Starting an ecommerce business can be hard, and creating great products and an appealing online store is only the beginning. Once your ecommerce store is up and running, you have to find potential customers and bring them in, then convince them to buy.
You’ll need to then continually analyze your product and sales efforts, make adjustments, improve the user experience, decide when and where to spend money (SEO? Facebook ads?) and continually improve your marketing strategy in myriads of other small steps.
What’s working and what isn’t? How do you know what you need to work on next? A great place to start is looking at your ecommerce data.
What Is Ecommerce Analytics?
Ecommerce analytics refers to the process of gathering and analyzing relevant data to improve ecommerce sales. It involves tracking ecommerce data, then measuring and making judgements about that data, so you can take action.
Ecommerce analytics are fundamental to ecommerce business growth.
Why Are Ecommerce Analytics Important?
“If you're not looking at data, then you're just throwing darts at a wall. Ecommerce analytics tells you where and how to throw your darts so you can hit your goals,” says Richard Bernstein, VP of marketing at GhostBed by Nature’s Sleep. With over 20 years in digital marketing and ecommerce experience, he stresses the importance of paying attention to key data.
“Ecommerce analytics is important to review data about your customers,” he says. “It can help you understand what they are looking for, what their interests are, and how you can tailor your product offerings to meet their needs.”
Brian David Crane is CEO and founder of Spread Great Ideas LLC (SGI), a digital marketing fund that invests in e-commerce businesses. He’s had massive success in the industry, including launching Archives.com which was acquired by Ancestry.com for $100 million three years after its launch. Data-driven insights from ecommerce metrics have been integral to his success.
“E-commerce analytics helps you understand and analyze user behavior which can be used to improve the website structure, marketing initiatives, personalized offerings, and the type of product mix that would bring the most sales,” he explains.
What Metrics Are Used In Ecommerce Analytics?
There are many metrics that are commonly used in ecommerce analytics. Popular ones include:
CLV: Customer lifetime value
CTR: Click through rate
AOV: Average order value
Shopping cart abandonment rate
CAC: Customer acquisition cost
Sales conversion rate
ROAS: Return on ad spend
As the infomercials like to say, “That’s not all!” There are other metrics that can be used, but it is important to not get so lost in analysis paralysis. You need to think about your goals and have a plan for using the data you are able to access to grow your business.
Ben Kuhl is CEO of Shelf Expression which creates high-end, bespoke custom shelves for modern homes. The two most vital metrics he tracks to measure the website's success is website conversion rate and the combined ROAS for Google, Bing, and Instagram marketing campaigns. (Similar metrics can be tracked for any social media ad spend.)
Kuhl defines conversion rate as the percentage of website visits that result in a sale, and ROAS (return on ad spend) measures the amount of revenue earned for every dollar spent on advertising.
“Number of new customers and returning customers, customer lifetime value and conversion rate” are the main metrics Aviad Faruz, CEO of ecommerce jewelry store Faruzo.com, likes to track.
When asked to share favorite ecommerce metrics, Crane picks website traffic, sales conversion rate, customer lifetime value, and shopping cart abandonment rate.
How To Use Analytics To Increase Online Sales
Using analytics to increase sales isn't necessarily a straightforward process. Two similar online businesses with low customer retention rates could have different factors driving those low rates.
One company could have a product issue, and another could have a pricing issue. That’s why you need to look at a range of metrics within the context of the big picture, and test different solutions.
Kuhl uses analytics to continually monitor and analyze changes to his website design. “Every design shift we make on our website results in a change in our conversion rate,” he explains. “Most changes result in a negligible change. But sometimes, large layout shifts can have a large impact on the conversion rate.” He also warns that conversion rates can fluctuate seasonally, so comparing historic data is critical.
He shares this example:
“At the beginning of 2022, we wanted to make some dramatic changes to our site's layout and feel. Unsure in how these changes would affect our conversion rate, we created an A/B test to compare results. We essentially ran two different versions of our site for two months with website visitors being randomly shown one version or the other. One option had our previous layout and with some major design changes. The other was a complete redesign of our site.
Surprisingly, the previous version (with some major design changes), had nearly a .5% higher conversion rate than the new redesign. This .5% difference in conversion rate could potentially amount to over $50,000 in additional sales over the course of a year.”
And Crane shares the following example of how he was able to increase ecommerce sales by digging into the checkout process and then targeting visitors who had opened an account and put items in their shopping cart, but failed to complete the purchase.
“Post cart abandonment two follow-up emails were sent with a 48-hour gap between them. Based on the open and click-through rate, two additional emails with a personalized offer were sent over a week to entice them to complete the purchase. This model has helped us improve sales by as much as 13% over three months,” he shares.
These two examples illustrate how businesses can gather customer data at different touchpoints in the customer experience, and then turn those into actionable insights that improve marketing efforts. For one business that may mean A/B testing two versions of a landing page, while another may focus on creating more effective email marketing campaigns. (And some businesses will work on multiple efforts at once.)
Which Ecommerce Analytics Tool Is The Best?
The best ecommerce analytics tool is going to be the one that fits your company’s needs and budget, and that you learn well enough to use effectively. Newer businesses may want to start with free or low cost web analytics tools like Google Analytics (GA). (As you’ll hear in a moment, experienced marketers also use GA.)
If your business has been around for a while, you know where your ecommerce reports are weak and you may have already looked into what analytics platforms can help you strengthen ecommerce tracking and insights in those areas.
Here are some of the expert’s favorite picks:
Wizaly is Bernstein’s go-to marketing analytics tool. He calls it “an analytics tool ‘on steroids’, and says it helps give Ghostbed insight into marketing attribution across all channels.
Formtoro is another tool Bernstein says he’s recently enjoyed using. It allows the business to gather analytics in the form of pop up surveys. “It's great because it integrates with your Shopify ecommerce website,” he says.
Optimizely is Faruz’s pick for a favorite analytics tool for his online jewelry store. Despite nearly a decade of experience in ecommerce, he found himself struggling to make headway with his small business' ecommerce analytics. He says Optimizely helped him “understand what was happening on my website, and how I could improve.” And more importantly, helped him increase his website’s conversion rate significantly.
Google Analytics and Google Ad Center are Kuhl’s favorite data sources for helping Shelf Expression make better decisions about when and where to deploy ad spend. “The ability to segment data within Google Analytics allows us to fine tune our reporting and really hone in on targeting to use in Google Ads.”
Crane is also a fan of Google Analytics, and especially the Google Analytics Enhanced Ecommerce feature which he uses to help pinpoint website traffic sources, analyze user conversion data, bounce rate ratio, and shopping cart abandonment rates.
You may need to experiment with different data analytics tools to find the right one for your business. But taking the time to analyze key data and improve the customer journey can help you create a successful and sustainable ecommerce business.