Як виглядає маркетинговий аудит інтернет-магазину від UPLIFY?
A real (anonymized) marketing audit of an online store by UPLIFY: 15 findings across 10 modules — channel concentration risk, unused retention, manufacturer positioning, funnel, measurement. Customer voice and evidence behind every conclusion, plus a roadmap. Produced by Nestor AI + a senior marketer.
Marketing audit of an online store: where the money leaks
A real audit of a real UPLIFY client — fully anonymized. The niche is generalized; the brand, domains, names and all IDs are hidden; the methodology, structure, numbers and conclusions are preserved unchanged.
What narrows the conclusions — read these first
- Google Ads not connected — spend, ROAS and cost per order (CAC) are unknown in this report. 84% of traffic is paid (google / cpc), so all money estimates are L1 (directional), without accounting for traffic cost.
- CRM / margin not provided — unit economics is presented as a framework of questions for the owner, not as a verdict.
- A competitive map was not built in this pass (FIRST-PASS limit) — claims about competitors are flagged as hypotheses.
- That said, the 90-day data cut is complete: GA4 ✅ · Search Console ✅ · Merchant Center ✅ + live site checks.
The report in 90 seconds
Headline thesis. The store earns and converts well (3.7% CR, healthy checkout), but it sits on a single needle — google / cpc drives 84% of sessions and 83% of revenue: a 30-day ad pause is exposure to ~₴440K/mo of revenue (L1 — directional model). Meanwhile the two cheapest growth reserves are not used at all.
1. Concentration risk
P084% of sessions / 83% of revenue from a single paid channel. A pause, ban or rising click cost hits the entire business at once. Goal: bring organic + direct + lifecycle to ≥30% of revenue within 2 quarters.
2. Retention isn't monetized
P0Repeat buyers already deliver 37.8% of revenue (₴598K / 90 days) on their own — without a single email/Viber sequence (Email: 2 sessions per quarter). A base of ~1,300 buyers/quarter accumulates and does nothing.
3. Manufacturing advantage hidden
P1In-house manufacturing of [category A] ("we'll make it to your dimensions", 73% of the feed — own brand) — an advantage rare for the niche, absent from the H1, title and above the fold. The buyer and Google see "just another sports store".
ICP and buyer jobs — from data, not hypotheses
- Retail mobile buyer from ads — 82% of sessions mobile, CR 4.05%, order value ₴1,051. Evidence: GA4 device × channel.
- Parents / families — [category B] for a child's room; the category ranks #3 in organic (52 clicks). Evidence: GA4 item report + GSC.
- B2B: clubs, gyms, wholesalers — "wholesale prices from 10 units" on product cards; desktop segment: CR twice as low (2.33%), order value twice as high (₴2,080). Evidence: on-site copy + analytics segment.
The buyer's main job (JTBD): "cover/insulate a specific area for a specific activity and not get the size, thickness or density wrong". Confirmed by the customer voice: "Many thanks to the managers for their patience, for helping us find the size and density we needed" (buyer review, April 2026, the store's reviews page). The store closes the fear of "buying the wrong one" with its call center and FAQ — but doesn't close it at the positioning level.
5-second test of the homepage: partly failed
The H1 reads "goods for an active life", the title "online store of sporting goods", the meta description "professional equipment". Three different messages, all three generic "a store for everyone". Yet the business has something to say:
- "In-house manufacturing of [category A]" + "we'll make it to your dimensions" — a manufacturing advantage a typical dropshipper doesn't have;
- 73% of feed items are own brand (evidence: Merchant product attributes) — this is a manufacturer, not a reseller;
- "10 years on the market", "own warehouse", "own call center".
Conclusion: strong, evidence-backed differentiation exists, but it's buried in the middle of the pages. This is a messaging defect, not a business one — and the report's cheapest P1 fix.
Checkout is healthy, the bottleneck is product card → cart
| Step (90 days, unique users) | Users | Transition |
|---|---|---|
| Product view (view_item) | 22,387 | — |
| Added to cart (add_to_cart) | 2,200 | 9.8% |
| Began checkout (begin_checkout) | 1,676 | 76.2% |
| Purchased (purchase) | 1,301 | 77.6% |
Checkout is 76–78% at each step, above benchmarks (Baymard: ~70% cart abandonment on average). The only weak step is product card → cart (9.8%): hypotheses to test — few reviews on product cards, delivery time not visible without scrolling. Micro-conversions are alive: 269 phone clicks, 23 callback requests.
Concentration risk: 84% on one source
| Channel (90 days) | Sessions | Share | Revenue | Share |
|---|---|---|---|---|
| Cross-network (PMax, google/cpc) | 30,819 | 84.5% | ₴1,317,501 | 83.2% |
| Direct | 1,866 | 5.1% | ₴155,734 | 9.8% |
| Organic Search | 1,738 | 4.8% | ₴40,985 | 2.6% |
| 2 | 0.0% | ₴0 | 0.0% | |
| AI assistants (ChatGPT) | 55 | 0.2% | ₴5,917 | 0.4% |
>80% on one source = an active risk. Exposure model: a 30-day pause of google/cpc ≈ up to ₴440K of revenue at risk (L1). Social media: 219 sessions, 0 transactions. AI assistants have already brought the first sales (6 transactions, ₴5.9K — a small sample, an early signal) — but the site's bot protection selectively cuts off the AI ecosystem: ClaudeBot gets HTTP 423, while GPTBot and PerplexityBot pass. In Anthropic's assistants the store is invisible; the fix is a single whitelist edit.
Data you can trust — and data you must fix
What's good: purchase events match transactions 1:1 — revenue isn't double-counted; e-commerce events are complete.
- Product analytics is fragmented: the same product lives under two names (UA/RU), some products have purchases without a single view (one item: 112 purchases, 0 views). view_item and purchase send different item identifiers → any product-level CRO analysis is unreliable until the dataLayer is fixed (a hard finding).
- Duplicated custom events: copies of begin_checkout and add_to_cart under different names — noise in the reports.
- 7% of transactions have no source — attribution loss on payment redirects; check the referral exclusions of the payment gateways.
- JSON-LD with a non-existent "FAQSection" type on product cards — Google ignores it, FAQ without rich results.
- Measurement maturity: "the tools are in place, there are no experiments" — not a single A/B test. For decisions on discounts/delivery, that's already not enough.
The most underused asset — repeat buyers
The entire repeat-buyer flow is organic, without any lifecycle program. Consumables and companion products are already in the assortment — a natural cross-sell base. CAC/ROAS/margin is the audit's main unknown (Ads not connected): this is the boundary of confidence, not a verdict that "the economics are bad".
Consolidated findings table (15)
Each finding has a methodology module, a priority and a decision type — fix, verify, question for the owner, or deliberately leave alone. A defect ≠ a business decision: what's debatable isn't "fixed" but escalated to the owner.
| # | Finding | Module | Prio. | Decision | Money (L1) |
|---|---|---|---|---|---|
| 1 | 84% of sessions / 83% of revenue from google/cpc — concentration risk | Channels | P0 | protect | exposure up to ₴440K/mo |
| 2 | 37.8% of revenue from repeat buyers without an email/Viber program | Retention | P0 | fix | +₴26–42K/mo |
| 3 | RU/UA duplicate item_name + purchases without views → product analytics unreliable | Measurement | P1 | fix | enabler |
| 4 | Manufacturing advantage (own [category A], made-to-order sizes) absent from H1/title/above the fold | Positioning | P1 | fix | +₴10–30K/mo |
| 5 | Organic 2.6% of revenue; flagship category — 8 clicks/90 days; category CTR ~1% at positions 5–10 | Channels/SEO | P1 | fix | +₴14–30K/mo |
| 6 | Twin domain on a marketplace: 4,211 reviews and brand signals outside the main site | Trust | P1 | question for owner | — |
| 7 | Ads/margin unavailable → CAC, ROAS, LTV:CAC unknown with 84% paid traffic | Economics | P1 | question for owner | — |
| 8 | Product card → cart 9.8% — the only weak funnel step | Funnel/CRO | P1 | experiment | +up to ₴53K/mo |
| 9 | Permanent "−5% sale" across the whole catalog + timers on the twin | Offer | P2 | question for owner | margin? |
| 10 | B2B signals exist (wholesale from 10 units, desktop order ₴2,080), no wholesale pages/forms | Offer | P2 | fix | not estimated |
| 11 | ClaudeBot → HTTP 423 (GPTBot/Perplexity — 200); the AI channel has already made first sales | Channels/GEO | P2 | fix | channel growing |
| 12 | JSON-LD "FAQSection" (a non-existent type) on product cards — FAQ without rich results | Measurement | P2 | fix | — |
| 13 | Desktop CR 2.33% vs mobile 4.05% with 2× order value — segment not understood | Funnel | P2 | investigate | — |
| 14 | A month with +58% sessions and no transactions — source unknown | Measurement | P3 | investigate | up to ₴100K one-off (hypothesis) |
| 15 | Duplicate events ("checkout started" = begin_checkout) — noise in the reports | Measurement | P3 | fix | — |
Platform ceiling: nothing is blocked
Every recommendation was checked for feasibility on the store's platform (Horoshop): email/CRM automations, SEO templates, filter-preset landing pages, custom JSON-LD, popups and A/B — all available natively or via injection; editing the source HTML template isn't required for any fix. The operating model: UPLIFY prepares the content + a detailed spec + QA of each change; implementation is done by the client's own team in the admin panel.
Action plan — ICE-prioritized
Data and protection
Fix item_id in the dataLayer (a single UA/RU identifier) — spec + QA with a rollback plan; connect Google Ads; unblock ClaudeBot; fix the FAQ JSON-LD; remove the duplicate events.
Retention
Email/Viber sequences on the platform's native integration (welcome, post-purchase, consumables), a base-collection popup. Goal: +5–8% of revenue.
Positioning and organic
A new H1/above the fold ("manufacturer of [category A] — we'll make it to your size"), CTR rewriting of category titles/meta, filter-preset landing pages for top GSC queries, a wholesale page with a price-request form.
Experiments
PDP tests (delivery time above the fold, review collection on the top-40 SKUs); owner decisions on the −5% and the free-delivery threshold — and their A/B validation with a design document for each test.
Remove concentration
Goal: organic + direct + lifecycle ≥30% of revenue within 2 quarters.
Roles: UPLIFY — content, a detailed spec and QA of each change; implementation — the client's tech team/contractor. Every spec has acceptance criteria.
What the client provides for L2 level
Connect Google Ads (read-only) — and CAC/ROAS by category are computed on real data. Plus 3 numbers from the owner: average order value wholesale vs retail, margin on the main categories, share of repeat buyers from CRM — and all the report's money estimates are recomputed from directional (L1) to business level (L2).
How this audit was made
The report was produced by Nestor AI — UPLIFY's AI operator — using its own marketing-audit methodology (10 modules: from ICP and positioning to unit economics), and a senior marketer verified every finding. Honesty rules: every conclusion has a source; fact is separated from hypothesis; debatable matters are questions for the owner, not "fixes"; money estimates are honestly labeled with their confidence level.