What is Ecommerce Analytics?
Did you know that 58.4% of working-age internet users buy something online every week? The most popular categories of ecommerce sales are consumer electronics, fashion, groceries, furniture, toys, food, and beverages.
The worldwide ecommerce retail industry was worth $4.9 trillion in 2021. It is projected to grow at a CAGR of 13.25% to reach $7.4 trillion by 2025.
These figures showcase the ecommerce industry is flourishing.
However, ecommerce companies are facing several challenges, including but not limited to:
- Streamlining the customer experience
- Customer loyalty
- Shopping cart abandonment
- Conversion rates
- Attracting the perfect customer
So how can ecommerce stores overcome these challenges?
The only possible solution is to gather and analyze data about consumer behaviors, marketing channels, sales, product lines, and conversions that help guide appropriate decision making. Making the right decisions consistently over time can help ecommerce companies improve operational efficiencies and increase customer loyalty to drive retention. It all boils down to the data!
Ecommerce stores capture a lot of data from various sources, including search engines, social media, inventory and sales platforms, shopping carts, and customer reviews. Since most of these sources provide raw data, ecommerce managers should make sure they use ecommerce analytics tools that help analyze data on key performance indicators (KPIs) for their store and provide actionable insights for decision-making, all in one place. It’s important to note that a comprehensive understanding of your business is key. This means that, while best-of-breed solutions exist for things like performance marketing, you should also have a platform that incorporates analytics and data across customers, products, and inventory. Imagine if you only tracked which ads and campaigns generated the most last-click sales, but had no idea on the profit margins, LTV, or customer segments of those campaigns?
This article provides everything you need to know about how ecommerce analytics help you drive more sales with data.
Why is Ecommerce Analytics Critical for Store Success?
Ecommerce analytics is critical for store success because it helps ecommerce managers understand:
- Their store performance
- Factors that deter sales
- Customer behaviors that help develop and offer better products
1. Understand how you’re performing.
Ecommerce analytics provide a big picture of how your store is performing by tracking financial metrics such as gross profit margin, net profit margin, cost of goods sold (COGS), and operating costs. These metrics help managers make appropriate, data-driven decisions that reduce costs and improve their bottom line.
For example, COGS is associated with inventory costs, but it also plays a critical role in your overall profitability. COGS, when combined with your product pricing, shipping costs, and acquisition costs, can help set the tone and strategy for your desired margins.
Ex. Your pricing strategy can be largely based on a multiple of your COGS. If you target a 5x markup, you can then layer in your acquisition costs and shipping costs to determine what your margins should be. Out of those three costs (COGS, shipping, acquisition), your acquisition costs are the most variable, so measuring and improving them at the channel level is crucial.
2. See what deters sales.
According to a recent survey by McKinsey, 53% of fast-growing and high-performance sales organizations are effective users of analytics.
With ecommerce analytics, ecommerce managers can identify the factors that discourage people from making a sales transaction. For instance, it helps track consumer behaviors related to the price of a product. The highest abandonment rate for a particular product may be a sign that the purchase price of the product is higher than expected.
Oftentimes, customers will add products to their cart and then may abandon it after seeing additional shipping costs, taxes, and the unavailability of discount coupons during the checkout process. Once these behaviors are identified, addressing them isn’t a difficult job for ecommerce managers.
As a rule of thumb, the more transparency you can provide upfront - from pricing to shipping - the more likely a customer will convert and be satisfied with the entire experience.
3. Develop and offer better products.
No matter how good your marketing, pricing, or customer strategy is, your store will struggle to survive if your products don’t meet customers’ expectations. This means that the priority for any ecommerce business should be to develop products that exceed customer expectations.
In order to successfully develop and offer better products, online stores may need to collect data that helps them better understand the reasons for:
- Changes in consumer behaviors
- Poor sales figures of a particular product or multiple products
- High margin and best-selling products
Ecommerce reports help online stores take the first step towards developing better products by providing real-time insights on key metrics, such as repeat customer rate, least-performing products (reasons for the poor product performance), customer churn, customer retention rate, and cart abandonment rates.
Best Ecommerce Metrics and KPIs to Track
Ecommerce analytics tools leverage a broad range of metrics and KPIs to track the performance of an online store. Ecommerce managers may need to create dashboards that combine two or more relevant metrics related to store performance, products, marketing, and customers for better decision-making insights from ecommerce analytics tools.
Ecommerce managers can get a more complete picture of their online store’s performance with ecommerce analytics. By tracking metrics such as return on investment (ROI), gross profit/revenue, average order value (AOV), refunded orders, and customer lifetime value (CLTV), ecommerce analytics help ecommerce managers identify reasons for poor revenues, increased number of refunded orders, and lower AOV.
- AOV: AOV is the dollar amount a customer spends each time they purchases a product from an organization. For example, if a store generates a revenue of $30,000 for 1,000 orders in a month, the AOV would be $30.
- Revenue: Revenue or gross sales is the money a business generates from the sales of goods or services in a particular financial period. For example, if a store sells 100 products at an average price of $100, the revenue of the store would be $10,000.
- ROI: ROI is the ratio between income and investment. For an ecommerce store, the ROI is the ratio between income and the total cost. For example, if a store generates sales of $8,000 against the total costs of $6,000, the ROI would be 33.3%.
Ecommerce companies spend over 30% of their revenue on marketing or customer acquisition. It is important for ecommerce companies to track marketing metrics because they help benchmark the performance of digital marketing channels, such as search engine optimization (SEO), social media marketing (SMM), pay-per-click advertising (PPC), email marketing, and others against KPIs like conversion rate, cost per acquisition, and profitability.
- Channel profitability: Marketing channel profitability is the net profit that a marketing channel has generated. Let’s say that a store has spent $8,000 on a PPC campaign in a particular month, and the campaign generates a sales revenue of $14,000. Additionally, the COGS were $2,000. In this case, the profit margin of that campaign would be 40%.
- LTV by channel: This represents the value of a customer through a particular channel. Let’s say that a channel produces customers whose AOV is $100 and who have a purchase frequency of 1.5. The LTV of a customer from that particular channel would be $150. LTV by channel is an important metric, because it factors in repeat purchases from clients that might get lost in the shuffle. If you only look at last-click attribution by channel, you might cut off the funding to a channel/campaign that, while the initial purchase price might be low, creates a lot of repeat purchasers.
Customer data metrics
It is important to track customer data metrics because they enable you to:
- Segment your customers
- Identify better ICP targeting
- Analyze the trend in AOV and customer acquisition cost (CAC) over a period of time
- Identify what products your most valuable customers are buying
- Evaluate customer satisfaction levels
Ecommerce managers may need to use KPIs such as CLTV, CAC, customer segments, and repeat purchase rate to gather and analyze customer data.
- CLTV: CLTV is the total value a customer generates over the lifespan of their relationship with your store. For instance, the lifetime value of a customer who associates with the organization for two years, spending on average $50 per month would be $1,200.
- CAC: CAC is the amount of money an organization spends to acquire a new customer. If a store spends $10,000 to acquire 1,000 customers within a specific timeframe, the CAC would be $10.
Conversion optimization metrics
Conversion optimization metrics are vital to an ecommerce business because they help ecommerce managers make appropriate decisions to increase conversion rates and revenue per visitor. The most commonly used conversion optimization metrics are conversion rate and shopping cart abandonment rate.
- Conversion rate: This is the percentage of visitors that complete a desired action on your ecommerce store. For ecommerce brands and merchants, the desired action would be to purchase a product, so the calculation would simply be transactions/visitors.
- Shopping cart abandonment rate: Is the percentage of visitors that add products to their shopping cart, but don’t follow through with completing the purchase. For example, If 100 completed transactions were reported out of a total of 1,000 shopping carts opened, the shopping cart abandonment rate would be 90%.
User experience metrics
User experience metrics are crucial for online businesses because they help identify if their website has any usability, findability, accessibility, or consistency issues. An improved user experience can result in higher customer engagement and conversion rates. Two of the most important user-experience KPIs are bounce rate and page load time.
- Bounce rate: Bounce rate is the percentage of visitors that leave a website without visiting the second page. For example, if 200 out of 500 visitors on a particular day navigate away from a website without visiting the second page, the bounce rate of the website would equal 40%.
- Page load time: This is the average amount of time it takes for a web page to appear on the screen. Ecommerce websites with a shorter page load time have higher visitor engagement and more conversions. The Google recommended page load time for ecommerce websites is under two seconds.
Best Practices for Ecommerce Analytics
Ecommerce managers may need to follow a few best practices for ecommerce analytics to guide towards the desired results.
Use the right ecommerce analytics tool.
Nothing beats a superior ecommerce analytics tool. Without an analytics tool that provides industry-standard, out-of-the-box metrics and KPIs, ecommerce managers will need to do some heavy lifting to establish their own homegrown system for reporting. If you’re going to pay for a solution, you should be sure to select a tool that connects and visualizes data on customers, products, inventory, and promotions through prebuilt KPIs for enhanced ecommerce reporting.
With over 300 prebuilt KPIs, 150 standard data sources, and 180 integrations with prebuilt data joins, including Google Analytics, Shopify and Klaviyo, Glew is the best ecommerce analytics tool for your online business.
Centralize all of your data.
Ecommerce stores should centralize all of their data for various reasons, including improved data integrity and accuracy, unified reporting, valuable decision-making insights, and reduced redundancy.
Scattered and incompatible data requires more time and effort to maintain, aggregate, and analyze. We’ve never met a growing organization who had a plethora of available bandwidth, so being able to redirect those resources and efforts to driving value-added change is worth its weight in gold. This is why many ecommerce companies use a single backend source to aggregate all of their ecommerce data to better understand their campaigns, products, and customers to make data-driven decisions.
Continue testing your marketing strategies.
No marketing strategy is perfect and not all marketing strategies work for every organization. Because the target market of every ecommerce store is unique, marketing teams should customize promotional strategies to achieve better results. Continuous testing of marketing strategies is the only way to improve the efficiency of marketing campaigns.
The following steps may help in testing marketing strategies:
- Establish advertising objectives and KPIs or rely on industry-standard metrics like LTV, conversion rates, cost per acquisition, and profit margin.
- Establish a process to track the performance of marketing channels with the help of an ecommerce analytics tool.
- Iterate on your marketing strategy (such as changing the content and copy of ads, dropping marketing channels that are not working, etc).
- Rinse and repeat. Let your ecommerce analytics tool be the thesis tester of your marketing programs.
Improve your ecommerce analytics with Glew.
Data is the backbone of an ecommerce business. Ecommerce managers need to obtain ecommerce data about customers, products, inventory, and marketing efforts to make informed decisions that drive sales. Implementing an ecommerce analytics tool is a critical decision for online stores that plan to keep a close eye on how their store is performing and what factors are driving and/or deterring sales. Ecommerce analytics help track the performance of an online store with data from important KPIs such as AOV, revenue, COGS, channel profitability, conversion rate, CLTV, CAC, shopping cart abandonment rate, bounce rate, and many more.
Glew is the leading ecommerce analytics tool in the market. With its sleek and user-friendly interface, Glew will help you visualize the performance of the store through metrics related to customers, products, channels, and subscriptions. Glew has 30+ pre-built customer segments, including abandoned carts, high AOV, recently purchased, big spenders, repeat customers, refunders, never purchased, and more to filter data. Insights from this type of data can help marketing teams roll out more personalized email campaigns that enhance the user experience and increase sales revenues.
Schedule a demo to learn how Glew’s ecommerce analytics platform can help you drive more sales with data.