketing fraud.
It depends on the baseline conversion and MDE. For a landing page at 3% conversion with 20% MDE (lifting from 3% to 3.6%) you need 17-20K visits per variant at a 95% confidence interval. With less traffic I switch the team to bandit algorithms, qualitative research (Hotjar sessions, usability tests) and CRO without A/B (for example, direct redesigns based on Nielsen heuristics). An honest answer beats pseudo A/B on 200 visits.
A UX audit is a diagnostic of the interface against heuristics, accessibility and JTBD fit. CRO is a system of experiments that changes conversion and unit economics. I often start with a UX audit because it quickly finds low-hanging fruit (broken funnels, unclear CTAs, mobile checkout issues), and then we move to A/B tests for fine tuning. It is a sequence: first remove obvious barriers, then test growth hypotheses.
That is the classic CRO trap. Optimising only immediate conversion can pull in "hot" traffic that later churns. I always look at 30/60/90 day retention of segments going through the test variant and at the LTV/CAC ratio. If a new version gave +15% sign-ups but LTV dropped by 25%, that is a loss, not a win. In reports I always show both numbers and recommend a rollback if unit economics worsened.
For event analytics — GA4 with a custom event model, Mixpanel or Amplitude for product events, BigQuery for deep SQL analysis. For qualitative insights — Hotjar (heatmaps, recordings) and FullStory (rage clicks, dead clicks, frustration signals). For A/B tests — VWO, Convert.com or Statsig depending on budget and tech stack. For voice-of-customer — Typeform, Hotjar Surveys, on-site polls. I am not locked to one vendor — I pick the stack to fit the product and team.
I use RICE tied to ROI. Reach — how many users a test will touch per month. Impact — expected conversion lift (based on data, benchmarks and expert estimates). Confidence — how sure we are about impact (0-100%). Effort — person-weeks for design, dev and QA. On top of RICE I add a unit-economics safety filter: tests that might damage LTV go through a separate review. The backlog is always open to the team — it removes politics and disciplines the discussion.
It depends on stage. If a page has many problems (irrelevant UX, confusing navigation, weak value proposition), single-variable tests will not move the needle — you need a radical redesign and to test the whole variant against control. If the UX foundation is healthy and we are looking for fine improvements, single-variable gives a clean signal. I usually start with radical redesigns on the worst-performing pages and then move to targeted tests.
I lock in the baseline at kick-off: key conversions for 30/60/90 days before the project, ARPU, LTV, CAC. After 3 and 6 months we compare. Separately I calculate incremental revenue from winning tests — delta conversion times traffic times AOV gives the additional monthly revenue. Typically my projects pay back in 2-4 months. I always show this math in the quarterly report — no shadows, no "conversion grew but it is hard to say".
The 7th Kilometre wholesale market is the largest textile hub in Eastern Europe, and its B2B portals serve buyers from Poland, Romania, Moldova and Czechia. Typical pains are a tangled catalogue structure, no MOQ data and unclear pricing logic (retail vs wholesale vs drop). I rebuild the funnel: in 3-5 clicks from the landing page a buyer must see the assortment, price tiers and a "price request" or "order batch" button. I add multi-language (PL/RO/RU/EN), live stock and a mix calculator. Lead conversion typically grows 2-3x because we simply remove friction that has piled up over years.
Khmelnytskyi DTC e-commerce is mostly clothing, cosmetics, kids' goods and local food brands. The biggest hole is mobile checkout (60-70% of orders start on a smartphone but close on desktop or not at all). I optimise: guest checkout, Apple Pay/Google Pay, Liqpay/Monobank one-click, address auto-fill from Nova Poshta, clear shipping costs before payment. The second big topic is abandoned carts due to lack of trust: reviews, return guarantees, clear delivery dates. Payment conversion typically grows by 20-40% per quarter.
Podillia agritech is a long B2B cycle (3-12 months from first contact to contract), and "conversion" here is not one metric but a funnel: lead -> MQL -> SQL -> pilot -> contract. I build multi-touch attribution in GA4, add Hotjar to diagnose behaviour on case-study and pricing pages. The highest ROI usually comes from: case-study page optimisation (where an agronomist sees a similar farm already using the product), a demo form with qualification (fields for farm size and crops), and a 14-30 day follow-up sequence. SQL conversion grows by 30-60%.
Hybrid. Strategic workshops with the team (kick-off, funnel analysis, CRO sprint planning) are better offline — in Khmelnytskyi these are clients' offices around Proskurivska, Kamianetska, Soborna Square or meetings at KhNU and PDU spaces. Analytics work, GA4/Mixpanel setup and test reviews run async via Loom, Notion and weekly Zoom syncs. For teams in Kyiv, Lviv and the EU I work fully remote. Details on the conversion optimisation in Khmelnytskyi page.
Why choose me?
Comparison with other options
| Me | Other consultants | |
|---|---|---|
| Approach | AARRR funnel + unit economics | Landing-page optimisation only |
| Analytics | GA4, Mixpanel, Amplitude, Hotjar, FullStory | Basic GA without an event model |
| Testing | Hypotheses with MDE, statistics, stopping rule | Eyeball tests without significance |
| Prioritisation | RICE/ICE tied to ROI | Random list of ideas |
| Segments | B2B wholesalers, DTC retail, agritech | One template fits all |
| Metrics | Conversion, AOV, LTV, CAC payback | Only CR with no P&L impact |
Conversion Optimization Khmelnytskyi — A/B Tests, 200%+ ROI
Conversion optimisation in Khmelnytskyi: context and why it matters
Khmelnytskyi is a city on the Southern Buh with around 270 thousand residents and a strong Podillia economy. Three powerful business layers coexist here: the 7th Kilometre wholesale market (one of the largest textile hubs in Eastern Europe), local retail DTC e-commerce, and agritech platforms serving the agricultural sector. Each segment has its own conversion specifics, funnel and pain points. Universal CRO templates do not work here — local expertise and an understanding of specific users' JTBD are required.
I am Oleksandr Filyuk, with 15+ years in conversion optimisation and 130+ product projects under my belt. I work with Khmelnytskyi and Podillia teams offline (around Proskurivska, Kamianetska, Soborna Square, KhNU and PDU spaces) and remotely with teams across Ukraine and the EU. My philosophy is simple: CRO is not about "button colours", it is about unit economics. Every test must bring incremental revenue without harming LTV.
Methodology: AARRR, RICE/ICE, statistically valid A/B tests
It all starts with an AARRR funnel audit (Acquisition, Activation, Retention, Revenue, Referral). I configure the GA4 event model, plug in Mixpanel or Amplitude for product events, and add Hotjar and FullStory for qualitative insights. At this stage it becomes clear where users are really lost. In 80% of projects the biggest hole is not where the team thought — it is often activation after sign-up or mobile checkout, not the landing page.
Next we shape the hypothesis backlog and prioritise with RICE/ICE. For every A/B test we document the statistical hypothesis, MDE (minimum detectable effect), expected duration and stopping rule. I never run "eyeball" tests — that is the most expensive mistake in CRO, leading to false wins and wasted money. If traffic is too low for a statistically valid A/B, we switch to bandit algorithms or qualitative methods (Hotjar sessions, usability tests, heuristic redesigns based on Nielsen).
Tooling: GA4, Mixpanel, Amplitude, Hotjar, FullStory
Event analytics is the CRO foundation. I build a custom event model in GA4 tied to business metrics: ARPU, AOV, LTV. For product events I plug in Mixpanel (better for funnels) or Amplitude (better for cohort analysis and retention). For deep SQL analysis — BigQuery. For qualitative insights — Hotjar (heatmaps, recordings, surveys) and FullStory (rage clicks, dead clicks, frustration signals).
For A/B tests I use VWO, Convert.com or Statsig depending on the client's budget and tech stack. For voice-of-customer — Typeform, Hotjar Surveys, on-site polls. I am not locked to one vendor — I pick the stack to fit product, team and budget. For smaller teams part of the toolkit can be swapped for free analogues without losing signal quality.
B2B portals for 7th Kilometre wholesalers
The 7th Kilometre wholesale market is the largest textile hub in Eastern Europe, and its B2B portals serve buyers from Poland, Romania, Moldova and Czechia. Typical pains are a tangled catalogue structure, no MOQ data, unclear pricing logic (retail vs wholesale vs drop) and no multi-language support. A buyer lands, does not understand where the actual wholesale is, and goes to a competitor.
I rebuild the funnel: within 3-5 clicks from the landing page a buyer must see the assortment, price tiers, MOQ and a "price request" or "order batch" button. We add multi-language (PL/RO/RU/EN), live stock from Excel/1C, a mix calculator and clear delivery dates. Separately we set up CRM integration so the wholesaler's managers see leads in Pipedrive or KeyCRM in real time. Lead conversion typically grows 2-3x because we remove friction that has piled up for years.
Podillia retail DTC e-commerce
Khmelnytskyi DTC e-commerce is mostly clothing, cosmetics, kids' goods and local food brands. The biggest hole is mobile checkout: 60-70% of orders start on a smartphone but, because of poor UX, close on desktop or do not close at all. That is a classic 30-50% revenue loss without an obvious reason in "general" statistics.
I optimise: guest checkout (no mandatory registration), Apple Pay and Google Pay, Liqpay/Monobank one-click, address auto-fill from Nova Poshta, clear shipping costs before payment. The second big topic is abandoned carts due to lack of trust: we integrate reviews (Trustpilot, Google Reviews), return guarantees, clear delivery dates, live chat during business hours. Payment conversion typically grows by 20-40% per quarter, AOV by 10-15% thanks to upsell blocks in the cart.
Podillia agritech platforms: the long B2B cycle
Podillia agritech platforms operate in completely different logic. The sales cycle is 3-12 months, and "conversion" is not one metric but a funnel: lead -> MQL -> SQL -> pilot -> contract. Reducing the funnel to "CTA click rate" is a gross mistake that leads to wrong decisions.
I build multi-touch attribution in GA4 tied to the CRM, and add Hotjar to diagnose behaviour on case-study and pricing pages. The highest ROI usually comes from three things: case-study page optimisation (where an agronomist sees a similar farm already using the product), a demo form with qualification (fields for farm size and crops), and a 14-30 day follow-up sequence via email and messengers. SQL conversion grows by 30-60%, the lead-to-contract time shortens by 20-30%.
How to start and the link with product strategy
The first step is a 60-minute free session where I diagnose the current funnel, key metrics and team pain points. Next we pick a format: a 12-16 week CRO sprint with audit and 4-6 A/B tests, or long-term mentorship (3-6 months) with an ongoing hypothesis backlog and monthly ROI reports. For Khmelnytskyi teams I work hybrid — strategic workshops offline, analytics and tests async.
CRO works best paired with product strategy — without the right ICP and JTBD, even the best A/B tests will hit a ceiling. For a deep UX view see UX audit in Khmelnytskyi. Conversion optimisation details and session booking on the conversion optimisation page.