Who encouraged the customer to purchase your product?
It’s a simple question that becomes difficult to answer the more you start digging into it.
Did they see a post on Instagram or a video on TikTok, or did they search for your product on Google, or open a promotional email?
Marketing analysis becomes more complex as your company grows, with social media presence, influencer programs, offline interactions, and other touchpoints to consider. As consumer behavior evolves over time, it becomes even more challenging.
While it is not an exact science, the more marketing analytics data you can see across the customer journey, the better decisions you can make for your business. Below, learn the basics of marketing analysis, the different marketing models, and how to effectively track and measure your marketing channels.
What is Marketing Analysis? Laying the Foundation for Marketing Improvement
Marketing analysis is the process of evaluating and tracking the performance of your marketing channels.
The goal of marketing analysis, of course, is to gain a clearer understanding of all the interactions and various touchpoints that customers engage with your brand on their path to conversion.
Marketing analysis allows you to identify specific channels and campaigns that contribute to conversion, which in turn helps you understand how and where to invest your money and attention. Why does marketing analysis become more difficult then?
Although the definition of marketing analysis seems simple in theory, effectively tracking your marketing touchpoints can be extremely complex in practice. With advancing technology and changes in consumer trends, the methods of tracking marketing also change. Consider the following factors:
- We live in a multi-device world. Sometimes people have more than one smartphone, a tablet, a work computer, a home computer, and even a smart home device. Each of these devices may appear as a unique visitor to your site when in reality they all belong to the same customer.
- The world is becoming stricter regarding privacy and tracking. Devices and browsers are much more cautious about the information and tracking they allow to be stored. With public data protection laws and privacy concerns, consumers will increasingly have to agree to be tracked online.
- Most marketing models rely on clicks. Since most marketing and reporting are based on click behavior and UTM tracking (as we will outline below), they miss the impact of ad or content views without clicks.
Laying the Foundation for Marketing Improvement
Before we discuss how marketing works or the different marketing models, we need to make one thing clear: there is no such thing as 100% “correct” marketing analysis.
You can never fully understand how each marketing touchpoint has influenced every customer journey, even when using the best marketing analytics software. All marketing analysis models and tools are merely approximations of the real world.
The only accuracy you can strive for is:
- Correctly set up tracking pixels and conversion tracking (like Meta Pixel and Google Ads conversion tracking, and goals/events in Google Analytics)
- Create a consistent system for UTM (Urchin Tracking Module) tagging and tracking that prioritizes clean and complete data about your customers’ journeys
- Understand the perspective of different marketing models and how they affect your marketing decisions
About UTM Parameters
UTM parameters are a series of tags that start with “?” or “&” that you might find after a URL:
www.yourstore.com?utm_source=facebook&utm_medium=cpc
Although it may look and seem strange, UTM is a standardized tagging system in digital marketing. You can easily create tags using a Google Campaign URL Builder tool or a Chrome extension like UTM.io. The Google Campaign URL Builder will encode special characters like spaces or question marks that might break your URL.
There are
Five standard types of UTM parameters can be used to describe incoming traffic for analytics tools so that it can be aggregated, organized, and analyzed into categories:
- Campaign Source (utm_source) describes the website or the main source where the link will be placed (for example, if you are promoting a link to your store in your Instagram bio and doing a lot of social media marketing, you might label it as utm_source=instagram).
- Campaign Medium (utm_medium) describes the marketing activity (for example, if you are using the link to track traffic from a Google Ads campaign, you might tag it as utm_medium=cpc so that you know it’s from cost-per-click ads).
- Campaign Name (utm_campaign) allows you to specify traffic from a specific campaign you are running, even if it’s from the same source (for example, for a well-known search campaign, you could use utm_campaign=branded%20search%20exact. Spaces can be encoded as “%20” to avoid breaking the URL).
- Campaign Term (utm_term) is used to track specific keywords that you are targeting if you are running a Google Ads campaign.
- Campaign Content (utm_content) is useful if you are testing ads. In this case, you can track each ad to see which one was most effective at attracting visitors.
Custom UTM Parameters
You can also create custom UTM parameters to get more details on how your traffic is aggregated. For example, you can use “utm_season=fall” to track a specific seasonal campaign.
Additionally, you can also use any of the valuetrack parameters to dynamically tag different marketing campaign settings or user attributes. For example, &utm_device={device} will automatically change {device} to identify which browser is visiting your site.
Here is an example of what that might look like. If you want to track traffic and sales from a Google search campaign for winter jackets by targeting the unknown keyword “winter jackets”, my URL with UTM tracking might look like this:
www.mystore.com?utm_source=google&utm_medium=cpc&utm_campaign=nonbranded\r\n%20search%20winter%20jackets&utm_term=winter%20jackets
Breaking that down, each parameter tells you something about the traffic:
- Source: Google
- Medium: CPC (cost-per-click)
- Campaign: Non-branded search campaign advertising winter jackets
- Term: Bidding on the keyword “winter jackets”
UTM parameters help you track your traffic to specific sources so you can analyze its performance at a finer level, but only if you keep the following in mind:
- UTM parameters are personal and defined by you. While there are common practices for naming your UTM parameters, use what works for you. As long as you are consistent and it is easy for your team to understand what you are using, you should be in good shape.
- UTM parameters are case-sensitive. “utm_source=Facebook” and “utm_source=facebook” will show up as different sources in Google Analytics.
- Keep a record of your parameters. Create a consistent system for logging your UTM parameters so you know which are in use and can understand what they mean when you see them.
- Be consistent with your tags. Guide any new members of your team through your UTM system and double-check your UTM before using them.
- Test your final URLs. Sometimes your final URL may break. Get into the habit of double-checking your landing pages before spending money on ads, and encode any special characters (you can use a URL Encoder).
- Use a URL shortener when appropriate. UTM parameters can make links long and unappealing to click. If you are displaying your links publicly, such as in a social media bio or even a presentation at a trade show to track traffic and sales, use a URL shortener like bit.ly to shorten them.
When
executing it correctly, you can aggregate and analyze traffic from various sources in Google Analytics and other reporting tools.
Aggregating User Journeys Across Devices Using User IDs
Proper UTM tracking is a step in the right direction, but by default, if the same user visits your site on multiple devices, each “visit” will be attributed as a separate user and a separate “journey.”
For example, if a user saw a story on Instagram about a product, they might view the product but not purchase it immediately. Instead, they might search for the product on their phone while returning home, then search for it again on their laptop before bed and click on a Google Shopping ad.
To overcome this and aggregate all behavior coming from the same user, you’ll need to enable User ID in Google Analytics and integrate your CRM system.
User IDs in Google Analytics create unique identifiers that are not personally identifiable (non-PII) for each user, which are then embedded anywhere their data is sent from. You can use the ID to unify interactions across devices, in addition to online and other touchpoints, for each customer.
The ability to convert what may appear to be many independent user journeys across different devices into a series of interactions from a single user with your brand is critical for painting a clearer picture of how your customers are interacting with you across different devices and campaigns.
Push Your Business Forward with Shopify Analytics
Shopify’s user-friendly reporting and analytics capabilities help you make better decisions faster. Choose from pre-built dashboards and reports or create your own custom reports to uncover trends, seize opportunities, and enhance your decision-making process. Explore Shopify Analytics
7 Marketing Analysis Models
In general, it is believed that there are seven different types of marketing analysis models you can choose from based on your business goals and the greater value you want to place in the channel:
- Last Click Model
- First Click Model
- Indirect Last Click Model
- Equal Attribution Model
- Time Decay Model
- Position-Based Model
- Algorithmic Model (Custom)
Each model is explained below to help you understand each marketing model across your marketing touchpoints. Note how the same customer journey can be interpreted differently based on the model used.
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Last Click Model
The last click model is the most commonly used model and is the default for most marketing platforms and analytics tools. This one-touch attribution model is useful when you’re trying to maximize traffic conversion into customers.
It gives 100% of the credit to the ad clicked last and the corresponding keyword. As a result, campaigns at the bottom of the funnel, such as brand search or retargeting, receive greater value, while brand awareness and top-of-funnel campaigns may get no credit.
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First Click Model
The first click model is another single-touch model, where the first touch is regarded as the most important, receiving 100% of the credit for bringing customers into your funnel in the first place. This is useful when prioritizing spending on campaigns that increase traffic and refresh your audience.
It assigns all credit to the ad or keyword that garnered the first click. Therefore, high-value upper and top-funnel models, such as retargeting, are missed in this model, which may lead to reduced investment in these efforts that actually drive overall incentives and revenue down.
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Indirect Last Click Model
The indirect last click model gives credit to the last click before the buyer comes directly to your store to purchase a product. It gives 100% of the credit to the last indirect touchpoint.
In
The above example will be that email.
Direct traffic is often considered from customers who have already decided to make a purchase due to marketing on a different channel. The indirect last-click model helps filter out direct traffic and focus on the last marketing activity before conversion.
Using the indirect last-click model, you will learn that it was actually the email that drove the final conversion. Direct traffic will be a recognized channel in this model when the only trackable event for customers is coming directly to your store.
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Equal Credit Model
The equal credit model distributes credit evenly across all clicks on the customer journey to purchase. This is considered the simplest form of multi-touch marketing analysis. With this model, you do not miss any recorded interactions.
However, it does not specifically tell you which marketing channel had the biggest impact.
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Time Decay Model
The time decay model is similar to the last-click model. However, it also gives some credit to interactions that preceded the conversion, placing more weight on clicks that occurred closer to the time of conversion.
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Position Model
The position model (or U-shape) gives equal weight to the first click and the last click – each of these interactions receives 40% of the credit. The remaining 20% is distributed to other clicks in the middle.
The assumption here, however, is that the first click and last click are the most valuable interactions, while there may be campaigns or touchpoints in the middle that also play a significant role.
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Algorithmic Model
This model is often referred to as custom attribution. When you have enough available data, you can allow machine learning to determine which touchpoints deserve the most credit in the customer journey.
Theoretically, this is the best model, but it relies on having enough historical data to distribute weight across the different touchpoints.
Differences in Marketing Models Across Platforms
When studying marketing analytics in Google Ads, Facebook Ads, Google Analytics, or Shopify reports, you may notice differences. Which is the source of truth? Technically, they are all “correct” – they just present marketing in different ways. Here is an introduction to how each one works.
Shopify
In the channel performance report in Shopify, marketing analytics models provide a comprehensive understanding of your customers’ journey to conversion. Through the report, you can switch to the analytical model you prefer:
- Conversion by last click
- Conversion by indirect last click
- Conversion by first click
Shopify’s marketing tools and reports help gain deeper insights into your business. Look at the analytics overview, analyze the marketing channel performance, and choose the analytical model that best fits your business.
Google Ads
Google Ads only tracks traffic from Google Ads. It does not accumulate conversions from ad campaigns on other platforms because it does not see those touchpoints. Instead, credit will be given to any user who touches a Google campaign at any time – even if they later interacted with a Facebook/Instagram campaign, email, or visited your site directly and converted.
By default, Google Ads’ last-click window setting shows actions taken within 30 days of clicking your ads using last click.
Facebook Ads
The Facebook Ads platform only tracks traffic and interactions with Facebook ads (also including Meta’s properties like Instagram).
It also does not aggregate duplicate data from ad campaigns on other platforms and will give credit to any user who sees or clicks a Facebook ad within a certain timeframe, even if they later interacted with a Google Ads campaign, email, or visited your site directly and converted.
It depends
Facebook by default attributes to the last click with a last-click window of 24 hours from your ad view and for 28 days from your ad click.
Facebook Ads is the only one among detailed advertising platforms that will credit users who may “see” an ad (even without clicking it) and convert in another way. It is recommended to change the settings to be click-based if you’re looking for a better comparison of your results across platforms.
Google Analytics
Google Analytics and other analytics platforms track clickable actions across paid and organic channels. Generally, analytics platforms can be configured to connect to external/offline data sources, user identifiers, and/or other web properties that do not directly track parts of your online store.
Google Analytics offers a data import feature that allows you to upload data from other sources so you can analyze it all in Google Analytics. Adding additional data sources and merging user IDs are the best ways to incorporate the majority of customer interactions across platforms in one place.
Google Analytics will also aggregate conversions from all channels and will credit the last touchpoint in the conversion journey, unless the visit was direct to your site. In that case, credit will be given to the last indirect touchpoint.
Understanding Marketing to Make Marketing Dollars Work
Understanding the marketing analytics landscape, its gaps, and the various models you can apply is a good first step toward better tracking, cleaner customer databases, and smarter decision-making. Although marketing analytics becomes more complex, the many benefits of marketing analytics are undeniable.
Marketing analytics can provide valuable insights into how customers interact with your brand on their path to making a purchase decision. This data can be used to set up marketing campaigns and an overall marketing strategy to maximize return on investment.
Frequently Asked Questions about Marketing Analytics
What are the four types of marketing?
The most common marketing models include:
- Last-click model: This model gives credit to the last point in the user journey before a purchase is made.
- First-click model: This model gives credit to the first point in the user journey before a purchase is made.
- Equal attribution model: This model gives equal credit to all clicks along the user path before a purchase is made.
- Time decay model: This model gives greater weight to clicks that happened closer in time to the conversion.
Why does marketing analytics matter?
Marketing analytics is important because it allows marketers to measure the effectiveness of their campaigns and track the customer journey. It helps marketing understand which channels and marketing activities drive conversions and customer interactions, and which do not. This data can be used to make informed decisions about future marketing strategies, allocate budgets more effectively, and optimize campaigns for better performance throughout your sales cycle.
What is marketing analytics?
Marketing analytics is the process of attributing sales or customers to various touchpoints in the customer journey. It is the practice of analyzing the impact of each touchpoint or marketing activity on the customer’s decision to buy or take action. There are different models of marketing to assign credit to different parts of the customer journey based on your preferences.
How to set up marketing analytics?
First, define your goals: Start by identifying the goals you want to track and measure. These can be anything from sales to website visits, lead generation, and more.
Choose a marketing model: Next, select a marketing model that reflects your business objectives and goals. There are several marketing models to choose from, including last-click, first-click, equal attribution, and time decay.
Implement tracking: Set up tracking systems to measure the performance of each marketing channel and activity. This can include website analytics, email marketing, or any other platform or software you use.
Continue
Reporting setup: Configure reporting systems to present data in a way that is useful for decision-making. This may include setting up dashboards, creating report templates, and more.
Monitor and Adjust: Monitor data over time to identify trends and areas for improvement. Make adjustments to your campaigns and strategies as needed.
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