E-commerce Analytics Masterclass: Lesson Five
Every online store out there is trying to please the consumer. We’re not just talking about the deals and discounts that one has to offer, but also the range of products that are being sold. After all, no one wants to lose a customer to a competitor for simply not having a t-shirt in another color. Right?
But is stocking up endless inventory really the answer to success?
That’s because you never know when a market trend changes and that the additional color of the t-shirt goes out of fashion and doesn’t get sold at all.
This is why it is important for online stores to take concrete decisions when it comes to their product portfolio or inventory.
In this lesson, we’re discussing the one segment of e-commerce analytics that will help you make better business decisions related to inventory – Product Analytics.
What is product analytics?
If you go by Gartner’s definition, product analytics is an application of business intelligence and analytics software. It includes consuming service reports, product returns, warranties, customer feedback, and other product-related data to turn them into actionables. The data is then used by businesses to help identify product improvements, understand consumer usage of the products, etc.
Simply put, product analytics show you which products in the store are performing, which don’t tend to sell out and what you can do to increase sales.
Why should you use product analytics?
1. It gives you insights into performing (and underperforming) product lines
Consumer needs are forever evolving. But does your store really need to bring ‘all’ those products to your store? Does your product range need to continually expand with the market trends? Well, it’s okay to experiment but to continually make decisions based on assumptions is going to lead you to losses.
With product analytics in place, you get insights into product lines that perform well and those that don’t. You can then further create product segments like ‘top-selling’, ‘high-value’, ‘fast-selling’ and more to categorize your product performance better.
2. It gives you a better understanding of the consumer purchase behavior
Once you start taking note of what products perform well, you’re also able to understand who your customers are and what their purchase behavior looks like.
For example, if some shoppers are purchasing only from the limited edition range of products, you know they’re ‘luxury shoppers’. Similarly, if you notice a pattern of shopping only during the sale season, you can segment the shoppers under ‘price-sensitive’.
Knowing the purchase behavior of shoppers helps you price products in a smart way and plan your discounts accordingly.
3. It helps you with better marketing and sales campaigns
A typical online shopper has the option to purchase from at least ten other stores at any given point of time. Will they go for a store with a greater product range or the one with a bigger discount or one that has a site-wide sale going on?
Product analytics turns your store data into actionable reports for your better marketing and sales campaigns. For example, knowing which products are top-sellers, you can cross-sell the lesser discovered products in a bundle with them!
4. It helps you optimize your inventory budgets
When you know what works amidst your target consumers and what doesn’t, you’re able to optimize your inventory budgets. You can eliminate products based on their performance, and divert the resources to offer more of the products that are popular amongst the online shoppers.
Just like how knowing that you didn’t need to stock up on the new color of t-shirt we spoke about at the beginning.
5. It helps you make profitable inventory decisions
Being able to clearly identify products that are a hit amongst shoppers and those that struggle to get a handful of sales, is important. The data is a clear indication of which product line is ‘wanted’ and which you’ve been trying to ‘push’ to the consumer.
Using product analytics, you can make inventory decisions that optimize your budgets (as above) and maximize your profits.
Your Shopify store’s analytics is an untapped opportunity to grow your sales. Make your data work for you. Give RevTap a spin!
What metrics should you track in product analytics?
1. Total inventory
This is the simplest e-commerce metric in product analytics. It simply refers to the total number of products in your inventory at a given point in time.
2. Active inventory
The e-commerce metric gives you the exact number of products from the inventory that is available for purchase on the store.
3. Product page clicks
The metric represents the number of visitors on your store that clicks through a product thumbnail to the product description page.
4. Additions to cart
The number of visitors who added a product to their cart – from the thumbnail or from the product description page.
5. Removal from cart
The number of shoppers who removed a said product from their cart and the possible reason for it.
6. Conversion rate
The number of shoppers that add a product to the cart and complete a purchase, divided by the total number of views the same product has got.
7. Product revenue
This e-commerce metric is simple yet important. It refers to the total revenue generated from the product being sold over a defined period of time.
When it comes to business decisions, this is the e-commerce metric that you should care about the most. Profits refer to the difference between the revenue and cost of products, divided by the revenue.
It is simply the percentage of the sale that a company gets to keep after the product is sourced, stocked, sold, shipped and delivered.
How do you start tracking profits from products?
Considering you already have Google Analytics set up (if you haven’t, read this guide), here are the three things you should be measuring for actionable product analytics:
1. Sales by product category
The Google Analytics e-commerce tracking system can report the sales your store makes based on the product categories. All you need to do is click on Conversions > e-commerce > product performance and select ‘product category’ there.
2. Cost of goods by product category
Don’t fret, Google Analytics actually has a feature that enables you to important product cost data easily. But to be able to track the cost of goods by product category, you need to create a custom metric by clicking on Admin > Property > Custom Definitions > Custom Metrics > Create “Product Cost” and assign scope at “Product” level.
Set the currency in decimal, leaving the minimum and maximum values blank. Now to import the data, go to Admin > Property > Data Import. Here you can create a new data set for “Product Cost”.
Select “Product Cost” as imported data. Leave the remaining set to the default “No”. Save and then click on “Get Schema”. By downloading the schema, you’re basically getting a template to populate with your product details and costs.
After this, create a “Calculated Metric” that represents the cost of goods by heading over to Admin > View > Calculated Metrics.
Set the cost of goods calculation to be: (Quantity of goods)/ (unique purchases + product views + number of products added to cart).
Similarly, create another Calculated Metric to present the “Product Profit”. To calculate this, define the formula as: Product Revenue – (Quantity/ Unique Purchases + Product Detail Views + Product add to cart * Product Cost).
Struggling to this all on your own? Reach out to us on email@example.com and we could help you create this custom report.
3. Cost of advertising by product category
The best way to get the cost of advertising by product categories is to structure your campaign identifiers well. Align ad groups to your product categories to combine data with the overall category sales.
You can get your advertising spend reports by heading over to Acquisition > Campaigns > Cost Analysis.
Getting data from product analytics together
When you set up your Google Analytics, to track product performance based on category, you’re able to identify the amount being spent to promote the products. But at the same time, you’re also able to clearly see the gross profits you’re making on each of your products/ product ranges.
You can then pull in all the three reports into an excel to see how different products or product ranges are performing. Diving deep into this data helps you understand if consumers are really looking for these products and how many of them are really willing to purchase them.
But we agree, calculating data from excel sheets can be overwhelming – especially when we’re talking about thousands of products.
And if you’re using multiple analytics tools, getting together data only gets tougher.
That’s where RevTap comes in.
RevTap simplifies product analytics for your store.
It connects with your store and integrates with all your analytics apps to bring all the data onto one dashboard. RevTap then gives you a visual, easy-to-consume overview of how different products are performing – what’s selling out fast, what’s hot and what’s not!
With easy-derived actionables, you can then put this data to use to plan your inventory better. The closer you are to matching it with what’s trending and what your customer needs, the greater are the number of sales you bag.
All without you having to pull data manually from different tools and creating excel sheets!
Sounds like something you’ve been looking for? Let’s show you how RevTap works to offer in-depth product analytics.
Ready to put Performance Analytics to work?
Turn your marketing data into more revenue with RevTap
Now that you have customer analytics, performance analytics and product analytics in place, it’s time to put it all to use – collectively.
In our next lesson, we’re going to cover how you can optimize your conversions and increase sales with data.