The six-figure fix: How clean data fueled Flux Footwear's growth
SUMMARY As a company that values both data and creativity, Flux Footwear leveraged Littledata’s plug-and-play connections to Google Analytics (UA and GA4) and Facebook Ads to capture complete first-party data across the customer journey. Littledata’s automatic tracking solution not only saved them valuable time, but primed Flux for success with highly-targeted ads and in-depth customer insights as they scaled from launch to major DTC footwear brand. THE CHALLENGE Goal: Send complete Shopify data to Google Analytics (UA and GA4) and Facebook Ads The founders of Flux Footwear launched their Shopify store in July 2021, offering a minimalist shoe that works in harmony with the natural strength of bare feet. By embracing research on the positive effects of barefoot shoes and the value of sustainability, they created designs that feel just as good as they look. But after launching their Shopify store and installing Shopify’s native browser-side pixel, Flux’s team struggled with duplicate data, inaccurate attribution insights, and large data discrepancies between Shopify Analytics and Google Analytics. Unable to get an accurate understanding of their store’s performance, they needed to implement a data layer that tracks the entire customer journey across tools and platforms. The rollout of iOS14 made matters worse, inhibiting their Facebook Ad performance and limiting Flux’s reach to their target market. Their need for first-party data to maintain deep, accurate customer insights grew stronger than before. THE SOLUTION Fixing the data Within minutes of installing Littledata’s server-side tracking, accurate data was flowing seamlessly from Shopify to GA, capturing complete first-party data at every touchpoint and stitching together multiple sessions. In addition to connecting their Universal Analytics property, Flux started sending data in parallel to GA4. By building up historical data in GA4 now, Flux will be able to conduct year-on-year analysis to understand their business’s seasonality in years to come. Flux worked hand-in-hand with Littledata’s team of analytics experts, creating filters and views in GA to better interpret their data and build custom reports in GA4 based on their unique business goals. https://www.youtube.com/embed/plg4YWdJ97o Hear from Flux's co-founder, Benjamin Loschen on how Facebook Conversions API from Littledata improved their Meta Ad Campaigns. Integrating the tools Beyond the initial setup, Littledata made it easy for Flux to integrate their existing tech stack, see crucial insights in Google Analytics, and establish a single source of truth for customer data. [tip]Don't reinvent the wheel. See the top 5 data tracking mistakes made by DTC brands[/tip] With an accurate view of their Facebook Ad performance and marketing attribution, Flux is able to spend more on channels and campaigns that are converting at higher rates, and less on those that are falling short. Utilizing Littledata’s Facebook Ads integration, Flux built lookalike audiences based on their highest-spending customers, leading to a boost in both conversion rate and monthly revenue. There were three parts to this: Making Facebook Ads data match Shopify for actual conversions (real purchases instead of just clicks) Tracking checkout funnel events Getting the right LTV data to build high-value lookalike audiences in Facebook Ads and Instagram Ads All three were accomplished using Littledata's Conversions API connection. Conversion API (or "CAPI" for short) is a powerful way to get complete, accurate data about purchases and repeat buying behavior (shoppers who come back to buy again). Lots of brands don't even know about CAPI at all, but those that do often end up hiring agencies to do expensive manual implementations. Flux Footwear took the smart route and used an automated CAPI connection instead of trying to reinvent the wheel. The results were big and fast! RESULTS Flux Footwear cites Littledata’s seamless technology for helping them launch their brand with an accurate data layer. One of the most significant results, in their experience, is having “a team of people managing the data flow—a total no-brainer.” This helped to free up their most valuable resource—time—and allowed them to focus on their product. Since Flux relies predominantly on Facebook and Instagram ads to reach new customers, Littledata’s Facebook Conversions API integration plays a key role in Flux’s growth strategy. Seamlessly sending Shopify data to Facebook Ads and building powerful lookalike audiences for targeting and retargeting campaigns has fueled their recent growth—scaling their monthly revenue by 500% in under a year. They have also estimated over 30 hours of work were saved if they were to attempt to learn and set up tracking manually. With accurate data and a reinforced tech stack in place, Flux Footwear now has a complete picture of attribution, repeat orders, and conversions from customers and their affiliates.
Analytics showing wrong numbers for yesterday's visits
We've noticed a few issues with clients using Universal Analytics this last month, when visits for the last day have been double the normal trend. It then corrects itself a few hours later - so seems to be just a blip with the data processing at Google. Others have noticed the same problem. The temporary fix is to only generate reports with time series ending the day before yesterday. i.e. ignore yesterday's data. Now Google have officially acknowledged the problem Looking forward to seeing that one fixed!
Measuring screen resolution versus viewport size
There’s a difference between the ‘screen size’ measured as standard in Google Analytics and the ‘browser size’ or ‘browser viewport’. Especially on mobile devices, there are pitfalls comparing the two. Browser viewport is the actual visible area of the HTML, after the width of scroll bars and height of button, address, plugin and status bars has been allowed for. Desktop computer screens have got much bigger over the last decade, but browser viewports (the visible area within the browser window) are not. The CSS tricks site found only 1% of users have their browser viewing in the full screen. While only 9% of visitors to his site had a monitor less than 1200px wide in 2011, around 21% of users have a browser viewport of less than that width. Simply put, on a huge monitor you don’t browse the web using your full screen. Therefore, 'screen resolution' may be much larger than 'viewport size'. The best solution is to post browser viewport size to GA as a custom dimension. P.S. Google Analytics does have a feature within In Page Analytics (under Behaviour section) to overlay Browser Size, but it doesn’t work for any of the sites I look at.
How many websites use Google Analytics?
Google Analytics is clearly the number one web analytics tool globally. From a meta-analysis of different surveys, we estimate it is currently installed on over 50% of all websites or 80% of operational websites using any kind of analytics tracking. We looked at the following sources for this chart: Datanyze survey of Alexa top 1m sites (04/2014) BuiltWith survey of all websites (04/2014) MetricMail survey of Alexa top 1m sites Pingdom survey of Alexa top 10k sites (07/2012) W3Techs survey of their own sites (04/2014) LeadLedger survey of Fortune 500 sites (04/2014)
What's included in Analytics traffic sources?
The Channel report in Google Analytics (under 'Acquisition' section) splits out into 6 or more types of visit channel: Direct Where a visitor has: typed the URL into the address bar clicked on a link which is NOT in another web page (e.g. in a mobile app) visited a bookmarked link Organic Search All visits from search engines (i.e. Google, Bing, Yahoo) which were not an advertisement. You used to be able to filter out people searching for your brand (which are more like Direct visits), but now the search terms are not provided. Paid Search Visits from search engines where the visitor clicked on an advert. Referral Where a visitor has clicked on a link in another website (not your own domain), but not including search engines or social networks. Social Networks Specifically links from known social network websites (including Facebook, Twitter, LinkedIn etc) Email From links tagged as medium = 'email'. Your email software needs to be configured correctly to add this tag. Display Links tagged as 'display' or 'cpm'. FAQs Can I change the channel groupings? Yes, you can change this under Admin .. (Selected View).. Channel Grouping. But we recommend you don't do this for your default view, as you won't be able to compare the historical data.
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