Comparing 3 time ranges in Google Analytics

For merchants who run subscription-based businesses, accuracy is crucial for tracking recurring orders. The problem: popular platforms like Shopify provide merchants with native analytics that are broken. In other words, these platforms don't offer a complete picture (or an accurate one) of data that subscription-based stores depend on. There are many potential blockers for these store owners, but we narrowed it down to three: 1) Customisable orders & levels of membership Many successful subscription-based stores allow shoppers to customise their monthly orders. While this is an effective draw for consumers, it causes all kinds of headaches for the teams that manage the orders. The ability for customers to customise monthly orders adds layers of complexity for teams who manage product inventory, fulfillment and logistics in the back end. Perhaps the best example is from the hugely popular Dollar Shave Club. Known for their humor-driven marketing approach, the brand constantly encourages its subscribers add more and more products to their monthly shipments, which go out at different times each month. Due to the brand's meteoric growth over the past five years, this creates headaches — imagine fulfilling dynamic orders each month (different cart sizes, products and membership levels) for hundreds of thousands of customers across America. The 'curated box package' is another common subscription model. StitchFix, a curated clothing company for men and women, surprises its customers each month with a package containing 'personalised' new outfits. While the surprise factor might not be a draw for some, the brand's main appeal is the diversity of its products. Every month, StitchFix's variety is what appeals to its majority millennial market. Whether your store offers dynamic monthly ordering (where customers can change the contents of their cart) or follows a more traditional subscription model, it's crucial to have data you can trust. This means finding an ecommerce solution built to handle both customer changes and increased payload as your store scales. [subscribe heading="Automatically track your subscription orders" background_color="green" button_text="find out how" background_link="https://www.littledata.io/connections/recharge"] Affiliate marketing & partnerships It's common for subscription-based stores to partner with affiliate marketers to generate an additional source of revenue and tap into new customer groups. However, with more customers comes more demand, and the importance of accurate data only increases — this includes tracking sales made through affiliate partners, commission owed on each sale, etc. 2) Customer loyalty & reward programs When done right, effective customer loyalty programs create more loyal customers, boost customer retention and increase sales. These programs aren't used by every subscription-based brand, but for the brands that use them, they really do work, according to LoyaltyLion. However, as high shopper expectations continue to soar, the landscape for rewards programs is getting more competitive. Shoppers know that if they don't absolutely love one aspect of a brand's rewards program, they can easily run to a competitor that offers what they're looking for — whether it be a cheaper price tag, better discounts or more rewards available. Mark Hook, Head of PR and Communications for retail management software Brightpearl, had this to say: Over two-fifths of millennial shoppers (45%) admit to being less loyal to brands when compared to a year ago, and are quicker to abandon buying from companies that don’t meet expectations A great example of a rewards program within a subscription is Nike+. By putting the mobile shopping experience at the top of its priority list, Nike has developed multiple apps that work hand-in-hand with the Nike+ loyalty program by allowing its members to 'take the brand wherever you go.' By offering easy member access to the program, Nike gets higher engagement from community members and increased brand loyalty from repeat buyers. However, for merchants, a successful customer loyalty program hinges on back end analytics and whether or not it's set up properly. For merchants relying on Google Analytics for tracking, do you have custom dimensions set up? Are there parameters to track recurring orders, free trial offers, promo codes or even brand events? 3) Payment security & order changes Ecommerce businesses not operating on a subscription model typically receive credit card information every time a transaction is made. On the other hand, subscription-based businesses store data for recurring purchases, which simplifies the user experience and helps encourage users to continue paying each month. With potentially millions of credit card numbers stored in a database, brands are constantly at risk for large-scale fraud. This forces brands to invest in airtight security measures to protect your own revenue and the sensitive data of your customers. Merchants need to stay prepared for orders with expired credit card info, subscription cancellations and changes to recurring orders — all of which make it tougher to accurately track individual events and transactions. Running a subscription-based store with data you can trust Even with these hurdles, there's a shiny silver lining for merchants who rely on subscriptions. Littledata's plug-and-play ReCharge integration connects with Shopify and Google Analytics to do the following: Automatically track first-time payments and recurring transactions Provide accurate marketing attribution for subscription revenue Segment performance by payment source, subscription plan type and product category Benchmark your site and offer access to professional-level subscription analytics tools With Littledata's Shopify ReCharge integration, there's a better way forward for merchants who manage subscription orders. BullyMax, a popular nutrition and muscle-building supplement for dogs, and Dry Farm Wines, a health-focused natural wine club, are two top subscription brands that have seen great success with Littledata's Shopify ReCharge connection. Read more about our topintegration for subscription analytics. In a follow-up post, we discuss a fool-proof solution for Shopify merchants who manage subscription orders. Check it out!

Recently, Smart Goals in Google Analytics have resurfaced as a helpful feature for ecommerce merchants, but particularly Shopify merchants. In a previous post, we outline what Smart Goals are and why some ecommerce businesses use them. However, a lack of trust (and lack of endorsement) with the Google Analytics feature has turned away ecommerce merchants, particularly Shopify merchants. Like we discussed in the previous post, Smart Goals is a goal-setting users can enable in Google Analytics. Unlike other goals, Smart Goals uses both behavioral data and contextual (shared) data to predict which of your web sessions will result in a conversion. The pitfall here is that the data is not your data, which would naturally be the best predictor of future conversions. Instead, Google's algorithm seeks highly-engaged visitors and then uses that data to conclude the likelihood a given web session ends with a conversion. Google puts it this way: To generate Smart Goals, we apply machine learning across thousands of websites that use Google Analytics and have opted in to share anonymized conversion data. From this information, we can distill dozens of key factors that correlate with likelihood to convert: things like session duration, pages per session, location, device and browser. We can then apply these key factors to any website. The easiest way to think about Smart Goals is that they reflect your website visits that our model indicates are most likely to lead to conversions. Are Smart Goals a good idea? There's a big hitch in the original concept. Smart Goals was designed for merchants using Google Ads who don’t use conversion tracking. Smart Goals was to help optimise their Ads campaigns by collecting important metrics of user engagement. In theory, it sounds brilliant and helpful for ecommerce merchants and business owners of all scales. But here's how it breaks down in real life: Advertise, measure, repeat As a rule of thumb, ecommerce merchants with stores of all sizes should be measuring their advertising performance. Even if you're creating a "set it and forget it" Google Ads campaign, it's still crucial to track product views, page views, user engagements, cost per click, etc. If you're advertising your products without measuring, you're likely wasting your time and your budget. So how do you ensure you're making good use of ad dollars? Properly set up conversion tracking. Littledata's Google Ads connection is a great place to start. With the connection, you can be confident in your data reporting and that you're tracking the metrics that matter. [subscribe heading="Get Littledata's connection for Google Ads" background_color="grey" button_text="Get the connection" button_link=https://blog.littledata.io/2019/02/28/link-analytics-to-adwords-with-our-new-google-ads-connection/] With conversion tracking, you can follow a shopper's journey and see how many ad clicks lead to purchases, contacts, downloads, signups and more. This data will help you better optimise your campaigns and adjust the ad copy, visuals and calls-to-action to what performs best. Unfortunately, there are thousands of ecommerce merchants who advertise their products without proper conversion tracking. This sets them up for underperforming campaigns and stalls their online store from scaling. Can you really trust anonymous data? The short answer is a resounding no, and for a few reasons: Using other people's data to make crucial product and marketing decisions around your campaigns, your website and your customers isn't a good idea. Only your own customer behavior trends will guarantee you're making optimal business decisions for your product marketing campaigns and your online store. How does Google's algorithm determine likely conversions? If conversions aren't defined and conversion tracking isn't properly set up, how can likely conversions be determined? Google basically assigns each web session a score, with the top sessions made into Smart Goals. That begs the question, "what defines top sessions?" Google scans anonymous data (such as session duration, pages per session, location, device, and browser) to select the users that are "most engaged" in your online store. For example, let's say Shawna the Shopify merchant. Shawna uses Google Analytics to track her product sales and other "big data" figures. However, Shawna has never set up goals in GA. For someone like Shawna, Google would use engagement metrics in place of conversion metrics, since Shawna has no conversion tracking for her Shopify store. This is not necessarily problematic. What is problematic is that other important metrics are left untracked. This includes metrics like: Average order value Customer lifetime value Cost of engaged users Sales increases Google Ads campaign optimisation If conversion tracking was set up (rather than Smart Goals), Shawna would easily be able to trace the online journeys and user engagements on her Shopify store. Littledata's Shopify connection with Google Analytics would also provide Shawna with curated reports and analytics to help make sense of her GA data stream. What's the verdict? While even Google advocates for conversion tracking, there is a better way to track the metrics that support better decisions for your ecommerce business. When advertising, especially with Google Ads, it’s incredibly important to use your own data to make decisions for the positive growth of your campaigns.