What is Marketing Analytics?

Marketing analytics is the collection and study of data from various online marketing campaigns and platforms.

The objective of marketing analytics is to assess the efficacy and performance of your marketing tactics so that informed business decisions can be made about the future direction of a particular strategy.

In the earlier days of marketing, advertisements ran in newspapers and on radio channels, but there was no way to understand if the ads were working. We weren’t able to assess if the right audience saw an ad and how many people bought a product or service after seeing it. It was a ‘pay and hope it works’ method.

Today, businesses can understand what device a person uses to search for their products or services (laptop, cellphone, or tablet) and where or how they found them. They also understand what type of content or media works best for their target audience.

 

Table of contents

Why is marketing analytics and data important?

Marketing analytics and data allows a business to serve the right advertisement to the right target audience at pivotal moments within each buyer stage.

Whether it’s paid media, search engine optimization (SEO), or social media, marketing analytics allows you to take stock of your marketing activities and determine if they are stacking up against your business objectives or target key performance indicators (KPI).

Marketing analytics and data are vital because they allow you to make informed decisions about your marketing efforts. All of the data collected comes together to tell a story. This story empowers you to make decisions about which platforms receive a larger portion of the budget and what media types to use on those platforms. You can also use analytics to plan campaigns based on historical data or trends. The more accurate and precise the data, the better the business decisions.

Here are four opportunities that come from paying attention to marketing analytics.

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1. Prioritize your audience

Whether your marketing is using an inbound or outbound approach, not knowing who you are targeting or where they are in the world hinders even the most well-meaning efforts. You could end up spending large sums of marketing capital only to miss out on sales and leads.

Understanding who you are trying to attract is pivotal when it comes to business growth. With correct data and analysis, you can prioritize your target audience because you know their location, online search preferences, and what they require to make a buying decision.

2. Compare marketing data

Do you know how your Facebook ads stack up to your pay-per-click (PPC) ads? Is SEO bringing in more sales and leads? Are your marketing efforts meeting business expectations and objectives?

Marketing analytics answers all these questions so that you can assess where you should invest more time, money, and effort to further your business growth.

Ultimately, you don’t want to be spending large portions of the marketing budget in areas that don’t yield results. It would be a waste. Comparing data will allow you to invest where it is needed most based on business goals and KPIs.

3. Drive investment into marketing efforts

One of the biggest frustrations when it comes to marketing is budget. Where do we assign the majority of the marketing spend? How do we see a return on our investment? Can we have more money, please?

Presenting this data and validating the effort that has gone into each marketing tactic will allow marketers to get more funds and justify the budget allocation. Data and analysis can inform stakeholders on performance and tweak and fine-tune the best ways to allocate budget according to what will deliver the best results.

4. Stay focused on your goals

When you assemble a marketing strategy, you must base this strategy on key business objectives and goals. The data you collect keeps you focused on these objectives — giving you the latitude to change or shift focus if you are not on track to meet these objectives.

Without data and marketing analytics, we would be flying blind, unable to show the results from our efforts, or understand what platform works best for us, or how to get sales and leads. We would also be unable to validate our strategies to gain more budget.

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Analyzing marketing analytics data

With marketing analytics, you can identify patterns in campaigns and calculate the return on investment for your efforts. For example, you can find out whether a campaign resulted in an increase in conversions or you can see how many people engaged or interacted with an advertisement on your website.

There are many methods for analyzing marketing data. The first step is to decide on the key metrics you want to measure your efforts against. These metrics are known as key performance indicators or KPIs.

If we are looking to measure growth brand awareness, we would look at different data sets and interpret them differently from measuring conversions. To measure brand awareness, we would look at growth in a traffic channel called direct (more users typing in the website URL in a browser) as well as the growth in traffic from brand-related search terms in organic traffic.

As an example, imagine you are a company that just went through a big rebrand — new name, new look, new website, the works. How could you measure the success of the rebrand using analytical data? One way is to look at the growth of direct traffic to the website as well as the number of brand-related searches in web browsers for the company’s new brand name. To measure this, you would use two marketing analytics tools — Google Search Console and Google Analytics — to see how many people recently searched for the new brand name. If these searches are increasing, you can conclude that brand awareness efforts have proved successful.

Let’s unpack some examples of the models used to collect and analyze marketing data.

Media Mix Models

With Media Mix Models (MMM), data collected from analytics tools is analyzed to assess the impact of marketing efforts on the bottom line. The question we are looking to answer is, how are our efforts contributing to leads or sales? The goal of MMM is to create an ideal campaign that drives engagements and sales.

With this model, companies can adjust marketing efforts on consumer trends, seasonality, and offline efforts. For this model, you must collect data over a long period of time to assess trends. Typically, this allows the measurement of year over year (YoY) growth.

Multi-touch attribution

As technology has evolved, so has the number of touchpoints for accessing the internet. People no longer browse the internet on one device (now you have a laptop, a phone, and a tablet) or just one channel (you use Google as well as social media platforms like Facebook, Instagram, LinkedIn, etc). A person can use multiple touchpoints before they complete an action, such as making an online purchase or submitting an online form.

Multi-Touch Attribution (MTA) is focused on collecting data based on these touchpoints to assess where marketing efforts would be best spent. This helps ensure you don’t spend most of your money and efforts on platforms or campaigns not delivering a solid ROI.

Unified marketing measurement

As the name suggests, Unified Marketing Measurement (UMM) combines both MTA and MMA to offer more comprehensive data insights. This model helps reduce blind spots when collecting data and gives you more qualified data to make better marketing decisions. For example, understanding how seasonality influences and impacts the various touchpoints will help businesses plan their marketing efforts more accurately.

The challenges of marketing analytics

Now that we know what kind of models and metrics are used in marketing analytics, we need to understand the challenges.

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1. Too much data

Often, companies and individuals will have too much data on their hands, resulting in the inability to process or take action. It’s referred to as analysis paralysis. Having data is great, but too much of it can cloud and hinder movement in any direction. Often, the vast quantities of data collected are actually irrelevant to objectives. 

Data should only be collected if it can be easily structured for analysis.

2. Poor data quality

The quality or accuracy of data is vital. If the information that is collected is inaccurate, the impacts are far-reaching. Budgets could be allocated to low performing accounts or taken away from campaigns that are performing well.

Decisions are only as good as the quality of data and insights provided. When data is collected, it needs to be:

  • Current
  • Comprehensive
  • Error-free
  • Relevant

3. Unskilled data analysis

To make decisions or recommendations based on data, one needs to be able to analyze it. Without a trained person, the data could be misinterpreted, and again, wrong decisions are made.

Using data to affect growth

Data is robust when segmented, accurate, and interpreted correctly. It allows businesses to make decisions that will affect and impact growth. They can identify weak channels, adjust their strategies, optimize campaigns, and better understand their audience with well-organized and correctly interpreted data.

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Identifying weak channels

When you have your data broken down into channels or sources, you can see which channels perform poorly. This helps you make a decision about whether to allocate less resources to a channel or to change the content or information used.

Adjusting strategies

With data on your side, you can be smart about adjusting your strategy to cater to changes in trends, seasons, and patterns over time. Let’s take food bloggers as an example. Traditionally, food bloggers often receive the highest traffic numbers during fall and winter holidays such as Christmas and Thanksgiving. During summer, there aren’t as many big holidays that would garner as much traffic. To increase their traffic during the spring and summer, a food blogger may change the type of content or recipes they produce during that time to gain more traffic.

Optimizing campaigns

You can also use data to improve campaign performance. There are often gaps or missed opportunities within a specific marketing activity that can be filled with the correct data to maximize the return or reach. 

Understanding your audience

The most important aspect of marketing is understanding your audience. Who are you trying to reach? Where are they based? These questions need to be answered to deliver messaging that appeals to them.

Marketing analytics allows you to do just that. You can gain valuable insight into who your audience is, what their interests are, and their location.

Where to begin with marketing analytics

Marketing analytics can be overwhelming, and not knowing where to start often leads to the common problems we highlighted earlier. To help, we outlined some steps for you as a starting point.

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Step one

Decide what to measure

Starting with the question of what you want to measure is essential. Break your answer down into the following elements:

  • Your objectives
  • The problems you are trying to solve
  • What information are you looking to gain

Step two

Benchmark success

What does success look like to your business? You need to understand your success metric and how it is currently performing to measure your growth.

For example, if you want to grow sales for a particular brand, you need to know how many items are currently selling. Then, to determine success and measure performance, you need to identify how many you should be selling.

Step three

Pick the right tool

Companies often use too many tools to collect too much data and miss out on the essential metrics. You must be able to collect the right information to make the most informed decision.

If you are running ad campaigns, it is pointless investing in SEO tools, as these aren’t going to accurately inform your decisions.

Marketing analytics tools

Now that we understand what marketing analytics is and why it is so important let’s look at some of the tools we use to collect data, what data we can collect, and what these metrics mean.

You can use a host of tools to gather the information you need. We’ve gathered up the most common marketing analytics tools.

We will be updating this page with more tools and information as we test and trial them to ensure that we provide you with the most accurate information possible.

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Google tools for marketing analytics

Google analytics

Google Analytics (GA) is the most common tool used to measure traffic to a website, conversions, and a host of other data sets. GA is free to use and requires that you place a tracking code on your site.

Metrics often tracked by GA include traffic by channel and device.

Traffic is a broad metric that measures how many people visited your site or platform. It covers three general metrics, which we will cover below:

Traffic by channel

This metric allows us to see how people come to visit our site. The questions answered with this metric are:

  • Where did our visitors come from (organic search, Facebook, an ad campaign)?
  • How many new visitors came from these channels?
  • How many sessions did they have on the site?
  • How many conversions (leads or sales) did each channel bring?
Traffic by device

As we know, there are multiple touchpoints or ways to access a website, and this metric allows us to gain insight into the device used. The metric tracks visit by users via:

  • Desktop
  • Mobile
  • Tablet

Data collected will allow you to plan and optimize based on the most used device. GA can also break down data according to the type of device used to access a website. Was the user on a Samsung device, or was it an iPhone?

Google Analytics covers a wide range of data, which gives you valuable insight into understanding your audience and allows you to plan how best to go about optimizing your campaign.

Google Search Console

Google Search Console (GSC) focuses on how your site performs from a search perspective. SEO specialists and webmasters use GSC to gain insight into how Google indexes the website (for the Google Search index) and where the site ranks for a target search term.

The metrics we look for here from a broad basis are clicks, impressions, click-through rate, and average position.

Clicks

The clicks metric tells us how many users saw our search result snippet on a search results page and clicked on it. We can compare this to a set period of time to see if we are growing or not. 

Impressions

Impressions tell us how many saw our search result snippet for a particular search in their web browser. 

Click-through rate

Click-through rate (CTR) is calculated using the clicks and impressions metrics to determine how many saw a result snippet and then clicked on it to visit the site. We use this metric to understand how to improve the essential SEO elements on our web pages to get a better CTR. 

Average position

The average position is where you rank on a search results page for a search query. Are you on the first results page for that query, or are you on page three or four? We call this metric “average position” because each website has a different set of results for the same search term. Why? Because of personalized search.

GSC then takes where your site ranked and gets an average over the number of times it appeared in an online search.

GSC is essential from an organic search perspective. Even though it focuses on one channel, the insights available can help you make informed decisions for alternative marketing campaigns. For example, if you are trying to get more sales around a specific search term, but can’t rank for it organically, perhaps it is wise to have a paid search campaign for that search term instead.

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Tools by tactic

Each marketing channel or service has tailored tools to measure the performances based on commonly used metrics within each field. In inbound marketing, there are tools specifically created to collect data based on the marketing tactic. These tactics would be SEO, paid advertising, or social media marketing.

We have highlighted some of these tools based on the marketing tactic or channel below.

SEO data collection tools 

SEO analytics measures how well your site performs in organic search. The goal is to answer how well you rank in search, how much organic traffic you get, and if that traffic converts.

The most common SEO data tools are:

  • SEMRush
  • Ahrefs
  • Moz
  • UberSuggest
  • Google Trends

SEO media data collection tools

Being able to track how people engage with your social media pages or content is vital. How they found you is equally important. Are you reaching the right audience? This is a question you need to answer if you want to drive better engagement or increase your social media reach. The tools most commonly used for collecting social media data are:

  • Facebook Insights
  • Instagram Insights
  • Twitter Analytics
  • BuzzFeed
  • Hootsuite

User-experience based tools

User experience (UX) is the analysis of how a user interacts with a website. What are the points that disrupt their user journey or cause the experience to be a negative one? With UX-based tools, we use heat maps, click maps, and funnels to understand a platform’s experiences.

The most common tools used for UX data analysis are:

  • HotJar
  • CrazyEgg
  • Mixpanel

Marketing analytics FAQs

What is a tracking code?

A tracking code is a small snippet of code added to the HTML portion of a website. It is this code that allows you to collect usage data on a website.

A Google Analytics tracking code looks like this:

<!– Global site tag (gtag.js) – Google Analytics –>

<script async src=”https://www.googletagmanager.com/gtag/js?id=UA-164787428-1″></script>

<script>

  window.dataLayer = window.dataLayer || [];

  function gtag(){dataLayer.push(arguments);}

  gtag(‘js’, new Date());

  gtag(‘config’, ‘UA-111111-12’);

</script> 

Where is a tracking code added to a website?

Each tracking code has specific requirements regarding placement on a website. However, the majority of tracking codes are added to the <head> section of a website.

Google Tag Manager has two placement requirements. One being in the <head> section and the second in the <body> section of a website.

 

 

What is the average acceptable bounce rate?

The average bounce rate for a website is 55 percent. Anything below this rate is considered excellent. Once the bounce rate is over 70 percent, it would be cause for concern.

However, a bounce rate could indicate a person finding the information they need and then leaving, or submitting a form on a page.

Should I rely on bounce rates?

Bounce rates are only part of the data that needs analyzing. One should look at bounce rate data in conjunction with other metrics such as time on site, conversions, and pages on the website.

In isolation, the bounce rate doesn’t provide the full story.

What is a UTM tag?

A UTM tag is a snippet of information added to the end of the URL or destination page.

Here’s an example:

https://sitecare.com/blog/why-is-wordpress-so-popular/?utm_source=Youtube&
utm_medium=CPC&
utm_campaign=Email%20Lead%20Generation

A UTM tag determines how many people visit the website or target page from a specific campaign. The parameters are segmented as follows:

Campaign Source: The platform the URL is on. For example, if you are running a YouTube advertising campaign, and the button targets a page on your website, YouTube would be the source.

Campaign Medium: The type of campaign you are running. Is it a paid campaign, newsletter, or organic? Continuing with the example above, if the campaign were a YouTube advertising one, the medium would CPC.

Campaign Name: What is the name of the campaign you a running?

To build a UTM tagged URL, click this link: https://ga-dev-tools.appspot.com/campaign-url-builder/.

What is an event in Google Analytics?

An event measures the desired action a user takes on a website. Events are measured differently from page views. An event is recorded when a user does something on your site, like clicking on a button you are tracking or filling in and submitting an online form.

Marketing analytics glossary

Acquisition

Acquisition measures which channels brought users to your site, using the traffic source (name of the platform) and the medium (organic or paid or campaign name).

An example would be someone who visited the site from a Google search (source) and clicked on an organic search result (medium).

Average session duration

The measurement of time spent on a site is the average session duration. It is calculated by how many sessions the site had and how long users were on the site.

This metric helps to understand if your audience is engaging with the site and finding the information and content useful or not.

Bounce

A bounce indicates when a person visits the site but only views a single page.

Bounce rate

Bounce rate is the percentage of sessions with only single-page views. Bounce rate helps you understand the quality of content on your site.

People often misinterpret bounce rate as being wrong if itis too high and good if too low. Without the context of data around it, however, the opportunities for inaccuracy are common.

Channel

Channels in analytics are high-level categories showing how people found your site. Examples of the high-level categories would be organic search (Google Search), paid search (advertising via Google Ads), social (people visiting from social media platforms like Facebook), referral (a website or platform referring people to your site via a link), and email (an email newsletter or campaign with a link to your site).

These are existing channel sources within Google Analytics and other tools, but you can create custom channels depending on your data collection requirements.

Click-through rate

Click-through rate is the percentage of clicks against the number of views or impressions on an ad or search result.

Conversion or goal completion

Conversions are the measurement of the number of desired actions (or goals) completed by online users. For example, a conversion could be a sale on your site or a form being populated and submitted to your Sales team.

Conversion rate

Conversion rate is the percentage of leads or sales against the number of visitors — if you have ten conversions per 100 visits, the conversion rate would be 10%.

CPC

CPC is Cost-per-click. It is a measure for paid media campaigns within Google Ads or on relevant social media campaigns. CPC measures how much it costs for each click on a paid advert. We calculate the average cost-per-click by dividing the amount of budget spent on each click (to display the ad online) by the number of clicks on a paid advert.

Dimensions and metrics

Metrics are the quantitative measurements of data. Dimensions are labels. For example, The channel (organic search) would be the dimension, while the number of users from the channel would be the metric.

Google Tag Manager

Google tag manager (GTM) is a tool used to implement various tracking codes on a website. Instead of adding every tracking code to the site, GTM is the single point of entry. A GTM code is added to the site, and then the required tracking codes are added to the site via tags on GTM.

Interactions per visit

These are actions your users took when visiting your website. Tracking this metric will provide a clearer understanding of how many interactions visitors take and what these interactions are. This is known as the ‘path to purchase’ or, more traditionally, the buyer’s journey.

New vs. returning

This is the net percentage of new visitors to your site compared with the total number of returning visitors.

Pageviews

Pageviews are measured by the number of times your tracking code is loaded from your page loading in user browsers.

Sessions

Sessions are a single visit to your site with multiple interactions. These interactions would be pageviews, conversions, and actions. A typical session times out, by default, after 30 minutes.

Traffic

Also known as visits, traffic is the total number your site receives in a given period.

Traffic by device

‘Traffic by device’ is the total number of page or site visits to a site by device type, e.g., tablet, desktop, or smartphone.

Visitors

Visitors are internet users who visit your site; they can be tracked by browser cookies and a GTM tracking code installed on your site.

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