5 steps to higher ecommerce search traffic

Search traffic is essential for ecommerce growth, and it takes time to build. In this guest post, SEO expert Bill Widmer highlights 5 easy steps to rise to the top. There are over 1 billion websites on the internet today, with almost 2.4 million websites created every day. Of those sites, only 10 make it to the front page of Google. And the top result gets 30% or more of all the search traffic. Where does that leave you? If you don’t take SEO seriously, there’s no way your ecommerce site will beat the competition. If you want to make tens of thousands of extra sales every year, without spending a dime on marketing, listen up. It’s time to boost your ecommerce search traffic. Step 1: Start a blog and produce high-quality content Don’t think you can get away with slapping together a few paragraphs about your latest collection and calling it a blog article. The content gods are watching! In all seriousness, quality content is crucial to ranking on the first page of Google. It’s one of their top 2 ranking factors to determine what to show (the other is backlinks). But what exactly does quality content entail? Let’s hear it from the horse’s mouth: Google's basic principles for high-quality content Make pages primarily for users, not for search engines. Don't deceive your users. Avoid tricks intended to improve search engine rankings. A good rule of thumb is whether you'd feel comfortable explaining what you've done to a website that competes with you, or to a Google employee. Another useful test is to ask, 'Does this help my users? Would I do this if search engines didn't exist?' Think about what makes your website unique, valuable, or engaging. Make your website stand out from others in your field. In a nutshell, Google wants you to focus on providing value to your readers with every blog article. Producing high-quality, long-form content (at least 1,500 words) is the key to ecommerce content marketing and pleasing the search gods. Pro Tip: Not sure what kind of blog articles to produce? As a general rule of thumb, steer clear from anything that’s too obvious and salesy (eg. 5 Shoes From Our Latest Collection That You’ll Love). Instead of this, try to produce content that’s useful to your customers (eg. How To Maintain Leather Shoes: A Comprehensive Guide). With these less salesy articles, you can still include links and call to actions for readers to shop your products after they’re done reading the article. As an added bonus, these articles can help you rank for keywords which your product and category pages can’t (such as 'how to maintain leather shoes'). Step 2: Fix your on-page SEO On-page SEO refers to elements which you can optimise within your website (off-page SEO, on the other hand, deals with external links and other factors). Image from FlightMedia.co With on-page SEO, the first thing you need to do is select the keywords you want to target. Once you’ve got your keywords in mind, optimize your title, header tags, content, image alt texts, and metadata for each page and post on your website. If this sounds like Greek to you, don’t stress. Here’s a step by step guide which will take you through the entire process. Pro Tip: Only target one keyword per page to increase your chances. However, it’s always a good idea to include LSI keywords! Step 3: Add internal links to your most important pages By adding internal links (links from one page on your site to another page on your site), you’re helping Google to understand the relationship between the different pages and posts on your ecommerce site. The more internal links a specific page or post on your website has, the more 'important' it is deemed by Google. Think of your website as a pyramid, with the most important content - your 'cornerstone' content - at the top. You should be linking from your cornerstone content to other related pages in order to pass on link value to them. At the same time, link to these cornerstone pages from other pages in order to bolster their standing. Want to learn more about internal links? Check out this article. Step 4: Build external links Once your internal links are done, it’s time to move on to building external links. You might need to invest some budget into this, but since Google has confirmed that external links are amongst the top 3 ranking factors, I’d say it’s definitely worth your while. First, look for influencers in your industry and reach out to them to enquire if they’d be willing to link to your website in exchange for a small fee OR for a partnership. You can use platforms such as Mailshake and VoilaNorbert to speed up the communication process. Another way of getting backlinks is to guest-post on other websites. Whilst this typically takes longer to execute, it’s a great way of building your brand and establishing thought leadership whilst getting more backlinks. Step 5: Consider paid traffic Assuming you’ve completed all the above steps (and you reallllly should!), this doesn’t mean you’ll see results overnight. It’ll take some time (a few months, or even a year) for you to experience a boost in your organic traffic. In the meantime, you can consider 'supplementing' with paid traffic. Image from ThinkDigi.org The two most commonly used channels are Facebook Ads and Google Ads - and there are tons of useful resources online that will teach you all the basics (read this guide for Facebook ads or this guide for Adwords). Alternatively, if you don’t want to handle your ads yourself, you can always outsource them to an expert. Once those ads are running, a full-cycle analytics platform like Littledata is essential to help you optimise your ad spend and connect it to revenue. After all, the idea isn't just to get more traffic, but to get the best kind of traffic and sell to your best type of customer - the kind that's more likely to convert. The truth about ecommerce growth A few parting words. A lot of ecommerce store owners think that as they become more established, they’ll automatically have more people visiting their website. The truth is, word of mouth can only get you so far - and if you’re serious about growing your ecommerce store and increasing your profits, you’ll need to boost your search traffic through SEO and the other methods discussed above. And you'll want to optimise that search traffic by paying attention to specific metrics such as bounce rates from mobile Google search. Do you want to see a nice exponential curve in your search traffic analytics, or are you content to have your traffic flatlining? The sooner you get started, the sooner you’ll be able to snag that highly coveted spot in the first page of Google. I’m rooting for you! Bill Widmer is a content marketing and SEO expert who has worked with many well-known brands like Content Marketing Institute, Social Media Examiner, and SEMrush.

2017-10-05

Introducing Report Packs

We're excited to announce that the first automated report packs are live in the app! Each pack contains a curated set of reports proven to help ecommerce businesses scale faster and smarter. Looking for next-gen analytics reporting that doesn't break the bank? We developed report packs to make advanced analytics accessible to every customer - in just the right combination. You can subscribe to an entire pack for one low monthly price. Why we built report packs Call us crazy, but we believe that every ecommerce business should have the tools to automatically transform their Google Analytics data into actionable insights. Otherwise, what's the point of all that tracking? Unlike the reporting features in some other analytics apps, Littledata's reports never sacrifice accuracy for usability, nor the other way around. Put simply: we have no time for fluff. We believe that the most useful analytics can - and must - be both clean and accurate, and we've built the app's reporting functionality around the actual reporting needs of successful ecommerce businesses, based on our experience with enterprise customers, Shopify stores, and some of the biggest charities in the world. Our analysts considered the many setups we’d built for customers on top of the core Littledata app, and the idea for report packs grew out of this work. We found that growth-oriented ecommerce businesses weren't just looking for clutter-free analytics, but the right combinations of reports to guide ad spend, marketing channel priorities, ecommerce site design and customer journeys. As a result, report packs are next-gen reporting with just enough algo-awesomeness to keep the data geeks happy while letting your marketing team focus on actionable insights to increase engagement at every stage of the shopper journey, from first views and clicks to repeat buying behaviour. The first three packs We've launched three report packs to start: a Basics pack, an Ecommerce Performance pack, and a Shopify marketing pack. Basics pack Overview of site performance Sessions and bounce rate by city Sessions by device type Pages where users enter and exit The Basics pack includes four essential reports on site performance and user behaviour. It's a must-have for any ecommerce site with active users, whether you have a ton of conversions or are still growing your shopper base. Ecommerce Performance pack Overview of ecommerce stats Product category performance Number of sessions to make a transaction Number of days until a purchase is made Many Littledata customers use an enhanced ecommerce setup in Google Analytics. With four essential reports on shopping behaviour and store performance, the Ecommerce Performance pack will help you get the most out of that setup and make data-driven decisions for rapid growth. Shopify pack Conversion rate by marketing campaign Conversion rate by marketing channel When users are most likely to buy Shopping behaviour by channel The Shopify pack includes four reports that connect marketing channels with shopping behaviour. Built to give our Shopify app users a pro reporting experience, the pack contains essential analytics for growing a Shopify store through intelligent targeting. Anticipated addition to our reporting feature set Report packs offer high value at a lower price point by automating data collection and presentation based on proven ways to use and interpret Google Analytics data. Even though they're newly launched, they've already become a much-used feature alongside our popular custom reports, which agencies and large ecommerce stores use to dig deeper into marketing channels and user behaviour specific to their site design and business models. We recommend starting with one report pack and then adding more packs and custom reports to fit your needs. Subscribe to a report pack today to lock in an early-bird discount and start making better-informed marketing and product decisions. New to Littledata? Sign up for a free analytics account. PS. Our developers are hard at work on a number of new report packs, including packs for enhanced ecommerce, ReCharge subscription businesses, email marketing, Facebook ad performance, and more. Subscribe to this blog for the latest updates.

by Ari
2017-09-20

The end of the ecommerce 'thank you' page

For two decades the ecommerce customer journey has stayed roughly the same. Customers browse, add to cart, checkout, and then see a page confirming their purchase: the 'thank you' page. That last step is changing, and this is no small change as it threatens to break how many sites measure purchases. Ecommerce stores that stop using a final 'thank you' page without adjusting their analytics setup accordingly are in danger of getting inaccurate purchase data, or even losing track of shoppers altogether. In order to help our customers get ahead of the curve, we've gone through a number of test cases to find short and long term fixes to this issue. But first, a little history. In the old days... In the early days of ecommerce the biggest barrier during checkout was trust. Retailers paid to be certified as ‘hack-proof’ and customers wanted to make quite sure when and how their money was taken. Fast forward twenty years to today, and in the developed world most consumers have transacted online hundreds of times. They are familiar with the process, expect a seamless user experience, and confident that when they click 'buy' their payment will be taken and the products delivered. Online shoppers are so confident, in fact, that an increasing number we observe don’t even bother waiting for that ‘thank you for your order’ page. That page is becoming redundant for three reasons: Almost every checkout process captures an email address to send an order receipt to, and the email acts as a better type of confirmation: one that can be searched and referenced. Seriously, when was the last time you opted to ‘print the confirmation page’ for your records? Many retailers are forced to compete with the superb customer support offered by Amazon. This includes refunds for products that were ordered in error, and quick handling of failed payments. So from a customer's perspective there’s little point in waiting for the confirmation page when any issues will be flagged up later. Which leads to the third reason: as retailers improve the speed of checkout, the payment confirmation step is often the slowest, and so the one where customers are most likely to drop out on a slow mobile connection. This is no small issue, as mobile revenues are expected to overtake desktop revenues for ecommerce businesses globally this year. What does this mean for ecommerce sites? The issue is that for many sites the linking of sales to marketing campaigns is measured by views of that ‘thank you' page. In the marketing analysis, a ‘purchase’ is really a view of that 'thank you' page - or an event recorded on the customer’s browser with the sale. If customers don’t view the page, then no sale is recorded. If you have ever been frustrated by the lack of consistency between Google Analytics and your own payment/back-end records, this is the most likely issue. A dependency on viewing the 'thank you' page brings other problems too: a buggy script, perhaps from another marketing tag, will block the recording of sales. This is another source of the type of analytics inaccuracy which the Littledata app combats automatically. How to adjust your ecommerce tracking The short-term fix is to tweak the firing order of marketing tags on the 'thank you' page, so that even customers who see the page for fractions of a second will be recorded. Sites with a large number of marketing tags will have the greatest room for improvement. But in the long term, as this trend continues, the analytics solution is to link the marketing campaigns to the actual payments taken. This removes the need for the customer to see any type of 'thank you' or confirmation page, and also removes discrepancies between what your marketing platform tells you was purchased and what actually got bought. This is known as server-side tracking. The good news for those of you on the Shopify platform is that our Shopify reporting app does this already - and solves a lot of other analytics problems in one install. For those on other stores, please do contact us for advice. The Littledata team has worked with ecommerce businesses to set up integrations with Magento, DemandWare and numerous custom platforms. Not only can we help fix your analytics setup for accurate tracking, but our app then automates the audit and reporting process for all of your sites going forward.

2017-08-30

Introducing Buyer Personas

This week we're excited to introduce Buyer Personas, a game-changing new feature for marketers and ecommerce teams that are serious about hacking growth at a major scale. Do you know which types of customers are most likely to convert? Gathering customer data is one thing, but turning it into actionable insights is another. We've found that Littledata users are often struggling to find the exact differences between web visitors that buy and those that don't buy, especially when it comes to particular marketing channels. Littledata's new Buyer Personas feature automatically generates user personas based on your particular Google Analytics ecommerce setup or conversion goals, making it easier than ever to target your marketing and on-site content at those shoppers most likely to engage, convert, and grow with your online business in the long term. For example, if you know that users who arrive on your site on the weekend, in the afternoon are more likely to buy, then you should allocate more of your budget to those times. Or if users on tablets are most likely to convert, then target campaigns and ad formats most relevant for that screen size. Accurate Data If you have a decent Google Analytics setup it is possible to look at how different attributes of the user (age, browsing device, time of visit, etc.) affect their likelihood of converting. The better the data setup for your 'people analytics', the more detailed the report can be – when's the last time you audited your website's Google Analytics setup? Buyers or Users? We’re calling the new feature Buyer Personas since this is often requested by retail customers, but it is equally relevant if you have another conversion goal (eg. registrations, event bookings). In all of these cases, your customers are essentially 'buying in' to your product or service. You can switch the conversion metric at the bottom of the Buyer Personas page in the app. Marketing Channels Buyer personas give you actionable insights on particular channels, such as paid search, while also improving your overall understanding of your ideal customer base. The feedback is split out by channel so you can action it more easily: how you would re-organise your paid search marketing is very different to how you re-target your email marketing, but both are needed. The reality is that most smaller websites won’t have any of the ideal people of their site. We are not saying that only that exact profile will convert but that, by targeting the marketing on those who convert most easily, you can improve your return on investment. Pick the category with the biggest potential audience first. The first iteration of the new feature is live in the app this week. We look forward to hearing your feedback! Note that to generate Buyer Personas, you will need an active conversion goal or ecommerce tracking setup, and a minimum of 50 conversions in the previous month. Don't have a Littledata account yet? Sign up today to fix your Google Analytics setup for free and start generating buyer personas.

2017-07-04

Shopify Marketing Events vs Google Analytics

At the Shopify Unite conference today I heard plenty of great ideas such as ShopifyPay but the most interesting for me as a data specialist was the marketing events API. Since we launched our Fix Google Analytics Shopify app earlier this year we’ve known that reporting was a weak spot in Shopify’s platform offering, and they admit that ‘understanding marketing campaign performance’ is one of the biggest challenges of Shopify merchants right now. The ability for other Shopify apps to plug their campaign cost and attribution data into Shopify (via the marketing events API) is a logical step to building Shopify’s own analytics capability, but I don’t believe it will be a substitute for Google Analytics (GA) anytime soon. Here’s why: 1. Google Analytics is the industry standard Every online marketer has used Google Analytics, and many have favourite reports they’ve learned to interpret. Moving them to use a whole new analysis platform will take time– and it’s taken GA 10 years to achieve that dominance. 2. GA provides platform-agnostic data collection For a store using Shopify as their only source of insights, moving away from Shopify would mean losing all the historic marketing performance data – so it would be very hard to make like-for-like comparisons between the old platform and the new. Many of our customers have used GA during and after a platform shift to get continuous historical data. Which ties into my first point that over 85% of businesses have a history of data in GA. 3. Incomplete marketing tagging will still cause issues Making valid analysis on multi-channel marketing performance relies on having ALL the campaigns captured - which is why our GA audit tool checks for completeness of campaign tagging. Shopify’s tracking relies on the same ‘utm_campaign’ parameters as GA, and campaigns that are not properly tagged at the time cannot be altered retrospectively. 4. Google is rapidly developing Google Analytics I’d like to see the Shopify marketing event collection evolve from its launch yesterday, but 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. 5. More integrations are needed for full campaign coverage Shopify’s marketing analysis will only be available for apps that upgrade to using the new API.  Marketing Events has launched with integrations for Mailchimp and Facebook (via Kit) but it won’t cover many of the major channels (other emails, AdWords, DoubleClick for Publishers) that stores use. Those integrations will get built in time, but until then any attribution will be skewed. 6. GA has many third-party integrations Our experience is that any store interested in their campaign attribution quickly wants more custom analysis or cuts of the data. Being able to export the data into Littledata’s custom reports (or Google Sheets or Excel) is a popular feature – and right now Shopify lacks a reporting API to provide the same customisations. You can only pull raw event data back out. That said, there are flaws with how GA attribution works. Importing campaign cost data is difficult and time consuming in GA – apart from the seamless integration with AdWords – and as a result hardly any of the stores we monitor do so. If Shopify can encourage those costs to be imported along with the campaign dates, then the return on investment calculations will be much easier for merchants. I also think Shopify has taken the right pragmatic approach to attribution windows. It counts a campaign as ‘assisting’ the sale if it happens within 30 days of the campaign, and also whether it was ‘last click’ or ‘first click’. I’ve never seen a good reason to get more complicated than that with multi-channel reports in GA, and it’s unlikely that many customers remember a campaign longer than 30 days ago. In conclusion, we love that Shopify is starting to take marketing attribution seriously, and we look forward to helping improve the marketing events feature from its launch yesterday, but we recommend anyone with a serious interest in their marketing performance sticks to Google Analytics in the meantime (and use our Shopify app to do so).

2017-04-21

How to track recurring billing & subscriptions

Recurring billing & subscriptions have proved to be, at least in the last few years, the most viable model of business. The return on investment, value per customer and frequency of buying are all higher for any business that adopted a recurring subscription model. This article is focused on Shopify stores that use apps like ReCharge solution and Fix Google Analytics - Littledata app. Nonetheless, everything in here can be applied to all recurring payments business models. Recharge is the most used Shopify recurring billing solution powering thousands of stores and processing tens of thousands of orders daily. Fix Google Analytics - Littledata app completes ReCharge app by providing accurate sales attribution through Google Analytics. If you don't know what the Fix Google Analytics - Littledata app does, here is a short description: We fix your data collection, offer marketing insights and suggest improvements all in one app. Say goodbye to inaccurate data and start getting the full Enhanced Ecommerce experience. Install this app to get: Proper marketing attribution in Google Analytics Product views and shopping behavior Checkout conversion funnels (including voucher usage) Understanding of repeat buyers The first steps to install the Google Analytics tracking for Shopify are illustrated here: How to install the “Fix Google Analytics” Shopify app. Besides this, if you want to go ahead and make an advanced analysis of your customers then you need to make the following setup also: Enable the feature in Google Analytics Firstly, go into Google Analytics (both your normal Google Analytics property and the property that has been created by Littledata) and enable the User-ID feature by going to Admin > Property > Tracking info > User-ID. Click On, next, On, next, give the new view a name and you're done. Attention: The new view will start to collect data from the point of creation so you will need to wait a bit to use this report. The sources of the purchases will be collected from the point of creation so most of the orders will be shown in the first month from direct / (none). Enable the Enhanced Ecommerce feature in Google Analytics Go in Google Analytics, Click Admin. In the right side under view choose the new Registered Users view, that you've created earlier and click Ecommerce Setings. Toggle to ON and then click Next step. Toggle ON for Enhanced Ecommerce, save and you're done. How to see what was the initial source for recurring subscriptions? Using the registered view go under ACQUISITION -> All traffic -> Source/Medium or Channels. This report will show both new customers and recurring ones. We need to apply a segment to this report in order to show only the recurring users. This is how you set up the segment to exclude first time buyers: Now, with the above segment applied, you can check what was the original source or the sale for all transactions from repeating buyers. The other cool and helpful report is the AUDIENCE->Cohort Analysis report. You can see what was the retention of these users in this report for each day, week or month. This report must be read from left to right for the bellow image: Users that bought in December continued to buy in January in a proportion of 38% and in February in a proportion of only 10%. Combining this report with an advanced segment that excludes the first-time buyers AND includes only buyers that had their first transaction in December will provide the number of users that started the subscription package in December and what was the retention of these people. We would love to hear how you use these reports and what you think of the new version of our Fix Google Analytics - Littledata app.

2017-03-22

6 reasons Facebook ads don’t match the data you see in Google Analytics

If you run Facebook Ads and want to see how they perform in Google Analytics, you may have noticed some big discrepancies between the data available in Facebook Ad Manager and GA. Both systems use different ways to track clicks and visitors, so let’s unpick where the differences are. There are two kinds of metrics you’ll be interested in: ‘website clicks’ = the number of Facebook users who clicked on an advert on your own site, and (if you do ecommerce) the transaction value which was attributed to that advert. Website Clicks vs Sessions from Facebook 1. GA isn’t picking up Facebook as the referrer If users click on a link in Facebook’s mobile app and your website opens in an in-app browser, the browser may not log that ‘facebook.com’ was the referrer. You can override this (and any other link) by setting the medium, source, campaign and content attributes in the link directly. e.g. www.mysite.com?utm_medium=social&utm_source=facebook.com&utm_campaign=ad Pro Tip: you can use GA’s URL builder to set the UTM tags on every Facebook campaign link for GA. In GA, under the Admin tag and then ‘Property settings’ you should also tick the box saying ‘Allow manual tagging (UTM values) to override auto-tagging (GCLID values)’ to make this work more reliably. 2. The user leaves the page before the GA tag fires There’s a time delay between a user clicking on the advert in Facebook and being directed to your site. On a mobile, this delay may be several seconds long, and during the delay, the user will think about going back to safety (Facebook’s app) or just closing the app entirely. This will happen more often if the visitor is not familiar with your brand, and also when the page contents are slow to load. By Facebook’s estimation the GA tracking won’t fire anywhere between 10% and 80% of clicks on a mobile, but fewer than 5% of clicks on a desktop. It depends on what stage in the page load the GA pixel is requested. If you use a tag manager, you can control this firing order – so try firing the tag as a top priority and when the tag container is first loaded. Pro Tip: you can also use Google's mobile site speed suggestions to improve mobile load speed, and reduce this post-click drop-off. 3. A Javascript bug is preventing GA receiving data from in-app browsers It’s possible your page has a specific problem that prevents the GA tag firing only for mobile Safari (or Android equivalent). You’ll need to get your developers to test out the landing pages specifically from Facebook’s app. Luckily Facebook Ad Manager has a good way to preview the adverts on your mobile. Facebook Revenue vs GA Ecommerce revenue 4. Attribution: post-click vs last non-direct click Currently, Facebook has two types of attribution: post-view and post-click. This means any sale the user makes after viewing the advert or clicking on the advert, within the attribution window (typically 28 days after clicking and 1 day after viewing), is attributed to that advert. GA, by contrast, can use a variety of attribution models, the default being last non-direct click. This means that if the user clicks on an advert and on the same device buys something within the attribution window (typically 30 days), it will be attributed to Facebook.  GA doesn't know about views of the advert. If another campaign brings the same user to your site between the Facebook ad engagement and the purchase, this other campaign takes the credit as the ‘last non-direct click’. So to match as closely as possible we recommend setting the attribution window to be '28 days after clicking the ad' and no 'after view' attribution in Facebook (see screenshot above) and then creating a custom attribution model in GA, with the lookback window at 28 days, and the attribution 'linear' The differences typically come when: a user engages with more than one Facebook campaign (e.g. a brand campaign and a re-targeting one) where the revenue will only be counted against the last campaign (with a priority for ads clicked vs viewed) a user clicks on a Facebook ad, but then clicks on another advert (maybe Adwords) before buying. Facebook doesn’t know about this 2nd advert, so will attribute all the revenue to the Facebook ad. GA knows better, and will attribute all (or part) of it to Adwords. 5. Facebook cross-device tracking The main advantage Facebook has over GA is that users log in to its platform across all of their devices, so it can stitch together the view of a mobile advert on day 1 with a purchase made from the user’s desktop computer on day 2. Here’s a fuller explanation. By contrast, unless that user logs into your website on both devices, and you have cross-device tracking setup, GA won’t attribute the sale to Facebook. 6. Date of click vs date of purchase In Facebook, revenue is attributed to the date the user saw the advert; in GA it is to the date of purchase. So if a user clicks on the advert on 1st September, and then buys on the 3rd September, this will appear on the 1st on Facebook – and on the 3rd in GA. 7. The sampling problem Finally, did you check if the GA report is sampled? In the top right of the screen, in the grey bar, you'll see that the report is based on a sample.  If that sample is less than 100% it means the numbers you see are estimates.  The smaller the sample size used, the larger the possibility of error.  So in this example, a 45% sample of 270,000 sessions could skew our results plus or minus 0.2% in the best case. As a rule of thumb, Google applies sampling when looking over more than 500,000 sessions (even if you select the 'greater precision' option from the drop-down menu). You can check your own sample using this confidence interval calculator. Conclusion Altogether, there’s a formidable list of reasons why the data will never be an exact match, but I hope it gives you a way to optimise the tracking. Please let us know if you’ve seen other tracking issues aside from these.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2017-02-08

Top 5 Google Analytics metrics Shopify stores can use to improve conversion

Stop using vanity metrics to measure your website's performance! The pros are using 5 detailed metrics in the customer conversion journey to measure and improve. Pageviews or time-on-site are bad ways to measure visitor engagement. Your visitors could view a lot of pages, yet be unable to find the right product, or seem to spend a long time on site, but be confused about the shipping rates. Here are the 5 better metrics, and how they help you improve your Shopify store: 1. Product list click-through rate Of the products viewed in a list or category page, how many click through to see the product details? Products need good images, naming and pricing to even get considered by your visitors. If a product has a low click-through rate, relative to other products in the list, then you know either the image, title or price is wrong. Like-wise, products with very high list click-through, but low purchases, may be hidden gems that you could promote on your homepage and recommended lists to increase revenue. If traffic from a particular campaign or keyword has a low click-through rate overall, then the marketing message may be a bad match with the products offered – similar to having a high bounce rate. 2. Add-to-cart rate Of the product details viewed, how many products were added to the cart? If visitors to your store normally land straight on the product details page, or you have a low number of SKUs, then the add-to-cart rate is more useful. A low add-to-cart rate could be caused by uncompetitive pricing, a weak product description, or issues with the detailed features of the product. Obviously, it will also drop if you have limited variants (sizes or colours) in stock. Again, it’s worth looking at whether particular marketing campaigns have lower add-to-cart rates, as it means that particular audience just isn’t interested in your product. 3. Cart to Checkout rate Number of checkout processes started, divided by the number of sessions where a product is added to cart A low rate may indicate that customers are shopping around for products – they add to cart, but then go to check a similar product on another site. It could also mean customers are unclear about shipping or return options before they decide to pay. Is the rate especially low for customers from a particular country, or products with unusual shipping costs? 4. Checkout conversion rate Number of visitors paying for their cart, divided by those that start the process Shopify provides a standard checkout process, optimised for ease of transaction, but the conversion rate can still vary between sites, depending on payment options and desire. Put simply: if your product is a must-have, customers will jump through any hoops to complete the checkout. Yet for impulse purchases, or luxury items, any tiny flaws in the checkout experience will reduce conversion. Is the checkout conversion worse for particular geographies? It could be that shipping or payment options are worrying users. Does using an order coupon or voucher at checkout increase the conversion rate? With Littledata’s app you can split out the checkout steps to decide if the issue is shipping or payment. 5. Refund rate Percent of transactions refunded Refunds are a growing issue for all ecommerce but especially fashion retail. You legally have to honour refunds, but are you taking them into account in your marketing analysis? If your refund rate is high, and you base your return on advertising spend on gross sales (before refunds), then you risk burning cash on promoting to customers who just return the product. The refund rate is also essential for merchandising: aside from quality issues, was an often-refunded product badly described or promoted on the site, leading to false expectations? Conclusion If you’re not finding it easy to get a clear picture of these 5 steps, we're in the process of developing Littledata’s new Shopify app. You can join the list to be the first to get a free trial! We ensure all of the above metrics are accurate in Google Analytics, and the outliers can then be analysed in our Pro reports. You can also benchmark your store performance against stores in similar sectors, to decide if there are tweaks to the store template or promotions you need to make. Have more questions? Comment below or get in touch with our lovely team of Google Analytics experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-30

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