As part of our series on connectors and how to use them, we take a look at eCommerce platform Shopify to see how online sellers can best leverage Shopify data to gain new and interesting insights into their eCommerce business.
eCommerce has hit an all-time high, and online retailers need to use every tool at their disposal to cut through the noise. Fortunately, the data that can help marketers make better decisions is more abundant than ever - but the potential of this data is often left untapped. By combining Shopify data with data from other platforms, retailers can gain practical insights into which ads are converting, when certain inventory is more likely to sell out, and which products are causing problems for customers.
What is Shopify?
Shopify is an all-in-one cloud-based eCommerce platform that enables businesses to easily create an online storefront where they can sell their goods and services.
Because of its flexibility and ease-of-use, Shopify is one of the world’s most popular eCommerce platforms, with approximately 20% of the global market share.
What data can you get from Shopify?
As you’d expect from an ecommerce platform, Shopify data includes things like:
- Transaction data, like what products or services your customer has ordered, and how much they spent on them.
- Sales data, including the average amount customers spend at your store
- Product inventory across all of your SKU’s.
- Financial data, like revenue, profit, and (most importantly) tax.
- Customer behaviour such as which products are getting attention and cart abandonment rates.
What data can a Shopify connector combine this with?
While the data you can get from Shopify is good, you can take this to a whole new level when you start by combining it with data from other platforms. This is where you can start getting some really advanced eCommerce analytics and insights that can help grow your business.
1. Which ads are converting
One of the biggest questions for eCommerce marketers is, “Which of my promotional channels is leading to sales?” It’s a simple question, but it’s often not so simple to answer. However, by combining your sales data from Shopify, with your promotional data from other sources in a data visualization tool; you can apply Attribution, or Marketing Mix Models to easily see which promotional channels and creatives are performing. From here, you can adjust your ad spend to maximise your return on investment, and ultimately drive more sales.
2. How the weather is affecting sales
If you really want to get ahead of the competition, you can compare your sales data, customer session information, and product inventory with historical weather information. By doing this, you can analyse the correlation between the seasons, days, and climate on your customer behaviour, to learn when certain products are likely to be popular. Take sunglasses for example. By comparing the weather and sales data, you’ve noticed that when the weather gets warmer, sunglasses sales tend to pick up on Thursday - ready for the weekend. With this knowledge in mind, you can get proactive, and promote these products on subsequent Thursdays when it is predicted to be a sunny weekend. You can even target these adverts down to the exact city where the sun will be shining. This creative use of your data can protect you from lost revenue due to low inventory, and enable you to be proactive in your promotion of these products for maximum return on investment.
3. Customer sentiment for specific products
Customer reviews are one of the greatest contributors to brand reputation for an eCommerce business. It’s great to optimise your promotions and inventory, but if you don’t have visibility on what your customers are saying about your products, brand, or user experience, then it’s your bottom-line that suffers. To identify these potential pain-points, you can compare your customer feedback, (from Shopify and other review aggregation sites, social media, and feedback forms) with your historical Shopify order, refund, and cart abandonment data. By doing so, you can turn this data into actionable feedback: discover which products are not up to standard, and where friction points lie in your user experience; ultimately improving your brand reputation and customer lifetime value.
