How Google Analytics works

Google Analytics is a free Web analytics service that provides statistics and basic analytical tools for search engine optimisation (SEO) and marketing purposes. The service is available to anyone with a Google account. As a person that’s at the beginning and trying to get familiar with the field of analytics and data, it’s definitely important to understand how Google Analytics works. There are four components that come together and make Google Analytics work: 1. Collection 2. Processing 3. Configuration 4. Reporting Collection: Data can be collected from different sources, such as a website, a mobile application or pretty much any device that has a connection to the internet. For a website, in order to collect the information, we need to include a Tracking code (JavaScript). This code should be included on every single page of the website in order for Google Analytics to capture the information properly. The JavaScript that we get from Google is okay, but don’t forget that it tracks a limited amount of information. If you are active in a niche field of work, you might want to take a look at adapting that code in order to track the correct data. For a mobile application, we need to use a specific software development kit (SDK), depending on the operating system. In this case, activities will be tracked instead of pageviews. Because we might not always have an internet connection available, the hits will be stored and sent to afterwards to Google’s collection centres. Processing + Configuration: The processing step is the one that takes the longest to finish. It can take anywhere up to 4 hours (24 hours in Google's T&Cs) to turn all the raw data into reports that you are able to interpret and monitor. This doesn’t happen easily, but the only way you can skip the queue is by paying for Google Analytics 360. In Google Analytics, the configuration part comes in and it applies certain filters to the data that is collected. While some of those filters (new or returning users, linking between pages and time spent on certain pages) are pre-configured, you also have the possibility to apply some filters of your own to this process. Remember that you will not be able to change that information once it is stored in the database. Reporting: The final step what the users get to see. By using Google Analytics' own interface, you have access to all the processed information and this is the place where you can manage it from. There is also the possibility of using different applications by creating a custom code in the reporting API. Here is a short list of benefits that you will gain after using Google Analytics: 1. Visitor Segmentation: New vs Returning users, Geographical location and referral source. 2. Page visits: Finding out which pages are the most visited. 3. Locating the website: Finding out how the users got to your website and tracking the keywords they used. 4. Website optimization If you'd like some more information, please get in touch or leave a comment below! Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2017-03-15

How to improve your landing pages with clear CTAs

In the previous blog post, how to improve your landing pages using Google Analytics, we started analysis what makes a good landing page. Some of the ideas were related to call to actions. Your landing page must have a call to action (CTA) correlated with the marketing campaign and the full content of the page. Clear and unambiguous CTA(s) If you are offering app access, go with "Get Started" or "Create account" and don't say “Get your free ebook” or “go” or “submit”. Say short and clear what you want them to do. Don't mislead the users and don't use fancy words. When you're choosing the CTA for your landing page you should consider these three: what you say how your customer will interact with it where to place it What to say is the wording. If you want the customer to subscribe to the newsletter say "subscribe to the newsletter", if you want them to buy say "buy", if you want them to call say "call". Keep it short and clear. If the customer needs to subscribe you need to provide them with the field were to add their email address; If you want them to call you then you should use a dial function for mobile users or show the number for the desktop users; If you want them to buy then the press of the button should redirect them to a page where they can choose the option for delivery and payment. Where to place the call to action in your landing page is simple - where the customers will see it first. I presume you already have event tracking, in place (if no, find out how to set up in this blog post: Set up event tracking in GTM ). Based on some numbers from Google Analytics, let's see how good and bad engagement looks like for a landing page. Find out the level of engagement with the page Bounce rate: This will show you the number of people that entered this page and left without taking any other action (like seeing the second page or clicking on the call to action). The bounce rate will tell you how your whole landing page is engaging with the audience. In the example above, the landing page, /find-more has a bounce rate of 98,8%. This is very bad! On the other side, we have the landing page apps.shopify.littledata with 0% bounce rate. This is the holy grail of landing pages. These means that from an engagement point of view your landing page is perfect. As a rule: You should aim for at least the same bounce rate as you have on the entire website as a medium. Find out if your call to action performed Method 1 - Deducting from landing page report Go into Google Analytics -> in the search bar search landing page -> Choose Site content - Landing pages. Click on your landing page name and now add a second dimension: Second page. Find the link where your call to action redirects and analyse all elements in this report. If you don't have events in place, you will still be able to see how your traffic is clicking through the links on your landing page. If your landing page has more than 1 action then you can add a second dimension on the landing page report and see what was the second page they visited. In the example above, the call-to-action redirected them to the apps.shopify.com/littledata. From the numbers of sessions, we can see that only 10% of the users clicked the call-to-action button. 89% of the people wanted to find more about the product before purchasing. This is the example of bad engagement. The fact that 89% of the people wanted to find more means that we need to provide more details on the landing page and maybe have a clearer call-to-action. Method 2 - Deducting from Top Events report For this, go to Google Analytics and search for Top Events and add a second dimension to the report "Page". You can also build a custom report so you see the number of people that saw the page and the number of people that took the call-to-action. Have any questions? Comment below or get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2017-03-14

The Freemium business model revisited

After I concluded that freemium is not the best business model for all, the continued rise of ‘free’ software has led me to revisit the same question. In a fascinating piece of research by Price Intelligently, over 10,000 technology executives were surveyed over 5 years. Their willingness to pay for core features of B2B software has declined from 100% in 2013 to just over 50% today – as a whole wave of VC-funded SaaS companies has flooded the market with free product. For add-ons like analytics, this drops to less than 30% willing to pay. “The relative value of features is declining. All software is going to $0” – Patrick Campbell, Price Intelligently Patrick sees this as an extension of the trend in physical products, where offshoring, global scale and cheaper routes to market online have led to relentless price depreciation (in real terms). I’m not so sure. Software is not free to manufacture, although the marginal cost is close to zero – since cloud hosting costs are so cheap. The fixed cost is the people-time to design and build the components, and the opportunities for lowering that cost – through offshoring the work or more productive software frameworks - have already been exploited by most SaaS companies. To pile on the pain, a survey of software executives also found that the average number of competitors in any given niche has increased from 10 to 15 over those 3 years. Even if software build costs are falling, those costs are being spread over a small number of customers – making the chance of breaking even lower. And the other big cost – Customer Acquisition (CAC) – is actually rising with the volume of competition. To sum up the depressing news so far: 1. Buyers have been conditioned to expect free software, which means you’ll have to give major features away for free 2. But you’ll have to pay more to acquire these non-paying users 3. And next year another competitor will be offering even more for free What is the route of this economic hole? Focussing on monetising a few existing customers for one. Most SaaS executives were focussed on acquiring new customers (more logos), probably because with a free product they expected to sweep up the market and worry about monetization later. But this turns out to be the least effective route to building revenue. For every 1% increment, Price Intelligently calculated how much this would increase revenue. i.e. If I signed up 101 users over the year, rather than 100, that would increase revenue by 2.3%. Monetization – increasing the Average Revenue Per User (ARPU) – has by far the larger impact, mainly because many customers don’t pay anything currently. In contrast, the impact of customer acquisition has fallen over 3 years, since the average customer is less likely to pay. Monetization is not about increasing prices for everyone – or charging for previously free features – but rather finding the small number who are willing to pay, and charging them appropriately. My company, Littledata, has many parallels to Profit Well (launched by Price Intelligently). We both offer analytics and insights on top of existing customer data – Littledata for Google Analytics behavioural data, and Profit Well for recurring revenue data from billing systems. And we have both had similar customer feedback: that the perceived value of the reporting is low, but the perceived value of the changes which the reporting spurs (better customer acquisition, increased retention etc) is high. So the value of our software is that it creates a requirement – which can then be filled by consulting work or ‘actionable’ modules. For myself, I can say that while focusing on new customer acquisition has been depressing, we have grown revenues once a trusted relationship is in place – and the customer really believes in Littledata’s reporting. For Littledata, as with many B2B software companies, we are increasingly content that 80% of our revenue comes from a tiny handful of loyal and satisfied users. In conclusion, while the cover price of software subscriptions is going to zero, it is still possible to generate profits as a niche SaaS business – if you understand the necessity of charging more to a few customers if the many are unwilling to pay. Freemium may be here to stay, but if customers want the software companies they rely on to stay they need to pay for the benefits. Would you like to further discuss? Comment below or get in touch!

2017-03-10

How to improve your landing pages using Google Analytics

Landing page optimisation is one part of a broader digital marketing process called conversion optimisation, or conversion rate optimisation (CRO), with the goal of improving the percentage of visitors to a website that becomes sales leads/or customers. Let's see how to improve your landing page performance. There are some things to check when you want to improve the conversion rate of a particular page. In order to get the best data, we use Google Analytics and Hotjar. I will start with Hotjar because it is faster! With Hotjar you will understand what users want, care about and interact with on your site by visually representing their clicks, taps and scrolling behaviour. This is shown with nice videos of a user's journey leading to conversion. With Hotjar, you can see what confuses people, what is not clear and if for your customer point-of-view is clear on your landing page. And now the hard and exciting part: Analyse the data collected in Google Analytics. If you think that the home page is a landing page please read this before you go further: Website Homepage vs Landing page - what's the difference? and this: Don’t obsess over your homepage – its importance will decrease over time! When a visitor clicks on a Pay-Per-Click (PPC) ad, they're taken to a landing page — a web page whose sole purpose of existence is to entice people to take an action. If done well, it could be the most effective marketing weapon in your arsenal. The correct analysis of data can save you a lot of money or even your business. If your visitors donʼt know what to do when they land on your landing page, then you are throwing your advertising money out the window. Your call-to-action (CTA) is the primary conversion goal of a visitor to your landing page. Next, I give you some examples of common actions that you might want a customer to do on your landing page: purchasing a product subscribing to a newsletter calling you on the phone downloading an ebook or whitepaper watching a demo requesting information Let's find out, step-by-step if your landing page is a winner using this checklist. Click on them to find out how to analyse and interpret data CTA(s) clear and unambiguous Do what you say and say what you do Don't be like Trump. Leave the Amazing! Awesome! words elsewhere Less is more Keep it where it can be seen Know your clients Twice is better Design matters Choose what matters the most CTA(s) clear and unambiguous Google Analytics report: "Landing pages" with a second dimension added to the report: "Second page" If you are offering an app access go with "Get Started" or "Create account" and don't say “Get your free ebook” or “go” or “submit”. Do what you say and say what you do Google Analytics report: "Landing pages" with a second dimension added to the report: "Second page" analyses the bounce rate on the call-to-action link. Donʼt promise one thing and then deliver something else or even worse nothing at all (a 404 page). To follow the same example, if you have an app and say "30 days free trial" don't let people click 'try for 30 days' and on the next page provide a PayPal form to charge them for a month period. Don't be like Trump. Leave the Amazing! Awesome! words elsewhere Google Analytics report: "Pages" see how many FAQ and Terms pageview you have. Resist the temptation to include bloated adjectives. Such claims are likely to make people think you are overselling and trying too hard. Less is more Google Analytics report: "Top Events" with a second dimension added to the report: "Page" analyses the clicks on your call-to-action versus other clicks in page or scroll actions. Make space for your call-to-action. Let them breathe visually. Using more whitespace will allow your button or statement to stand out on the page. Colour choice is important here also; create a high contrast between the call-to-action and surrounding elements to assert it’s dominance. Keep it where it can be seen Google Analytics report: "Top Events" analyse the scroll tracking. See how far your visitors are scrolling down If you have a long page, donʼt put the call-to-action below the fold. Take into consideration, the different screen sizes and adapt your landing pages for the most common. Most of the users will not scroll far down the page so be sure to put your value proposition and your call-to-action as a first-seen element in the page. Know your clients Google Analytics report: "Demographics - Language" Speak your client's language. Provide different landing pages based on country. Advertise differently based on specific demographics. However good your product or service is, the simple truth is that no one will buy it if they don't want it or believe they don't need it. And you won't persuade anyone that they want or need to buy what you're offering unless you clearly understand what it is your customers really want. Twice is better Google Analytics report: Combine "Top Events" (for scroll tracking) and "All Pages" for the propotion of sessions with FAQ/Terms pageviews Not all customers are ready to engage right away and might need some supporting information to ease their worries or answer their questions. If you are asking someone to buy something, a sensible secondary call-to-action can be to download a product brochure. This keeps them in your realm of influence (as opposed to leaving to do research elsewhere) and builds confidence. Ensure that the safety net CTA doesnʼt compete in size and visual dominance – often a simple text link is adequate, beneath the main big action button. If you are asking someone to purchase online, offering a phone number for phone orders can make a potential customer more likely to convert if thatʼs their preferred contact method. Design matters Google Analytics report: "Source/medium" shows the bounce rate for each campaign Carry your primary call-to-action throughout the entire acquisition and conversion experience, from audience acquisition ads (PPC, email, banner, social media link) through your landing page and on to the final destination page. Choose what represents you the most (maybe some colours or even the call-to-action itself), you should be able to look at the page and have your eye immediately drawn to the action area. Be audience appropriate Google Analytics report: there is no report in Analytics for this. Just remember your experience when reading an email or a Facebook comment Previously, I said to speak the customers' language. Now I'm saying to take care what they can interpret. Reading a statement is different from hearing it. So don't be too pushy, don't use a lot of exclamation signs, don't use a lot of caps lock wording and be a friend when they say what they feel when they see the call-to-action. I recommend reading this blog post from January: How to improve your conversion rate optimisation and this one: Conversion friendly experiences: reducing landing page friction with psychology. These two are related and complementary to the actions you're trying to take. In the next couple of weeks I will go deeper in each section and show you how good and bad engagement looks like for a landing page. Have any questions? Get in touch with our experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2017-02-17

Shine a light on ‘dark’ Facebook traffic

If Facebook is a major channel for your marketing, whether sponsored posts or normal, then you’re underestimating the visits and sales it brings. The problem is that Facebook doesn’t play nicely with Google Analytics, so some of the traffic from Facebook mobile app comes as a DIRECT visit. That’s right – if a Facebook user clicks on your post on their native mobile app they won’t always appear as a Facebook social referral. This traffic is ‘dark Facebook’ traffic: it is from Facebook, but you just can’t see it. Since around 40% of Facebook activity is on a mobile app, that means the Facebook traffic you see could be up to 40% less than the total. Facebook hasn’t shown much interest in fixing the issue (Twitter fixed it, so it is possible), so you need to fix this in your own Google Analytics account. Here are three approaches: 1. Basic: use campaign tagging The simplest way to fix this, for your own posts or sponsored links on Facebook, is to attach UTM campaign tags to every link. Google provides a simple URL builder to help. The essential tags to add are “utm_source=facebook.com” and “utm_medium=referral”. This will override the ‘direct’ channel and put all clicks on that links into the Facebook referral bucket. Beyond that, you can add useful tags like “utm_campaign=events_page” so you can see how many click through from your Facebook events specifically. 2. Moderate: use a custom segment to see traffic What if much of your traffic is from enthusiastic brand advocates, sharing your pages or articles with their friends? You can’t expect them to all use an URL builder. But you can make a simple assumption that most users on a mobile device are not going to type in a long URL into their browser address bar. So if the user comes from a mobile device, and isn’t visiting your homepage (or a short URL you deliberately post), then they are probably coming from a mobile app. If your website is consumer facing, then the high probability is that that mobile app is Facebook. So we can create a custom segment in GA for traffic which (a) comes from a mobile device (b) does not have a referrer or campaign (i.e. direct) (c) does not land on the homepage To start you need to create a segment where source contains 'facebook'. Then add the 'Direct mobile, not to homepage' segment: Next, you can create a custom report to show sessions by hour: You should see a strong correlation, which on the two web properties I tested on resulted in doubling the traffic I had attributed to Facebook. 3. Advanced: attribute micro spikes to Facebook Caveat: you’ll need a large volume of traffic – in excess of 100 visits from Facebook a day – to try this at home The final trick has been proved to work at The Guardian newspaper for Facebook traffic to news articles. Most Facebook activity is very transitory – active users click on a trending newsfeed item, but it quickly fades in interest. So what you could do, using the Google Analytics API, is look for the ‘micro spikes’ in referrals that come from Facebook on a minute-by-minute basis, and then look at the direct mobile visits which came at the same time, and add these direct spikes to the total Facebook traffic. I've played around with this and it's difficult to get right, due to the sampling Google applies, but I did manage to spot spikes over around 5 minutes that had a strong correlation with the underlying direct mobile traffic. Could these approaches work for your site?  I'm interested to hear. (Chart: Dark Social Dominates Online Sharing | Statista)   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2017-02-09

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

Cross Domain tracking for Eventbrite using Google Tag Manager (GTM)

Are you using Eventbrite for event registrations? And would you like to see the marketing campaign which drove that event registration correctly attributed in Google Analytics? Then you've come to right place! Here is a simple guide to adding a Google Tag Manager tag to ensure the correct data is sent to Eventbrite to enable cross-domain tracking with your own website. Many thanks to the Lunametrics blog for their detailed solution, which we have adapted here for GTM. Before this will work you need to have: links from your site to Eventbrite (including mysite.eventbrite.com or www.eventbrite.co.uk) the Universal Analytics tracking code on both your site and your Eventbrite pages. only have one GA tracking code on your own site - or else see the Lunametrics article to cope with this 1. Create a new tag in GTM Create a new custom HTML tag in GTM and paste this script: [code language="javascript"] <script> (function(document, window) { //Uses the first GA tracker registered, which is fine for 99.9% of users. //won't work for browsers older than IE8 if (!document.querySelector) return; var gaName = window.GoogleAnalyticsObject || "ga" ; // Safely instantiate our GA queue. window[gaName]=window[gaName]||function(){(window[gaName].q=window[gaName].q||[]).push(arguments)};window[gaName].l=+new Date; window[gaName](function() { // Defer to the back of the queue if no tracker is ready if (!ga.getAll().length) { window[gaName](bindUrls); } else bindUrls(); }); function bindUrls() { var urls = document.querySelectorAll("a"); var eventbrite = /eventbrite\./ var url, i; for (i = 0; i < urls.length; i++) { url = urls[i]; if (eventbrite.test(url.hostname) === true) { //only fetches clientID if this page has Eventbrite links var clientId = getClientId(); var parameter = "_eboga=" + clientId; // If we're in debug mode and can't find a client if (!clientId) { window.console && window.console.error("GTM Eventbrite Cross Domain: Unable to detect Client ID. Verify you are using Universal Analytics."); break; return; } url.search = url.search ? url.search + "&" + parameter : "?" + parameter; } } } function getClientId() { var trackers = window[gaName].getAll(); return trackers[0].get("clientId"); } })(document, window); </script> [/code]   2. Set the tag to fire 'DOM ready' Create a new trigger (if you don't have a suitable one) to fire the tag on every page at the DOM ready stage.  We need to make sure the Google Analytics tracker has loaded first. 3. Test the marketing attribution With the script working you should see pageviews of the Eventbrite pages as a continuation of the same session. You can test this by: Opening the 'real time' reporting tag in Google Analytics, on an unfiltered view Searching for your own site in Google Navigating to the page with the Eventbrite link and clicking on it Looking under the Traffic Sources report and checking you are still listed as organic search after viewing the Eventbrite page Need more help? Comment below or get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2017-02-07

WWI Codebreaking and Interpretation

Reading Max Hasting’s excellent book on The Secret War, 1939-1945, I was struck by the parallel between the rise of radio communications in the 1930s and the more recent rise in internet data. The transmission of military and diplomatic messages by radio in the 1930s and 1940s provided intelligence agencies with a new gold mine. Never before had so much potential intelligence been floating in the ether, and yet it threatened to flood their limited manpower with a tide of trivia. The bottleneck was rarely in the interception (trivial with a radio set) or even decryption (made routine by Bletchley Park with the Enigma codes), but rather in filtering down to the tiny number of messages that contained important facts – and getting that information in real time to the commanders in the field. The Ultra programme (Britain’s decryption of German radio intercepts) was perennially understaffed due to the fact that other civil servants couldn’t be told how important it was. At Ultra’s peak in 1943, only around 50% of the 1,500 Luftwaffe messages a day were being processed – and it is unknown how many of those were in time to avert bombing raids. The new age of technology provided an almost infinitely wide field for exploration, as well as the means of addressing this: the trick was to focus attention where it mattered. The Secret War, page 203 The ‘new age of technology’ in the last two decades poses much the same problem. Data on internet behaviour is abundant: there are countless signals to listen to about your website performance, and the technology to monitor users is commonplace. And the bottleneck is still the same: the filtering of useful signals, and getting those insights to the ‘commanders’ who need them in real time. I started Littledata to solve this modern problem in interpreting website analytics for managers of online businesses. There is no decryption involved, but there is a lot of statistics and data visualisation know-how in making billions of data points appreciable by a company manager. Perhaps the most important aspect of our service is to provide insights in answer to a specific question: Group-Captain Peter Stewart, who ran the Royal Air Force’s photo-reconnaissance operations, was exasperated by a senior offer who asked for ‘all available information’ on one European country. Stewart responded that he could only provide useful information if he knew roughly what intelligence the suppliant wanted – ‘naval, military, air or ecclesiastical’. The Secret War, page 203 In the world of online commerce, the question is something like whether the client needs insights into the checkout conversion rate of all customers (to improve site design) or for a specific marketing campaign (to improve campaign targeting). So by focusing on insights which are relevant to the scale, stage or sector of the client company, and making these accessible in a real-time dashboard, Littledata can feed into decision making in a way that raw data can never do. Want to discuss this further? Get in touch or comment below!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2017-02-01

Try the top-rated Google Analytics app for Shopify stores

Get a 30-day free trial of Littledata for Google Analytics or Segment