How to conduct an audit of website analytics

The decisions you make are based on the quality and completeness of the data in your reports. Therefore, before you analyze any reports, you must audit your website analytics and ensure that your data is collected correctly. 

In this article, we tell you what to pay close attention to when setting up website analytics and what reports you can use to check the quality of data collected in Google Analytics.

If you require a full audit of your site, you can request a consultation with OWOX BI. Sign up for a demo and we’ll discuss possibilities.

At OWOX, we choose Google Analytics for ourselves and advise our customers to use it for their website analytics too. There are several reasons for this. 

According to a graph by StatCounter of search engine market shares worldwide from 2017 to 2019, Google is still the leading search engine across the globe. It accounts for more than 90% of all searches.

Google’s main source of income is advertising. Accordingly, it can allocate most of its resources to the development of related tools such as Google Analytics and Google Ads. The main advantage of Google Analytics is that most of the functionality is available in the free version. Therefore, it’s attractive for both small and large businesses. 

Another strong argument for Google Analytics is the user experience. If you look at the feedback of G2 Crowd visitors in the digital analytics segment, you’ll see that Google Analytics is at the top.

Now let’s consider Google Analytics settings. The first thing we want to pay attention to is data security. Google has many certificates that confirm its ability to securely store your data. 

In addition, Google Analytics has a very simple system for providing access to data at different levels, though many users don’t pay attention to this functionality. Its relevance will depend on the size of your company. We recommend you check who has access to your data every time you dismiss or hire an employee.

For example, say you work with an advertising agency and give its employees access to 5 or 10 different accounts. Then you stop cooperating with that agency but forget to cut off access to those accounts. As a result, employees of this ad agency can still view your website and ad campaign statistics.

To avoid this, regularly check and update access permissions in Google Analytics. You can do this from the Admin tab by selecting User Management at the account, property, or view level:

With this setting, you can give each user or agency the rights they need and access to the data required for their work.

Clicking the bell icon in the upper right corner of Google Analytics opens a window with diagnostics messages. Most users ignore them, but in some cases, they can be very useful.

Google Analytics sends error notifications about:

• Exceeding hit limits
• Incorrect integration with AdWords
• Missing UTM settings in campaigns
• The presence of anomalies, such as targets for which conversions have suddenly ceased to register

Try to check such messages, especially those marked red — these are critical errors.

In the Property Settings, there’s a field called Industry Category that indicates your area of activity. Many companies consider this setting unimportant and ignore it.

However, if you don’t specify an industry category, you won’t have access to templates to create targets in Google Analytics. These templates are tailored to different industries (finance, gaming, real estate, etc.). If you don’t specify an industry in your account, templates will be disabled.

The next thing to pay attention to is setting up manual or automated tagging of advertising campaigns:

If you specify UTM tags manually, you must check the Advanced Settings box so that when traffic enters your account, manual campaigns are given priority. However, if no UTM tag is specified in the URL, the value will be drawn from the automatic markup. For more information on this, see Google Help.

There’s also a Property Hit Volume field in the property settings. It shows how many hits have been transferred from your site to Google Analytics in the last day, week, and 30-day period. Pay attention to this data, as the free version of Google Analytics has a limit of 10 million hits per property every 30 days.

If you see you’ve had more hits in the last 30 days than Google Analytics allows, you need to do something about it. Google Analytics won’t immediately disable your property, but if you ignore this message and the number of hits exceeds 30 to 50 million, you run that risk.

The next setting is the timeout for sessions and campaigns. A session is a set of user interactions (hits) on your site. If a user performs an action on your site and then doesn’t do anything for a while — i.e. they don’t close your page but simply don’t interact with it — by default the session will be closed in 30 minutes. 

For example, say someone goes to your website, clicks on a few buttons, then goes to the kitchen to make tea and leaves the tab open. If they return and continue to interact with this tab 31 minutes later, Google Analytics will consider it a new session. 

But for some sites, the default session timeout of 30 minutes is not appropriate. For example, the duration of one film can be two hours or even longer. So online streaming services should increase the session timeout. 

What is a campaign timeout? Let’s consider an example. Say you launched a New Year’s campaign in the second half of December. Users saw this campaign for 2 to 3 weeks, and Google Analytics recorded the corresponding traffic. 

But remember that Google Analytics uses the Last Non-Direct Click attribution model by default. So if someone went to your site by clicking on a link in an ad in January, Google Analytics would attribute the value of that transition to their previous interaction from the New Year’s campaign, even if that campaign had already been disabled. 

By default, Google Analytics has a campaign timeout of six months, but you can make it shorter. To do this, select Tracking Info –> Session Settings in the property level section.

The Tracking Info section also includes a Referral Exclusion List that lets you exclude any sources from your referral reports.

When exclusions are useful: 

1. If your company has multiple domains, it makes sense to list them as exceptions so they aren’t considered sources of transitions. At the same time, if you have subdomains — say, with names of regions — then you don’t need to list all of them. Just specify the primary domain.
2. If customers are forwarded to the site of a payment system, this payment site should also be included in the list of exceptions so it isn’t considered in referrals.
3. If users can authorize using a Facebook or Google account, the URLs for automated authorization should also be listed as exceptions.
4. When you don’t want to see any other particular sources in your referral reports.

When you create parameters for data, you can select from four levels (access areas) in Google Analytics: View, Session, User, and Item. How data is displayed in Google Analytics reports depends on this level.

For a single interaction (a click on a button or link, for example), the data parameters you transfer will mainly be at the View level. That is, you’re directly interested in the parameters of a particular interaction. 

For the User ID or its key parameters — for example, age — you must specify the User level so you can see all interactions of the user with this User ID.

The Item level is used primarily for Enhanced Ecommerce events. For example, if in one hit you can have views of five products, Enhanced Ecommerce events allow you to assign each its own unique value. Accordingly, you can select the Product level and then view your additional settings in Enhanced Ecommerce reports. 

The Session level must be selected if you want to distribute the value of any parameter throughout the current user session — for example, in an A/B test. For instance, say an event occurs during checkout and you need to attribute all interactions within the session to variant A or B.

A session-level parameter will be attributed to all hits within a session no matter what the user does. 

There are only two levels of dimensions: View and Item. The logic for assigning dimension levels is the same as for parameters. 

You can view and change the levels of parameters and dimensions in the property settings: Custom Definitions –> Custom Dimensions and Custom Metrics.

Before you check your view settings, decide on which view you want to focus on. Then in the view settings, see that the User-ID feature is enabled.

You can enable User ID tracking in the property settings. You can then create a User ID view.

If the User ID is disabled, the view will contain data for all users, both authorized and unauthorized. 

If it’s enabled, only sessions of authorized users will be included in this view. That is, if a user has an account on your site but doesn’t log in, their session will not be included.

Before analyzing your reports, make sure you’re satisfied with the completeness of your data.

Filters allow you to include or exclude traffic from reports. For example, say you have a website where customers can make purchases and traffic comes from a certain region. At the same time, your company has many employees who also visit the site but are not the target audience. 

The first thing to do is to cut out the traffic that employees generate. You can filter it by the IP addresses of your offices or agencies. Filters are configured at the view level.

If your business works in one time zone, the Time Zone Country setting is not critical to you. If you work in several different time zones, we recommend that you create a separate view for each time zone to analyze your data accurately.

You can also configure bot filtering at the view level. Google Analytics doesn’t disclose the logic by which it detects traffic from spiders and bots. However, it makes sense to select this option to clear your data of unnecessary noise.

If you have internal search on your site, we recommend that you enable site search tracking right away. It will allow you to see what goods and services users are looking for on your site. 

The parameter you need to enter in the Query parameter field can be found by going to your site, typing a query in the search bar, and pressing enter. The parameter name will appear in the URL after the question mark and next to the query text. This value can be different for each site. If you have several similar values on your site, you can list them separated by commas (up to 5 values).

The next important setting is Enhanced Ecommerce. It will allow you to see the user’s entire funnel on your website. Prior to Enhanced Ecommerce in Google Analytics, there was a standard eCommerce plugin that mainly focused on buying.

With the new Enhanced Ecommerce module, you have the opportunity to trace the entire path through your funnel, from viewing the item to buying it. This allows you to see at what stage users fall out of your funnel so you can prevent them from doing so. 

You can enable Enhanced Ecommerce Reporting at the view level. You can also add checkout steps for sites where checkout takes place on more than one page. You can manually name these steps. Next, we’ll take a closer look at the reports that will become available to you after you turn on Enhanced Ecommerce.

Each time you introduce new functionality or make a critical change on your website, we recommend you take notes about it in Google Analytics. Otherwise, you may get into a situation when your statistics change dramatically for the worse and you forget that two months ago you launched new functionality.

In order not to forget what you did, enter notes in the view settings.

Google Analytics reports use their own channel grouping by default. Traffic is assigned to a channel by internal system rules. However, users may find a large proportion of traffic falling into the (Other) group. It could be 20% or more.

Naturally, it’s important for businesses to see and distinguish all channels. To do this, we recommend that you configure custom grouping, minimizing the traffic that falls into the (Other) group. 

There are two configuration options. First, you can make changes to the default grouping (though historical data will remain unchanged). To ensure that all data (new and historical) is in a single format, however, we recommend that you go with the second option: immediately create a custom grouping of channels according to your own rules. This setting is within the view.

Custom alerts are needed to quickly learn about critical changes in key performance indicators on your site. For each business, the KPIs can be different. For ecommerce sites and retailers, the most important KPI will be revenue. For sites that don’t sell things, it will be traffic or a target action. 

By defining key metrics, you can configure critical change alerts. For example, you can set an alert when your revenue goes down or up by a certain percentage relative to the previous day, week, or month. You can set conditions for sending these alerts in the Special Notifications section.

Read more about this in our article on automating reports in Google Analytics.

Here’s the tricky bit! If you look closely at this screenshot, you’ll see that the problem I was notified about happened on March 11, but I didn’t get the alert until March 14. The speed of the notification depends on the indicator you choose.

If delayed alerts won’t work for you and you want to receive notifications as soon as possible, you can use alternative tools to receive notifications about critical changes on your site in near-real time. For example, you can do this by uploading raw unsampled data from Google Analytics to Google BigQuery. And then set up automated reports in Google Sheets using data from Google BigQuery and send them to email.

The paid version of Google Analytics 360 allows you to do this too. It has automatic integration with cloud storage (BigQuery Export), in which you can analyze data using SQL. 

Once you’ve configured data export, you’ll receive the current day’s data table in Google BigQuery. The data in this table is updated every 8 hours. Accordingly, if a critical change happens in the morning, you’ll only learn about it 8 hours later.

Google Analytics 360 also allows you to set up real-time data transfer at an additional cost of $0.05 per gigabyte. In this case, the information in the Google BigQuery table will be updated every 15 minutes, but some parameters will not be available in this table:

• userId
• trafficSource
• hits.latencyTracking
• hits.publisher

If you don’t like Google Analytics 360, you can use OWOX BI, which also allows you to transfer data from your website to Google BigQuery almost in real time. This option will update your current day table every 15 minutes. In addition, you can see data in the table on the costs of all your advertising sources, which is not the case with Google Analytics BigQuery Export tables. 

Plus, OWOX BI has an optional OWOX User ID that allows you to identify users who have visited your sites from different domains. You’ll be able to know that these are the same users without setting up cross-domain tracking.

You can read more about the differences between OWOX and Google Analytics 360 in our article on how OWOX BI differs from Google Analytics 360.

Why is it important to have data in near-real time? So you can respond quickly to critical changes in key indicators on your site. Naturally, you won’t be able to follow all reports in Google Analytics. Therefore, we recommend that you set up separate dashboards for each KPI group and also set up custom notifications. 

By opening one dashboard, you’ll be able to see in real time what’s happening on your site, for what sources revenue has grown or expenses have increased, etc.

In the links below, you’ll find examples of dashboards from OWOX BI that you can use as templates to create your own.

• Technical performance
• Digital Marketing KPIs
• Marketing Attribution

If you want to see additional data on your dashboards, contact us. We’ll be happy to help you set them up.

Let’s now look at the reports in Google Analytics that you need to monitor to see how complete the information you collect from your website is.

Let’s say that recently, many users have been using VPNs to visit your site. If you go to the Audience –> Geo –> Location report and see that your users’ countries are badly out of line with your expectations, there’s no point in focusing on such data. Because if your business is in Norway and half of your users supposedly come from Uganda, the regional report won’t be too informative.

In such cases, we recommend seeking out alternative ways of collecting data on the region your visitors are coming from. For example, you can use a custom parameter. If your site provides some opportunity for users to choose which city or region they’re in, you can transfer this information to user parameters (as a Custom Dimension):

• City Name
• City ID
• Region
• etc.

This way you’ll get more accurate statistics without unnecessary noise.

Next, you should review the All Traffic –> Campaigns –> Cost Analysis report. By default, only Google campaign costs are available here. To see data on other paid sources, you’ll need to connect them yourself. Doing so will allow you to compare how much you spend on attracting traffic and the profitability of different advertising sources and channels.

In the Conversions –> E-Commerce –> Shopping Behavior Analysis report, you can see how users interact with your products: how often they buy things, add items to the shopping cart, etc. 

If you’ve configured everything correctly on your website, you’ll see the funnel will be filled with users. The first step in the funnel is visiting the site, the second is viewing goods, the third is adding those goods to the basket, the fourth is completing the checkout, and the fifth is buying.

What is the convenience of this report? Immediately in the funnel, you can create segments that are then sent to Google Ads to target specific audiences. For example, if you’re interested in users who have dropped an item in the shopping cart, you can create an audience with those users and target them with certain ads or emails.

There’s a similar funnel just for checkout. If you define checkout steps during setup, you’ll have access to this report:

You can create segments in this report too.

By looking at this report, you can see which steps you forgot to implement on your site. If you have everything configured correctly, you’ll see this full report.

If any of the steps have zeros, it makes sense to go to your site, double-check your data transmission, and ask your developers to correct any errors so the data is displayed correctly.

You can view a similar report for transactions, showing whether all transaction parameters are passed and whether revenue is passed along with them. To make sure there are no gaps or bottlenecks before you check for errors on the site, look at this report and the completeness of its data.

Once you’ve gone through the standard reports and made sure everything is okay, you can create a custom report and and add columns for Transaction ID and number of transactions. Then see if you have duplicate Transaction IDs.

If there are duplicates, that’s bad. You’ll need to carry out a technical check on why this information is being transferred twice. The reasons may be various — for instance, the user finished the order, left the tab open, and walked away. The next day they opened the browser, the page loaded again, and Google Analytics again recorded the ID of this order. As a result, you’ll have incorrect statistics on at least conversions. If you have such a problem, it needs to be fixed.

You can also check the custom report on the share of sessions that reach the hits limit. In a single session, Google Analytics allows you to send up to 500 hits (in the standard version of Google Analytics).

Any hits beyond this limit will not be recorded. Therefore, it’s necessary to check whether any users have actually taken more than 500 actions in one session. If you have sessions that are exceeding the limit, perhaps you’re tracking some hits/events that are not actually important to you. If so, you can remove the settings you don’t need from the code on your site to reduce the number of hits and stay under the limit.

Note that in order to build a report on sessions with hits over the limit, you’ll need to pass the SessionId to a custom variable. If you have any questions on how to do this, consult with OWOX BI.

To reduce manual work and automate everything to the maximum, you can create a checklist of important settings that need to be checked at a certain frequency and run through this checklist once a month, quarter, etc. Write the date on which you check the settings, any errors you found, and comments. This way if your analysts go on vacation or beginners join your team, your specialists won’t have questions and won’t need to study everything from scratch — how everything was introduced and checked — to make changes to a single document. 

We also recommend that you create (and regularly update) a separate file where you record all the metrics you collect on your site.

• High-quality audit = trustworthy data. Before you analyze your data, you need to make sure that it’s collected correctly.
• Regularly check access to your properties to avoid situations where your data is available to individuals who shouldn’t have access.
• Set up daily/weekly/quarterly dashboards to monitor the completeness and quality of data collected. Make auditing more convenient by reducing manual work. Create automatic dashboards with all the metrics you need.
• Configure notifications of critical changes in collected data so you can respond quickly to problems.
• Record all changes on your site so you can easily find the reason for any changes in your KPIs if necessary.
• If you have multiple data sources, consolidate your data into a single repository.
• Give an Analytics 101 session to all your employees. Make sure everyone knows basic things so they can go into the reports themselves and see the information they need without distracting your analysts.