Top 6 pitfalls of Shopify analytics

The out-of-the-box analytics solution Shopify provides is a basic one, and unfortunately, the ecommerce data (transactions, add-to-carts, etc.) is incomplete and unreliable. With the help of Littledata, you can now be sure that "Shopify has you covered" with Analytics data collection. If you run a store with a large marketing budget you know how important it is to have accurate Analytics data to establish how your marketing budget is performing. It's also important to read the top 5 pitfalls in tracking ecommerce in Google Analytics as these will also apply to Shopify users. These are the known pitfalls for the out-of-the-box Analytics solution from Shopify: 1.Cross-domain and subdomain tracking issues The Shopify checkout is sending the customers to a Shopify domain (checkout.shopify.com). This makes the visitor sessions end suddenly even if they are in the process of buying something. The sales attribution for Shopify store owners is also painful due to the change of domains causing 'checkout.shopify.com' or a payment gateway to be attributed as the 'last click'. At the moment, Google Analytics can help you track both micro and macro moments in a customer journey. Example of micro-moments are: Clicking on a product link Viewing product details Impressions and clicks of internal promotions Adding / removing a product from a shopping cart Purchases and refunds All of these ecommerce interactions help you as a marketer / acquisition manager / owner to know more about your customer's interactions with your products. You can read more about the benefits of tracking the enhanced e-commerce in the article: use enhanced ecommerce to optimise product listings. 2.Clicking on a product link Clicking on a product link will show you the most appealing products, so you can improve the click-through-rate on the category page. If the click through rate is bad, the action to take is to check your product's master picture and see if there are any errors in getting to the product page. Also, you can investigate if these products are in the right category list. See how can you make these products more appealing to your audience. Read more on our blog on how to improve click-through-rate. 3.Viewing product details Viewing product details will show what are the most viewed product details. You can see this using the URL also, but having this info in a structured way (the product name and product SKU) will make the business analysis far easier. 4.Impressions and clicks on internal promotions Impressions and clicks on internal promotions. Every website uses at least one banner. But how many are tracking the effectiveness of these marketing assets? Knowing how they perform can mean a better visual strategy, a better usage of website space and maybe will save you some money when creating fancy banners with fancy designers! 5.Add-to-carts and removes from cart. Add-to-carts and removes from cart. Every store owner before Christmas asks themselves which products should have discounts or which to should be promoted? Finding out what products are added to cart and removed can answer some of those most vital questions in ecommerce. You can check your product picture and description and see if there are any errors on getting to the checkout. Also, be sure you give your customers access to the information about delivery and refunds. You can compare these products with your competition and see if the price and delivery costs are for the customer's advantage. See how can you make these products more appealing to the customer. 6.Purchases and refunds Purchases. The solution Littledata comes with is a server-side integration to provide a 100% match between your Shopify store and Google Analytics. This ensures that you register the sales data, even if the customer never gets to see the thank you page on your store. Refunds. We all know when seeing online sales, that it doesn't necessarily mean the end of the process. There can be a lower or higher percentage of returns from customers. Shopify is adding back the refunds on the day the packages return to the warehouse and this can be really sad for a normal day when there are negatives sales. There are multiple ways in which you can mess up your Google Analytics data while using Shopify but these were the most important ones to take in while tracking a Shopify store. Want more information on how we will help improve your Shopify analytics? Get in touch with our experts! Interested in joining the list to start a free trial? Sign up!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-12-08

Why do I need Google Analytics with Shopify?

If the lack of consistency between Shopify’s dashboards and the audience numbers in Google Analytics is confusing, you might conclude that it’s safer to trust Shopify. There is a problem with the reliability of transaction volumes in Google Analytics (something which can be fixed with Littledata’s app) - but using Shopify’s reports alone to guide your marketing is ignoring the power that has led Google Analytics to become over by over 80% of large retailers. Last-click attribution Let’s imagine your shoe store runs a Google AdWords campaign for ‘blue suede shoes’. Shopify allows you to see how many visits or sales were attributed to that particular campaign, by looking at UTM ‘blue suede shoes’. However, this is only capturing those visitors who clicked on the advert and in the same web session, purchased the product. So if the visitor, in fact, went off to check prices elsewhere, or was just researching the product options, and comes back a few hours later to buy they won’t be attributed to that campaign. The campaign reports in Shopify are all-or-nothing – the campaign or channel sending the ‘last-click’ is credited with 100% of the sale, and any other previous campaigns the same customer saw is given nothing. Multi-channel attribution Google Analytics, by contrast, has the ability for multi-channel attribution. You can choose an ‘attribution model’ (such as giving all campaigns before a purchase equal credit) and see how much one campaign contributed to overall sales. Most online marketing can now be divided into ‘prospecting’ and ‘retargeting’; the former is to introduce the brand to a new audience, and the latter is to deliberately retarget ads at an engaged audience. Prospecting ads – and Google AdWords or Facebook Ads are often used that way – will usually not be the last click, and so will be under-rated in the standard Shopify reports. So why not just use the analytics reports directly in Google AdWords, Facebook Business, Twitter Ads etc.? Consistent comparison The problem is that all these different tools (and especially Facebook) have different ways of attributing sales to their platform – usually being as generous as possible to their own adverting platform. You need a single view, where you can compare the contribution of each traffic source – including organic search, marketing emails and referrals from other sites – in a consistent way. Unfortunately, Google Analytics needs some special setup to do that for Shopify. For example, if the customer is redirected via a payment gateway or a 3D secure page before completing the transaction then the sale will be attributed to a ‘referral’ from the bank - not the original campaign. Return on Advertising Spend (ROAS) Once you iron out the marketing attribution glitches using our app, you can make meaningful decisions about whether a particular form of marketing is driving more revenue that it is costing you – whether there is a positive Return on Advertising Spend. The advertising cost is automatically imported when you link Adwords to Google Analytics, but for other sources, you will need to upload cost data manually or use a tool like funnel.io . Then Google Analytics uniquely allows you to decide if a particular campaign is bringing more revenue than it is costing and, on a relative basis, where are the best channels to deploy your budget. Conclusion Shopify’s dashboards give you a simple daily overview of sales and products sold, but if you are spending more than hundreds of dollars a month on online advertising – or investing in SEO tactics – you need a more sophisticated way to measure success. Want more information on how we will help improve your Shopify analytics? Get in touch with our experts! Interested in joining the list to start a free trial? Sign up! Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-12-07

Top 5 Google Analytics metrics Shopify stores can use to improve conversion

Stop using vanity metrics to measure your website's performance! The pros are using 5 detailed metrics in the customer conversion journey to measure and improve. Pageviews or time-on-site are bad ways to measure visitor engagement. Your visitors could view a lot of pages, yet be unable to find the right product, or seem to spend a long time on site, but be confused about the shipping rates. Here are the 5 better metrics, and how they help you improve your Shopify store: 1. Product list click-through rate Of the products viewed in a list or category page, how many click through to see the product details? Products need good images, naming and pricing to even get considered by your visitors. If a product has a low click-through rate, relative to other products in the list, then you know either the image, title or price is wrong. Like-wise, products with very high list click-through, but low purchases, may be hidden gems that you could promote on your homepage and recommended lists to increase revenue. If traffic from a particular campaign or keyword has a low click-through rate overall, then the marketing message may be a bad match with the products offered – similar to having a high bounce rate. 2. Add-to-cart rate Of the product details viewed, how many products were added to the cart? If visitors to your store normally land straight on the product details page, or you have a low number of SKUs, then the add-to-cart rate is more useful. A low add-to-cart rate could be caused by uncompetitive pricing, a weak product description, or issues with the detailed features of the product. Obviously, it will also drop if you have limited variants (sizes or colours) in stock. Again, it’s worth looking at whether particular marketing campaigns have lower add-to-cart rates, as it means that particular audience just isn’t interested in your product. 3. Cart to Checkout rate Number of checkout processes started, divided by the number of sessions where a product is added to cart A low rate may indicate that customers are shopping around for products – they add to cart, but then go to check a similar product on another site. It could also mean customers are unclear about shipping or return options before they decide to pay. Is the rate especially low for customers from a particular country, or products with unusual shipping costs? 4. Checkout conversion rate Number of visitors paying for their cart, divided by those that start the process Shopify provides a standard checkout process, optimised for ease of transaction, but the conversion rate can still vary between sites, depending on payment options and desire. Put simply: if your product is a must-have, customers will jump through any hoops to complete the checkout. Yet for impulse purchases, or luxury items, any tiny flaws in the checkout experience will reduce conversion. Is the checkout conversion worse for particular geographies? It could be that shipping or payment options are worrying users. Does using an order coupon or voucher at checkout increase the conversion rate? With Littledata’s app you can split out the checkout steps to decide if the issue is shipping or payment. 5. Refund rate Percent of transactions refunded Refunds are a growing issue for all ecommerce but especially fashion retail. You legally have to honour refunds, but are you taking them into account in your marketing analysis? If your refund rate is high, and you base your return on advertising spend on gross sales (before refunds), then you risk burning cash on promoting to customers who just return the product. The refund rate is also essential for merchandising: aside from quality issues, was an often-refunded product badly described or promoted on the site, leading to false expectations? Conclusion If you’re not finding it easy to get a clear picture of these 5 steps, we're in the process of developing Littledata’s new Shopify app. You can join the list to be the first to get a free trial! We ensure all of the above metrics are accurate in Google Analytics, and the outliers can then be analysed in our Pro reports. You can also benchmark your store performance against stores in similar sectors, to decide if there are tweaks to the store template or promotions you need to make. Have more questions? Comment below or get in touch with our lovely team of Google Analytics experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-30

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