Are you looking at the wrong Black Friday metrics?

Paying attention to the right ecommerce metrics can help you establish the best customer base and shopping experience for long-term growth. But many retailers still focus only on the most popular metrics -- especially during the online shopping craze of Black Friday and Cyber Monday (#BFCM). Over the next few weeks ecommerce managers will be obsessing over data, but which stats are the most important? Two popular metrics -- ecommerce conversion rate and average time on site -- may be misleading, so I recommend looking instead at longer-term benchmarks. Here's how it all breaks down. Littledata's ecommerce benchmark data now contains indicators from over 12,000 sites, making it an ideal place to get a realistic view of Black Friday stats. Last year we found that the impact on Black Friday and Cyber Monday was larger in 2017 than in 2016. Using that same data set of 440 high-traffic sites, I dove into the numbers to see how this affected other metrics. Metrics to avoid I think that overall ecommerce conversion rate is a bad metric to track. From the leading ecommerce websites we surveyed, the median increase was 30% during the BFCM event last year...but nearly a third of the stores saw their conversion rate dip as the extra traffic didn’t purchase, with this group seeing a median 26% drop. Some stores do extremely well with deals: four sites from our survey had more than a 15-fold increase in ecommerce conversion rate during BFCM, and nearly a quarter saw more than double the conversion rate over the period. But the real question is: will tracking conversion rate hour-by-hour help you improve it? What could you possibly change within in day? Another misleading metric is average time on site. You may be looking for signs that the the extra traffic on the holiday weekend is engaging, but this is not the one to watch. The time on site for visitors who only see one page will be zero, which will mask any real increase from engaged visitors. Where to focus instead Now, do you know what good performance on funnel conversion metrics would look like for your sector? If not, have a look at Littledata’s industry benchmarks which now cover over 500 global sectors. Littledata’s benchmarks also include historic charts to show you how metrics such as add-to-cart rate vary for the average retailer in your sector month by month. Next try the ‘speed’ performance page to see how fast a user would expect a site in your sector to be. If you see site speed (as measured in Google Analytics) drop below average during Black Friday trading it’s time to pick up the phone to your web host or web operations team. Then, are you tracking return on adverting spend for extra Facebook Ads you're running during the quarter? Ad costs will spike during the peak trading period, and you make not be getting the same volume of traffic conversion into sales. Here are some quick pointers. Facebook Ads. Littledata’s Facebook Ads connection will ensure accurate data, with a dedicated Facebook report pack for automated insights. Shopify. If you're running your site on the Shopify platform, read up on which metrics are most important for Shopify stores and check out Shopify's BFCM Toolbox for seasonal online marketing. Missions. Use Missions in the Littledata app to make permanent improvements to your user experience. BFCM may be over before you can make the changes, but customers will keep buying the rest of the year. For example, can you increase add-to-cart rate with tips such as highlighting faster selling items or recommending an alternative to out-of-stock products? So focus on some clearer metrics and I hope Black Friday brings you every success! [subscribe]

2018-11-19

How to increase Average Order Value (AOV) on your ecommerce site

Average order value (AOV) is a bona fide north star metric for Shopify stores, and ecommerce companies more broadly. Increasing AOV is a priority goal for ecommerce teams as it directly boosts revenue (and profits, if you’re doing things right). Growing revenue often requires retailers to acquire more traffic, but with AOV you can increase sales simply by convincing shoppers to spend that little bit more. AOV can be improved by adopting a number of proven optimisation techniques. Many of these have their roots in offline retail, where price, promotion, placement and merchandising all play a part in persuading customers to buy additional - or more expensive - items. We’ll get onto these tactics soon enough, but for now let’s start at the beginning. What is average order value? AOV is the average amount spent by customers when they place an order. To calculate AOV you divide total sales by the total number of orders (typically over a certain period of time). You can monitor AOV via Google Analytics. If you’re using Littledata then you’ll see it on your dashboard and in ecommerce report packs. Why is average order value important? AOV is one of the primary KPIs in ecommerce. It is a measure of sales trends and reflects customer behaviour and buying preferences. This insight can be used to optimise your website, pricing strategy, and guide decisions on what you choose to sell. It is also a good indicator of your ability to optimise ROI, as your marketing budget will go that much further if you increase AOV. It is worth investing time and money into moving the AOV needle, as it will create universal uplift. Implement the right kind of tactics - and technology - and we are sure that you will see some positive results, especially if this is an activity you haven’t yet spent too much time on. The results? New and existing customers are likely to spend more with you whenever they buy. Better sales numbers, bigger profits, and various additional benefits. Just like the other ecommerce KPIs, it is best not to view AOV in isolation. Related metrics include customer lifetime value (CLV) and customer acquisition cost (CAC), particularly for ecommerce subscription businesses. How do I know if my average order value is in good shape? Littledata has robust benchmarking data from a sample of 12,000 ecommerce sites. You can drill down by category and revenue to see how you compare vs your peers. For example, we analysed AOV across 379 medium-sized ecommerce sites in September and found that $123 is the typical amount spent. But average is relative - it very much depends on the sector. Start a free Littledata trial to see your AOV alongside the benchmark for your sector (we will show you some other juicy metrics and benchmarks too). It will look like this: Pretty cool, huh? If you happen to be underperforming in any area then our app will suggest some proven optimisation ideas to help you improve your store. Other stores have used our ecommerce benchmarks to grow sales, and we're confident that you will experience similar results. What affects average order value? Lots of things influence how much people spend when they buy from your site. Consider the last time you bought a higher priced item, such as a TV, laptop or mobile phone. More often than not there are upsells and cross-sells as you progress down the purchase path. You end up buying related items (mobile phone cases), upgrading your initial choice (256MB memory vs 64MB), purchasing add-ons (extended warranty), or clicking on a compelling product bundle (phone + case + warranty = 15% off). This kind of buying behaviour helps ecommerce teams to sleep soundly at night. It is to be encouraged. A real world example Apple is an absolute master of maximising AOV. Let’s take a quick walkthrough of one of its purchase pathways. First, we’ll select a Macbook Pro and will then see the following page, which invites us to customise our order. Add a little more memory and one item of software, and the order value increases by about 30%. Boom. Now let’s click the ‘Add to Bag’ button. We’ll progress to an ‘Essentials’ page. Yet more ideas to help us spend extra money. Think we’re all done? Not so fast. Click on ‘Review Bag’ and you’ll enter the checkout. Note the ‘Related Products’ that appear underneath the basket summary. Is it any wonder that Apple is valued at more than one trillion dollars? How can I increase my average order value? The million dollar question (or maybe a few billions, in the case of Apple). The researchers for our newest product feature - called Missions - have discovered plenty of ideas for you to try out. Littledata Missions provide step-by-step guides to help ecommerce teams optimise performance, and AOV was one of the very first metrics we wanted to explore. The following ideas are taken from our Average Order Value Fundamentals mission. There are a bunch of others in there to try too. Missions automatically generate based on your ecommerce benchmark data in the Littledata app (try Missions for free today). I’ll wager that at least one of the following will help you to grow AOV. And a super combo might seriously move the dial. Once you’ve optimised AOV - and there might be a ceiling - you can work on increasing purchase frequency, customer referrals, and then scale up your customer acquisition efforts. So then, here are 12 ideas to help you start to grow average order value... 1. Provide free shipping for orders above a certain amount Betterware grew AOV by 20% after introducing free shipping for orders above £30. M&S also provides free standard delivery for orders that exceed £30, as seen in the screenshot. A study by UPS found that 58% of consumers would add extra items to their cart in order to qualify for free delivery. As such this is a great way of increasing average order value. Free delivery is an expectation these days, so if you're late to the party - and concerned about margins - then a minimum threshold is worth testing. 2. Offer minimum spend discounts Much like introducing a free shipping threshold, you can provide a discount if the customer spends a certain amount on your site. Although it might seem to go against the goal of increasing average order value, setting offers such as this can tempt visitors into spending whatever is necessary to achieve the discount, because it appears like a deal. There are a number of ecommerce plugins to help with this. A lot of happy Shopify stores use the Product Discount app. 3. Make the most of up-selling Up-selling is the art of convincing prospective customers to increase their spend, typically by buying a more expensive item to the thing they're looking at. For example, in the screenshot below we can see how Amazon shows higher priced TVs to the one initially selected. By listing out the features side by side it may be enough to convince the prospective buyer that the next model up is a more attractive option. This is a sure-fire way to increase average order value, though it's not without its risks as you'll need to change the shopper's mind about something ("You don't really want that, you want this."). So be careful when experimenting with up-selling techniques. 4. Embrace cross-selling Amazon has attributed around 35% of its revenue to cross-selling. Not exactly small change. As such it is crucial to find a cross-selling strategy that works for your website. Cross-selling is the science of persuading customers to buy additional products related to the thing they’re about to purchase. For example, buy a camera and you might see recommendations for camera cases, bigger memory cards, battery chargers, etc. Adding items to the basket in this way is highly likely to increase average order value. However, it is important to specify which customers receive cross-sell offers. You should certainly think twice before cross-sells to customers who regularly return items. 5. Allow customers to use live chat A Forrester study found that there is a 10% increase in order value from customers who used the live chat function. The study also discovered that live chat helps to increase revenue by 48% per chat hour, and increased conversion rate by 40%. The business case for live chat would appear to be strong. Why is this? Mainly because customers like the immediacy - and familiarity - of chat. It has been reported that 73% of consumers who have used live chat were pleased with the experience. So, live chat is good for AOV, sales, conversion rates and customer satisfaction. What's not to like? [subscribe] 6. Show how others have enjoyed the product Average order value is 6% higher among shoppers who read reviews, compared with those who don't bother, according to a Bazaarvoice study. Positive social proof is incredibly powerful. It goes a long way towards encouraging people to progress to the checkout. Social proof comes in many forms, from reviews and ratings to testimonials and buyer videos. Make it highly visible at key points in the buyer journey, to build trust and reinforce the decision to buy. 7. Offer financing for high-ticket items Analysis by Divido has shown that sales can increase by 40% when high-ticket items are offered in monthly instalments. Your most expensive items are the ones which can be heavily responsible for driving up your average order value. If you offer customers the option to pay in instalments it can help you sell more of these higher valued products. For example, Goldsmiths offers shoppers 0% interest-free credit on purchases which total more than £750. This may appeal to people looking at items in the £500+ range - they might end up being tempted to spend more once they see the financing available. 8. Offer volume-based discounts Office supplies company Paperstone generated a 19% average order increase when a bulk discount deal was offered. As well as helping to grow AOV, strategic discounting can be great for clearing out excess inventory. However, remember that it is important to calculate bulk discounts very carefully. You need to offer deals that attract customers, but which do not hurt your profit margins. 9. Use dynamic retargeting to increase average order value Stella & Dot increased AOV by 17% after experimenting with dynamic retargeting, which allows ecommerce firms to show shoppers the right kind of ads during the shopping journey (such as product recommendation ads, based on their browsing behaviour or purchase history). This technology also recaptures lost sales from visitors who leave websites, by showing them personalised offers to re-engage them. 10. Send personalised emails OneSpot found that average order value increased by 5% upon the personalisation of emails. Simply put, customers are more likely to feel valued by your site if you provide them with messages that are relevant to their specific interests. Personalisation often starts at the customer's name ('Dear sir' won't cut it), but extends to the content of the email. If this is based on prior browsing and purchase history then you're more likely to engage the shopper, to reinforce - or complete - the purchase. 11. Offer a gift card or loyalty scheme By offering customers rewards for shopping with you, you’re likely to see an increase in orders, as well as an increase in the size of those orders. It has been shown that offering rewards for purchases 15-20% above average order size can increase the amount people are willing to spend. Encouraging big spenders to buy more frequently will also have the effect of increasing AOV. A study by BigDoor found that loyal customers make up 70% of total sales in some cases, so it is important to give something back to those customers once in a while. 12. Create product packages A case study into BaubleBar, a jewellery site, showed that average order value increased significantly when product bundling was offered. One pair of its earrings costs $30, but a bundle of three is just $48. This bundle screams “deal” to a customer. BaubleBar saw its average order increase by $22 in a matter of days. Bundling reduces cognitive load. If you can help shoppers avoid thinking too much then you're onto a good thing. Bundles can be viewed by visitors as a valuable deal, especially if they contain products which supplement the one they are already interested in. Packaging up items this way can be incredibly persuasive, particularly when you're offering a discounted price. They can also save the shopper time - no need to browse for add ons. Start the AOV mission today In summary, trying to increase average order value is worth the effort, and will be a gift that keeps on giving once you move the dial in the right direction. You can launch the Average Order Value mission directly from your Littledata dashboard. Our app will track your progress as you test ideas to discover what works best for your site. People trust Littledata to audit, fix and automate reporting. They use our benchmarks to check and compare their performance, relative to their peers. And now, with Missions, digital teams can actively set about increasing ecommerce revenue.

2018-10-25

Categorising websites by industry sector: how we solved a technical challenge

When Littledata first started working with benchmark data we found the biggest barrier to accuracy was self-reporting on industry sectors. Here’s how we built a better feature to categorise customer websites. Google Analytics has offered benchmarks for many years, but with limited usefulness since the industry sector field for the website is often inaccurate. The problem is that GA is typically set up by a developer or agency without knowledge or care about the company’s line of business - or understanding of what that industry sector is used for. To fix this problem Littledata needed a way to categorise websites which didn’t rely on our users selecting from a drop-down list. Google Analytics has offered benchmarks for many years, but with limited usefulness since the industry sector field for the website is often inaccurate. [subscribe] The first iteration: IBM Watson NLP and a basic taxonomy Our first iteration of this feature used a pre-trained model as part of IBM Watson’s set of natural language APIs. It was simple: we sent the URL, and back came a category according to the Internet Advertising Bureau taxonomy. After running this across thousands of websites we quickly realised the limitations: It failed with non-English websites It failed when website homepage was heavy with images rather than text It failed when the website was rendered via Javascript Since our customer base is growing most strongly outside the UK, with graphical product lists on their homepage, and using the latest Javascript frameworks (such as React), the failure rate was above 50% and rising. So we prioritised a second iteration. The second iteration: Extraction, translation and public APIs The success criteria was that the second iteration could categorise 8 sites which the first iteration failed with, and should go on to be 80% accurate. We also wanted to use mainly public APIs, to avoid maintaining code libraries, so we broke the detection process into 3 steps: Extracting meaningful text from the website Translating that text into English Categorising the English text to an IAB category and subcategory The Watson API seemed to perform well when given sufficient formatted text, at minimal cost per use, so we kept this for step 3. For step 2, the obvious choice was Google Translate API. The magic of this API is that it can detect the language of origin (with a minimum of ~4 words) and then provide the English translation. That left us focussing the development time on step 1 - extracting meaningful text. Initially we looked for a public API, and found the Aylien article extraction API. However, after testing it out on our sample sites, it suffered from the same flaws as the IBM Watson processing: unable to handle highly graphical sites, or those with Javascript rendering. To give us more control of the text extraction, we then opted to use a PhantomJS browser on our server. Phantom provides a standard function to extract the HTML and text from the rendered page, but at the expense of being somewhat memory intensive. Putting the first few thousand characters of the website text into translation and then categorisation produced better results, but still suffered from false positives - for example if the text contained legal-ease about data privacy it got categorised as technical or legal. We then looked at categorising the page title and meta description, which any SEO-savvy site would stuff with industry language. The problem here is that the text can be short, and mainly filled with brand names. After struggling for a day we hit upon the magic formula: categorising both the page title and the page body text, and looking for consistent categorisation across the two. By using two text sources from the same page we more than doubled the accuracy, and it worked for all but one of our ‘difficult’ websites. This hold-out site - joone.fr - has almost no mention of its main product (diapers, or nappies), which makes it uniquely hard to categorise. So to put it all the new steps together, here’s how it works for our long-term enterprise client MADE.com's French-language site. Step 1: Render the page in PhantomJS and extract the page title and description Step 2: Extract the page body text, remove any cookie policy and format Step 3: Translate both text strings in Google Translate Step 4: Compare the categorisations of the title vs page body text Step 5: If the two sources match, store the category I’m pleased that a few weeks after launching the new website classifier we have found it to be 95% accurate. Benchmarking is a core part of our feature set, informing everything that we do here at Littledata. From Shopify store benchmarks to general web performance data, the improved accuracy and deeper industry sector data is helping our customers get actionable insights to improve their ecommerce performance. If you’re interested in using our categorisation API, please contact us for a pilot. And note that Littledata is also recruiting developers, so if you like solving these kind of challenges, think about coming to join us!

2018-10-16

Ecommerce trends at Paris Retail Week

Physical or digital? We found merchants doubling down on both at Paris Retail Week. At the big event in Paris last month, we found retailers intent on merging the online and offline shopping experience in exciting new ways. See who we met and what the future of digital might hold for global ecommerce. Representatives from our European team had a great time at the big ecommerce event, one of the 'sectors' at Paris Retail Week. Outside of the event, it was great to have a chance to catch up with Maukau, our newest Shopify agency partner in France. (Bonjour!) Among the huge amount of digital sales and marketing trends we observed throughout the week, a few emerged again and again: mobile-first, phygital experience, and always-on, multi-channel marketing. Getting phygital Phygital? Is that a typo? Hardly. It’s the latest trend in ecommerce, and it was prevalent everywhere at Paris Retail Week. Phygital combines “physical” and “digital” experiences in a new ecosystem. This offers the consumer a full acquisition experience across different channels. From payment providers to marketing agencies, everyone was talking about going phygital. One of our favourite presentations was by AB Tasty. They focused on how optimising client experience can boost sales and conversions in the long-term. It’s not enough to promote your products, nor to link to an influencer for social proof -- you need to create a full customer experience. Starbucks and Nespresso are good examples of how this works offline, assuring that a customer who comes in to drink a coffee will linger around for the next 20-30 minutes. By keeping the customers in the shop, they will eventually order more. The goal is to reproduce this immediately sticky experience online too, and focusing on web engagement benchmarks is the best way to track your progress here. Using the example of conversion rate optimisation (CRO) for mobile apps, AB Tasty's Alexis Dugard highlighted how doing data-driven analysis of UI performance, on a very detailed level, can help clarify how mobile shopping connects with a wider brand experience. In the end, customer experience means knowing the customer. 81% of consumers are willing to pay more for an optimal customer experience. Brands that are reluctant to invest in customer experience, either online or offline, will hurt their bottom line, even if this isn't immediately apparent. Those brands that do invest in multi-channel customer experience are investing in long-term growth fuelled by higher Average Order Value (AOV). 81% of consumers are willing to pay more for an optimal customer experience -- the statistic speaks for itself! Another great talk was from Guillaume Cavaroc, a Facebook Academie representative, who discussed how mobile shopping now overlaps with offline shopping. He looked at experiments with how to track customers across their journeys, with mobile login as a focal point. In the Google Retail Reboot presentation, Loïc De Saint Andrieu, Cyril Grira and Salime Nassur pointed out the importance of data in retail. For ecommerce sites using the full Google stack, Google data represents the DNA of the companies and Google Cloud Platform is the motor of all the services, making multi-channel data more useful than ever in assisting with smart targeting and customer acquisition. The Google team also stated that online shopping experiences that don’t have enough data will turn to dust, unable to scale, and that in the future every website will become, in one way or another, a mobile app. In some ways, "phygital" really means mobile-first. This message that rang out clearly in France, which is a mobile-first country where a customer's first encounter with your brand or product is inevitably via mobile -- whether through a browser, specific app or social media feed. [subscribe] Multi-channel experience (and the data you need to optimise it) Physical marketing is making a comeback. Boxed CEO Chieh Huang and PebblePost founder Lewis Gersh presented the success of using online data for offline engagement, which then converts directly back on the original ecommerce site. Experimenting heavily in this area, they've seen personalised notes on invoices and Programmatic Direct Mail (with the notes based on viewed content) generate an increase of 28% in online conversion rate. Our real-world mailboxes have become an uncluttered space, and customers crave the feel of a paperback catalogue or simple postcard, to name just a bit of the physical collateral that's becoming popular again -- and being done at a higher quality than in the years of generic direct mail. Our real-world mailboxes have become an uncluttered space, and customers crave the feel of a paperback catalogue or simple postcard. However, data is still the backbone of retail. In 2017 Amazon spent approximately $16 billion (USD) on data analysis, and it was worth every penny, generating around $177 billion in revenue. Analysing declarative and customer behaviour data on the shopper’s path-to-purchase is a must for merchants to compete with Amazon. Creating an omni-channel experience for the user should be your goal. This means an integrated and cohesive customer shopping experience, no matter how or where a customer reaches out. Even if you can't yet support an omni-channel customer experience, you should double down on multi-channel ecommerce. When Littledata's customers have questions about the difference, we refer them to Aaron Orendorff's clear explanation of omni-channel versus multi-channel over on the Shopify Plus blog: Omni-channel ecommerce...unifies sales and marketing to create a single commerce experience across your brand. Multi-channel ecommerce...while less integrated, allows customers to purchase natively wherever they prefer to browse and shop. Definitions aside, the goal is to reduce friction in the shopping experience. In other words, you should use anonymous data to optimise ad spend and product marketing. For marketers, this means going beyond pretty dashboards to look at more sophisticated attribution models. We've definitely seen this trend with Littledata's most successful enterprise customers. Ecommerce directors are now using comparative attribution models more than ever before, along with AI-based tools for deeper marketing insights, like understanding the real ROI on their Facebook Ads. The new seasonality So where do we go from here? In the world of ecommerce, seasonality no longer means just the fashion trends of spring, summer, autumn and winter. Online events like Black Friday and Cyber Monday (#BFCM) define offline shopping trends as well, and your marketing must match. "Black Friday" saw 125% more searches in 2017, and "Back to School" searches were up 100%. And it isn't just about the short game. Our own research last year found that Black Friday discounting is actually linked to next-season purchasing. Phygital or otherwise, are you ready to optimise your multi-channel marketing? If not, you're missing out on a ton of potential revenue -- and shoppers will move on to the next best thing.

2018-10-09

Web design fails to avoid for ecommerce success

Your website is an essential tool for attracting and converting customers. Driven by the uptake in online shopping, having a well-designed ecommerce site is no longer a luxury. It’s now a necessity -- you need to regularly convert browsers into buyers. Web design has the power to really grab your customers attention and portray your messaging. But when it goes wrong, the customers you lose will rarely come back. In this post I take a look at common web design fails that drive customers away, so you can avoid them. They may be common mistakes, but they're often overlooked! Fail #1: The CMS, plugins and theme are outdated You don’t need to modernize your website every day, or even every week, but you do need to make sure it doesn’t feel outdated. That means you should regularly update your website theme, your plugins and your content. Updating your theme and plugins will ensure you have the latest features and boost your security, while regularly updating your content will improve your SEO ranking and make your website more interesting for repeat visitors. Fail #2: Your website is not mobile responsive Over 50% of online traffic is from mobile phones and tablets, so having a website that properly displays itself on those devices is essential. If your website is non-responsive, you’ll be missing out on a massive amount of potential business. Below is the website Dribble, a powerful example of a responsive website (here's a big list of mobile-responsibe web design done well). Plus, your SEO will suffer and it makes your business look unprofessional. Common issues with non-responsive websites are text being displayed too small to read, irregular formatting, un-clickable links and images not loading. How many of your customers are shopping on mobile? Where are they falling out of the checkout funnel? Use this tool to find out. Fail #3: Stock photos and generic content Building customer loyalty and trust -- both of which are vital for repeat business -- begins with establishing credibility and authenticity. Nobody wants to read the same blog they have already read 50 times on your website, or look at stock photos they have seen on other brands websites. Good writing should be original, punchy and relevant to your target audience. And copy should be matched with credible, original imagery. Stock photos are easy to spot a mile off. Using original imagery significantly helps to build a website design that stands out and wins customer trust. [subscribe] Fail #4: It’s slow and your bounce rate is high Speed matters. If your website loads too slowly, you can say goodbye to the impatient modern-day consumer and watch your bounce rates rise. First impressions of a website are made immediately, so if your website takes more than a few seconds to load, your content and design won’t be given the chance to see the light of day. Make sure your images are compressed, limit the amount of videos and animations published within, make sure your hosting provider can handle fluctuating amounts of traffic, and disable any plugins you aren’t actually using. Then make sure to check your speed and performance rates against other sites. Benchmarking is the most accurate way to do this, so you can see how you compare to similar sites in your industry. Fail #5: Your site is unbranded and doesn’t stand out The minute a possible customer comes to your website, they should know exactly whose website they are on. Having a nicely designed logo is, therefore, critical for making a good first impression and improving brand awareness. And best of all, it’s really easy to do. Online tools are readily available to create stunning high-resolution logos in second, such as Shopify’s logo maker. Fail #6: Face it, your site's just not that interesting There is nothing worse than going on to a website and finding it incredibly boring. Content needs to compliment design, so it’s vital you have interesting content throughout to keep your customers engaged and coming back for more. Using banners, photos and graphics, along with authentic and interesting copy is the right way to grab your customers’ attention and encourage them to make a purchase or opt-in via a form. Fail #7: It’s not made for converting If your website doesn’t have clear calls to action (CTAs), then it’s not going to have good conversion rates. Plain and simple. This 'fail' can easily be eradicated by using smart opt-in offers, having clear navigation menus ('nav menus' in designer jargon), and writing relevant, targeted content. Evernote use an excellent CTA.   Without a clear CTA, how are your customers meant to know what you want them to do? Simply put, they won’t - they will leave. Every page (including your blog posts) should have a clear CTA to guide your online visitors down the buyer journey. Fail #8: It’s not optimized for SEO Optimizing each aspect of your website begins with understanding what works well and what doesn’t. The only way of doing this accurately is by using analytics to get deeper insights into how your potential buyers are using your site. You’ll be able to see which pages perform well, which keywords attract the best traffic (SEO is an area that you should be continually optimizing), which promotions work best, and which images resonate with your customers the most. As search engines become smarter, continually optimizing for SEO is an excellent way to get a clearer view of what's working and clarify anything that isn't clear. Then you'll be on the road to becoming an SEO-driven business - an easy way to improve revenue. Fail #9: It’s cluttered and noisy If your website is too cluttered, it will create a bad customer experience for any visitor. It will also distract potential buyers away from doing what you want them to do, such as making a purchase, filling out a form or requesting more information via chat. Don’t make the mistake of cramming too much into each page, or filling your web pages with in-your-face advertising. Your website should be easy to navigate, simple and concise. Customers should be able to convert with minimal effort. Conclusion The bottom line: if your ecommerce site has many design fails that impact the user experience, your company may lose out on potential profits. Use the tactics mentioned in this article to get started on improving the design of your website today!   Michelle Deery is the content writer for Heroic Search, a digital marketing agency based in Tulsa. She specializes in writing about eCommerce and loves writing persuasive copy that both sells and educates readers.

2018-10-01

Are you benchmarking your ecommerce site in the right sector?

Littledata launched benchmarks for websites two years ago. They quickly became a key feature of our app, and as customers became more engaged, so did ideas for how to improve our benchmarking and the algorithms that learn from those benchmarks. In response to customer feedback and deeper research into industry sectors, we've made some really exciting improvements over the last few months to make the comparisons even more useful -- and even more dynamic. The changes are five-fold. Detailed sectors and sub-sectors. Almost every customer we talked to said the benchmark comparison was most useful if it was for very similar sites. Previously we only had 50 high-level sectors to compare with; now we have hundreds of low-level sectors. You can visualise the full range. Smarter auto-categorisation of your website. Our machine learning process now has a 95% chance of finding the best sector for your website, meaning you can compare against the most useful benchmark without filling in a single form! Ability to manually change industry sector. And of course, if you're in that 5% that needs human input, then you (or your Enterprise account manager) can pick a better sector in the general app settings page. You might also want to change sectors just to see how you compare. No problem. Benchmarks for technology stacks. Want to see if you are making the most of a technology such as Shopify or Yieldify? Now you can compare with other sites using the same technology, making our ecommerce benchmarking even more powerful for agencies and web developers. Benchmarks for starter websites. Previously we only generated benchmarks for sites with at least 500 monthly visits. We dropped that to 200 monthly visits, so starter websites can see a comparison - and see more detail as they grow. We've launched a live visualisation of how our AI-based website categorizer is mapping a range of industry sectors. It offers a full overview of website categories and segments. And you can drill down to see more details. For example, we've seen a big rise in wine, coffee and health shake retailers this year, many of whom are using our ReCharge integration to get insight into their subscription business models. As our algorithms learn about ecommerce businesses selling beverages of many varieties and automatically categorises sites accordingly, you can now look closely at a particular segment to see how your site compares. Littledata is an Agile company. We're constantly iterating, and continuously improving the benchmarks to make them more actionable, so please give us feedback if you'd like to see more. Happy benchmarking! [subscribe]

2018-09-25

How Pufushop used our ecommerce benchmarks to grow sales

"Is my conversion rate good or bad?" We built Littledata's benchmarking feature to help you say goodbye to guessing games and start automatically benchmarking your site against top performers. Now that our benchmark tool has been around for awhile, we've started to get a sense for which ecommerce sites are using it most effectively. In other words, we've seen how benchmarks can help websites increase revenue - not in theory but in actual practice. Littledata has now helped hundreds of companies understand where their performance is compared with other websites in their niche, using our benchmarking algorithms and clean user interface. But can benchmarks really help you grow sales? I understand if you want to see the data for yourself. One of our long-term customers makes for an ideal case study. Case study - Pufushop Over the course of 2017, we helped Pufushop, a Romanian ecommerce site, understand if their website changes were helping to increase performance - and where they still had work to do. Pufushop is a retailer of baby goods, with a main focus on baby carriers. The products in their store are all premium quality and from top vendors, so comparing them with just any other baby store wouldn't have been relevant. Instead, we compared their ecommerce metrics with specific benchmark segments that were most relevant to their market landscape and business goals. Ecommerce benchmark segments Benchmarking is used to measure and compare the performance of a specific indicator, and it's most useful when you map that data onto your internal KPIs and compare performance against similar sites. Littledata specialises in ecommerce analytics and our benchmark population now includes Google Analytics data from almost 10,000 sites. We break that data into specific categories, such as Marketing, Ecommerce and Speed (site performance), and within each category you can filter by industry, location, website size, and more. Littledata aggregates reliable data from those thousands of high-performing websites so that you can focus on results. In this customer's case, we analysed their website and business model to provide 5 relevant benchmark segments: Romanian websites to compare KPIs across regional market Small SEO websites because 60% of Pufushop's traffic comes from search engines SEO-driven online stores (more generally, to see how they compare) General online shopping websites across the globe, to get a sense for how their funnel compares And a specific revenue per customer category based on shoppers' average basket spend (sites with a similar average order value, no matter the sector) Key metrics Web behaviour is not necessarily consistent across industries. We started Pufushop's analysis by looking at key ecommerce KPIs such as Checkout completion rate, Ecommerce conversion rate and Add-to-cart rate, but we didn't just pull these metrics blindly. Starting with the first month, February 2017, we looked at how other stores with a similar average basket value were performing. This helped our client establish what was working and what could be improved. As we worked with them to make sure everything was tracking correctly (after all, benchmarks are only as useful as your data is accurate), they could also check these benchmarks directly in the Littledata app. Results Now for the first time, both Pufushop's Marketing Director and Senior UX Designer had clarity on which areas of the website could be improved to increase sales. Based on the benchmark data they could see that the main places to improve were: The checkout process (to increase the checkout completion rate) Product pages (to increase the add-to-cart rate) Resolving those two main issues will automatically resolve the e-commerce conversion rate KPI and will indirectly influence the Revenue per customer. Pufushop decided to use Google Optimize in order to improve the checkout completion rate. Using Google Optimize is an easy-to-use, fast and scalable tool in order to A/B-test different experiences on the checkout page. Pufushop conducted a variety of targeted experiments, including: Shortening the checkout process Eliminating unnecessary fields Testing variants of checkout pages Split-testing different product pages Testing a variety of shipping costs After a couple of months of testing, the results were significant: The add-to-cart rate grew from 3.7% to 5.5% The checkout completion rate jumped from 52.8% to 89.7% Now those are some real results! Having a direction as well as a target helped Pufushop's digital team to focus on clear, achievable goals. As they continue to grow, we're glad to have them as a part of the Littledata family. [subscribe] Ready to benchmark your site? If you're in the same place as Pufushop was a year ago, here's a quick guide for how to use ecommerce KPI benchmarks to improve your store performance. Sign up for Littledata's main app or Shopify app Look at the benchmark data and pick an industry and a set of KPIs - the right sectors and segments will help you optimise campaigns Use tools like Hotjar and Littledata's automated reporting to analyse user behaviour around those benchmarks and define a short list of actions you're going to take Use Google Optimize or hire a developer to put those actions into place Monitor how users are interacting with the changes When you have sufficient data to see a clear relationship between those changes and an increase in traffic, revenue or conversions, make those changes permanent and move on to focus on a new set of KPIs Keep in mind that there are situations where the KPIs will show you issues of wrong messaging, for example of a product page or advertisement - technical issues where the change is fairly easy to make. In other cases, you will need to develop a long-term strategy for radical changes to your website, such as altering your checkout process. The online environment is a fast-moving industry, so you need to be agile and ready to change accordingly. Either way, we're here to help you scale with data-driven strategies for sustainable growth. Now stop reading this post and start benchmarking your site!   Note: In order to maintain data-confidentiality, KPI values have been altered in this case study (the results are real, only the benchmarks have been adjusted).

2018-05-24

6 essential benchmarks for Shopify stores

Understanding how your website performs versus similar sites is the best way to prioritise what to improve. In this post we take a look at 6 top benchmarks for optimising Shopify store performance. Accurate benchmark data is especially useful to the increasing number of ecommerce companies using web performance benchmarks, such as bounce rates and home page reliance, as core elements of their sales and marketing KPIs. Understanding benchmarks is a key to success. To put together this new benchmarking report, we analysed current data from 470 Shopify retailers. If you're wondering how you compare, check out our Shopify analytics app. Average order value Average order value (AOV) or Average revenue per paying user (ARPU) is the total monthly revenue divided by the number of users which transacted that month. It is a measure of how well you are up-selling and cross-selling your products, depending on your product mix. What is a good average order value for Shopify stores? The benchmark is $69. The average is slightly lower ($63.50) if you are a smaller Shopify store. More than $120 AOV would put you in the top quartile, and one of our top-performing stores in the luxury ecommerce sector is averaging $2,080 per order! If your Shopify store has a lower AOV than the benchmark, you might try increasing your average checkout value by cross-selling other products, offering free shipping above a minimum threshold or increasing pricing on selected products. Ecommerce conversion rate Ecommerce conversion is the number of purchases divided by the total number of sessions. Most visitors will take more than one session to decide to purchase, but this is the standard measure of conversion rate. It is a measure of how good a fit your traffic is for your products, and how well your site converts this traffic into customers. What is a good ecommerce conversion rate for Shopify stores? The benchmark is 1.75%. Larger stores have pushed this to 1.85%, and if you are more than 2.8% you are in the top quartile. The highest conversion rate we’ve seen on Shopify is 8%. Can you increase the conversion rate with more attractive product displays, or improving the checkout process? Enhanced ecommerce tracking will help you identify exactly where the blockers lie. Bounce rate from mobile search Since more than 60% of Google searches are now done on mobile, ensuring your site design works on a small screen is important for branding and sales. Bounce rate is the percent of visits of only one page – and will be high if your landing pages do not engage. Google will even adjust your mobile ranking for a given keyword depending on what proportion of visitors stick on your page - a good indication that your link was useful. What is a good bounce rate from mobile search for Shopify stores? The benchmark is 47.5%. The biggest Shopify stores have got this below 40%, and overall large retailers have 38% mobile bounce rate. So it’s not a problem with the Shopify platform, so much as a problem with the store theme – or how the options and products are displayed on a smaller screen. Can you improve the first impressions of the landing pages, put key content higher up the page, or decrease the page load speed to reduce that bounce rate? [subscribe] Delay before page content appears The delay between a page request by the user and them being to read or click on that page. This is more important than full page load speed for AJAX / lazy loading sites (also called the ‘DOM Interactive Time’). What is a good delay time before page content appears? The benchmark for Shopify stores is 2.75 seconds. Even larger retailers have this down to 2.8 seconds, so Shopify sites do well on this score. Anything less than 3 seconds is generally acceptable. Internet users are increasingly intolerant of slow sites. Your developers could look at Google PageSpeed Insights for more details. Often the delay will be down to extra scripts which could be delayed or removed. Server response time This is the part of the page load speed which is entirely outside of your control – and due to the speed of the servers your site runs on. What is a good server response time for Shopify stores? The benchmark is 322ms. The average for larger ecommerce is 542ms – so Shopify’s server infrastructure is serving you well here. Reliance on the homepage This is the percent of visitors who land on your homepage. If this is below 40% you rely heavily on your homepage to capture brand or paid search traffic. Google increasingly rewards sites with a greater volume of landing pages targeting more specific keyword phrases. What is a good reliance on homepage percentage for Shopify stores? The benchmark is 32%. Larger Shopify stores, with many more landing pages, have reduced this to 7.3% of traffic landing on the homepage on average. Can you build out product landing pages and inbound links to copy their advantage? Ready to benchmark your own website, stop playing guessing games and start scaling your ecommerce business? Our Shopify reporting app is the easiest way to get accurate benchmarking. Install Littledata today and you'll get instant access to up to 20 relevant industry benchmarks for ecommerce sites, plus the tools you need to fix your analytics for accurate tracking, so you'll always know for sure where your website stands. It's all about smart data that helps you focus on making changes that drive revenue and increase conversions. We're here to help you grow!

2017-11-14

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