We audited 50 Shopify stores last quarter. Here is what almost all of them were getting wrong.
Before we give you the list, some context.
These are not novice stores. The 50 Shopify brands whose accounts we reviewed over the last quarter were all generating between £15,000 and £200,000 per month. They all had paid media running. They all had Klaviyo connected. They all had, to varying degrees, invested in building their ecommerce operation properly.
And almost all of them had the same problems.
That is the part that should interest you. Not that individual brands make mistakes — everyone does. But that the same mistakes appear across brands at completely different revenue levels, in completely different categories, with completely different teams and histories. These are not individual failures. They are systemic patterns.
Here are the ten most common.
PROBLEM 1: THE PIXEL IS VERIFIED BUT THE DATA IS WRONG
In every one of the 50 stores we audited, the Meta Pixel was installed. In 34 of them, when we verified actual event firing using Meta’s Events Manager, something was misconfigured.
The most common issue: the purchase event was firing but not passing revenue values correctly. The Pixel reported a conversion but attributed £0 or £1 to it rather than the actual order value. The consequence: Meta’s algorithm was optimising for purchase events without understanding which purchases were worth more than others. Value-based bidding — which consistently outperforms conversion bidding at scale — was impossible.
Check this now: install Meta Pixel Helper, complete a test purchase, and verify the purchase event shows the actual order value. If it shows £0 or a fixed value, your Meta campaigns are significantly underperforming their potential.
PROBLEM 2: THE POST-PURCHASE FLOW TRIGGERS ON EVERY ORDER
We found this in 31 of the 50 accounts. The post-purchase welcome sequence — “Welcome to the family! We are so glad you found us!” — was triggering on every Shopify order, not just first orders.
Customers who had bought four times in the last six months were receiving first-time buyer onboarding emails. The brand was communicating to loyal customers as if they did not exist. The loyalty those customers had built was being systematically ignored.
Fix: In Klaviyo, add a flow filter to your post-purchase flow trigger: “Placed Order count equals 1.” One change. Immediately prevents the problem. Takes five minutes.
PROBLEM 3: CAC IS CALCULATED WRONG — OR NOT AT ALL
In 28 of the 50 stores, when we asked the founder their blended CAC, they either could not answer or gave a figure that included returning customers in the denominator.
Blended CAC = total marketing spend ÷ new customers acquired. Not total orders. Not total revenue. New customers.
If you divide your marketing spend by total orders and your returning customer rate is 30%, you are understating your CAC by approximately 43%. That gap matters for every downstream decision — maximum viable spend, channel allocation, scaling decisions, LTV:CAC assessment.
PROBLEM 4: THE ABANDONED CART FLOW HAS NO EXIT CONDITIONS
Found in 27 of 50 accounts. The abandoned cart flow would trigger when a customer started checkout, then continue sending all three emails — even if the customer completed their purchase 20 minutes later through a different browser or device.
The result: customers who bought were receiving “you left something behind” emails. The brand looked like it had no idea they had purchased. Trust damage, unsubscribes, occasionally a confused customer service query.
Fix: On every email in your cart abandonment flow, add an exit condition: “Has placed order in last 4 hours.” Customers who convert before the next email fires exit the sequence automatically.
PROBLEM 5: MOBILE CONVERSION RATE IS HALF OF DESKTOP AND NOBODY IS ADDRESSING IT
This one appeared in all 50 stores. Without exception, every brand had a significantly lower mobile conversion rate than desktop — average gap was 52%.
What varied was whether anyone was doing anything about it. In 38 of the 50 stores, no CRO work had been done specifically on mobile. The team was running A/B tests on desktop, making copy decisions based on desktop behaviour data, and wondering why conversion rate was not improving despite the tests.
The majority of traffic for most DTC brands is mobile. The majority of conversion gap is on mobile. The CRO work should be mobile-first.
Start with: installing Microsoft Clarity (free, unlimited recordings) and watching 20 session recordings specifically of mobile visitors who viewed a product page but did not add to cart. The friction points will be immediately visible.
PROBLEM 6: EMAIL IS GENERATING LESS THAN 15% OF REVENUE
Found in 39 of 50 stores. Not 39 stores without email — 39 stores with Klaviyo connected, campaigns sending, flows live, and email revenue still below 15% of total.
The common causes: flows built at launch and never updated, campaigns sent to the entire list without segmentation, attribution window set to the default 5-day open (which inflates email revenue figures and masks the real underperformance), and critical flows missing (browse abandonment was absent in 44 of the 50 stores).
The benchmark: above-average email programmes generate 28–35% of total revenue. The difference between 12% and 30% at £50k/month revenue is £9,000 per month. That is the revenue sitting in a correctly configured Klaviyo account — untouched.
PROBLEM 7: GOOGLE PMAX IS RUNNING WITHOUT BRAND EXCLUSIONS
Found in 22 of the 24 stores running Performance Max campaigns. No brand exclusion list applied.
The consequence: Performance Max was serving ads on branded search queries — customers searching for the brand name directly. These conversions were credited to PMax, inflating its reported ROAS significantly. The actual contribution of PMax to incremental revenue (customers who would not have bought without it) was dramatically lower than the dashboard suggested.
Fix: In Google Ads, create a brand list containing your brand name and variations. Apply it to your PMax campaign as a brand exclusion. The dashboard ROAS will drop. The actual business performance will stay the same. The budget allocated to PMax may then correctly reduce, freeing spend for genuinely prospecting-focused campaigns.
PROBLEM 8: CREATIVE IS NOT BEING REFRESHED PROACTIVELY
In 33 of the 50 stores, the process for refreshing Meta creative was reactive rather than proactive. New creative was added when performance had already deteriorated — after CPA had risen, CTR had fallen, and the algorithm had already spent weeks optimising toward a fatigued creative set.
The brands with the best Meta performance had a systematic creative rotation: new concepts entered the account every 2–3 weeks regardless of current performance, creatives were retired when frequency exceeded 3.5 on a 14-day window, and the team had a hypothesis for each new concept (not “let’s try something different” but a specific angle with a specific expected outcome).
PROBLEM 9: PRODUCT DESCRIPTIONS LEAD WITH FEATURES, NOT BENEFITS
Without exception, all 50 stores had at least one hero product page that opened with specification language rather than outcome language.
“High-strength magnesium glycinate 400mg capsules with L-Theanine complex” rather than “The sleep supplement that works when others have not — because it uses the form your body actually absorbs.”
The distinction matters because a visitor to your product page already knows what category they are in. They found you by searching for what they want. The job of the product page is not to describe the product — it is to confirm that this specific product is the right choice for their specific situation.
The fix is rarely a full rewrite. Often it is reversing the order: benefit first, then features as evidence of the benefit.
PROBLEM 10: NOBODY KNOWS THE FIRST-TO-SECOND PURCHASE RATE
In 41 of the 50 stores, when we asked the founder their first-to-second purchase rate at 90 days, they could not answer.
This is the single metric most predictive of a brand’s long-term financial trajectory. It tells you whether customers who try your product once are sufficiently impressed to come back. It tells you whether your post-purchase experience is working. It tells you whether your cross-sell strategy is effective.
A brand at 35% first-to-second purchase rate at 90 days has significantly better economics than a brand at 18% — at the same AOV, the same gross margin, and the same CAC. The difference in 12-month LTV:CAC ratio between these two brands is often the difference between a business that scales sustainably and one that plateaus.
How to find it: Shopify Analytics > Customers > filter by cohort > track repeat orders from the same cohort.
If any of these ten problems apply to your store, you are not unusual. You are in the majority. The reassuring part is that every single one of them is fixable and the revenue impact of fixing them consistently exceeds the cost of the fix by a significant margin.
If you want us to run this audit on your store specifically — our free Growth Audit covers all ten of these areas plus 40 more.
Book at exposegrowth.com/contact. We respond within 24 hours.