Marketing Analysis: Definition and Different Models (2024)

Who prompted the customer to purchase your product?

It’s a simple question that becomes difficult to answer the more you delve into it.

Did they see a post on Instagram or a video on TikTok, did they search for your product on Google, or did they open a promotional email?

Marketing analysis becomes more complex as your company grows, with the website, social media, influencer programs, offline interactions, and other touchpoints to consider. As consumer behavior evolves over time, it becomes even more complicated.

While it’s not an exact science, the more marketing analytics data you can observe throughout 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 customers engage with your brand on their conversion path.

Marketing analysis allows you to attribute specific channels and campaigns that contribute to conversions, which in turn helps you understand how and where to invest your money and attention. Why does marketing analysis become more challenging?

Although the definition of marketing analysis seems straightforward in theory, effectively tracking your marketing touchpoints can be quite complex in practice. As technology advances and consumer trends change, the methods of marketing tracking also evolve. Consider the following factors:

• We live in a multi-device world. Sometimes people have more than one smartphone, tablet, work computer, home computer, and even a smart home device. Each of these devices may appear as a unique visitor to your site when in fact they all belong to the same customer.
• The world is becoming stricter regarding privacy and tracking. Devices and browsers are becoming more cautious about the information and tracking they allow to be stored. With public data protection regulations and privacy concerns, consumers increasingly will have to consent to being tracked online.
• Most marketing models rely on clicks. Because most marketing and reporting are based on click behavior and UTM tracking (as we will explain below), they miss the impact of ad or content views without clicking on them.

Laying the Foundation for Marketing Improvement

Before we discuss how marketing works or the different marketing models, we must make one thing clear: there is no such thing as “marketing analysis” that is 100% accurate.

You can never fully understand how each individual marketing touchpoint has affected every customer journey, even when using the best marketing analysis software. All marketing analysis models and tools are merely approximations of the real world.

The only accuracy you can strive for is:

• Properly setting up tracking pixels and tracking conversions (such as Meta pixel, Google Ads conversion tracking, and goals/events in Google Analytics).
• Creating a consistent UTM (Urchin Tracking Module) tagging and tracking system that prioritizes clean and complete data about your customer journeys.
• Understanding the perspective of different marketing models and how they affect your marketing decisions.

About UTM Parameters

UTM parameters are a series of tags that begin with “?” or “&” you might find after a URL:

www.yourstore.com?utm_source=facebook&utm_medium=cpc

While it may look and sound strange, UTM is a standard tagging system in digital marketing. You can easily create tags using a URL builder tool for your Google campaigns or a Chrome extension like UTM.io. The Google campaign URL builder will encode special characters like spaces or question marks that could break your URL.

There are
Five standard types of UTM parameters can be used to describe inbound traffic for analytics tools so that it can be aggregated, organized, and analyzed into categories:

• Campaign Source (utm_source) describes the website or primary source where the link will be placed (for example, if you’re promoting a link to your store in your Instagram bio and doing a lot of social media marketing, you might tag it as utm_source=instagram).
• Campaign Medium (utm_medium) describes the marketing activity (for example, if you’re using the link to track traffic from a Google Ads campaign, you might label it as utm_medium=cpc so you know it’s from cost-per-click ads).
• Campaign Name (utm_campaign) allows you to identify traffic from a specific campaign you’re conducting, even if it’s from the same source (for example, for a 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 you are targeting if you’re running a Google Ads campaign.
• Campaign Content (utm_content) is useful if you are A/B testing ads. In this case, you can track each ad to see which one was most effective in attracting visitors.

Custom UTM Parameters

You can also create custom UTM parameters for more granular details on how your traffic is aggregated. For example, you could use “utm_season=fall” to track a specific seasonal campaign.

Additionally, you can also utilize 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 the browser visiting your site.

Here’s an example of what that might look like. If you want to track traffic and sales from a Google Ads 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 promoting winter jackets
• Term: Bidding on the keyword “winter jackets”

UTM parameters help you track your traffic to specific sources so you can analyze their performance at a more granular level, but only when you take the following points into consideration:

• 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’re consistent and it’s easy for your team to understand what you’re 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 recording your UTM parameters so you know they are in use and can understand what they mean when you see them.
• Be consistent in your tags. Guide any new team members to your UTM system and double-check your UTM syntax before using them.
• Test your final URLs. Sometimes your final URL can break. It’s good practice to double-check your landing pages before spending money on ads and encode any special characters (you can use a URL Encoder).
• Use a link shortener when appropriate. UTM parameters can make links long and unattractive to click. If you’re displaying your links publicly, such as in a social media bio or even a booth display to track traffic and sales, use a link shortener like bit.ly to shorten them.

Aggregation

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 sees a story on Instagram about a product, they may look at the product but not purchase it immediately. Instead, they might search for the product on their phone while heading home, before searching for it again on their laptop before bed and converting on a Google Shopping ad.

To overcome this and consolidate all behavior coming from the same user, you will need to enable User IDs in Google Analytics and integrate your CRM system.

User IDs in Google Analytics create unique identifiers that are non-personally identifiable (non-PII) for each user, which are then included wherever their data is sent from. You can use the ID to unify interactions across devices, as well as online and offline touchpoints, for each customer.

The ability to turn what might look like many independent user journeys across different devices into a sequence of interactions from a single user with your brand is crucial for painting a clearer picture of how your customers interact with you across various devices and campaigns.

Push Your Business Forward with Shopify Analytics

Shopify’s user-friendly reports and analytics capabilities help you make better decisions faster. Choose from pre-built dashboards and reports or create your own reports to uncover trends, seize opportunities, and enhance your decision-making process. Explore Shopify Analytics.

7 Marketing Attribution Models

In general, there are believed to be seven different marketing attribution models you can choose from based on your business objectives and where you want to place the most value in the funnel:

1. Last Click Model
2. First Click Model
3. Last Non-Direct Click Model
4. Linear Attribution Model
5. Time Decay Model
6. Position-Based Model
7. Algorithmic Attribution Model (Custom)

Each model is explained below to help you understand each marketing attribution model through your marketing touchpoints. Note how the same customer journey could be interpreted differently depending on the model used.

1. Last Click Model

The Last Click Model is the most commonly used model and is the default for most marketing platforms and marketing analytics tools. This single-touch model is useful when you are fiercely trying to convert traffic into customers.

It gives 100% of the credit to the last-clicked ad and the corresponding keyword. Consequently, lower funnel campaigns, such as branded search or retargeting campaigns, will receive more value whereas top-of-funnel brand awareness campaigns might receive no value.

2. First Click Model

The First Click Model is another single-touch attribution model, giving 100% of the credit to the first click that brought customers to your funnel in the first place. This is useful when you are spending money on campaigns to drive traffic and attract a new audience.

It assigns all credit to the ad or keyword that generated the first click. As a result, high-value top-of-funnel models, such as retargeting, are overlooked in this model, which can reduce investment in these efforts that actually lead to overall lower incentives and top-line revenue.

3. Last Non-Direct Click Model

The Last Non-Direct Click Model gives credit to the last click before the buyer directly comes to your store to make a purchase. It allocates 100% of the credit to the last non-direct touchpoint.

In

The example above will be that email.

Direct traffic is often from customers who have already decided to purchase due to marketing on a different channel. The indirect last-click model helps filter direct traffic and focuses on the last marketing activity before conversion.

4. Linear Attribution Model

The linear attribution model distributes credit evenly across all clicks on the customer journey to purchase. This is the simplest form of multi-touch marketing analysis. With this model, you won’t miss any interactions. However, it won’t tell you exactly which marketing channel had the biggest impact.

5. Time Decay Model

The time decay model is similar to the last-click model. However, it also gives some credit to interactions that led to conversion, placing more weight on clicks that occurred closer to the conversion time.

6. Position-Based Model

The position-based model (or U-shaped model) 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 among the other clicks in between.

The assumption here, however, is that the first click and the last click are the most valuable interactions, while there may be campaigns or touchpoints in the middle that also play an important role.

7. Algorithmic Attribution Model

This model is referred to as customized marketing. When you have enough data available, you can let machine learning determine which touches 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 different touchpoints.

Differences in Marketing Models Across Systems

When studying marketing analytics in Google Ads, Facebook Ads, Google Analytics, or Shopify reports, you may notice differences. Which one is the source of truth? Technically, they are all “correct” – they just present marketing in different ways. Here’s an overview of 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 analysis tools and reports help provide deeper insight into your business. Get insights at a glance, analyze the performance of your marketing channels, and choose the analytical model that best suits your business.

Google Ads

Google Ads only tracks traffic from Google Ads. It does not aggregate conversions from ad campaigns on other platforms as it does not see those touchpoints. Instead, credit will be granted to any user who interacts with a Google campaign at any time, even if they later interacted with a Facebook/Instagram campaign or email or visited your site directly and converted.

By default, the attribution window setting in Google Ads shows actions taken within 30 days of clicking your ads using last-click attribution.

Facebook Ads

The Meta advertising platform only tracks traffic and interactions from Facebook Ads. It also does not aggregate duplicate data from ad campaigns on other platforms and will credit any user who sees or clicks on a Facebook ad within a certain timeframe, even if they later interacted with a Google Ads campaign or email or visited your site directly and converted.

Facebook relies by default on last-click attribution with attribution windows ranging from 24 hours after viewing your ad to 28 days after clicking your ad.

Google Analytics

Google Analytics and other analytics platforms track clickable traffic across paid and unpaid channels. Generally, analytics platforms can be configured to connect to external/offline data sources, user IDs, and/or other web properties that do not directly track part of your online store.

Provides
Google Analytics offers a data import feature that allows you to upload data from other sources so you can analyze everything within Google Analytics. Adding additional data sources and merging user IDs are the best ways to include the majority of customer interactions across platforms in one place.

Google Analytics also aggregates conversions from all channels and gives credit to the last touchpoint in the conversion journey unless the visit was direct to your site. In this case, it will credit the last indirect touchpoint.

Understanding Marketing to Make Your Marketing Dollars Work

Understanding the marketing landscape, its gaps, and the different models you can apply is a good first step towards better tracking, clean customer databases, and making smarter decisions. Although marketing analytics becomes more complex, the many benefits of marketing analysis cannot be denied.

Marketing analysis can provide valuable insight into how and where customers interact with your brand on their path to making a purchase. This data can be used to set up marketing campaigns and an overall marketing strategy to increase return on investment.

FAQs About Marketing Analysis

What are the four types of marketing attribution?

The most popular attribution models include:

• Last Click Model: This model gives credit to the last click in the user’s journey before a purchase is made.
• First Click Model: This model gives credit to the first click in the user’s journey before a purchase is made.
• Linear Attribution Model: This model gives equal credit to all clicks in the user’s path to purchase.
• Time Decay Model: This model gives more weight to clicks that occurred closer to the time of conversion.

Why does marketing analysis matter?

Marketing analysis is important because it allows marketers to measure the effectiveness of their campaigns and track the customer journey. It helps marketing to understand which channels and marketing activities drive conversions and customer engagement, 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 across your sales cycle.

What is marketing analysis?

Marketing analysis is the process of attributing sales or customers to the 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. Different marketing models exist to attribute credit to different parts of the customer journey, depending on your preferences.

How do you set up marketing analysis?

Here are the basic steps to set up marketing analysis:

1. Set objectives: Start by defining the goals you want to track and measure. These can be anything from sales to website visits to lead generation, and so on.
2. Choose an attribution model: Next, select a marketing attribution model that reflects your business goals and objectives. There are many attribution models to choose from, including last click, first click, linear, and time decay.
3. 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 you use.
4. Set up reporting: Configure reporting systems to present data in a useful way for decision-making. This may include setting up dashboards and creating report templates, etc.
5. Monitor and adjust: Monitor data over time to identify trends and areas for improvement. Make adjustments to your campaigns and strategies as needed.

Source: https://www.shopify.com/blog/marketing-attribution#1

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