Beyond Shopify default reports: 5 insights you're missing
Five actionable insights hidden in Shopify Analytics that most store owners overlook showing product opportunities and customer behavior patterns worth investigating.
Shopify's default dashboard shows revenue, orders, and conversion rate prominently—but the most actionable insights for small stores hide in secondary reports that 73% of merchants never open according to Shopify's usage analytics. These hidden metrics reveal product opportunities, customer behavior patterns, and optimization priorities that directly impact profitability.
Here are five insights worth checking weekly that most store owners miss because they stick to the dashboard summary without exploring specific reports.
1. Which products get viewed but never purchased
What it reveals: Products with high page views but zero or very low conversions indicate pricing problems, unclear descriptions, poor photos, or missing trust signals.
Where to find it: Shopify Admin → Analytics → Reports → Products → Search for "Products by product view" report. Compare products with high views but low sales.
Why it matters: You're driving traffic to products that don't convert—wasted marketing effort. A product with 500 views and 1 sale (0.2% conversion) versus store average of 2% conversion is bleeding traffic. Fix it or remove it.
What to check: For products with high views but low conversions, investigate product page specifically. Common issues: price too high versus perceived value, unclear product descriptions not answering buyer questions, low-quality or insufficient product photos, missing reviews or trust signals, or confusing variants (too many options paralyzing choice).
Action items: If pricing is the issue, test bundling with complementary products to increase perceived value. If descriptions are weak, add detailed specifications, use cases, and benefits. If photos are poor, invest in better product photography. If reviews are missing, implement review request automation.
Time investment: 5 minutes weekly to identify problem products, 1-2 hours monthly to fix highest-traffic non-converters.
Expected impact: Fixing one high-traffic, low-conversion product typically improves overall store conversion rate 0.1-0.3 percentage points. On $50k monthly revenue at 2% conversion, 0.2% improvement = $5,000 additional annual revenue from same traffic.
2. Time of day and day of week conversion patterns
What it reveals: When your customers actually buy versus when they browse. Conversion rate varies significantly by hour and day—knowing peak buying windows informs email send times, ad scheduling, and discount timing.
Where to find it: Shopify Admin → Analytics → Reports → Behavior → Sessions by hour or Sessions by day of week. Export data and calculate conversion rate by time period (orders ÷ sessions for each hour/day).
Why it matters: Running ads or sending emails during low-conversion windows wastes money and attention. One store discovered 6pm-9pm converts at 4.2% versus 2.1% overall average. Shifting email sends to 5:30pm (arriving during high-conversion window) improved campaign ROI 38% without changing content.
What to check: Run reports for 30 days minimum to smooth daily variance. Identify your top 3 highest-converting hours and your highest-converting day of week. Look for patterns: Do mornings convert better than evenings? Does Friday convert better than Tuesday? Does Sunday have high traffic but terrible conversion (browsers planning purchases but not buying)?
Action items: Schedule email campaigns to arrive during your peak conversion hours (email most people check evening, so send 2-3 hours before your peak). Adjust Facebook/Instagram ad scheduling to concentrate budget during high-conversion windows. Launch flash sales during known high-conversion days. Increase customer service coverage during peak hours (more buyers means more questions).
Time investment: 10 minutes monthly to analyze patterns, one-time 30 minutes to adjust email and ad scheduling.
Expected impact: Timing optimization typically improves campaign conversion rates 15-30% without changing creative or offers. Same traffic, same content, better timing = better results.
3. Cart abandonment reasons (inferred from data)
What it reveals: Why customers add products to cart but don't complete purchase. While Shopify doesn't directly show abandonment reasons, comparing checkout started versus completed plus average cart value versus average order value reveals patterns.
Where to find it: Shopify Admin → Analytics → Reports → Sales → Checkout funnel. Compare "Reached checkout" to "Completed purchase." Also check Orders → Abandoned checkouts to see what people almost bought.
Why it matters: Your checkout abandonment rate (percentage of checkouts started but not completed) typically ranges 60-80% for e-commerce. Even small improvements in completion rate create significant revenue increases. If 100 people start checkout weekly and 70 abandon, reducing abandonment to 60 means 10 additional orders weekly—520 orders annually.
What to check: High abandonment with high average cart value often indicates unexpected shipping costs shocking customers. High abandonment with complex checkout flow (account creation required) indicates friction. High abandonment on mobile versus desktop indicates mobile UX problems. Abandoned carts containing specific products might indicate those products have concerning aspects (misleading descriptions, unclear pricing).
Action items: If shipping cost is the issue, show estimated shipping earlier in process or offer free shipping threshold. If account creation causes abandonment, enable guest checkout. If mobile abandonment is high, simplify mobile checkout experience. If specific products appear frequently in abandoned carts, investigate and fix product page issues. Implement abandoned cart email recovery (Shopify has built-in abandoned checkout recovery).
Time investment: 10 minutes weekly to review abandoned checkout report, one-time 2-4 hours to fix identified friction points.
Expected impact: Checkout optimization typically recovers 5-15% of abandoned carts. On 100 weekly checkouts with 70% abandonment, recovering 10% of abandoned carts = 7 additional weekly orders (364 annually).
4. Customer acquisition source profitability (not just revenue)
What it reveals: Which traffic sources acquire customers who spend more and return more often, not just which sources drive most traffic or revenue.
Where to find it: Shopify Admin → Analytics → Reports → Acquisition → First-time vs returning customer sales by traffic source. Compare first-time customer average order value and returning customer rate by source.
Why it matters: A traffic source driving high volume but low average order value and no repeat purchases is less valuable than a source driving lower volume but higher AOV and strong retention. One store found Instagram drove 40% of traffic but customers acquired via Instagram had $42 AOV and 8% return rate versus email driving 10% of traffic but $78 AOV and 35% return rate. Email customers were 3.8x more valuable over time despite lower volume.
What to check: For each traffic source, calculate first-time customer average order value, returning customer rate from that source (percentage who order again within 90 days), and average time between first and second purchase. Identify your highest-quality customer source (combination of AOV and retention, not just volume).
Action items: Shift marketing budget toward sources acquiring valuable, loyal customers even if volume is lower. Investigate why certain sources acquire better customers (audience quality, intent level, messaging alignment). For low-quality sources (high volume, low value, poor retention), either improve targeting to attract better customers or reduce investment. Adjust customer acquisition cost expectations by source—paying $25 to acquire a customer with $80 AOV and 40% return rate is profitable; paying $15 for customer with $35 AOV and 5% return rate loses money.
Time investment: 15 minutes monthly to analyze acquisition source quality, ongoing budget reallocation as you identify patterns.
Expected impact: Optimizing toward high-quality customer sources improves customer lifetime value 30-60% without increasing acquisition volume. More profitable customers create better business economics even at lower volume.
5. Seasonal and trending product patterns
What it reveals: Which products have seasonal demand curves or emerging popularity trends, informing inventory planning and promotional timing.
Where to find it: Shopify Admin → Analytics → Reports → Products → Product sales over time. Select 12-month view to see seasonal patterns. For trending products, compare last 30 days to previous 30 days for each product.
Why it matters: Seasonal products require advance inventory planning. Trending products (sales accelerating) deserve immediate promotional attention while momentum exists. Declining products need investigation or clearance. One store noticed a product's sales doubled month-over-month for three consecutive months (trending up)—they aggressively promoted it and it became their #1 revenue driver. Without noticing the trend early, they would have understocked it.
What to check: Review each product's 12-month sales graph to identify seasonal patterns. Do certain products spike in specific months? Plan inventory 8-12 weeks ahead of seasonal peaks. Check month-over-month growth for all products to spot emerging trends (products growing 30%+ monthly deserve immediate attention) and concerning declines (products declining 30%+ monthly need investigation or clearance).
Action items: For seasonal products, plan inventory buys 2-3 months before peak season to ensure stock availability. For trending products (accelerating sales), increase inventory immediately, feature prominently on homepage, run targeted ads, and send dedicated email campaigns. For declining products, investigate why (is it being discontinued? quality issues? competition?) and either fix the problem or run clearance promotions to sell remaining inventory. Use historical data to forecast next year's seasonal demand more accurately.
Time investment: 20 minutes monthly to review product trends and seasonality, 1-2 hours quarterly for strategic inventory planning based on patterns.
Expected impact: Catching trending products early and promoting aggressively often converts them to top revenue generators. Seasonal planning prevents stockouts during peak demand (missed revenue) and overstock during slow periods (capital tied up). Stores using data-driven seasonal planning typically improve inventory turnover 20-40%.
How to incorporate these insights into your routine
Weekly 10-minute check (every Monday)
Check products by product view report—identify top 3 high-view, low-conversion products (2 minutes)
Review abandoned checkouts from last week—note any patterns (3 minutes)
Check product sales trends—spot any products growing or declining rapidly (3 minutes)
Note one action item for the week based on findings (2 minutes)
Monthly 30-minute deep dive (first Sunday of each month)
Analyze conversion by hour/day patterns—adjust email and ad timing (10 minutes)
Review customer acquisition source quality—calculate AOV and retention by source (10 minutes)
Check seasonal patterns and plan inventory 2-3 months ahead (10 minutes)
Quarterly 60-minute strategic review
Full product portfolio analysis—identify winners, losers, opportunities (20 minutes)
Customer source profitability deep dive—reallocate marketing budget (20 minutes)
Seasonal planning based on 12-month historical data (20 minutes)
The automated alternative
For teams wanting these insights delivered automatically without manual report checking, some Shopify analytics tools surface hidden patterns proactively.
Automated analytics platforms can alert you to trending products (sales accelerating), declining conversion rates, high-view low-conversion products, and seasonal pattern changes automatically rather than requiring manual weekly checks.
When automation makes sense: Teams of 3+ people benefit from automated insights distribution. Solo operators spending 15+ minutes weekly checking reports benefit from time savings. Stores with 50+ products struggle to manually review all product trends weekly.
Cost consideration: Automated Shopify analytics tools typically cost $30-100+ monthly depending on features. Calculate time savings (weekly hours saved × your hourly rate × 52 weeks) versus annual subscription cost. If you save 30 minutes weekly at $50/hour value, that's $1,300 annual value—easily justifying tools under $100/month.
Peasy (starting at $49/month) includes automated Shopify insights in daily email reports, surfacing hidden patterns without manual report checking. Try free for 14 days to see which insights get delivered automatically.
Common mistakes when using these insights
Mistake 1: Noticing patterns but not acting on them. "Oh interesting, this product has high views but low sales" without fixing the product page. Insights are worthless without action. Each discovery should generate specific next step.
Mistake 2: Reacting to small sample sizes. One week of hourly conversion data isn't statistically meaningful. Aggregate 30+ days minimum before identifying patterns. One month of product trend data might be noise—three months of consistent trend is signal.
Mistake 3: Optimizing low-traffic products or sources. Fixing a product with 10 monthly views won't move business metrics. Focus on highest-traffic non-converters first—biggest opportunity for impact.
Mistake 4: Checking these reports daily. These are weekly or monthly insights, not daily metrics. Checking daily creates noise and wastes time. Establish weekly and monthly review routines.
Mistake 5: Analysis paralysis. Finding 10 issues and trying to fix all simultaneously. Pick one highest-impact insight weekly and fix it. Consistent small improvements compound better than sporadic massive overhauls.
Beyond the Shopify default dashboard
Shopify's default dashboard serves daily operational monitoring well—but the specific reports contain insights that separate growing stores from plateaued stores.
Start with one insight: This week, check products by product view to find your biggest high-traffic non-converter. Fix that one product page. Next week, check abandoned checkouts to identify your biggest friction point. Fix it. Month three, analyze timing patterns and adjust email scheduling.
Build the routine gradually: Don't try to check all five insights immediately. Add one to your weekly routine per month. After five months, you'll have comprehensive insight coverage without overwhelming complexity.
Focus on action, not analysis: Every insight should generate specific next step. No insights are valuable without execution.
For Shopify stores wanting automated insights without manual report checking, tools like Peasy surface hidden patterns in daily email updates. Try free for 14 days to see which insights get automated.
