Web Analytics applications
Checking the profitability of a banner.
Let’s imagine that we have decided to advertise in a digital newspaper. We are offered one, in two different newspapers. But we don’t really know which one we are going to hire.
Usually they will show us analytical data on the number of times the banner will be seen, visits to the website, etc. But BEWARE, they do this to sell it. It does not mean that they are false, but the fact that you have a banner on a website with 100,000 daily visits does not mean that it will be profitable, nor that all of them will click on it.
The first thing we have to define is the objective for which we are going to place the banner. If the decision is ours, we will have a clear objective. If it has been offered to us, and we have created the need, that objective may not be correct. One way or another, the objective must meet a series of requirements. That’s why I always advise using the SMART technique.
S: Specific. The goal should be specific to a project itself. It does not have to be copied from another similar project.
M: Measurable. We must be able to measure the objective, measure the percentage of that objective that has been met. An objective that cannot be measured cannot be a good objective.
A: Attainable. Goals must be real, moderate and achievable. I always give the same example: “If I have an online store, I want to be the No. 1 store in the world”. I will not be the one to take away people’s dreams, but we must set goals that we know we will be able to achieve, because an unfulfilled goal, a goal not achieved, generates negative thoughts and feelings, which in the long run can weigh down a project. You can be doing things very well, but if you have set a very high goal, and you have not achieved it, you will feel like a failure, and this is a serious problem.
A: Relevant. The goals should be relevant to the extent that we are going to measure something that has to do with our project, but that also brings us something positive. Many times we measure kpi’s and set goals that are of no use to us. Before setting a goal, we should check if achieving it will really bring us something or not.
T: Time. Any self-respecting goal must be measured in a period of time. I always say that the important thing is not the actual data, but the evolution of this data over time. Objectives cannot be eternalized. That’s why we have to set goals for a period of time.
In the case of banners the objectives could be:
- Visits to the website
- Conversions on our website
- Branding (generate brand image)
- Information about a product or a discount…
Once we have defined the objective for which we want to place a banner, we must make decisions. But we can’t make decisions if we don’t have analytical data or measured KPIs. The only data we have are the ones that digital newspapers are going to provide us with. But as I said in previous paragraphs, this data is not enough to make a decision.
The best thing to do in this case is to negotiate with two of them to place a banner for a month. We are going to track them with the Google URL creator, so that we will be able to measure the visits we get from these banners in particular.
What is this technique useful for?
To know which banner works best and to bet only on the one with the best conversions based on the objective we have.
Conversion funnels to see what users do in my store
This is the eternal question: What does a user do in my store? Or how do they move through it? Why don’t they buy? Why do we have full carts but very few sales? Why don’t they enter a certain category?
We will be able to answer all these questions with the famous conversion funnels.
Conversion funnels are filters that are applied to a certain target to verify if users follow a specific path or not.
Conversion funnels can be as simple as measuring sales after entering the homepage and a category or even measuring email marketing conversions.
Let’s imagine that we are going to generate a goal that is to get a sale. In this case the goal can be by direct conversion (sale) or by measuring the number of times the thank you page is accessed after a sale. In some cms, there is no thank you page, or they just show you a sentence on the screen. So we should opt for the first option.
We mark as filters the home page, the product category, the product and the cart.
We are not going to mark the thank you page in the filter because it is the goal we want to achieve. If we mark it, it will appear double in the funnel.
This way when we click on Funnel Graph a graph will appear with all the information related to this goal.
It is important to know that the data that will appear in the funnel graph will be the data that will be obtained from when the funnel is defined. At the moment of creating the goal, all the data will appear at 0.
Conversion funnels to see why they abandon a cart
This is another very common technique used in e-commerce. If your online store has a system called one page checkout, or one click checkout, this application is not going to help you at all. But if the checkout process is done in 3 or 5 steps we can see in which step is the one in which customers really abandon the purchase process. If we have it configured correctly we can obtain valuable information.
Brackets mode on:
- Mouse Flow (limited to 100 plays, although new plays erase the last ones. If you have a lot of visits it is not the most suitable).
- Yandex Metrics. This is the web analytics section of the Russian search engine Yandex. It is tremendously powerful, being able to reproduce both visits and see link click or scroll maps. It is unlimited, but it slows down the web a bit.
- Smartlook. I discovered it recently. You can record up to 20,000 visits per month, although it only stores 1000 and the deletion must be manual. It doesn’t slow down the web at all.
Parenthesis off mode.
When is the ideal time to launch a post?
This is another question that we get an answer to with web analytics. We explained it in this previous post: “Web analytics tricks for everyone” in which you can see how to export data from Analytics and import them into a spreadsheet to cross them and know what are the most interesting times of the day to publish.
This is really important, because the day and time when you launch the post is crucial to get a greater impact of it, and get the maximum ROI. If we also combine this with a tool that tells you at what time our audience is connected, we get a total effect.
Effectiveness of Retargeting or Remarketing
I have always said that we use Adblock (Chrome or Firefox extension to block ads on pages) because the targeting of ads and the way they are displayed is extremely outdated and out of place. In most cases they show us products or services that we have already purchased, which makes not only that the ROI is zero in that campaign, but causes a negative effect on the user who has purchased the product.
That is why it is so important to monitor retargeting and know how effective it is.
To not show ads to people(I like to talk more about people than users) who have purchased products or services, you have to configure the Pixel that is placed on the advertiser’s website, so that the Cookie identifies the person who has purchased the product and does not show ads in their navigation. This is programming and is not within the reach of everyone if you don’t have advanced knowledge.
But we can measure how effective retargeting campaigns are being.
Let’s imagine that you have a product, a soccer ball, that you are going to promote with retargeting. This means that people who have viewed the product page will see the Soccer Ball ad in Google Display ads. If the person who is viewing the advert clicks on it, they will go to a Landing Page ready to convert, which will look nothing like the Ecommerce page they originally visited.
Adwords will only give you details of ctr, QS, number of clicks …. But it doesn’t give us ROI or effectiveness metrics. This is something we have to configure ourselves.
The option here is to create a goal, Buy the product Soccer Ball, and in the funnel filter we can put the following steps:
- Landing of the ball
- Start of the purchase process (buy button)
We can put more filters, but if we put the cart steps or whatever, we can’t get the necessary data that we want to analyze.
We also have an alternative, and that is to track the adwords link to be able to measure it in a campaign and then create a segment, to visualize and even buy… But this is another story.
Also if we link adwords with Google Analytics we can get first hand information, even enabling intelligent links…
But this time we talk about being able to do it with conversion funnels and goals.
This way we are going to see how many people have bought the soccer ball, but we are also going to know how many of those who have bought the soccer ball come from the retargeting link. In addition we can also see how many people have abandoned the cart in this process, and how many visitors have left the Landing without clicking on buy. In short, with this funnel we can know:
- Users who buy the product
- Users who do not buy the product
- Users who leave the Landing without clicking on buy
- Users who click on buy but finally do not buy
(it is understood that they are users who come from the adwords banner).
It is important to know the ROI(Return on Investment) of an ad to be able to optimize it and know how effective it is being. Obviously only for retargeting that have the objective of direct conversion by product purchase or lead generation. For those whose objective is branding, this option would not be valid.
Effectiveness of E-mail Marketing campaigns in conversion funnels
It goes without saying that if we use a marketing automation program we can measure thousands of factors in a campaign, because in addition all users are categorized, or “scoritized” to be able to segment campaigns based on the behavior of this person on our website.
But for those who use “normal” marketing campaigns without automation, lead scoring, etc., we can check how these campaigns are working.
For example, let’s imagine that we use a mass emailing platform to promote a new product. The email is in text mode, and only carries a link to a Landing Page like the one above. From here it will work in the same way as the previous point. The platform already tells you the open rate, the click rate, the bounce rate… (which is different from the bounce rate in web analytics. Do you want to know the difference? Ask me), but this way we can see graphically who of those people who have clicked on the link in the email campaign finally buy the product.
We could be here doing a post of 10000 words and we still wouldn’t end up finding new uses for conversion funnels in Google Analytics. The most important thing about funnels is not knowing how to configure them, not even knowing how to read them (which sometimes is not easy). What is really important is to interpret them and be able to make the right decisions. In a Funnel Chart we can get a lot of information, we have to interpret it properly, because with some of this information we will be able to answer many questions that we have previously asked ourselves. For example, let’s imagine that we have a problem of “no purchase” or “cart abandonment” but at the same time we have a very loyal audience. With a funnel we could detect that this is producing a loop (it may be due to technical errors) in which the user returns to a previous point and never ends up closing a purchase. In this case we have to realize that this is happening because the user does not understand the purchase process correctly, or that some of the points are not well specified in the specifications. It often happens with shipping costs, or with taxes if they are not well placed.
In short, we can see that web analytics can be a lot of fun when we use it properly, and it helps us in our day-to-day decision making process.