The process of using data to analyze a product’s performance is known as product performance analytics.
Keeping up with the competition these days necessitates a data-driven strategy, and product performance analytics is one of the most effective ways to gain insights from your business’s data.
Product Performance Analytics Definition
Product performance analytics is the collection and strategic analysis of data points (metrics) related to the purchasing funnel, such as how many times a visitor views a product page, how many times a product is abandoned in a cart, how many times a specific product gets to checkout, unique purchases, and so on.
These metrics obtained from each product might tell you a wider story about your complete product portfolio! Many people ignore this level of analysis because they don’t know why or how to perform it.
Why is Product Performance Analytics Important?
Product performance analytics are important for ecommerce brands for one major reason: they help you increase sales and improve overall operations.
1. Improve your merchandising choices
It’s easier to figure out why certain products require assistance in reaching the checkout. For example, the amount of space your product takes up on your store could be proportional to the number of sales it generates. You can start changing the layout of your store to make it easier to find a specific product. You can display collections or expand your suggested items section.
Another issue that is frequently observed is that the product photos or descriptions are insufficiently sturdy. You can add in-context photos, product demo videos, or more thorough product descriptions to product pages. With the statistics, you’ll be able to understand how your merchandising efforts are affecting your product’s overall performance and learn how to improve it.
2. Understand the product funnel
At its most basic level, product performance metrics assist you in determining how successfully a product flows through the purchasing funnel. So, from initial impression through final purchase, there’s a lot to consider. Because no two products are alike, it’s critical to determine which product categories are more or less likely to be abandoned before checkout.
With this knowledge, you can determine whether products are underperforming or are being picked up by competitors during comparison shopping.
3. Understand and plan marketing efforts
This allows you to understand how marketing and promotional efforts affect sales when showing different items or images by measuring performance at the product level.
Let’s pretend you’re promoting a fantastic new handbag on Instagram for a limited time. If you watch the sales of that handbag over time, you’ll be able to observe if the advertisement had an immediate impact on sales and how long it took for them to even out after the campaign finished.
You can also discover products for marketing faster, easier, and more methodically with product performance indicators available to slice and dice.
4. Avoid stockouts
Inventory management is a crucial aspect of product performance analysis. Knowing how many things are being sold at any one time might help you estimate stock needs and collaborate more effectively with suppliers. When you combine this type of performance data with regional or seasonal sales data, it becomes even more beneficial.
Many larger businesses and retailers share this type of point-of-sale data in order to get a better picture of who needs what and when. Being out of stock is inconvenient for everyone, even if it isn’t a strategic decision.
5. Identify revenue-boosting opportunities.
The ultimate purpose of owning an ecommerce store is to make money. Product analytics make it easier to find possibilities to do so. If you examine first-time versus recurring transactions, for example, you can uncover things like laundry detergent or coffee capsules that function particularly well on a subscription basis.
If you track category impressions and shop searches, you can discover that your consumers aren’t discovering a specific product they’re looking for, which you could stock. Then, of course, all of the pricing, merchandising, and marketing experiments you can conduct are plenty to assist you optimize your entire online shop profit!
Product Performance Metrics
In an ideal world, your product team would include a dedicated product analytics manager. Smaller businesses, startups, and larger enterprises who are still building out their product team can, nevertheless, undertake a product performance study on their own.
Product performance analytics should eventually become the product’s domain, but it typically makes sense to start with marketers conducting the research because many essential product metrics will be recognizable to the marketing team.
Reading a few product analytics books is a great start, but here are a few key metrics that practically any organization will want to investigate for each product they offer.
These figures are just a starting point. While simply checking up these numbers might yield valuable information, the real gold is discovered by delving as deeply as possible into the data to understand the factors that drive these crucial business metrics.
1. Revenue Per Product
Another baseline data point is revenue per product, which will answer a basic but critical question: Which products are bringing in the most money?
This may lead you in a different route than the basic sales figures, so it’s always worth investigating.
Is it better to concentrate on selling a few more of your most expensive, highest-margin products, or to focus on increasing the volume of sales of lower-margin products? You won’t know unless you’ve dug into the data.
2. Revenue Per Customer
Looking at how much money you make per customer is a terrific approach to learn more about your product category and how well it matches the demographics of the customers you’re attracting.
If you’re looking into why a $500 fashion item isn’t selling well, but your average revenue per client is less than $100, you’ve probably discovered the source of the problem: the audience you’re attracting isn’t interested in making purchases in that price range.
Looking at a product’s performance in the context of broader revenue per customer trends can be quite useful in determining where a product fits into your product line and identifying promising paths.
3. Conversion Rate and Abandonment Rate
The rate of conversion and the rate of abandonment are two sides of the same coin. The percentage of people that view a product and buy it is known as your conversion rate. The percentage of people that look at a product but don’t buy it is known as the abandonment rate.
If a product converts effectively, it’s probably due to a combination of variables, including a well-designed marketing funnel that attracts the ideal customers to your site.
An effective user experience on the page that leads customers to the product they want, as well as an effective sales page that makes consumers feel at ease about buying. If, on the other hand, a product has a high abandonment rate, it may not reflect the product’s quality.
Everything from inadequate audience targeting at the top of the marketing funnel to low-quality images on the sales page might hurt a good product’s conversion rate. That is why it is so important to go deeply into the facts.
4. Churn Rate
The rate at which customers abandon a subscription-based service is known as churn rate, and it’s a crucial metric for any company using a SaaS or other subscription-based model. It’s possible, for example, to have a product that appears to be perfect: it has a high conversion rate, is meeting sales targets, and is bringing in a steady stream of new monthly subscribers. However, if those users abandon the product after a month, the product’s high sales will not translate into significant profits.
Even with a highly successful product, you may be able to identify ways to improve its performance and lower the churn rate, thus increasing the income you can receive from each customer.
When it comes to churn analysis, looking at the behavior of active users is often a useful statistic. When do your customers decide to quit using your product? If you can improve the product experience, reduce friction, or make other changes that make your users happy, that’s great.
For products with a longer product life cycle, looking for early indicators in user behavior that might be connected to churn in the long run can help you measure the impact of changes without having to wait months for new data.
Early customer satisfaction measurements, such as a Net Promoter Score (NPS), might also be beneficial . Just keep in mind that these don’t always correspond to churn!
A customer who submits a rousing 10 NPS score in their first week isn’t necessarily immune to churn – you’ll need to dive into your company’s statistics to understand how NPS numbers correspond with attrition for your specific product and audience.
5. Customer Lifetime Value (LTV)
Another indicator related to churn is LTV. Increasing your customers’ lifetime value is a reliable strategy to boost income without increasing your marketing cost. The challenge, of course, is determining how to boost LTV, which is where product performance analysis comes in.
Analyzing product metrics such as user activity in a SaaS model can help you boost customer happiness, reduce churn, and ultimately raise a client’s LTV.
Analyzing visitor activity, purchase trends, product page bounce rates, and other web analytics using an eCommerce platform model can help you make better recommendations and convert more one-time buyers into repeat customers.
Product performance analytics are a critical part of optimizing your ecommerce operations. They give you deeper insight into what works. It’s simple to get started with the tools on the market, and you may learn quickly if you start with a limited collection of measurements.
General measures such as revenue and visitors provide high-level insights into an e-commerce store’s performance. Product performance analytics, on the other hand, gives firms a greater understanding of their product portfolio. This data not only aids product managers in developing better goods. It’s also important for inventory management and sales and marketing optimization.