Category : Google Analytics
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!
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.
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.
GDPR compliance for ecommerce businesses
Ecommerce companies typically store lots of personally identifiable information (PII), so how can you make compliance easier without compromising analysis? With the deadline for GDPR compliance looming, I wanted to expand on my previous article on GDPR and Google Analytics to focus on ecommerce. Firstly, who does this apply to? GDPR is European Union legislation that applies to any company trading in Europe: so if you sell online and deliver to European Union member countries, the regulations apply to you. It's essential that you understand how your online business is collecting and storing PII. Splitting PII from anonymous data points Your goal should be to maintain two separate data stores: one that contains customer details, from where you can look up what a specific customer bought, and one that contains anonymous data points, from where you can see performance and trends. The data store for the customer details will typically be your ecommerce back-end and/or CRM (see below). This will include name, email, address, purchase history, etc. It will link those with a customer number and orders numbers. If a customer wants the right of access all the relevant details should be in this store. We use Google Analytics as the anonymous data store (although you may have a different ecommerce analytics platform). There you can store data which only refers to the customer record. These are called pseudo-anonymous data points under GDPR: they are only identifiable to a customer if you can link the customer number or order number back to your ecommerce back-end. Pseudo-anonymous data points you can safely send to Google Analytics include: Order number / transaction ID Order value / transaction amount Tax & shipping Product names and quantities Customer number Hashed email address (possibly a more flexible to link back to the customer record) If a customer exercises their right to removal, removing them from the ecommerce back-end will be sufficient. You do not also have to remove them from your Google Analytics, since the order number and customer number now have nothing to refer to. You do still need due process to ensure access to Google Analytics is limited, as in extreme circumstances a combination of dimensions such as products, country / city and browser, could identify the customer. Isn’t it simpler to just have one store? Every extra data store you maintain increases the risk of data breaches and complexity of compliance – so why not just analyse a single customer data store? I can think of three reasons not to do so: Marketing agencies (and other third parties) need access to the ecommerce conversion data, but not the underlying customer data Removing a customer’s order history on request would impact your historic revenue and purchase volumes – not desirable Your CRM / ecommerce platform is not built for large scale analysis: it may lack the tools, speed and integrations needed to get meaningful insights Beware of accidental transfers There are a few danger areas where you may inadvertently be sending PII data to Google Analytics: Customer emails captured in a signup event A customised product name – e.g. ‘engraving for Edward Upton’ Address or name captured in a custom dimension Our PII audit check is a quick, free way to make sure that’s not happening. Multiple stores of customer details GDPR compliance becomes difficult when your customer record is fragmented across multiple data stores. For example, you may have product and order information in your ecommerce database, with further customer contact details in a CRM. The simplest advice is to set up automatic two-way integrations between the data stores, so updating the CRM updates the ecommerce platform and visa-versa. Removing customer records from one system should remove them from the other. If that’s not possible, then you need clear processes to update both systems when customer details change, so you can comply with the right to rectification. Conclusion GDPR compliance need not require changing analytics tools or databases, just a clear process for separating out personally identifiable information – and training for the staff involved in handing that data. I hope this brief overview has been helpful. For further advice on how your ecommerce systems comply, please contact us for a free consultation. Littledata has experience with every major analytics platform and a wide range of custom setups. However, as a number of global companies are concurrently prepping for compliance, we highly recommend that you get in touch sooner rather than later!
How to improve AdWords 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 to improve marketing ROI using ecommerce tracking. In this post I share three simple steps you can take to improve your AdWords 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 couple of 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 AdWords (and other platforms). In order to improve AdWords retargeting using checkout steps, you must have checkout tracking and Enhanced Ecommerce enabled in Google Analytics. Then you can follow this checklist to set up accurate product tracking that can be used for Audiences in AdWords. 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 Once this data is successfully coming into Google Analytics, you're ready to create Audiences and share them with AdWords 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 be tracking 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, as 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 AdWords? 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 key word 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 AdWords. 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 AdWords 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 AdWords 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. 3. Set up retargeting campaigns based on that data How do you retarget users in AdWords based on Google Analytics data? Fear not, my 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 AdWords 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 AdWords. 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.)
Our top 5 posts from 2017
We're an ecommerce analytics company, so it's no surprise that Shopify and Google Analytics top the list of topics in our most-read and most-shared posts of 2017. But what continues to surprise us is how many online businesses know that their analytics setup needs to be fixed, but put off the decision to take action. Luckily tools like our Shopify reporting app are making it easier than ever to get accurate data and automated reporting that really drives revenue. If fixing your tracking and making decisions based on trustworthy data wasn't your main new year's resolution for 2018, it should be! Here are the top 5 posts from our analytics blog in 2017. They should provide some inspiration. 1. Is Google Analytics compliant with GDPR? From May 2018 the new General Data Protection Regulations (GDPR) will come into force in the European Union, causing all marketers and data engineers to re-consider how they store, transmit and manage data – including Google Analytics. This popular post looks at basic and full compliance. The rights enshrined by GDPR relate to any data your company holds which is personally identifiable: that is, can be tied back to a customer who contacts you. 2. Shopify Marketing Events vs Google Analytics The ability for other Shopify apps to plug their campaign cost and attribution data into Shopify (via the new marketing events API) is a logical step to building Shopify’s own analytics capability, but is it really a viable substitute for Google Analytics? Google already has a team of hundreds working on Google Analytics, and it seems unlikely that Shopify will be able to dedicate resources to keep up with the functionality that power users need. 3. Is Google Analytics accurate? 6 common issues and how to resolve them How do you know if your Google Analytics setup is giving you reliable data? In this much-linked blog post we look at common problems and explain what can be done to make your tracking more accurate. If the journey of visitors on your site proceeds via another payment processor or gateway, you could be losing the link between the sale (or goal conversion) and the original marketing campaigns. 4. How to increase revenue with Refersion and affiliate marketing Affiliate marketing consistently outperforms other channels for ecommerce businesses. In this special guest post, our integration partner Refersion shares essential tips about how Littledata customers can get a piece of the action. When customers come through affiliate channels, their average customer revenue is 58% higher than other channels. 5. What you can track with our Shopify app Here at Littledata we believe that everyone should have access to professional-level analytics tools for tracking, reporting, and improving sales and engagement. That’s why we built the ultimate Shopify reporting app. This much-shared post outlines 'Shopify’s Standard Tracking vs Littledata for Shopify'. It's a match we're betting on! Shopify is one of the best ecommerce platforms on the planet, but their standard analytics are extremely limited.
How to set up demographics tracking in Google Analytics (VIDEO)
Could you be missing out on your best customers - those that are more likely to convert, and more likely to make big purchases when they do? Watch this quick video to find out how to to set up demographics tracking in Google Analytics. [embed]https://www.youtube.com/watch?time_continue=5&v=PAeCubNxoKI[/embed] Demographics and interests data provides information about the types of customers that are using your site, along with the interests they express through their online travel and purchasing activities. Once you set up this tracking, you'll be able to see your customer base broken down by age group, gender and interests. This data isn't just nice to have; it helps you market to the biggest potential spenders by discovering who's most interested in your products or services. Analytics and AdWords use the same age, gender, and interests categories, so this is particularly useful for improving your targeting on the Google Display Network. That said, connecting demographics data with shopping activity and revenue is a complicated art. Our popular Buyer Personas feature automates reporting and shows you how to improve that spend. And we don't just stop with paid ads. We include personas for every significant channel, including email marketing, organic search, affiliates/referrals and social media campaigns. Wherever you want to use demographics targeting to increase revenue, we've got you covered.
How to dramatically increase revenue with Refersion and affiliate marketing
Affiliate marketing consistently outperforms other channels for ecommerce businesses. In this special guest post, Refersion's Robert Woo shares essential tips about how Littledata customers can get a piece of the action. Affiliate marketing is a powerful channel to drive sales, but is surprisingly overlooked by many small and medium-sized businesses. In a 2016 report by Heinz Marketing, referrals made the most positive impact on revenue for businesses, by far. As business owners know, the easiest sales come from customer recommendations to their friends and family. Especially for SMBs, word-of-mouth is often the backbone of how they acquire new customers. Now here’s another statistic: when customers come through affiliate channels, their average customer revenue is 58% higher than other channels. In other words, not only is it easier to get more customers via word-of-mouth, if they are referrals, but those customers also spend more. As you can see, getting into affiliate marketing is a double win for your business. But it can seem tricky to get started. The traditional way of doing affiliate marketing Online affiliate, or referral, marketing is as old as the internet. Here’s how it traditionally works: Research various affiliate networks that are accepting new merchants (that’s you). Pay a fee to join one (as high as $5000). Use this network to find affiliate partners to market your product/service. Pay out a commission to these partners. Pay out a monthly fee, and a portion of these commissions (15 to 25%) to the affiliate network. In this traditional way, you can see a clear trade-off for the benefit of joining an existing network. While you’ll have immediate access to many publishers waiting to market your product, there are a lot of fees for this privilege. So much so that for smaller businesses often find it hard to make a good profit from this model. On the other hand, you could start your own program up from scratch. But while you’d save a fortune in fees, the big trade off is your time investment. It takes time to put an affiliate marketing program in place. From creating a portal for your affiliates to use, to finding these influencers in the first place, to getting the hang of the metrics you need to monitor; it can all be a lot, especially for SMBs with a small team devoted to marketing. The better way, for Littledata customers Luckily, we here at Refersion have made it easy and affordable to forego joining an existing affiliate network and start your own. What we do is help businesses take a 'hybrid approach', taking the best of both worlds, making running a program cheap and simple. The best part? We’ve now integrated with Littledata to make data analysis even more insightful, so your business can easily maximize the ROI of your in-house affiliate marketing program. Used together, Littledata and Refersion are a supercharged toolbox for ecommerce entrepreneurs who have always wanted to launch a referral program, but was afraid to commit the time and energy. With Refersion, you can set up your business to start taking advantage of affiliate marketing in less than ten minutes. Connect your online shopping cart, create custom affiliate emails and coupon codes, and quickly find the right publishers to work with in the Refersion Marketplace. And if you’re already a Littledata customer, you’ll know that you can get all your affiliate marketing metrics and analysis in your dashboard and reporting. Don’t leave money on the table With the rise of ad blockers, many types of online marketing have taken big hits. But affiliate marketing isn’t subject to this limitation. Don’t ignore one of the best channels of getting new customers and higher sales! If you want to learn more about Refersion, watch this short intro video on how it all works. Ready to take the plunge? Here’s a special signup page for Littledata customers. Get a 14 day free trial today! Robert Woo is a Marketing Manager at Refersion.
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