Why BigCommerce's Built-in Analytics Aren't Enough (And What to Do Instead)

If you're running a BigCommerce store, you already have access to an analytics dashboard. Revenue charts, order counts, top products - it's all there.

But if you've ever tried to answer a slightly deeper question - like what is my customer lifetime value? or which customer cohort is churning fastest? - you've probably hit a wall.

The reality is that BigCommerce analytics was designed to provide quick summaries, not deep business insights. For early-stage stores, the built-in reports are helpful. But as your store grows, you need better visibility into customer behavior, revenue trends, and retention metrics.

In this guide, we'll break down:

• What BigCommerce built-in analytics actually provides
• The key metrics it doesn't track
• Signs that you've outgrown the native BigCommerce dashboard
• The best options for upgrading your ecommerce analytics tool

By the end, you'll know whether BigCommerce reporting is enough for your store - and what to do if it isn't.

What BigCommerce Analytics Actually Gives You

BigCommerce includes a built-in reporting suite available under Analytics in the store admin panel.

This dashboard provides several categories of reports designed to help merchants monitor store performance.

BigCommerce Analytics Dashboard Reports

Report Category	What It Shows
Dashboard	Revenue, orders, conversion rate, and average order value
Merchandising	Product and category performance
Marketing	Traffic sources and coupon usage
Search	On-site search terms and results
Customers	New vs. returning customers and geographic breakdown
Abandoned Carts	Cart abandonment rate and value

Figure 1: The standard BigCommerce Analytics overview provides high-level order data but lacks deep cohort-based insights.

For new merchants, this is usually enough to get started. You can quickly answer questions like:

• Which products are selling the most?
• Where is my traffic coming from?
• Are my discount campaigns working?
• What is my store's daily revenue?

These insights are useful for operational monitoring. But once a store begins scaling, these reports quickly start to feel limited.

What BigCommerce Analytics Doesn't Include

The biggest limitation of BigCommerce reporting is that it focuses on surface-level metrics rather than the deeper indicators that drive long-term growth.

Here's a side-by-side comparison between BigCommerce built-in analytics and what a dedicated ecommerce analytics tool can provide.

| Feature | BigCommerce Built-in Analytics | Dedicated Analytics Tool (e.g., Chartsy) | |-|--|| | Revenue dashboard | ✅ Basic | ✅ Advanced + AI insights | | Customer lifetime value (LTV) | ❌ Not available | ✅ Per-customer & segment LTV | | Cohort analysis | ❌ Not available | ✅ Retention by signup month | | Churn rate | ❌ Not available | ✅ Subscription & repeat buyer churn | | Natural language queries | ❌ Not available | ✅ Ask questions in plain English | | Custom dashboards | ⚠️ Limited widget builder | ✅ Fully customizable | | Product performance deep-dive | ⚠️ Basic top products list | ✅ Revenue, margin, velocity | | Refund & dispute tracking | ⚠️ Order-level only | ✅ Aggregate trends & alerts | | Automated reports | ❌ Not available | ✅ Scheduled weekly reports |

These gaps matter more than they might seem.

Once a store surpasses roughly $10K/month in revenue, the metrics that matter most change. Merchants start asking questions like:

• What is my customer lifetime value?
• Which acquisition channels bring the best customers?
• Are newer customers retaining better or worse than previous ones?
• Which products drive repeat purchases?

Unfortunately, BigCommerce's built-in analytics simply doesn't answer these questions.

Figure 2: BigCommerce's 'Customers' report shows total spend, but lacks the time-bound cohort data needed for true LTV calculation.

5 Signs You've Outgrown BigCommerce Analytics

Many merchants don't realize they've outgrown their analytics until reporting becomes a weekly headache.

Here are the most common warning signs.

Warning Sign	What It Means
You export reports to Excel every week	You're building reports manually instead of seeing them automatically
You can't answer “what’s my churn rate?”	BigCommerce doesn’t track this metric
You don't know your customer LTV	Without LTV you can't optimize ad spend
Your team constantly asks for numbers	Lack of self-serve dashboards creates bottlenecks
You find problems only after customers complain	No automated monitoring or anomaly alerts

If two or more of these apply to your store, you're likely spending more time managing data than learning from it.

The Real Cost of Relying on Built-in Analytics

Limited analytics isn't just inconvenient - it can directly impact profitability.

Here are a few common ways this happens.

Overspending on Ads

Without knowing your customer lifetime value by acquisition channel, it's impossible to calculate true return on ad spend.

For example:

• You might spend $50 to acquire a customer
• But that customer may only generate $45 in lifetime revenue

Without LTV insights, this loss remains invisible.

Inventory Blind Spots

Basic product reports show top sellers, but they don't show:

• Product sales velocity trends
• Margin-adjusted product rankings
• Changes in repeat purchase rates

These signals are critical for preventing stockouts and overstocking.

Retention Guesswork

BigCommerce provides a repeat customer rate, but this metric alone doesn't show whether retention is improving.

Cohort analysis is needed to answer questions like:

• Are customers acquired in January retaining better than February?
• Did a pricing change affect retention?
• Which acquisition channels bring loyal customers vs one-time buyers?

Without cohort analytics, retention trends remain hidden.

Delayed Decision Making

When every analysis requires:

1. Exporting a CSV
2. Cleaning data in Excel
3. Building formulas
4. Sharing spreadsheets

…decisions slow down.

In ecommerce, where pricing, ads, and inventory decisions happen daily, delayed insights can create a real competitive disadvantage.

What to Do Instead: Your Options

If you've reached the limits of BigCommerce analytics, there are several paths forward depending on your technical resources.

Option 1: Hire a Data Analyst

A dedicated data analyst can build custom reports and dashboards from your BigCommerce data.

Pros

• Fully customized analytics
• Advanced analysis possible

Cons

• Expensive (typically $60K–$120K per year)
• Requires onboarding and ongoing management
• Still dependent on one person for insights

For large ecommerce companies, this can be worthwhile. For most growing stores, it's overkill.

Option 2: Use Google Looker Studio or Power BI

Visualization tools like Google Looker Studio or Microsoft Power BI can connect to BigCommerce using third-party connectors.

Pros

• Flexible dashboards
• Powerful visualization tools

Cons

• Setup can take weeks
• Requires technical skills
• Metrics like LTV and churn must be defined manually

These tools are powerful but require significant setup and maintenance.

Option 3: Use a Dedicated Ecommerce Analytics Platform

The fastest option for most merchants is using a purpose-built ecommerce analytics tool.

Platforms like Chartsy connect directly to BigCommerce and automatically calculate metrics such as:

• Customer lifetime value
• Cohort retention
• Monthly recurring revenue (MRR)
• Churn rate
• Revenue trends

Figure 3: Chartsy surfaces the deep ecommerce insights that BigCommerce misses, organized for growth-stage teams.

Instead of exporting spreadsheets or writing SQL queries, you can simply ask questions like:

• “What’s my LTV by acquisition channel?”
• “Which product drives the most repeat purchases?”
• “Which customer cohort has the highest retention?”

And receive an instant answer.

For most growing ecommerce businesses, this approach delivers the fastest path to data-driven decision making.

The Bottom Line

BigCommerce built-in analytics is a starting point - not a complete analytics strategy.

It gives merchants a quick overview of store performance, but it doesn't provide the deeper insights needed to optimize acquisition, retention, and profitability as your business grows.

If you're spending more time exporting spreadsheets than analyzing your business, it's a clear signal that it's time to upgrade your analytics stack.

Tools like Chartsy connect to BigCommerce in minutes, automatically calculate the metrics that matter, and let your entire team explore insights without needing SQL or complex reporting workflows.

If better data leads to better decisions, better analytics tools lead to faster growth.