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! 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.

2018-03-28

Tracking the online customer journey for luxury ecommerce

Today I'm excited to be participating in the Innovation Meets Fashion event in Lugano, Switzerland. As an increasing amount of luxury and fashion retail moves online, high-end brands are finding it complicated to track the complete customer journey. In many cases, difficulties in tracking customers through to eventual purchase are holding back investment in the digital experience and online marketing. But it doesn't have to be this way. We've found a straightforward correlation in ecommerce between the average ticket price of the item being purchased and the number of web pages or sessions before that purchase is made. Simply put, customers spend longer considering big ticket items than they do with smaller ticket items and impulse purchases. Luxury retail involves many touch points with the brand across your websites, social sites and physical stores. The problem is that the longer than online customer journey, the harder it is to get consistent data on which top-of-funnel experiences are leading to purchasing. So first the bad news: since many potential customers browse anonymously, perfect ecommerce tracking across a long online and offline journey is not possible. Tracking browsers based on first-party cookies (such as Google Analytics) will fail when customers use multiple devices, clear their cookies or browse in-app (such as from Facebook). Yet there are three ways we have seen retailers selling high value items increase the reliability of their online behavioural data. 1. Track online shopping behaviour in detail Understanding whether customers browse certain products, view the detail of product variants and even add-to-cart is a good proxy for seeing which campaigns eventually convert. Does your brand have a good understanding of how each marketing channel influences browsing behaviour, after the landing page but before the checkout? 2. Offer a good reason to get customers to login before buying VIP offers, registering for events and discounts all offer a good way of getting customers to login from different devices. With the correct analytics setup, this login information can be used (without infringing the users’ privacy) to link together different interactions they make across multiple devices 3. Make the most of your email list Even without having a login before purchase, customers clicking through links in a marketing email can allow the same stitching together of sessions. This means that if a customer visits a link from their mobile device, and on another week from their home laptop, these two devices can be linked as belonging to the same email – and therefore the same person. Luxury online retail involves a complex journey. Littledata is here to make your tracking and reporting both easy and accurate. Sign up today to get started with our complete analytics suite, and feel free to reach out to our Google Analytics consultants with questions about best practices for luxury ecommerce. Your success is our success!

2018-03-26

Introducing Team Invites

Team invites are here! It's now easier than ever to collaborate with team members in your Littledata account. In the new digital landscape, collaboration is the mother of invention. Our new Team feature lets you easily manage additional users for your Littledata account, so that everybody on your home team - or on a particular marketing or ecommerce project - can view smart metrics and reports for your site. What's new All Littledata accounts now include team functionality. You can invite and manage team members from your Littledata admin. Here's what you can do with Team members in Littledata: Invite new team members Manage current members Respond to requests to join your team From simply sharing reports to collaborating on complex analytics projects, team invites are a straightforward way to share information and hone down on accurate data, whether you're currently in the data setup phase or focusing on making and understanding business decisions based on that data stream. Adding team members to your account helps to ensure that your colleagues can take advantage of the automated reporting you set up in Littledata to get a clear view of your online business performance. And it doesn't stop there. Team members have access to all of the features in your Littledata plan, so you can collaborate on projects such as setting up accurate tracking, benchmarking your site, and running data-driven campaigns based on buyer personas. Note that while you can have multiple team members, there can only be one account owner for each Littledata subscription -- and only the owner can use the app to make changes in GA. Team members can view audits and reports but cannot make changes to the connected Google Analytics property using the Littledata app. We automatically limit permissions in this way to ensure that the account owner has oversight on any changes to tracking and reporting. Benefits for users, partners and agencies Team invites aren't just for your core ecommerce team. They can be used to enhance collaboration and ensure accurate reporting on any number of projects. The benefits extend to every type of Littledata user: General users can collaborate with both internal teams and external consultants such as PPC agencies Agencies can manage customer accounts internally (as an owner) or externally (as a team member) Partners can access client website data in one streamlined tool, including benchmarks, and find ways to optimise custom report packs based on client needs Team owners can always remove member permissions at a later date, so the Team feature is ideal for growing ecommerce sites that want to control who has access to their Google Analytics data when they change agencies or move on to a different project. Your Littledata team might be composed of members from a variety of teams in your office, and that's okay. In fact, it's encouraged. Sometimes your marketing department needs a good way to collaborate with your data team, your online merchandising department or your ecommerce site developers. As Littledata offers ways to both fix your tracking and get more relevant reporting, our app often brings new teams together to make smarter decisions. Early adopters of our Team functionality have found it particularly useful for expanding the range of reports they use in Littledata. In addition to finding ways to further enhance custom dashboards and reports, sometimes a team member will notice a particularly relevant report pack that had previously been overlooked, and the metrics in that pack will end up making the biggest difference to your online revenue. How to invite new team members and manage invitations To manage team members, login to your Littledata account and go to Settings > Members. You can access the Settings menu by clicking on the gear icon on the upper right, and you'll find Members in menu bar on the left. From the Members page, you can send new invitations, manage sent invitations, and respond to requests to join your team. In addition to invites, users can request to join an existing team. When new users sign up for Littledata or current users add a new site/view to their account, they can search for your site and request to join your team. When someone requests to join your team, you'll receive a notification at your registered email. You can either accept or remove their request. Wondering how to join a current Littledata team? You can request to join an existing team when you sign up using your Google account or a supported social login (currently Facebook and Twitter). Scalability Team member functionality is the logical next step in helping to support sustainable business growth for our customers. Last year we switched to transaction-based pricing because we are dedicated to providing apps and managed services that easily scale with any online business, whether you're doing $5,000 or $250,000 per month in sales when you first get going with Littledata. Our pricing is per web property (you need a separate account for each particular Google Analytics view or data source), not per user. Standard and higher plans include unlimited team members, but if you need a unique team setup or multi-site dashboard, let us know. We hope you love the new Team feature as much as our team does here at Littledata!

by Ari
2018-03-23

How to quickly build user personas for PPC campaigns

Buyer personas. User personas. PPC personas. Are these just marketing buzzwords? Do they mean months of planning before you can even begin your PPC campaigns? The answer to both questions is a straightforward no. 'User personas' don't require months of extra work to build, and they aren't just another marketing buzzword. If you follow my suggestions below, you can quickly create personas to help target and optimise your next PPC campaign. Start with brainstorming Brainstorming should come at the very beginning of your process. What do you already know about your audience? This can be old-school brainstorming with a pen and paper, or a more business-like approach with a whiteboard in your conference room. If you do this with a team, hand out some Post-it notes for jotting down ideas. The Post-it notes approach makes it very easy to move your notes around and begin grouping by identified themes. Quickly create simple personas The key here is simplicity.  There is great content out there on creating more complex personas, by using a resource such as Hubspot’s 100 Questions. For the simple approach, I look at three areas to kick things off. Describe the audience by their demographics: gender, location, age, parental status, income, etc.. Identify the biggest problems they want to solve. If you are unsure how to define this one, start with 'I want' or 'I need' to put yourself in the position of your audience. For example, as a marketer, my ongoing problems include automating mundane tasks and creating simple personas. Ask how your offering specifically solves the identified problems. When it comes to creating personas, Littledata can help by automatically building personas with existing Google Analytics data. With this information, create a very short narrative with the key descriptors and needs of each identified persona. Find the perfect image Do this after you finish the above steps. You do not want to start with image and then create a persona to look like that person. (There’s some great discussion on that on UX Mastery). One step I often recommend is to look at images of people in existing marketing materials to see if they represent the personas created from this exercise. Digital tools to help you create user personas After you do some brainstorming and jot down initial notes about personas, you can next turn to digital tools to help you. MakeMyPersona.com is aptly named because it helps you do just that.  It is a way to organize some of the thoughts that came up in the earlier steps. Those in the B2B market can try Up Close & Persona. It meets my criteria of simple and takes you through questions that help you think of appropriate messaging for your audience. However, some of the questions have only a few preset answers so I would not start this tool. It could box you into narrow thinking. Littledata’s buyer personas feature helps you identify the website visitors that are most likely to convert.  We know that Google Analytics does not do all the work for us, but there is a lot of data available for analysis. Compare these findings to what was uncovered during brainstorming. Develop your PPC campaign around the user persona Take your 'I want' and 'I need' statements and pull out some of those phrases as keywords. When it comes to choosing PPC keywords, stay away from your corporate lingo, and instead think about how your prospects talk about you. These keywords will help you match your message to each persona. Is your persona trendy with a sense of humor? Maybe you will get a little snarky with your messaging.  Is the need something serious, such as a health issue? Stay away from the snark and instead be really clear about your benefits. Create an offer that matches the persona. An intellectual, highly educated executive may take the time to download and read your white paper. A busy single parent with four young kids wants a solution. And wants it quickly. Segment personas by channel. I like Littledata's buyer personas because they let you see how to adjust your ad spend based on specific marketing channels beyond Paid Search. PPC is not the only place to reach your audience. You will - hopefully - have a multi-channel approach and need to understand Organic Search, Email, Referral, and Social in addition to PPC. Unless you have an unlimited marketing budget, you may not be able to reach every persona and on every channel. One consideration for your PPC spend is to focus on the longer tail or brand name keywords. This is definitely a smaller audience, but it will capture people further down the funnel who are more likely to buy. What to do next I hope that you find this simplified approach to developing personas useful in kicking of the next stage of your digital marketing! My goal is to provide steps for you to take action and not get bogged down by the prospect of developing personas before kicking off a campaign. You may want to refine this approach over time, but the important thing is to get started now. Even with the best planning, you may find some surprises in your campaigns after you get started which is why I always watch new campaigns closely, especially in those first few days. Monitor your performance by channels in Google Analytics and be prepared to adjust your ad spend. Your ROI will vary by offer and user persona, so focus on actionable analytics from this wealth of data to make the right decisions for your particular business.   Want to know more? Get in touch with Tina's agency, 360 Internet Strategy, and follow her on LinkedIn.

2018-03-15

How to add Littledata's code snippet to your Shopify store templates

For most Shopify stores, the Littledata - Google Analytics reporting app automatically adds our tracking script to your shop's template. However, if your store has a custom template/layout, there will be some cases where our app isn't able to do this automatically. Luckily it's super-easy to resolve this issue by adding a code snippet yourself. Once you add the code, your store will automatically call our tracking script at just the right time. That way we can help you get accurate data across the customer life cycle. In this quick how-to guide I'll show you how to add the code snippet. How to add the snippet to your shop's code 1. Edit the code in your Shopify admin Go to your Shopify Admin > Online Store > Themes > Actions > Edit code. 2. Copy the snippet Copy the following snippet. (Even though our script has already been added to your store, it still needs to be called for each Layout.) [code language="javascript"] <!-- Start of Littledata - Fix Google Analytics Script--> {% include 'LittledataLayer' %} <!-- End of Littledata - Fix Google Analytics Script --> [/code] 3. Paste the snippet Now paste the snippet in every one of your store's layouts, just under the <body> tag. In the example below, we'll paste the snippet in row 77. 4. Save and repeat After you paste the code, click Save and repeat the steps above for each layout. Note that you will need to make this change for each layout when you are installing our app, but also when you create another layout for a new campaign. Anytime you create a new layout, just follow the steps above to add the right code snippet. That's it! You're now all set to get a consistent stream of accurate data and intelligent insights for your Shopify store. Remember that it takes about a week for the new analytics setup to start producing useful reports. If you've followed these steps but still have questions, please don't hesitate to get in touch with our team. We <3 code. And we're here to deal with it so you don't have to :)

2018-03-07

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   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!

2018-02-28

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. 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.

2018-02-23

Troubleshooting your Google Analytics goals setup (VIDEO)

https://www.youtube.com/watch?v=SGY013J9QGg So you've got your new sales plan in action and you've set up unique goals in Google Analytics. Are they tracking what you think they're tracking? Are you sure they're giving you reliable data? If you've audited your analytics setup, you might have noticed any number of incorrect audit checks about how you've set up custom events for your Google Analytics (GA) goals. Goals are used to make important business decisions, such as where to focus your design or advertising spend, so it's essential to get accurate data about them. In this quick video we cover common issues with setting up Google Analytics goals, including: Tracking pageviews rather than completed actions Selecting the wrong match type Inconsistent naming when tagging marketing campaigns Filters in your GA view rewriting URLs (so what you see in the browser is different from what you see in GA) Issues with cross-domain tracking In GA, a goal is any type of completed activity on your site or app. GA is a remarkably flexible platform, so you can use it to measure many different types of user behaviour. This could be visitors clicking a subscribe button, completing a purchase, signing up for membership -- known as 'conversion goals' -- or other types of goals such as 'destination goals', when a specific page loads, and 'duration goals', when a user spends over a particular amount of time on a page or set of pages. That all sounds well and good, but trouble comes if you simply set up goals and then trust the data they give you in GA, without double-checking to make sure that data's consistent and reliable. We hope you find the video useful. And don't despair -- even a little extra time spent on your GA setup can yield awesome results. Sign up for the Littledata app to audit your site for free, and let us know if you've experienced other common issues with setting up goals in GA.

2018-02-21

Get the app

See for yourself why Littledata is the smartest ecommerce analytics app

Free trial