What are Smart Goals in Google Analytics?
In a nutshell, Smart Goals measure the most engaged visits to your website and automatically turn those visits into Goals, even if you don't have conversion tracking or ecommerce tracking. Those Goals are then used to improve your Google Ads bidding. Not only are Smart Goals one of our favorite features of Google Analytics, but also a helpful resource for ecommerce merchants of all sizes. How do Smart Goals work? The Smart Goals feature in Google Analytics is the result of machine learning algorithms and configured at the view level. These algorithms scan dozens of signals within your website sessions to determine which signals are most likely to result in a conversion. Each session is assigned a score, with the "best" sessions being translated into Smart Goals. So what are these "signals"? Session duration, pages per session, location, device and browser type are among the most popular. To determine the best sessions, Smart Goals establishes a threshold by selecting approximately the top 5% of the traffic to your site coming from AdWords. Once that threshold is set, Smart Goals applies it to all your website sessions, including traffic from channels other than AdWords. After enabling Smart Goals in Analytics, they can be imported into AdWords. What do I need before setting up Smart Goals? If you're an online store owner interested in using Smart Goals, you'll need to have an existing Google Ads account linked to Google Analytics. You'll also need edit permissions at the view level in order to complete the setup. Before setting up Smart Goals, your linked Google Ads account must also have sent at least 500 clicks to the selected Analytics view over the past 30 days (if the linked account falls below 250 clicks over the past 30 days for the selected view, Smart Goals will be deactivated until the clicks rise again to 500 or more). Google Analytics recommends that Smart Goals be used when you aren't measuring conversions. In other words, they're an easy way to use your best sessions as conversions. You can then use Smart Goals to optimise your Google Ads performance based on the best sessions pattern. [subscribe heading="Try Littledata free for 14 days" button_text="Start your free trial" button_link="https://littledata.io/app/get-free-trial"] How to set up Smart Goals If your user permissions are eligible, you can enable Smart Goals by selecting the goal type when following the regular goal setup flow: Sign in to Google Analytics. Click Admin, and navigate to the desired view. In the view column, click Goals. Click + New Goal. Select Smart Goal (if available). Give your Smart Goal a name and click Save. No additional configuration or customization is required (they're called "Smart" for a reason!) How to import Smart Goals into Google Ads After you've activated Smart Goals in Google Analytics, sign in to your Google Ads account, click the Tools tab, and select Conversions. Click Analytics in the left-hand menu. Check the boxes next to the goals or transactions you want to import. Click Continue. On the next page, you'll see settings that will apply to all of the goals or transactions you selected. Make your choices, then click Import goals. Click Close, or to import more goals, click Import more. Google Ads will begin importing the data from your Analytics account. Historical data prior to your import will not be included. Your Smart Goals report To see exactly how Smart Goals perform, use the Conversions > Goals > Smart Goals report. This report shows how Smart Goals traffic differs from other traffic to your website. You can also include the Smart Goals Completed dimension in custom reports. The Smart Goals report also shows how Smart Goals would perform even before enabling them in your view. This helps you determine if Smart Goals will be a useful feature for your ecommerce business. Interested in getting help with any of these features? Littledata's enterprise plans include complete support, a dedicated account manager, data analytics experts and ecommerce Google Analytics consulting. We covered what Smart Goals are, but are they actually beneficial? Next, we cover the why (or why not) behind Smart Goals.
Do I need the Google Analytics tracking code on every page?
How to improve Google Ads retargeting using ecommerce checkout steps
In the ecommerce world, one of the smartest ways to improve ROI for marketing campaigns is to retarget customers who visited your website in the first place. These visitors are already in the market for the types of products that you sell, but how do you pull them back if they've dropped out of the checkout process? The most effective way to grab these customers is to target them based on where they dropped off. Luckily, Google lets you do exactly that: with the right analytics, you can set up retargeting campaigns based on checkout behaviour. At Littledata, we've helped online stores in over 50 countries improve marketing ROI using ecommerce tracking. In this post, let's look at three simple steps you can take to improve your AdWords retargeting (now Google Ads retargeting) based on ecommerce checkout behaviour. 1. Set up accurate product tracking for your store Enhance Ecommerce tracking has been available from Google Analytics for a few years now. If you're already using this Google Analytics feature, good for you! Having product data means you can take advantage of this and create Audiences that then can be shared with Google Ads (and other platforms). In order to improve Google Ads retargeting using checkout steps, you must have checkout tracking and Enhanced Ecommerce enabled in Google Analytics. Once it's enabled, you can follow this checklist to set up accurate product tracking to be used for Audiences in Google Ads: Check out this resource (or share it with your lead developer): Google's Guide to Measuring a Checkout. Repeat after me: "the fields must by dynamically populated!" This is important! Clarify where the checkout process starts and ends on your website (and again, if your developer is handling the setup make sure they're clear about each stage in your checkout funnel, including where the process starts and stops). Set up checkout tracking based on that process. Now, add account to Google Analytics. Once this data is successfully coming into GA, you're ready to create Audiences. Next, you can track the audience from AdWords and share each audience accordingly within Google Ads. At this point, it's important to mention that there are a lot of elements to Enhanced Ecommerce tracking and each part needs to be set up separately. For example, you will not automatically track product categories, listings and details. If you're not sure how to implement the full extent of Enhanced Ecommerce, we're here to help. If you're using the Shopify platform, you're in luck — our Shopify reporting app's audit feature checks for accurate product and checkout-step tracking, and automatically assists with setting these up for you. The app works directly with the Google Analytics setup for your Shopify store, so you don't have to deal with Shopify's native reporting (which doesn't let you see how users are progressing through the checkout process). 2. Analyse customer behaviour, including checkout steps Shopping cart abandonment is the most frequent complaint we hear from ecommerce marketers. Why does someone add products to their shopping cart and then just abandon it completely? This isn't common in brick-and-mortar stores, so why does it happen so often online? Remember that online shoppers don't want to leave those things behind. They were attracted to those products and have expressed the desire to buy. But with a bad checkout flow, too much information or too little, they'll fly away and leave behind only unloved products with high shipping costs or under-promoted benefits. One of the best Enhanced Ecommerce use cases is the Checkout Behaviour report. This is essentially a Shopping Cart Abandonment report, showing weaknesses in your checkout process and where to invest your time and money to convince users that have added-to-cart to go ahead and complete a purchase. Why is this important and relevant to Google Ads? Well, everything in marketing is about perspective. The above report doesn't only show you where you could improve your checkout flow, but also where you've lost customers. 'Lost' is the keyword here. If you're losing a significant percentage of customers at the shipping stage of your checkout process, this is an opportunity to improve — and to market those improvements using Google Ads. For example, you might look at that report and ask yourself: Are you charging customers too much for shipping? You can't really change that cost for all carts (we know that shipping costs are significant), but you could, for example, offer free shipping to shoppers with items in their cart over some profitability margin. Retargeting those users in Google Ads is an effective way to show them that you're ready to reward them for making large purchases from your online store. Are you limiting yourself to too few territories? Put your analysts to work to find out where customers that leave the purchase flow want their goods to be delivered. Can you extend your logistical capabilities, or do you have a brick-and-mortar store nearby where you can direct these shoppers? Use Google Ads retargeting to let them know. Of course, Google Analytics' native reports aren't for everyone. If you find them confusing or haven't worked extensively with Enhanced Ecommerce data, check out Littledata's report packs. These automated reports are an easy but comprehensive way to read and interpret ecommerce data without any hassle. For the purposes of tracking checkout steps to improve retargeting, I'd recommend our Ecommerce behaviour pack, which includes reports on shopping behaviour by marketing channel and checkout steps. [subscribe] 3. Set up retargeting campaigns based on that data How do you retarget users in Google Ads based on Google Analytics data? Fear not, brave colleagues! If you've made it to this step, you shouldn't have any trouble creating powerful retargeting campaigns. First, you'll need to create a new Audience. In your Google Analytics Admin, find Audience Definitions in the middle of the screen near the bottom. Click on New Audience. Click on Create New and on this screen go to Conditions and Filter Users to Include the steps you want to target with this Audience. Set the Shopping Stage to contain (equal) 'Checkout_Abandonment' or 'Checkout_1', 'Checkout_2', etc. - wherever your customers have been falling off and leaving a basket full of goodies without completing the purchase. (Note that this field is auto-completed, so give GA a second after you start typing to show the options here.) You'll then need to set a time period. Think about your specific business and how far back you want to go with the search. Once you're happy with your selection, pick which Google Ads account you'll want to link to this new Audience. That's it! You're now ready to run PPC promotions to a buy-ready audience that would otherwise have disappeared. I hope you've enjoyed this quick guide. Please drop me a line below and let me know how you use checkout steps in relation to Google Ads. I always love to hear how other specialists in the field combine platforms to create perfect marketing. PRO TIP: If you're in a country with Google Merchant available, you can benefit from dynamic remarketing. This does take some extra setup on the product level, so let us know if you have specific questions. (And stay tuned - we're planning some Google Merchant Center-related posts for the near future.)
Tips for ecommerce conversion rate optimisation (CRO)
How Pufushop used our ecommerce benchmarks to grow sales
"Is my conversion rate good or bad?" We built Littledata's benchmarking feature to help you say goodbye to guessing games and start automatically benchmarking your site against top performers. Now that our benchmark tool has been around for awhile, we've started to get a sense for which ecommerce sites are using it most effectively. In other words, we've seen how benchmarks can help websites increase revenue - not in theory but in actual practice. Littledata has now helped hundreds of companies understand where their performance is compared with other websites in their niche, using our benchmarking algorithms and clean user interface. But can benchmarks really help you grow sales? I understand if you want to see the data for yourself. One of our long-term customers makes for an ideal case study. Case study - Pufushop Over the course of 2017, we helped Pufushop, a Romanian ecommerce site, understand if their website changes were helping to increase performance - and where they still had work to do. Pufushop is a retailer of baby goods, with a main focus on baby carriers. The products in their store are all premium quality and from top vendors, so comparing them with just any other baby store wouldn't have been relevant. Instead, we compared their ecommerce metrics with specific benchmark segments that were most relevant to their market landscape and business goals. Ecommerce benchmark segments Benchmarking is used to measure and compare the performance of a specific indicator, and it's most useful when you map that data onto your internal KPIs and compare performance against similar sites. Littledata specialises in ecommerce analytics and our benchmark population now includes Google Analytics data from almost 10,000 sites. We break that data into specific categories, such as Marketing, Ecommerce and Speed (site performance), and within each category you can filter by industry, location, website size, and more. Littledata aggregates reliable data from those thousands of high-performing websites so that you can focus on results. In this customer's case, we analysed their website and business model to provide 5 relevant benchmark segments: Romanian websites to compare KPIs across regional market Small SEO websites because 60% of Pufushop's traffic comes from search engines SEO-driven online stores (more generally, to see how they compare) General online shopping websites across the globe, to get a sense for how their funnel compares And a specific revenue per customer category based on shoppers' average basket spend (sites with a similar average order value, no matter the sector) Key metrics Web behaviour is not necessarily consistent across industries. We started Pufushop's analysis by looking at key ecommerce KPIs such as Checkout completion rate, Ecommerce conversion rate and Add-to-cart rate, but we didn't just pull these metrics blindly. Starting with the first month, February 2017, we looked at how other stores with a similar average basket value were performing. This helped our client establish what was working and what could be improved. As we worked with them to make sure everything was tracking correctly (after all, benchmarks are only as useful as your data is accurate), they could also check these benchmarks directly in the Littledata app. Results Now for the first time, both Pufushop's Marketing Director and Senior UX Designer had clarity on which areas of the website could be improved to increase sales. Based on the benchmark data they could see that the main places to improve were: The checkout process (to increase the checkout completion rate) Product pages (to increase the add-to-cart rate) Resolving those two main issues will automatically resolve the e-commerce conversion rate KPI and will indirectly influence the Revenue per customer. Pufushop decided to use Google Optimize in order to improve the checkout completion rate. Using Google Optimize is an easy-to-use, fast and scalable tool in order to A/B-test different experiences on the checkout page. Pufushop conducted a variety of targeted experiments, including: Shortening the checkout process Eliminating unnecessary fields Testing variants of checkout pages Split-testing different product pages Testing a variety of shipping costs After a couple of months of testing, the results were significant: The add-to-cart rate grew from 3.7% to 5.5% The checkout completion rate jumped from 52.8% to 89.7% Now those are some real results! Having a direction as well as a target helped Pufushop's digital team to focus on clear, achievable goals. As they continue to grow, we're glad to have them as a part of the Littledata family. [subscribe] Ready to benchmark your site? If you're in the same place as Pufushop was a year ago, here's a quick guide for how to use ecommerce KPI benchmarks to improve your store performance. Sign up for Littledata's main app or Shopify app Look at the benchmark data and pick an industry and a set of KPIs - the right sectors and segments will help you optimise campaigns Use tools like Hotjar and Littledata's automated reporting to analyse user behaviour around those benchmarks and define a short list of actions you're going to take Use Google Optimize or hire a developer to put those actions into place Monitor how users are interacting with the changes When you have sufficient data to see a clear relationship between those changes and an increase in traffic, revenue or conversions, make those changes permanent and move on to focus on a new set of KPIs Keep in mind that there are situations where the KPIs will show you issues of wrong messaging, for example of a product page or advertisement - technical issues where the change is fairly easy to make. In other cases, you will need to develop a long-term strategy for radical changes to your website, such as altering your checkout process. The online environment is a fast-moving industry, so you need to be agile and ready to change accordingly. Either way, we're here to help you scale with data-driven strategies for sustainable growth. Now stop reading this post and start benchmarking your site! Note: In order to maintain data-confidentiality, KPI values have been altered in this case study (the results are real, only the benchmarks have been adjusted).
Using buyer personas to adjust Facebook ads
Facebook isn't just a social platform anymore. Even though the vast majority of users come to Facebook to keep up to date with news from friends, advertisers are finding in Facebook a real revenue stream and a platform to mine for more accurate data about their ideal customers. Around this time last year, I was struggling to use Google Analytics APIs and Google Sheets to identify user profiles for one of my top clients. This process was both tedious and time-consuming, but there was no alternative to doing it manually. I was basically making user personas by hand, and once I had established this user profile service, other customers began requesting it. By presenting it to them in my portfolio I found out just how little most companies actually knew about their user profiles and the invaluable data they provide. From a marketing perspective, most companies can’t afford not to know this information. These personas can dramatically improve ad performance because they’re based on accurate, useful consumer data. Littledata is committed to automating the most time-consuming parts of your day, so we started work on a Buyer Personas algorithm. The resulting Buyer Personas feature shows you which type of customer, on which type of marketing channel, is most likely to convert -- so you can spend smarter, not just more, on Facebook ad campaigns. Here's how to use those personas to get higher ROI on Facebook. Why it can be difficult to improve Facebook ad performance The first question you ask yourself when setting up a new ad campaign is: Who is the target audience? It seems simple, but companies often struggle to come up with an answer. I faced the same problem when I was working with Pufushop and was asked to help them set up a new Facebook ad campaign. I've set up many campaigns on Facebook, but usually the website has had a target audience in mind or the site had installed a Facebook Pixel so long ago that I could have found this out from Facebook Analytics. But for this particular project I needed to find the target audience based only on Google Analytics data. If you've read any of my blog posts you know that "feeling" is not a metric for me. We all know that Facebook and Google Analytics have different ways to define demographics and interests. And that’s okay, sometimes it’s even beneficial. On one side we have Facebook's audience definition, which is sourced from how users self-identify in their profiles and also what content they interact with. On the other hand, we have the Google Analytics audience definition, which is based on presumptions about user behaviour and less rooted in user-generated data. I created the Buyer Personas profile below directly in the Littledata app. Our algorithms generate accurate personas based on your conversion goals and ecommerce setup, broken down by specific marketing channel (in this case, Facebook ads). Using our Buyer Personas feature I was able to find out the demographics and interests of Pufushop buyers -- in under 3 minutes. That persona is the result of tens of automated permutations. Note that this sample website has relatively low volumes, so four user characteristics stand out. For higher-volume sites, more categories appear automatically. Creating effective Facebook Ads from Buyer Personas Once I had the required data, I was ready to start my campaign. Here is a step-by-step guide on how you can set up a Facebook ad campaign based on your Buyer Personas. Go to your Ads Manager in Facebook and click on "Create" to start a new campaign In my case, I used a catalog sale because the campaign was promoting some items that were sold out and all of my products were part of a Collection and had the same target audience. Once I've chosen the catalog for the products and added the campaign name, I can click "Continue" and move on to the next step. Define the Ad set and the audience I found out using Littledata's Buyer Personas that my highest conversion rate is with users from Oradea, who are bargain-hunting females aged 21 to 30, have their browser set up in Romanian, and like to shop on Monday evenings. So I will set up that exact same audience for this ad set. Using all this insight as well as my specific need to present a 5-day sale with a minimal budget, I've successfully set up an audience that should convert at a higher rate. I click ‘Continue’ and on the next screen I add the creatives for the advertisement (image and text) and then, just like that, I’m done. To top it all off, this discovery and set up was done in less than an hour! [subscribe] The many uses of Buyer Personas As you get to know Buyer Personas, you can also use them to: Create new campaigns when you're running on a low budget Narrow down your audience based on specific factors Reduce the frequency of your ads by choosing the best hour to deliver them Create a better re-marketing strategy by knowing when your abandoned carts are more likely to be converted into purchases Run territorial marketing campaigns, taking into consideration the interest and potential of each area Plus many more insights and discoveries to dramatically improve your conversion rate (doing something unique? Let us know!) At first glance a buyer persona like the sample above may seem to be only "four lines in a table," but if you look beyond the text you’ll start to really understand how users from a specific category interact with your website. And once you use your Buyer Personas to adjust and customize your Facebook ads, you'll come to the same conclusion I did: "This is so obvious, how did I miss it?" Facebook campaign reporting in Littledata If you're advertising on Facebook and want to see how your Facebook efforts are paying out, check out Littledata's Social traffic pack. The pack pulls from your Google Analytics data to create automated reports on social traffic and top-performing campaigns. Included in the pack are reports that will show you landing pages for untagged traffic from social networks, an overview of traffic from social media sources, and top campaigns from social networks that help you monitor your campaigns, enabling you to track how your traffic is being split between social channels. We've also recently launched a Facebook cost import feature (more details coming soon). The feature links your Facebook data with Google Analytics so that you can ensure accurate tracking of your Facebook Ads spend -- yet another way that Littledata helps you make informed, data-driven decisions. How are you using Buyer Personas and Facebook Ads? Leave a comment below! The buyer personas data in this blog post has been modified for illustrative purposes.
Google Analytics 360 versus the free version
We often receive questions about what customers get when they upgrade from the free version of Google Analytics to Google Analytics 360. The quick answer is that you get a lot - the possibilities are literally endless - as long as you're a big, data-driven company willing to put energy into customer engagement and marketing. Google emphasises that their enterprise analytics are designed to help large companies, like major ecommerce sites, create better customer experiences. But what does that mean in practice? There are a lot of details to understand if you're thinking of transitioning to the big paid version of Google Analytics. The main differences lie in how each product deals with the volume of data and integrations that they have available by default. I've broken those differences down into three categories: Data Collection, Data Sampling and Data Sources. Data collection In short, Google Analytics 360 allows for a faster, smarter, larger data collection. With unlimited hits per month and up to 200 custom dimensions per web property. Features Google Analytics (free) 360 Suite (paid) Hits per Month up to 10M unlimited Custom Dimensions/Metrics 20 Per Property 200 Per Property Calculated Metrics 5 Per View 50 Per View Properties per Account 50 50+ Views per Property 25 25+ Roll-Up Properties No Yes Data Freshness 24 – 48 hours 4 Hours [subscribe] Data sampling and limits As your web traffic grows, Analytics 360 lets you get more out of both sampled and unsampled data sets. Compared with the standard version of GA, you get better reporting on large amounts of data. Understanding how data is sampled in Google Analytics will help you scale the smart way. Features Google Analytics (free) 360 Suite (paid) Report Row Limit per Day Yes Yes Standard Reports Pre-Aggregated 50K 75K Sampling in Ad-Hoc Reports 500K Sessions per Property 100M Sessions per Property Custom Tables No 100 Custom Table Report Row Limit per Day No 1M Rows Unsampled Reports No Yes Unsampled Report Row Limit No 3M (for download) Data sources The 360 Suite makes it especially easy to pull in data from a wide range of advertising platforms and sources, including non-Google products like Salesforce. For some of our enterprise customers, especially large ecommerce sites with a focus on PPC lead gen and retargeting, the ability to seamlessly integrate with DoubleClick is itself enough to make their 360-buy worthwhile! Features Google Analytics (free) 360 Suite (paid) AdWords Yes Yes AdSense Yes Yes DoubleClick Campaign Manager No Yes DoubleClick Bid Manager No Yes DoubleClick For Publishers No Yes Custom Data Sources Yes Yes Query-Time Data Import No Yes Salesforce No Yes BigQuery No Yes Additional perks (GTM 360, beta testing) In addition to the above benefits, being able to connect Google Analytics to other Google 360 Solutions like Google Optimize 360 and Google Tag Manager 360 is a big plus. As an added perk, Analytics 360 clients often get early access to beta programs for testing and product feedback -- getting directly involved with product development to suit their needs -- plus first-hand support from Google. Google 360 can be purchased directly from Google or through a sales partner. We don't currently sell the 360 Suite ourselves, but we’ve been a certified Google Analytics Service Partner since 2015, including Google Tag Manager and Google Optimize certification, and have extensive experience with custom tagging and reporting. Plus, we built the Littledata app around those analytics best-practices. Our larger consulting clients get the most benefits out of our enterprise plans, which include automated analytics audits, unlimited access to app features, custom setup and reporting, and a dedicated account manager to help ensure deep, accurate tracking. Whether or not you've already upgraded to Google Analytics 360, we highly recommend getting in touch to make sure you're able to use this powerful tool to its full potential!
Using Google Analytics to refine merchandising and product promotions
The whole purpose of having Google Analytics tracking on your site is to find out how your website is performing and to use this data to improve your digital efforts. Yet many businesses miss the mark when it comes to taking action at the level of product listings, despite the fact that this can lead to huge revenue gains! Why do they miss the mark? Two reasons: inaccurate tracking and unclear reporting. The Littledata app helps to fix these issues automatically, providing users with a reliable data stream and automated reporting based on Google Analytics data, but it's still useful to drill down into Google Analytics itself to understand all of the details. In this post I break down how to use Google Analytics to refine merchandising, product promotions and product listings in a way that can have a direct effect on both short-term and long-term revenue for your ecommerce site. For this to work, you'll need to have Enhanced Ecommerce set up on your website. You'll also need some spreadsheet software (Excel, Google Sheets, etc.) so we can play with extracted data and drill down deep. [subscribe] Banners and creatives: getting users to see what we want them to see A full enhanced ecommerce setup will enable you the power to see how much money each of the creatives on your site is bringing you. If your website is like most ecommerce sites, you have several creatives displayed, such as: Homepage carousel Homepage pods Category main banner Choosing which creative should get on your homepage might feel like just a preference, but it doesn't have to be that way. You can use the 'Internal Promotion' menu in Google Analytics (Marketing > Internal Promotions) to make data-driven decisions about your homepage creatives. Imagine an online store that sells scooters and accessories: We have banners for categories like Helmets, Accessories, Mini Micro and Maxi Micro (different sizes of scooters). We have 2 banners on the homepage with these two creatives: Safety (the first one) and Built for Adults (the second one). We want to change one of the creatives on the carousel. Let's analyze what is the best strategy here. The first banner on the carousel was seen 24,404 times. It has a 5.01% click thru rate (CTR) and a £3.90 value per click. The second banner on the carousel was seen 17,109 times. It has a 5.52% CTR a £2.02 value per click. Now we can make a decision. What to discard and what to keep Even though we have a higher CTR on the second banner and this is an indicator that the message is more appealing, the reality is that the revenue that comes with that click is not even half of the revenue we get from a click on the first banner. If you want to make a 100% correct decision here you can analyze the margins on the product promoted by each of the banners. If you have double the margin for the products in the second banner you can get rid of the Safety banner and make the second banner primary. If your margin is the same for both categories then the best decision here is to replace the second banner with the first one. How to populate the carousel We already decided to keep the first banner, but now we need a replacement for the second one. So we need to find a creative in the website that had performed at least the same as the second banner. Based on the example above if we search by CTR higher than 5.52% we can see that we have a banner for Maxi Micro with 20% CTR and a value per click of £5.32. The action here is to replace the second slot of the carousel with this creative. After 1-2 weeks we can retake this process all over again and we may decide to reverse the creatives (Banner 1 will be Banner 2 and Banner 2 will be Banner 1 in the carousel). This is not a one-time job. The analysis should be made every time you add a new creative or make a new promotion.--or even as a weekly task. Many Littledata clients run this type of analysis on a regular basis, whether or not they've launched a new promotion, to make sure they are optimizing sales and conversions. You should pay attention to the average click thru rate (CTR) based on creatives category, and also you should know what is your standard deviation for each category so that you can quickly spot which are over- or under-performing. Based on the example above, the average CTR for a carousel banner on the site is 5.26% and the standard deviation is 0.25%. So I know that if I see a banner that has a CTR less than 5.01%, there is room to improve. As per above for the category pages, we have an average of 10.92% CTR with a standard deviation of 6.28. This means that everything under 4.63% should be replaced ASAP and everything above 17.20% should be promoted. List views: how to arrange products for ultimate engagement One of the best Enhanced Ecommerce features in Google Analytics is the Product List Performance Report (Conversions > Ecommerce > Product List Performance). This report shows you how many views each list gets. Why does this matter? Because if you have a high margin on some products from a specific category, you should find out if that list (category) is being sufficiently promoted on your site. From these reports, we can find out things like: Most viewed categories (sort by Product List Views) The category that has the biggest engagement (sort by Product List CTR) The list that is bringing you the most money per view (Product Revenue divided by Product List Views) Which categories are performing best -- and which are most profitable? Let's say I have three categories in my store: categories 1, 2 and 3. And my margin for products in category 3 is three times the margin for those in category 1. In the report above, we see that we don't have a click thru for Category 2. This could mean: The tracking is not working on that page Users have issues clicking on the products There is no call to action (CTA) on that page So we can assume that Category 2 is not working. Moving forward we should analyze the performance of Category 1 vs Category 3. Views Clicks CTR Revenue Revenue / click Margin at each $1 sold Margin at 1000 clicks Category 1 1,701,660 57,038 3.35% $329,799.67 $5.78 0.23 $1,329.88 Category 3 46,895 3,175 6.77% $23,881.37 $7.52 0.69 $5,189.97 We can see that even though we have a fraction of the views for Category 3, this category is for us almost 3 times more profitable per 1000 clicks. At this point, we should investigate how much marketing we're doing around Category 3 to see if there are options to push harder on this highly profitable category, alongside whatever's already working for promoting Category 1. Order matters The Product List Performance Report can also help us find out how customers progress from viewing a product in a list to clicking through for more information. Let's analyze the data in the above report. The table is sorted by Product List Views for Mobile devices. We know that the alignment for this website is one product under the other and for a product view to be sent the user needs to see it for at least one second. So we can draw these conclusions: Position 2 and 3 are normally visually scanned by users. The fourth product in a list is seen in more detail but has a lower CTR than the second or third product in the list. We know that each page has 10 products so the average Product List CTR rate for page 1 is 1.36% and the standard deviation is 0.42. From this, we can see that position 2 has a good CTR and we need to change the photo and text of the listing to attract more attention -- products placed in the second position in a product listing on this site tend to convert well. Position 4 gets attention but has low performance so we could try changing the photo and title of products in this position in order to increase the CTR. If we are looking at this report as aggregate data then we can conclude that if we want to make a push for particular products, we should place them in position 1 or 4 for maximum visibility, or position 1 or 2 for maximum CTR. How to monetize product list positions We can take this analysis further by examining how list slots relate to product revenue, whether on your site or via affiliate programs. Looking at the report in aggregate and extracting the data, we can give a monetary value to each slot in the product listings. Product List Position Product List Views Product Revenue Revenue/view per slot 1 2,290,505 £183,207.00 £0.08 4 2,279,917 £99,830.00 £0.04 3 2,246,164 £117,096.00 £0.05 2 2,239,943 £157,605.00 £0.07 6 2,062,271 £73,183.00 £0.04 5 2,053,534 £94,889.00 £0.05 8 1,788,080 £58,585.00 £0.03 7 1,775,762 £60,603.00 £0.03 9 1,750,248 £52,366.00 £0.03 10 1,606,599 £50,913.00 £0.03 From the above example, we can see that each of the slots in the listing has a value per view. And the value is decreasing with the position. Using the known margin for a specific product in a list, you can improve your ROI just by positioning it in a slot with a higher CTR based on the model above. Which photos should you show first in a listing? If you offer a product in multiple colors, you should use an image and a default (primary) product selection in the most popular color. But how do you figure that out? Product variants are too often left behind in analysis. The Product Variant field captures the specific variation of a product, e.g., XS, S, M, L for size; or Red, Blue, Green, Black for color. It is an Enhanced Ecommerce feature that can give you powerful insights into your users' searches, interests and preferences. Paying attention to variant performance can have a big effect on shopping behavior and sales. In the example above, we're looking closely at the Product Variant dimension to figure out which color is most popular. We have a product with 4 colors: Black, Grey, Midnight Black and Persian Grey. There isn't enough transaction data to make a decision based on purchases, but we can calculate the most popular variant (in this case, the most popular color) based on how often users have added items in each color to their shopping carts (Adds To Cart). For Black, we have a View to Add To Cart rate of 0.6% and for Grey 0.8%. So in this case we should use the main Grey color for advertisements and main photos in listings pages. We might also try using the Persian Grey variant. Note that in this example we can calculate for each product view because we've listed each color as a different product. If you're listing only one product and you show variants on the product page, then you'll need to divide the Adds To Cart for each variant by the total Product List Views. What to do next If you need help with Enhanced Ecommerce reporting, our analysts are ready to come to the rescue. You can either request a consultation or just sign up for a free Google Analytics audit and contact us directly from the app. How are you using Enhanced Ecommerce reports in Google Analytics? Drop us a note below.
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