Growth Detectives

For nearly two decades, Google Analytics has been the go-to tool for marketers and data analysts. But, as we get toward AI-powered search and privacy-first data collection, one question is quietly emerging: will there even be a Google Analytics 5?

The 2 main things that limit the number of people you track are: 1. Cookie consent banners 2. Ad blockers Depending on the profile of your visitors these things alone, can stop you from tracking more than half of your visitors. In this episode of Growth Detectives show I am going to tell you how you can prevent that from happening. So, let's start with consent banners. The truth is that privacy laws in over 60 countries require that website owners ask their visitors for consent before tracking. This consent should be given by clicking a button in a consent banner. Unfortunately, a big portion of visitors do not do that. And as a result, they cannot be tracked. So what to do about it? Should you just disrespect that and risk being fined? There is a better solution. The thing is you need to ask visitors for consent only when you want to track personal information about them and / or use techniqies that can identify them. One of them is cookies, from hich the banners took their name. However there are in fact many more of them. So what to do about it? Do not use a tracking tool, that tries to identify your visitors or collect their personal information. As simple as that. Then, you won't have to ask visitors for consent and will be able to track many more visits (although a little bit less accurately). However, there is still one problem, that can stop you from tracking a large portion of your visitors - ad blockers. This is because ad blockers actually not only block Ads themselves, but also prevent tracking.  They do it either by blocking scripts from specific sources (like Google Analytics) or by stoping them from sending data to specific domains (like Google's). However, there are 3 ways to make it more difficult for them: - server-side tracking - local hosting - ad file proxing let's start with the server-side tracking. The way it works is simple. Instead of sending traffic information directly to the tracking platform, the information is sent to your server and only then to the server of the tracking tool. The downside of this, however, is that your server has some additional work and may require an upgrade. Next we have local file hosting. In this case, the tracking script is not loaded from the domain of the tracking tool, but directly from your own server. Sometimes they are also renamed to cheat ad blockers. The downside of this solution, is that only few ad blckers can be cheated this way and the tracking file needs to be frequently updated. Last but not least, we have file domain proxying. In this case, the tracking file is still kept on the server of the tracking tool, but ad blockers believe that it is in fact hosted on your own server. This technique however has the the smallest impact of these three. So, what solutions should you use to track as much visitors as possible? Definitely a tool that does not require visitors consent and - if possible - offer server side tracking option. And these are all the solutions you can use  to maximize the number of visitors that your website tracks. Thank you.  

Hello and welcome to another episode of Growth Detectives show. I am your host Chris Planeta and in this episode we are going to talk about everything that is wrong with measuring page speed. Before we do that, however, let's think about one very important thing. How much does it really matter? How much does page speed, page load speed actually matter? Now, when you look this phrase up in Google, you might get different results saying that, for example, one second delay in page speed may result in 10-20 percent bigger bounce rate. However, none of these websites mention one super important thing - motivation.  Motivation of people that come to the website, who want to get some content, who want to buy a product, who want to do something on that website. And now, depending on how motivated they are, one second delay in page load speed may not have such great impact. The second thing that matters is the perception of speed. Because there are techniques to make your website seem much faster than it actually is and so people will have much better experience because of that. Now, let's think about the incorrect ways of measuring page speed.  So the first one, is looking at one-time snapshots of your website page speed.  Most of online tools that measure page speed give you such one-time snapshots. So, you are only getting the page load speed for one specific page at a particular time, from one particular device, with one particular screen resolution. Which is a problem. Why? Because you are not seeing the page speed results of all the other cases, of people in different countries using different devices, having different connection speeds to the Internet. I'm not saying, however, that it's totally useless. It is useful, but not to measure page load speed. What is it useful for? I will tell you about it later, but now let's concentrate on another incorrect way to measure page speed and this is measuring the speed from your own browser. This is, for example, the way Google Lighthouse does it. It measures how fast the page loads on your browser. So in this case, you are getting all the disadvantages of the snapshots I told you earlier, plus an additional disadvantage that your results are skewed by the speed of your internet connection - which of course may vary depending on the time of the day, depending on other users that may use the same connection. So, what is the right way of measuring page speed?  First, you need to have a lot of data and not only from one page, but all the pages on your website. The best way to do it, is to use your web analytics tool that measures your traffic and page load speed. Unfortunately, the most popular tool - Google Analytics - has no page load speed measuring feature in the latest version. Now, you need to create your own custom script, that measures all the page speed data and then send it to Google Analytics.  However, if you don't want to do it, if you prefer to have something that works out of the box, then I would suggest you take a look at Matomo.  Matomo is an open source alternative to Google Analytics and it gives you all the page performance numbers. So Matomo is the way to go here.  And now how to look at those numbers. Well, first you need to have at least a few hundred visits. The more, the better.  Then, when you get the data, you should segment the traffic and see how much it takes for mobile phones to load your website, how much it takes for other devices to load your website. You might even want to check how long it takes to load a site from different countries. Because if you have your website hosted on a single server in one country, then it may take significantly longer for the website to load if somebody comes from a totally different continent.  In such situations, you might want to to have a CDN set up to have your website available on different servers situated in different places in the world. Now, when you have the data and you see that there is something wrong with the page speed, if you see that there are some anomalies like pages that load significantly longer than other ones, then you should take a look if there are people whose page load speed took much longer than other users. If you still see that the numbers are greater than the average then you should take a look at the web page itself. Here is actually the only case when you should be looking at online page speed tools, because they will actually give you information what are the elements on your website that impact your page speed the most. However, it also comes with a catch - because these tools are still not perfect. And from my own experience, I noticed that if your website has a lot of content that is loaded dynamically, like some images in a slider, for example, or products, then the measured speed of page load can be greater than it actually is. So if you want to see the real numbers, you should either remove dynamically generated elements or change their settings so that the content wouldn't be generated dynamically. And only after you do all these things, you will get the right idea what's going on on your website, how long does it take to load for different visitors, for different devices and locations and what to do with pages that take significantly longer to load. And that would be all for this episode.  The next one will be published tomorrow or on Monday. And also I'll soon be launching a YouTube channel for Growth Detectives, where you can see the things that I talk about. Okie dokes, so that's it. See you soon.  

Hello, and welcome to another episode of Growth Detectives show. I am your host, Chris Planeta and in this episode, we are going to talk about simple web analytics tools - what are they, what are their advantages and disadvantages and who are they for. So. In my view, there are three qualities that make simple web analytics tools. First, they can track mostly very basic information like number of visitors, bounce rate, top pages, traffic sources and sometimes goals or events. So this is number one. Number two - the data you are getting is, in most cases, squeezed on one page. So you've got only one page with reports, with some tables, graphs, things like that. And the third thing is that there are very few ways of changing the data in the tables, segmenting traffic, filtering it. Usually it's pretty shallow when it comes to the number of options you are getting. And yeah, so these are the three things that in my view make simple web analytics tools. Some could also argue that these tools most often don't use cookies in order to track visitors. However, well, there are also other tools that don't use cookies. So I wouldn't just count it as a feature for simple web analytics tools. However, when it comes to those cookies. It is true that simple web analytics tools most often don't use cookies. They don't track personally identifiable information and as such they don't require the use of a cookie notice. So, as a result, the number of people that are tracked is much greater in comparison to tools that require cookies. However, it also comes as a disadvantage, because the cookies are actually useful to increase the precision of tracking. So without them there is big chance that a returning visitor will not be counted as a returning visitor. If this is something that is important to you, and in most cases it is, well, bad luck. Your visitors, in most cases, will not be counted as returning ones, even if they are. Now, other advantages and disadvantages.  Advantage of a simple web analytics tool is the fact that they are simple to use. They have low learning curve. They are accessible to most people without any extra trainings. They can jump right in and they can feel at home which is very nice. Tools that are much more complex, like a Google Analytics, Matomo, well, they are not the best choice for users who haven't had any experience with them before. And now when it comes to disadvantages the data that is being tracked, is mostly vanity metrics. It's not very useful in finding the issues on the website, improving the website or the business itself. So for many situations, the data that you're getting will simply not be enough. Yeah, so you'll either have to send to those tracking tools some extra events with extra information or, or you're left with vanity metrics alone, and then they will be useful only for a smaller group of people. And when it comes to groups of people, who are simple web analytics tools for? In my view, there are a few groups that can benefit from these tools. However, it all depends on how these tools are set up. First, we have website owners whose sites are either non-profit or very new. In most cases getting deeper into web analytics or more complex web analytics tools is just overwhelming for them. Right. And it's good to have some data. even though it may not be super useful, but it keeps their motivation going to see their, the numbers of, I don't know, visitors, et cetera, go up. It's always good to have data to keep your motivation to keep your spirit up.  So, now the next group of people that can benefit from simple web analytics tools are people who are running sites with affiliate links or a lot of ads. Why is that? Because in these cases, the vanity metrics that simple analytics tools track, they become your KPIs . So the number of visitors is important. The number of page views that specific pages are getting is important. And if the tracking tool that you're using can also track clicks on affiliate links or on advertisements.  So the people who are running these sites will be really, really happy with simple web analytics tools.  And finally, we have one group that may come as a surprise to some and these are CEOs. CEOs who need a dashboard with reports, with graphs, with metrics, with data showing only the KPIs, the most important stuff about their business, how it's doing. They don't need to know. All the advanced stuff, all the nitty-gritty, they just need simple to understand panel, simple numbers, simple way of getting the basic information they need, and such simple web analytics tools can give it to them. On one condition - that the KPIs that the CEOs care for are tracked by those tools. They are properly configured by the integration and sent to those analytics tools. So. In my view, these are the groups that can greatly benefit from simple web analytics tools. When it comes to other uses like online stores, like more specialized websites, business websites, I wouldn't go that far as to recommend web analytics tools beyond the first stage of running a business. So when a site is very new, okay. That's fine. You can use a simple web analytic tool. However, later you would be much, much better off using something more complex like a Google Analytics, Piwik or any of its competitors. And yeah, so this is it in this episode of Growth Detectives. Thank you very much. I hope you liked this episode. I'll post another one tomorrow or in two days. Thank you.  

Hello, and welcome to another episode of growth detectives. I am your host, Chris Planeta. And in this episode, we continue our conversation from the last episode, where I listed a few different ways of improving the quality of data that is tracked by the web analytics tools. Then I listed seven and today I'm going to tell you about 10 of them. So without further ado, let's start.  Number one. Know what data you're looking at. So this may sound silly because it's not actually something that improves the data quality. However, it's still very important. so important, in fact, that I decided to list it here at number one. Why is that? For some of you, it may be obvious for some of you, it may not, but depending on the tracking tool that you're using, you may be actually looking either at unsampled data that is collected from your website. So unsampled data is the real data, real numbers that happen there. However, there are tools that give you sampled data. So only a portion of the data is tracked on your website and some data is sometimes even AI generated. Unfortunately, data sampling and AI generation is a practice done by Google Analytics.  If you want to know more, you can just Google a behavioral modeling in Google Analytics and data sampling. You'll have something very interesting to read.  Okay, so number two.  You should turn off the consent mode or no cookies mode in your tracking tool. Why is it? Well, it's because when you're not using cookies, the data that you are getting is of slightly worse quality. You are getting much more quantity of this data, but you're getting less quality.  Number three.  Cross track. What's cross tracking? This is actually another term that I coined and it generally means that if you have different types of tracking tools installed on your website, you should have a common user identifier that is sent to all of these tracking tools so that later you will be able to see how a user was tracked by different, tracking tools, What information those tracking tools gathered on your user. Number four- you should track clicks with the middle mouse button. And yeah, you may be thinking like, Hey, am I not already tracking clicks? It's very possible that you are, but it's also very possible that you're not tracking clicks with the middle mouse button and tracking those clicks. It can be sometimes very, very important, especially for websites that have many affiliate links.  Those affiliate links, when they are clicked with the middle mouse button they are often not tracked, but should be. Number five- do not track page views of pages that are not viewed. But hey, wait a minute , am I tracking page views of pages that are not viewed? Well, yes, you are. The thing is that if you have like a standard integration of a tracking tool, when somebody opens different pages of your websites in tabs, then those tabs, even though they are not viewed. Or not yet. Yes, they are already sending the page view event to those tracking tools, but they shouldn't be. Yes, because the user might decide to close those tabs or the whole browser before taking a look on any of those tabs.  Number six- do not track page scrolling in the first three seconds after page load. When somebody comes to your website they may at the very beginning, try to look around, they may scroll the website until the very bottom in the first three seconds, only to realize that there is nothing interesting there, And leave the web page. Yes. So why should you consider this person interested in the content and send him some advertisements maybe. No, it's pointless. You shouldn't be tracking page scrolls that happen in the first three seconds after page load.  Next one- do not track form submissions if they happen in the first two seconds or three seconds after a page load. It all depends on what is the form that you want to track, how complicated and how visible it is. Usually people are not able to find a form, fill it in and send it in the first two or three seconds. If they do something like that, it's most probably either by mistake by some misclick or the submission was done by a robot.  Number eight, identify and prevent multitracking single time actions.  So let me repeat that. Identify and prevent multi tracking of single time actions.  Like, for example, you shouldn't track multi clicks. People sometimes may click twice, three times even, in the same link while they are waiting for the page to load. So why should you actually track multi clicks in the same link? That's pointless, right? You will, you're getting incorrect information in your tracking tools.  Next sometimes a page can refresh, but not because the refresh was requested by the user, but because it was triggered by some mechanism on your website. So for example, when a person adds a product to a cart, sometimes a web page can refresh. So why should you consider it another page view or another product view? This will only mess up your analytics reports. Number nine, do not track internal traffic. There are. good and bad methods of doing that.  Bad methods are, for example, requiring users to be logged in to your website so that the website can learn who this user is and whether they should be tracked or not. Why is it a bad idea?  Because in most cases it's unrealistic. People can view your website on a mobile phone just to show to their friends. So why should you request them to log in? Another bad method is to exclude users by IP. Why is that? Because people use different devices connected to different networks and those IP piece change.  So what is the correct way? The correct method is actually one that I implement in my WordPress plugin for marketing agencies. And this method is very simple. My plugin provides you with a link and this is a special link. Whoever clicks this link will no longer be tracked no matter whether they are logged in or logged out. As simple as that.  Okay. And the last one, the last method of improving the quality of tracked data is to prevent tracking payment gateways. So for example when somebody is just about to make a purchase, they are redirected to a payment gateway to leave their credit card details, they make the payment, they return to your store only to see the order confirmation page. However your tracking tool starts thinking that the last traffic source that led to conversion was in fact your payment gateway. So you should prevent tracking payment gateways. And this is my last point here. In total I discussed 17 different methods of improving quality of data that's tracked by web analytics tools. Most of these methods are implemented by my own WordPress. press plugin for marketing agencies that I told you about before. If you want to know a bit more about it, just click the link in the description of this video.  I hope you liked this episode. The next one will be coming tomorrow or in two days. ​  

Hello, and welcome to another episode of growth detectives this episode is going to be slightly different than the other ones, because it will be divided into two episodes. So today we are going to talk about ways to improve the quality of data that is tracked by web analytics tools. And this is plural web analytics tools, because most of the ideas here will apply not only to google Analytics, but also to tools like Matomo, PeeWeek Plausible Analytics, or many other ones. Okay, so let's start.  The first way to improve the quality of data is simply to check your setup of your web analytics tool. To make sure that all the pages that should be viewed that should be tracked are actually tracked as easy as that. Number two, use server side tracking. Not all tools let you employ server side tracking, but if you have a proper integration that allows you to do it and your Tracking tool has this option as well. You should definitely use it Why is that server side tracking allows you to collect data irrespective of ad blockers? So if users have ad blockers these ad blockers will block your tracking scripts. However, if you implement server side tracking then you will still be able to get this data. And another idea. Dear to improve the quality of data is to incentivize people to log into your website. Why is that? Well, as you, as you know, visitors can come to your website from different devices. At first somebody can, google your website on, on their mobile phone. Next, they can visit it using their laptop or company computer. So, you never know if somebody who comes to your website is a new visitor or a returning one. However, if they log into your website, then you will be able to send to the tracking services the ID of this logged in user. And the tracking service will be able to match the sessions from users of the same ID. This way you will be able to more accurately say whether someone is a new user or a returning one. Okay. Another way to improve the quality of tracked data is to rename and proxy the tracking scripts. This is another method to, kind of avoid being blocked by ad blockers because ad blockers, they, as I've already said, they block tracking scripts. So, if you download the tracking script directly to your server and rename it, then ad blockers will no longer see a Google analytics script that gets downloaded from Google analytics website, but they will see some randomly named script that comes from your own website. So the chance is now much smaller that this script will be blocked. Another way to improve quality of tracked data is to use UTMs. Whenever, wherever you can. UTMs are parameters that are added to the end of the URL A URL that can be shared or pasted in your, I dunno, social media posts. They can be put in your newsletter in PDF files , things like that. Yes. And information that is saved in the UTM can be read by your tracking service. And this information can for example, say that this particular user clicked a link in a PDF.  So another way to improve the quality of track. Data is not to use the default form tracking in Google Analytics. The thing is that Google Analytics 4 introduced a few automated ways of tracking some user actions. One of which is form tracking or actually tracking form submissions. The problem with this solution is. That is incredibly bad and it gives a ton of false positives. So it's much, much better if you simply stopped using it and started using some customer made solution. And the last way to drastically improve quality of tracked data that I'm going to talk about in this episode is to fix the incorrect labeling of traffic that comes from Android Applications. And this is a big one. I, I left the, the, the biggest and the most interesting one until the end. Okay. So let me, so let me explain what I mean by that. The thing is that when somebody clicks a link in an Android application, for example, for the LinkedIn or Facebook or Facebook messenger or Snapchat, yes. Then their browser opens the link. However the information that says what or who referred the traffic to your website is not recognized by by tracking tools. It's because this information, this referral information does not start with the usual HTTP, but it starts with Android app. The text android app and now depending on On the profile of your visitors you may be getting a ton of traffic from Android applications. And all of this traffic may be labeled as direct traffic. Yes, and I will give you an example here from two of my clients. In the case of Juan, about 14 percent of the traffic he was getting came from a Google search widget in Android phones. Yes. 14 percent of traffic. I mean, of direct traffic labeled as direct traffic. That's huge, right? So this information could have been labeled as Google search traffic, but it wasn't. It was labeled as direct traffic, which was of course. incorrect. And another one of my clients has quite a lot of traffic from social media applications and especially Pinterest. So it's turned out that also about like 14, 15 percent of his traffic was coming from a Pinterest application. So after adding a small script to his website I was able to correctly label all this traffic to Pinterest. Right? And what is interesting is that now we are talking only about Android applications. Yes, but we are not talking about iOS. Why is that? The thing about iOS is that applications on iPhones do not send any referral information. So We are now able to get the information from Android applications, but we are not able to get any referral information from iOS applications. However, with very simple maths, you can more or less accurately say how much traffic you are getting from the equivalent iOS applications. Simply. By looking at how much traffic you're getting from iPhones in comparison to Android. So for example, if you are getting twice as much traffic from iPhones than Android, and you are getting like let's say 10 percent of traffic from Pinterest Android application, then it would be safe to assume that about 20% is from iOS, so in total. You will be getting 30, 30%. So this is, this information is very, very important. And there are actually two easy methods to get this information and to have it visible in Google Analytics, in Matomo, in Plausible, in Pwik in other systems. However, it's impossible to correctly describe the. process, how to get this data in a podcast. That's why I will soon be recording a YouTube video about it. And I will add the link to this YouTube video, to the description of this podcast episode.  So this is it for this episode of growth detectives. Tomorrow or in two days, I will be posting another episode telling you about all the other methods to improve quality of data tracked by web analytics tools. Thank you. ​  

Hello, and welcome to another episode of Growth Detectives. I am your host, Chris Planeta. And in today's episode, we are going to talk about conversion attribution and different attribution models. And also I'll tell you why I don't like using attribution modelling, why I will never include attribution information in custom reports that I make for my customers and what I use instead. So let's dive in. First, what is attribution modelling? What's conversion attribution? For those of you who don't know, conversion attribution has one goal - to attribute part of conversion's value to different traffic sources that took part in the customer's journey. So for example, if somebody visits a page five times, every time from a different source from Google Ads, Facebook Ads, Google search, et cetera; each of these, let's call them, touchpoints should get 20 percent of the conversion value. But in reality, it's never so simple. Why is that? First because for the data to be precise, you actually need to know the full customer journey with all the touchpoints. However, nowadays, it is almost impossible to know it. Why is that? First of all, because users use different devices, they switch from their mobile phone to a laptop to a company computer. And so you can never know. You can never be 100 percent sure if somebody visits your website for the first time or is it a consecutive visit. Next, people use browsers or browser extensions that block tracking scripts. And these tracking scripts are indispensable to start tracking attributions. So this is reason number two. And reason number three - the problem with Apple iPhones. The thing is that iPhones or applications in iPhones that open websites or open links - usually I'm talking like about social media applications - they don't pass referral information to the website when it gets opened after somebody clicks a link in those apps. And so Google Analytics or other tracking tools actually have no way of knowing whether someone came from an application or from a different source. There is simply no referral information. And the fourth problem is with those tracking tools themselves. Because even though there is a problem with referrals or missing referral information in iOS devices however, this information is present in Android apps. So when somebody clicks a link in a Facebook Messenger on Android, there is this referral information getting passed through. However, this information is simply not understood by Google Analytics or other tools. And, all of this means, that the touchpoints, the traffic sources that you're seeing in your reports, are very much incomplete. So, in my view, this is one huge disadvantage of conversion attribution. The second reason why attribution modelling, in my view, is something that you shouldn't actually touch, is the fact that, well, there are many different models of attribution. You can attribute the conversions or the whole value of the conversion to the first source to the last source, divide it equally among all the sources or some combinations of them. There are also AI engines that try to solve this riddle - to put different values to different sources. But depending on which model you choose, you will get different data. So, well, actually, so what's the best model? There is no, best model. And that's the problem. So if the data that you based your conversion attribution on is incomplete and the attribution and every attribution model is imperfect, then why to use attribution modelling? So, these are the two reasons why I don't use attribution modelling. However, I will tell you what I use instead, and this is a very simple solution. However, I have not seen it discussed anywhere on the internet. So let me share it with you. The idea is very simple. When people visit your website, they do some actions. Some of them leave the page after three seconds. However, other people can stay there for longer. They can, I don't know, sign up to newsletters, they will open galleries, view products they can add products to cart, et cetera. So what I do is, I track these actions and apply point value to all of them. And this point value is then sent to tracking tools. And after some time, I create custom reports and see how many points were gathered by specific traffic sources. Like for example Google Ads or a particular Google ad gathered 650 points, then a different one got 20, things like that. So even though I don't attribute conversions or a part of the conversion value to these sources I can clearly see whether people who come from a specific source are potential customers, whether this source is valuable or not. And then this information is also very, very valuable to the marketing department. So yeah, this is basically it. Take care. Bye bye.  

Hello and welcome. I'm Chris Planeta and I'm a host of Growth Detectives show. This is our fourth episode to date. In this episode, we are talking about making web analytics reports dashboard - a dashboard that will let you see how your company or how your business, how your website is doing and how it will be doing in the near future. To create such report we need to start with the quality of traffic sources that you need to have, a number of active users that you are getting from each traffic source. And what I mean by active users? An active user is not a person who comes to your website and leaves 10 seconds later. It is a person who spends there some time, for example, a minute. It is a person who views a few pages. It's a person who scrolls your website and clicks some buttons, makes some actions that can tell you that this person actually likes what they are seeing. They are interested in the content of your website. And if you have these numbers of active users that you're getting from different traffic sources, then you can compare them to the cost of their acquisition. And this will tell you how much it costs you to get an active user.  It will be also a number that you will be able to improve in the future to lower the cost and to increase the number of the number of users you are getting. But this is step one, but there are also other things that you should put in your analytics dashboard.  Next things you should put are actually data of how many people you have on each step of your customer journey. So for example, if you have a web store, you could put their information, how many people are interested in your products, how many people added something to cart, how many people started checkout and checked out and made a purchase.  Some of this data is very easy to get some, some of it can be more difficult. So you need to set up some some custom segments in your analytics tools.  However, it is all achievable and when you get those numbers, you can put them in your analytics reports and turn them into a funnel, which will show you not only how many people there are in numbers like 300, 400, et cetera, but also how many people drop off on every stage. For example, out of a thousand active users, I'm getting only 300 people who are interested in specific products, only a hundred people who added something to cart, only 50 people who started checkout, things like that. And yeah, and actually this is it.  You don't need anything more to know how your website is performing and how it will perform in the future, or actually how your business will perform in the future. Because if you know your conversion rate, which is like 2%, for example, from the number of active users to the purchase, then you can easily say that, okay, so now I have like a thousand active users. The conversion path takes about a week and the conversion is 2%. So in a week, 2 percent of those thousand users will probably buy something from me. So this is something important, something that will let you plan for the future. And also all these numbers you are getting, even though they are very simple, they will also act as something to improve on, because you will be able to improve the number of people you have on each stage and also increase the percentage of people that move from one stage to another one. And yes, and this is everything you need to have great web analytics reports dashboard. And for those of you who are more into web analytics, who are professional marketers and are wondering "Hey, why there isn't anything about attribution conversion or attribution modeling" I will actually record another episode of this podcast. It should be out tomorrow or in two days and I will tell you there why I think attribution modeling does more harm than good and it shouldn't be used at all, actually, and especially not in your web analytics reports. Thank you. ​  

Hello, and welcome to another episode of growth detectives show. I am your host, Chris Planeta. In this episode, we are going to talk about ways to learn what's missing on your site. In the last episode, I talked about ways how to learn what content on your site is interesting for your website visitors. However, how should you know what's missing on your website?  This is something that we are going to talk about in this episode. So there are actually four ways you can learn that. The first one is very simple, it's simply to ask people and you can ask them during calls, email conversations. You can send them some emails asking for reviews, opinions. You can ask them during live chats, you can show them forms asking for opinions during different stages of their conversion paths or funnels on your website. So there are many ways to ask people for feedback. However, some of these are better. Some of these are worse. Definitely a better option would be to think of the path they are following at a given moment. So what is their final goal and then show them questions while they are, they are traveling on this path. Yes. So this is option number one. To ask people. Number two. So this is something I I like very much and it's very simple to do. It's simply to check what they search for on your website and what search results bring zero results.  The third method is very similar to to the previous One is simply to check what filters they use on your category pages. If you have like a list of products it is very likely that you also have some filters. But some, connections or combinations of those filters may bring zero results. So it's important to check what combinations bring no results.  And the last option is something that actually I coined myself. It's called a fail option or a fail path. What is it? Well normally when we are talking about the. User paths or conversion paths or funnels on a website. We assume that people travel from one yes to another. So we have a series of yeses.  So yes, I like this advertisement. It just speaks to me. Yes. I like the the image of the product. Yes. I like what it says in the in the description. Yes. I will click and add to cart button. Yes. So a series of yeses. Some of them are bigger. Some of them are smaller. However. There can always be a negation somewhere in this path. People may say, no, it, it's not for me. I would prefer something different. In most cases, people simply leave the page. Because they have no other option, and it's important to add this option. It can be either a fail option, so just simply another button that asks them, Hey, what's wrong? Is there anything we can do about your problem? Or a full fail path in your forms. If You have a form that spans over multiple pages Sometimes people are not very inclined to leave information of specific types or they don't know how to fill something in. Yes, so it's a good idea to give them an option not to respond to something, to give them an option to tell you what's wrong with the form, or even to conditionally show them an optional. Fail path. Yes. So a series of questions, one or a series of questions where you want to learn why they are not going to or they don't want to fill the form and what you can do to make it better for them.  So this concludes this episode. Thank you very much and see you soon or hear you soon in the next episode. It will be published on Monday or on Tuesday.    

Hello and welcome. I'm your host Chris Planeta. Welcome to the second episode of the Growth Detectives show. A show in which I teach you how to use data in order to grow your business. And in this episode, we are going to talk about seven ways in which you can learn what your website visitors want to know. I will start with methods that give you the most general information. And I will finish with ones that give you data that is most precise. So now you can get the general idea of what people are interested in by taking a look at what pages are visited most often. This data it doesn't actually tell you much about what specifically they want to know, but, well, it's well you need to start somewhere. You can also use tags and categories to have a broader, more general view on what content people are interested in throughout your whole website. So that's the second method. The third method is to take a look at your ad campaigns or actually the content of those ad campaigns, because the things that you promise people in those ads are things that you hope they may be interested in. So you might take a look at what what ad campaigns are clicked most and least often. Another method is looking at the attention heatmaps. Attention heatmaps are kinds of heatmaps from the heat mapping tools or session recording tools. And they specifically show you what areas of a page were looked at or what areas of the page people interacted with in those areas, there is some specific content that they were interested in. And this is just like a small tip If your website is very complicated and has many elements from one next to another it may not be clear what elements people looked at. However if you take a look at the same heat map but only from people who used mobile devices, then you will know more precisely what caught their attention.  And another, another way to learn what your website visitors want to know is to look at the keywords report from your search engines. And now I know that keywords ever since Google started using SSL, that keywords are no longer available .And neither Google nor Bing, show you keywords that brought you visitors. However, there is a way to retrieve this information using AI tools.  One of which is called keyword hero. I'm leaving a link in the description. And what this tool does it, it simply takes the data from your Google analytics and compares it with the data from Google search console and tries to find some similarities, some matches to see what keywords brought you visitors. And now we are getting to the two most precise methods that give you information of what people want to know. And the first one is table of contents. If you add a table of contents on your website and make each of the, like those elements of the, of the table, a clickable link, then you can track those clicks. And if you do it, you will know what section are they interested in, what. topic are they interested in.  And If in those sections you use tabs or hide some content in pop ups and require people to [00:04:00] click buttons to see this content, then you will know exactly what they wanted to know. And this concludes the list of seven ways to learn what website visitors want to know. The next episode of growth detectives will be released tomorrow or in two days. Thank you.  

Hello, and welcome to the very first episode of Growth Detectives. I'm your host, Chris Planeta and in this very first episode, we'll talk about something very basic. When will web analytics be actually useful to you? This episode is mostly for people who are just starting out because they may make many assumptions, incorrect assumptions. And this episode and the information here is just to straighten things out, make them more clear.  Okay. So, when will web analytics be useful for you? When you're just starting out the amount of data about your traffic will be minimal. You won't see patterns. You won't be able to correctly say which traffic source is better than the other. Because statistically the results you will be getting will be insignificant. Yes. You will simply have too little data to say that, okay, I'm 90 percent sure or 95 percent sure that this is correct, that this information is correct. So of course with time it will improve, the amount of data you will be getting will improve. However, until you actually start seeing patterns then data will be mostly useful for you in terms of like psychological support. Because seeing the numbers go up just has this psychological effect. It motivates you to go on, to keep pushing, to improve this and that in your business to invest more in marketing, to go talk to people about your products learn how they feel about it. However, I would refrain from making any changes on your website or in your business solely based on the data. Because the data will not be correct until you start seeing patterns. And what do I mean by patterns? Okay, so this is like my rule of thumb here. Pattern is when the amount of data makes you see waves in your graph charts. So, for example, when you have like monthly traffic, right, and you see that every weekend the amount of traffic goes down or increases, it depends on your website, yes. So you start seeing the waves, then the amount of data is just fine to make some evaluations to start making some decisions based on it.  Next, when you when your business starts maturing, growing when your website starts getting more traffic, you will be, of course seeing more and more patterns. You will see that, okay, so I'm a mostly visited from these and these sources, people from this ad campaign, they bring more food to the table. Then you will be able to start making some decisions and these decisions, of course, first should be tasted. Yes. How to test them using A/B testing tools. This is the best method. What are A/B testing tools? If you don't know, these are just tools that let you test a few versions of the same element of your website or content, button, whatever to see which one performs better. And of course, there is some learning curve when it comes to A/B testing. You'd need to know how to make these correctly. I definitely do not recommend going ad hoc or going commando at A/B testing. You actually really need to learn. However, when you do that it should go pretty smoothly. And then you will able to, well, test versions to see which one performs better, which one improves the funnel or your bottom line. And at this stage, your progress there will be, or making progress will be the easiest because you will be picking the low hanging fruit. You will be correcting the most visible errors in your website, in your web in your ad campaigns, things like that.  And, and what, what next. When your business matures even more than the low hanging fruit will be no more. So you will be doing A/B tests for smaller and smaller elements of your website. And so the impact will be smaller as well.  So you need to adjust to that and expect that to happen at some point. And then you will have actually two options. First, continue with these small changes and the small improvements or, option B, make a big change, big improvement - introduce a new product line, things like that - to skip this stage of like, of doing small things and actually try to run in front of the competition and not being like a step in front of them. And yeah, and that's basically it. These are the three most important stages of how you can use web analytics tools in the three stages of your business from the start to maturity. And I hope you will find it useful. So thank you very much. And the next episode will be published tomorrow or in two days.