How to calculate customer lifetime value (CLV) for subscription ecommerce in Google Analytics
Many of Littledata's subscription customers come to us with a similar problem: how to calculate return on advertising spend, considering the varying customer lifetime value (CLV) of subscription signups. Calculating marketing ROI for subscription ecommerce is a big problem with a number of potential solutions, but even the initial problem is often misunderstood. In this post I break down what the problem is, and walk through two proven solutions for getting consistent, reliable CLV reporting in Google Analytics. What is customer lifetime value? I work with all kinds of subscription ecommerce businesses: beauty boxes, nutritional supplements, training courses and even sunglasses-by-the-month. All of them want to optimise customer acquisition costs. The common factor is they are all willing to pay way MORE than the value of the customers' first subscription payment... because they expect the customer to subscribe for many months. But for how many months exactly? That's the big question. Paying for a marketing campaign which bring trial customers who cancel after one payment - or worse, before the first payment - is very different from paying to attract sticky subscribers. A marketing director of a subscription business should be willing to pay WAY more to attract customers than stay 12 months than customers who only stay one month. 12 times more, to be precise. So how do we measure the different contribution of marketing campaigns to lifetime customer value? In Google Analytics you may be using ecommerce tracking to measure the first order value, but this misses the crucial detail of how long those shoppers will remain subscribers. With lifetime customer value segments we can make more efficient use of media, tailor adverts to different segments, find new customers with lookalike audiences and target loyalty campaigns. There are two ways for a marketing manager to see this data in Google Analytics: one is a more difficult, manual solution; the other is an easier, automated solution that ties recurring payments back to the original campaigns. A manual solution: segment orders and assign a lifetime value to each channel It's possible to see the required data in GA by manually segmenting orders and assigning a lifetime value to each channel. For this solution you'll need to join together: (a) the source of a sample of first orders from more than a year ago, by customer number or transaction ID and (b) the CLV of these customers The accuracy of the data set for A is limited by how your Google Analytics is set up: if your ecommerce marketing attribution is not accurate (e.g. using Shopify's out-the-box GA scripts) then any analysis is flawed. You can get B from your subscription billing solution, exporting a list of customer payments (and anonymising the name or email before you share the file internally). To link B to A, you'll need either to have the customer number or transaction ID of the first payment (if this is stored in Google Analytics). [subscribe] Then you can join the two data sets in Excel (using VLOOKUP or similar function), and average out the lifetime value by channel. Even though it's only a sample, if you have more than 100 customers in each major channel it should give you enough data to extrapolate from. Now you've got that CLV by channel, and assuming that is steady over time, you could import that back into Google Analytics by sending a custom event when a new customer subscribes with the 'event value' set as the lifetime value. The caveat is that CLV by channel will likely change over time, so you'll need to repeat the analysis every month. If you're looking to get away from manual solutions and excessive spreadsheets, read on... A better solution: tie recurring payments back to the original campaign(s) What if you could import the recurring payments into Google Analytics directly, as they are paid, so the CLV is constantly updated and can be segmented by campaign, country, device or any other standard GA dimension? This is what our Google Analytics connection for ReCharge does. Available for any store using Shopify as their ecommerce platform and ReCharge for recurring billing, the smart connection (integration) ties every recurring payment back to the campaigns in GA. Here's how the connector works The only drawback is that you'll need to wait a few months for enough customer purchase history (which feeds into CLV) to be gathered. We think it's worth the wait, as you then have accurate data going forward without needing to do any manual imports or exports. Then, if you also import your campaign costs automatically, you can do the Return on Investment (ROI) calculations directly in Google Analytics, using GA's new ROI Analysis report (under Conversions > Attribution), or in your favourite reporting tool. Do you have a unique way of tracking your marketing to maximise CLV? Are there other metrics you think are more important for subscription retailers? Littledata's connections are growing. We'll be launching integrations for other payment solutions later this year, so let us know if there's a particular one you'd like to see next.
5 myths of Google Analytics Spam
Google Analytics referral spam is a growing problem, and since Littledata has launched a feature to set up spam filters for you with one click, we’d like to correct a few myths circulating. 1. Google has got spam all under control Our research shows the problem exploded in May – and is likely to get worse as the tactics get copied. From January to April this year, there were only a handful of spammers, generally sending one or two hits to each web property, just to get on their reports. In May, this stepped up over one thousand-fold, and over a sample of 700 websites, we counted 430,000 spam referrals – an average of 620 sessions per web property, and enough to skew even a higher traffic website. The number of spammers using this tactic has also multiplied, with sites such as ‘4webmasters.org’ and ‘best-seo-offer.com’ especially prolific. Unfortunately, due to the inherently open nature of Google Analytics, where anyone can start sending tracking events without authentication, this is really hard for Google to fix. 2. Blocking the spam domains from your server will remove them from your reports A few articles have suggested changing your server settings to exclude certain referral sources or IP addresses will help clear us the problem. But this misunderstands how many of these ‘ghost referrals’ work: they are not actual hits on your website, but rather tracking events sent directly to Google’s servers via the Measurement Protocol. In this case, blocking the referrer from your own servers won’t do a thing – since the spammers can just go directly to Google Analytics. It's also dangerous to amend the htaccess file (or equivalent on other servers), as it could prevent a whole lot of genuine visitors seeing your site. 3. Adding a filter will remove all historic spam Filters in Google Analytics are applied at the point that the data is first received, so they only apply to hits received AFTER the filter is added. They are the right solution to preventing future spam, but won’t clean up your historic reports. To do that you also need to set up a custom segment, with the same source exclusions are the filter. You can set up an exclusion segment by clicking 'Add Segment' and then red 'New Segment' button on the reporting pages and setting up a list of filters similar to this screenshot. 4. Adding the spammers to the referral exclusion list will remove them from reports This is especially dangerous, as it will hide the problem, without actually removing the spam from your reports. The referral exclusion list was set up to prevent visitors who went to a different domain as part of a normal journey on your website being counted as a new session when they returned. e.g. If the visitor is directed to PayPal to pay, and then returns to your site for confirmation, then adding 'paypal.com' to the referral exclusion list would be correct. However, if you add a spam domain to that list then the visit will disappear from your referral reports... but still, be included under Direct traffic. 5. Selecting the exclude known bots and spiders in the view setting will fix it Google released a feature in 2014 to exclude known bots and spiders from reports. Unfortunately, this is mainly based on an IP address - and the spammers, in this case, are not using consistent IP addresses, because they don't want to be excluded. So we do recommend opting into the bot exclusion, but you shouldn't rely on it to fix your issue Need more help? Comment below or get in touch!
Setting up a destination goal funnel in Google Analytics
Destination goal funnels in Google Analytics track how well certain actions on your website contribute to the success of your business. By setting up a goal for each crucial activity you will get more focused reports on how visitors are using your website, and at what stage they are dropping out of the conversion funnel. The first time I tried to set up a destination goal was daunting, but after some practice, I am now seeing valuable information on how well visitors are interacting with our clients' websites. If like Teachable you have different subscription packages, then you might want to track how each subscription is converting. For this, set up the purchase confirmation page of each subscription plan as a goal, with a funnel to get additional insight into where people drop off. Step 1: Create a new goal To set up a destination goal go to Google Analytics Admin settings > View > Goals. Click ‘new goal.’ Step 2: Fill in destination goal details Google has some goal templates that provide set-up suggestions. They will only display if you have set your industry category in property settings. Selecting any of the given templates will only populate the name and type of the goal, but not the conversion details, which are more complicated for some. This is not very useful for me so I will ignore this: select ‘custom’ and click ‘next.’ Goal name Give your goal a descriptive name. You will later see it in various reports in Google Analytics so use whatever makes sense for you. Here I am going to use the name of the subscription plan I am tracking - Basic Subscription. Goal slot ID Goal slot ID is set automatically and you might want to change it if you want to categorise your goals. Select ‘Destination’ and click ‘next step.’ Step 3: define your destination goal Destination type You have a choice between 3 different match types. If you have an exact URL that does not change for different customers (without '?=XXX'), then use ‘Equals to’ for an exact match. If the beginning of your converting URL is the same, but there are different numbers or characters at the end of the URL for various customers, then choose ‘Begins with.’ Use ‘Regular expression’ to match a block of text within the URL. For example, if all your subscriber URLs have 'subscriber_id=XXX' somewhere then type 'subscriber_id=' into the text field. You can also use 'regular expression' if you need to match multiple URLs and know how to use special characters to build regex. One of our favourite tools to test regular expressions is Regex Tester. The match type you select here will also apply to the URLs in the funnel, if you choose to create one. Destination page Destination page is the URL where the conversion occurs. For Teachable, and most other websites that sell something online, the destination is usually a ‘thank you' page that is displayed after successful purchase. You might also have a thank you page for contact forms and newsletter signups, which you would track the same way as a payment thank you page. Here you insert the request URI, which is the URL part that comes after the domain address. It would look something like this: /invoice/paid /thank you.html /payment/success Step 4: Should you set a goal value? (optional) You can set a monetary value to your goal if you want to track how much it contributes. e.g. If the goal is visitors completing a contact form, and you know the average lead generates you £100, then you can put the value at 100. If you are an ecommerce site and want to track exact purchases, then set up enhanced ecommerce tracking instead. Step 5: Should you set up a funnel? (optional) If you have several steps leading up to the conversion, you should set up a funnel to see how many people move through each defined step and where they fall out. If you do not set the first step as 'required', Google Analytics will also track people coming into funnel halfway through. i.e. If the first stage of your funnel is the homepage, then it will still include visitors who land straight on your contact page. Verify Now that you have set up your destination goal, click ‘verify the goal’ to check it works. If all is set up correctly, you should see an estimation of the conversion rate your goal would get. If you do not get anything, then check each step carefully. Once all is well, click ‘create goal’ and check it is working after a few days or a week, depending on how much traffic you get. If you set up a funnel, you will see it in Conversions > Goals > Funnel Visualisation. This is what a typical funnel would look like. Because I did not set the first step as 'required' you can see people entering the funnel at various steps. Need more help? Get in touch or comment below!
Will a computer put you out of a job?
I see a two tier economy opening up in England, and it’s not as simple as the haves and have-nots. It’s between those that build machines, and those that will be replaced by them: between those that can code, and those that can’t. We’ve seen the massive social effects that declining heavy manufacturing jobs since 1970s have had on much of the North of England and Scotland, and I believe we’re at the start of a similar long-term decimation of service industry jobs – not due to outsourcing to China, but due to automation by computers. Lots of my professional friends in London would feel they’re beyond the reach of this automation: their job involves being smart and creative, not doing production-line tasks. But it is these jobs, which currently involve staring at numbers on a screen, which are most at risk from computer substitution. If your job involves processing a load of data into a more presentable format (analysts, accountants, consultants and some types of traders) then a computer will eventually - within the next 20 years - be able to do your job better than you. In fact, within 20 years computers will be much better than humans at almost every kind of data processing, as the relentless extension of Moore’s law means pound-for-pound computer processing will be 1 million times cheaper than it is now. As Marc Andreessen put it, ‘Software is eating the world’, and we’re only just beginning to work through the implications. This worries me. With the greater and greater levels of automation of the working world, what happens to employment? Last year we saw an incredible event in the sale of WhatsApp to Facebook: massive wealth creation ($17bn) accompanied by almost no job creation (33 employees at the time of sale). If a tiny number of highly skilled people can create a service with 300m paying customers, why do companies need to hire lots of people? In the utopian view of future work we give up all boring admin tasks to the machines, and focus on face-to-face interaction and making strategic decisions based on selected knowledge fed to us by our personal digital agents (like Google search on steroids). Lots more thinking space leads us to be more productive, and more leisure time makes us happier. But 30 years ago they thought computers would evolve into very capable personal assistants, when in fact office workers are chained to the screen for longer hours by the tyranny of email and real-time information flow. Look at Apple’s forecast from 1987 of what computing might look like in 2006: the professor is freed from the tedium of typing or travelling to the library. Yet they didn’t consider whether the professor himself might be needed in a world where students could get their lectures as pre-recorded videos. So the cynical view is that more volume of data will require more humans to interpret, and the technology will always need fixing. As companies become more automated there will be more and more jobs shifting into analysis and IT support; analogous to how, as postal mail has been replaced by email, jobs in the company post room have shifted into IT support. The problem is that there really are a limited number of humans that can set up and maintain the computers. I’d love to see society grappling with that limitation (see grass-roots initiative like CoderDojo) but there are some big barriers to retraining adults to code: limited maths skills, limited tolerance for the boredom of wading through code, and limited opportunities for people to test their skills (i.e. companies don’t trust this most critical of job roles to new apprentices). So those that have commercial experience in programming can command escalating day rates for their skills – and this is most apparent in London and San Francisco, while pay in other skilled areas is not even keeping up with core inflation. That leads us to the dystopian view: that the generation starting their working lives now (those 10 years younger than me) will see their prospects hugely diverge, based on which side of the ‘replace’ or ‘be replaced’ divide they are. If companies akin to Google and Facebook become the mainstay of the global economy, then they’ll be a tiny number of silicon sultans whose every whim is catered for – and a vast mass of technology consumers with little viable contribution to the workplace. Let’s hope our politicians start grasping the implications before they too are replaced by ‘democracy producing’ software!
How to audit your Web Analytics Ecommerce tracking
5 common Google Analytics setup problems
Can you rely on the data you are seeing in Google Analytics? If you use it daily in your business you should really give some time to auditing how the data is captured, and what glitches could be lurking unseen. The notifications feature in Google Analytics now alerts you to some common setup problems, but there are more simple ones you could check today. Here are 5 aspects of your Google Analytics account to check now. Are you running the latest Universal Analytics tracking code? Is your overall bounce rate below 10%? Are you getting referrals from your own website? Are you getting ‘referrals’ from your payment gateway? Have you got the correct website default URL set in GA? Are you getting full referring URL in reports? 1. Are you running the latest Universal Analytics tracking code? You may have clicked upgrade in the Google Analytics admin console, but have your developers successfully transferred over to the new tracker code? Use our handy tool to test for universal analytics (make sure you copy your URL as it appears in the browser bar). 2. Is your overall bounce rate below 10%? The 'bounce rate' is defined as sessions of only one page. It’s highly unlikely to be in single digits unless you have a very unique source of engaged traffic. However, it is possible that the tracking code is firing twice on a single page. This double counting would mean Google Analytics sees every single page view as two pages – i.e. not a bounce This is more common on template-driven sites like Wordpress or Joomla, where you may have one tracking script loaded by a plugin – and another pasted onto the main template page. You can check if you have multiple pageviews firing by using the Google Tag Assistant plugin for Chrome. 3. Are you getting referrals from your own website? A self-referral is traffic coming from your own domain – so if you are www.acme.com, then a self-referrals would be appearing as ‘acme.com’. Have a look at the (recently moved) referrals list and see if that is happening for you. This is usually caused by having pages on your website which are missing the GA tracking code, or have it misconfigured. You can see exactly which pages are causing the problem by clicking on your domain name in the list and seeing the referring path. If you are on universal analytics (please use our tool to check) you can exclude these referrals in one step with the Referral Exclusion list. For a fuller explanation, see the self-referral guide provided by Google. 4. Are you getting ‘referrals’ from your payment gateway? Similar to point 3: if you have a 3rd party payment service where customers enter their payment details, after they redirect to your site – if you are on Universal analytics – they will show up as a new visit… but originating from ‘paypal.com’ or ‘worldpay.com’. You need to add any payment gateway or similar 3rd party services to that referral exclusion list. Just add the domain name - so PayPal would be 'paypal.com' 5. Have you got the correct website default URL set in GA? When Google Analytics was first set up for your website you may have set a different domain name than what you now use. Or maybe you have switched to run your site on https:// rather than http://. So you need to change the default URL as set up in the admin page. For this go to Admin > Property > Property Settings. Once that is setup correctly, the ‘All Pages’ report becomes a lot more useful – because you can click through to view the actual page using the open link icon. Advanced: Are you getting full referring URL in reports? If you run your website across different subdomains (e.g. blog.littledata.co.uk and www.littledata.co.uk) then it can be difficult to tell which subdomain the page was on. The solution to this is to add the hostname to the URL using a custom filter. See the guide on how to view full page URLs in reports. What other setup issues are you experiencing? Let us know in the comments or by tweeting @LittledataUK.
Best enhanced ecommerce plugins for Magento
Agriculture in Uganda: Measure and Improve
I had a truly inspiring day visiting Send a Cow project near Masaka in Uganda. A group of 30 farmers underwent 4 years of training, supported by weekly visits from a social worker and agricultural trainer. From a group living in absolute under-a-dollar-a-day poverty, there are now farmers owning thousands of dollars worth of livestock and selling export crops like coffee. This education and support, plus the capital grant of one animal per household, has transformed their community. Although the success relied on a solid base of family and group cohesion, organised labour and animal husbandry, I want to focus on three aspects which have ongoing potential for the community. 1. Record keeping Yep, data to you and I. Writing daily details of milk yields, crop inputs, market sale prices and even visitor numbers enabled the farmers to measure and improve. Data also allows farmers to forecast and be inspired. Selling a regular surplus of milk from two cows (after family consumption – yes, they have great teeth!) gave the farmer a regular income of US$3.50 per day at the farm gate. That is more than a teacher’s salary in Uganda. With tender care and back-breaking forage harvesting, they now have a calf being reared – and can count just how much that will mean in further milk and profits. Maybe in 10 years they will be entering yields into a smartphone app, and have market prices forecast automatically. 2. Organic agriculture Oil derivatives (like diesel and fertiliser) are nearly as expensive in Uganda as the UK – in ridiculous contrast to the local market prices for vegetables. Efficient farming therefore has to rely on minimal imported inputs, and maximise the local bounty of sun, rain … and manure. Every precious drop of animal urine is captured – to mix with ash and chilli as an insect repellant for plants – or used neat as a fertiliser. In dry season, every rainfall is maximised, with lots of mulching of vegetables to prevent evaporation; and with a permaculture approach of shading coffee bushes with banana plants, and vegetables under the coffee. I am a fan of organic farming for health and environmental reasons, but out here I just do not see an alternative, cost-effective way to increase crop yields. 3. Peer-to-peer lending Developed-to-developing country lending networks, like Kiva.org, have grown rapidly – but with inevitable problems in vetting funding applications at distance. What farmers need are equivalents of 19th century Europe’s co-operative societies – where savers and lenders from the same area are brought together. These farmer groups operate a very effective local system. All members pledge to save every month: from just 1 cent a week. Then any member can ask for a short term (maximum 3 month) loan from the fund – which is now $2000. The default rate is low – around 2% - as members know the debtors ability to repay, and can monitor progress in person. Plus every debtor has savings in the scheme – so wants to preserve their share of the capital. Three month loans (and flat 10% interest) make repayments easy to predict – and work in a country where planting to harvest is only 3 months. Uganda’s government abolished co-operatives in the 1990s when they started sponsoring political campaigns. But if these lending clubs can grow they could go some way to unlocking the capital that Africa needs to grow. This post was written by Edward Upton, Founder of Littledata, @eUpton
7 best business and tech conferences in 2015
Every year is jam-packed with conferences, forums and festivals, and I have spent enough time sifting through numerous event programmes for this year. There are plenty of opportunities to learn about new trends and techniques, discuss the future and network with peers, but which major events are worth your time (and money)? Here's my pick of must-attend business, digital and tech conferences in 2015. This list covers events in London only, taking place between March and May. MARCH London Enterprise Festival When: 8-19 March Where: Camden Foundry Twitter: @LEF2015 Hashtag: #LEF2015 The London Enterprise Festival brings together business leaders to share their experiences and stories on this year’s theme, starting and growing a business. Perfect for any company owner, director or manager wondering how to identify trends in their industry and grow in the current business climate. LEF covers various industries over 9 days. From gaming and fashion to education and wellbeing, there is a discussion or workshop for everyone. By having each day very focused on its theme, you have a much better opportunity to connect with the right people and take part in relevant sessions. Bonus points for a feel good factor. The organisers are committed to reinvesting the profits to providing free digital courses to unemployed and subsidising workshops and events that make better entrepreneurs and more powerful networks. Internet of Things Summit When: 12-13 March Where: etc.venues St Paul’s Twitter: @teamrework Hashtag: #IOT2015 The Internet of Things is aimed at technologists, entrepreneurs, innovators, industry leaders and managers. Recommended for futurists and those interested in breakthrough technology and cutting-edge science that will shape our future. It sounds very ominous, but with 200 leading innovators you will explore trends that promise to positively impact our lives and society. Experience two days of revolutionary discoveries, leading research and new technologies with university researchers, Paul Clarke (Ocado) and Jeremy Green (Machina Research). You can get a taste for what to expect at a casual IoT meetup event that's taking place on 28 February in London. Pipeline Conference When: 19 March Where: etc.venues Victoria Twitter: @PipelineConf Hashtag: #PipelineConf If you are looking for something smaller and more intimate, then have a look at a one-day Pipeline Conference. The conference has a more informal feel to it with talks and sessions focused on continuos delivery. The keynote speaker is Linda Rising, an international Agile thought leader, who will discuss the myths and patterns of organisational change. Other speakers will be selected anonymously and announced on or around 23 February. Bonus points for their fantastic commitment to 50/50 gender diversity and donating the profit to after school coding clubs. APRIL Chief Digital Officer Forum When: 9-10 April Where: Park Plaza Victoria Twitter: @IEGroup Hashtag: #DigiLeaders The Chief Digital Officer Forum has an impressive speaker line up that consists of senior digital professionals from global brands. Organised by the Innovation Enterprise, this summit is aimed at anyone with background in digital, analytics, ecommerce, social media and innovation. There are plenty of opportunities to take part in interactive workshops, network with attendees and discuss the future of digital. Join hundreds of other digital leaders at CDOF to hear from experts like Will Burns (L’Occitane en Provence), David Martin (Coca Cola Enterprises), James Keady (Samsung) and others. MAY BriForum London When: 19-20 May Where: etc.venues St. Paul’s Twitter: @BriForum Hashtag: #BriForum BriForum London is a highly technical conference dedicated to the best practices of end user computing, cloud, desktop virtualisation, security and application management. Keynote speaker is Brian Madden, one of the brains behind this event, but we are yet to hear about other speakers and exact topics covered. Nevertheless, BriForum promises to deliver informative two days with high profile speakers and attendees. Digital Shoreditch When: 11-24 May Where: Shoreditch Twitter: @DigiShoreditch Hashtag: #ds15 Digital Shoreditch is the trendiest event on this list. It's a vibrant festival that attracts creative, tech and entrepreneurial people, makers and doers, and others in between. Digital Shoreditch is on for two weeks and with hands-on sessions, cosmic parties and amazing speakers it promises to be one of the biggest digital community events. The full programme is yet to be announced but seeing that Mark Earls (HERD), Rory Sutherland (Ogilvy & Mather UK) and Jeremy Waite (Salesforce) are on the speaker line up, I have no doubts there will be other inspiring people joining them. Bonus points for their visionary look and feel, and Twitter profile photo. UX London 2015 When: 20-22 May Where: Trinity Laban Conservatoire of Music and Dance Twitter: @UXLondon Hashtag: #uxlondon Organised by design consultancy Clearleft, UX London 2015 brings together inspiring UX speakers and practical workshops. The conference is focused on a different theme each day and is aimed at product, web and user experience designers. On day 1 explore the secrets of product design with leading experts, such as Des Traynor (Intercom), Julie Zhuo (Facebook) and Jeff Patton (independent consultant, Agile coach and author). On day 2 improve your understanding of human behaviour and user experience by hearing from Cecilia Weckstrom (LEGO) and taking part in Sketch workshop with Meng To. Day 3 is platforms day. Learn about the latest design trends for mobile, desktop and smart TV, and join workshops and talks on responsiveness, wearable tech and designing for different screen sizes. What other conferences and events have you marked in your diary? Leave a comment below or send a tweet @LittledataUK.
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