As consumers interact with your brand through several channels—organic search, paid ads, social media, and email marketing—it can be difficult to pinpoint exactly where your successes originate.
This task becomes increasingly complex for marketers as the number of possible customer touchpoints rises. Without a clear understanding of how different marketing actions influence customer behavior, allocating resources and strategizing for future campaigns become a shot in the dark, leading to potential inefficiencies and lost opportunities.
To manage these multi-channel challenges, marketing attribution strategies are necessary. This article provides a comprehensive guide to shed light on these practical strategies for multi-channel analysis in your marketing attribution efforts. Even more, you’ll learn how to attribute customer actions to the right marketing touchpoints correctly.
Marketing Attribution in a Multi-Channel Landscape
Marketing attribution is the analytical science of determining which marketing tactics contribute to sales or conversions.
Customers interact with brands through a variety of channels in their marketing campaigns. They might first discover a brand through a social media post, read more about the product on its website, receive an email promotion, and finally purchase after seeing a retargeting ad. All of these touchpoints are multi-channels in the brand’s marketing strategy.
Talking about multi-channels, here are some major marketing channels:
- Paid Search: These ads appear atop the search results in search engines like Google.
- Organic Search: This includes visitors who find your website via a search engine rather than an ad.
- Email: This includes newsletters, promotions, and other direct-to-customer emails.
- Social Media: This encompasses both organic posts and paid ads on platforms like Facebook, Instagram, Twitter, LinkedIn, and more.
- Direct Traffic: A visitor types your URL directly into their browser or uses a bookmark to reach your site.
- Referral Traffic: This includes visitors who come to your site from links on other websites.
- Display Ads: The banner and sidebar ads appear on other websites.
- Affiliate Marketing involves third-party partners promoting your product or service for a commission.
💡 A customer’s journey through these channels is rarely linear, and multiple touchpoints often work together to lead to a conversion.
Marketing Attribution Models
A marketing attribution model is a rule or set of rules that determine how credit for sales and conversions is assigned to touchpoints in a customer’s journey.
It is the methodology marketers use to understand and assign credit to the marketing initiatives that lead the customer toward a conversion.
Consider a scenario where a consumer interacts with a brand through four touchpoints before purchasing. The touchpoints, in order of interaction, are:
- Clicks on a Google Ads (Paid Search)
- Reads a blog post on the company website (Organic Search)
- Clicks on a Facebook ad (Social Media)
- Receives an email promotion and then makes a purchase (Email)
Here’s how the attribution would be assigned according to each model:
1. First Touch Attribution Model
All the credit (100%) would go to the Google Ads. This first-touch model argues that the initial marketing touchpoint was most important because it introduced the consumer to the brand.
- It’s easy to understand.
- It highlights channels that are effective at customer acquisition.
- It disregards all other touchpoints that may have influenced the decision to convert.
- It tends to overemphasize top-of-funnel activities.
2. Linear Model
In the linear attribution model, each touchpoint in the customer’s journey shares equal credit for the sale. Hence, each touchpoint would receive 25%. This model suggests that each touchpoint is equally important in the purchasing process.
- It acknowledges the contribution of all touchpoints.
- It provides a holistic view of the entire customer journey.
- It doesn’t take into account the varying impacts different touchpoints may have.
- It may distribute credit to less effective touchpoints.
3. Position-Based Attribution Model
The position-based model (also known as the U-shaped model) assigns 40% of the credit to both the first and last touchpoints, and the remaining 20% is distributed evenly across all other touchpoints.
In our illustration, the Google Ads (first interaction) and the Email Promotion (last interaction) would each receive 40% of the credit, while the blog post and the Facebook ad would each receive 10%.
- It values both customer acquisition and closing strategies.
- It includes all touchpoints but emphasizes the first and last interactions.
- It may undervalue the role of middle touchpoints.
- The assigned percentages are arbitrary and might not reflect the actual influence of touchpoints.
4. Time Decay Model
The time decay attribution model gives more credit to the touchpoints closer to the conversion time. As the name suggests, the further back a touchpoint, the less credit it receives.
The email promotion, being the closest to the purchase, would receive the most credit, the Facebook ad would receive the second most, and so on, with the Google Ads receiving the least credit.
- It emphasizes the importance of touchpoints closer to the conversion.
- It makes sense for longer sales cycles where the last few interactions will likely influence the purchase decision.
- It may undervalue touchpoints at the beginning of the customer journey.
- It’s not ideal for fast, impulsive purchase behaviors where earlier touchpoints might be more influential.
Each model provides a different viewpoint on the customer’s journey and highlights various aspects of your marketing efforts. The choice of the most appropriate model depends on your business type, sales cycle, marketing strategy, and the specific objectives you’re focusing on.
Advanced Marketing Attribution Strategies
With a foundational understanding of basic attribution models, let’s explore more advanced marketing attribution strategies.
Multi-Touch Attribution Model
Multi-touch attribution models offer a more sophisticated approach by looking at the entire customer journey and assigning value to each touchpoint based on its influence on the final conversion.
Examples include the Linear, Time-Decay, and Position-Based models previously discussed, but with even more granular variations depending on the specific needs of your business.
This approach allows marketers to better understand the impact of each touchpoint and how they work together to encourage a customer to convert.
Use of Multi-Touch Attribution Model
Consider a hypothetical online retailer, “ShopifyRUs.” Before diving into a sophisticated attribution model, they used the first-click model, giving all the credit to a customer’s first interaction point with their brand.
However, they noticed customers often engaged with the brand through various channels before purchasing. They interacted with social media posts, clicked on email promotions, read blog posts, and finally purchased after being retargeted by an ad.
Recognizing the need for a more comprehensive view of their marketing performance, the ShopifyRUs team transitioned to a Multi-Touch Attribution Model. Here’s how they did it:
- Step 1: Define the Objectives: The aim was to understand the impact of each touchpoint on the customer journey to optimize their marketing strategies.
- Step 2: Identify All Touchpoints: They began by tracking all possible customer touchpoints. These included social media posts, email marketing, organic search, paid ads, and referral links.
- Step 3: Assign Value to Each Touchpoint: Since ShopifyRUs wanted to value each touchpoint that led to a sale equally, they decided to implement a Linear Model.
- Step 4: Gather and Analyze the Data: They then collected data over a specific period and used analytics tools to apply the attribution model and analyze results.
- Step 5: Implement Changes Based on Findings: Based on the insights they gleaned from the analysis, ShopifyRUs identified which channels drove the most conversions and made strategic decisions to optimize their marketing efforts.
Algorithmic or Data-Driven Attribution
Algorithmic or data-driven attribution uses advanced statistical techniques to assign value to each touchpoint in the customer journey. This model considers all available data and interactions over time to quantify the impact of each channel on conversions.
The advantage of this model is that it can adapt over time and improve with more data, providing a more accurate and tailored attribution model for your specific business.
Use of Algorithmic Attribution in a Startup
For our hypothetical startup, let’s take a burgeoning B2B software company, “SaaSy.”
SaaSy had several marketing actions, such as content marketing, social media, webinars, SEO, PPC, email marketing, and more. They initially used a linear attribution model, which resulted in some insight, but they realized they could miss out on the nuances of their customer’s journey.
They embraced the Algorithmic Attribution model to fully understand which touchpoints were most influential. Here’s how SaaSy implemented this strategy:
- Step 1: Define the Goals: SaaSy wanted to analyze the impact of each touchpoint and understand how various marketing actions influenced the customer’s decision to try their software.
- Step 2: Gather Comprehensive Data: They ensured proper tracking of every marketing action, collecting and centralizing data from all their marketing channels.
- Step 3: Implement an Algorithmic Attribution Tool: SaaSy integrated an advanced attribution tool capable of processing large amounts of data and using machine learning algorithms to assign credit to each touchpoint.
- Step 4: Data Analysis: The platform analyzed its marketing activities, considering the sequence of touchpoints, the time spent on each, the type of interaction, and other factors.
- Step 5: Act on Insights: Based on the rich insights gathered, SaaSy adjusted its marketing strategies. They invested more in the most influential channels and revised their tactics on underperforming channels.
Unified Measurement Model
Unified measurement combines the strengths of multi-touch attribution models and marketing mix modeling. It is a holistic approach that accounts for both online and offline marketing channels and macro factors like seasonality, economic conditions, and competition.
This model enables a comprehensive view of marketing performance and can help guide strategic decisions and budget allocation across all marketing channels and tactics. It’s especially useful for large organizations operating in diverse, multi-channel environments.
Use of Unified Measurement Model in an Enterprise
Our final illustration features a large multinational corporation, “GlobalTech.” They offer various products and services, invest in offline and online marketing, and operate in multiple regions worldwide.
They used a multi-touch attribution model, but this didn’t provide a full picture, especially regarding offline marketing activities and macro factors. So, they realized the need for a more comprehensive approach and implemented a Unified Measurement Model.
Here’s how they went about it:
- Step 1: Define the Objectives: GlobalTech wanted a comprehensive view of all marketing activities, both online and offline, and to understand how these activities were contributing to their bottom line.
- Step 2: Gather Data Across All Channels: GlobalTech collected data from all their marketing efforts. This included data from digital channels, like paid ads, SEO, and email marketing, and offline channels, like TV ads, direct mail, and events.
- Step 3: Implement a Unified Measurement Solution: They implemented a tool capable of unified measurement that could take all these different data sets and analyze them in conjunction.
- Step 4: Incorporate Macro Factors: In addition to their marketing channels, they also integrated data on macro factors such as competitive landscape, economic trends, and seasonality.
- Step 5: Analyze the Data and Gain Insights: The tool processed all this data and provided insights into the contribution of each marketing activity and how external factors impacted their performance.
- Step 6: Make Strategic Decisions: Based on the insights, GlobalTech made informed decisions about budget allocation, campaign optimizations, and strategic planning across multiple regions and channels.
Marketing Attribution Challenges and Possible Solutions
Attributing your marketing efforts can present a few challenges. Here are some of these complexities:
Data silos occur when marketing data is isolated within different departments, platforms, or systems which do not communicate with each other.
For instance, your social media data may differ from your email marketing data. This disconnection can make tracking a customer’s path difficult across multiple channels.
Implement a centralized system or platform that can integrate data from all marketing channels. Tools like Google Analytics, Adobe Analytics, or a Customer Data Platform (CDP) can help amalgamate and analyze data in one place.
With customers using multiple devices like smartphones, tablets, and computers, tracking user behavior across different devices can be challenging. For example, users might see an ad on their smartphone but purchase their desktop.
Use tools and platforms that support cross-device tracking. For instance, Google Analytics provides a User ID feature that allows you to track user interactions across different devices and sessions.
Accurate Time Stamp
Accurately recording the timing of interactions is crucial for certain attribution models like the time decay model. However, it can be difficult to accurately determine the time of an interaction, especially when dealing with offline marketing activities.
Invest in tools that can record the time stamp of online interactions. For offline activities, consider using unique codes or vouchers that the customer can use online, thus allowing you to track back the time of the initial offline interaction.
Strategically employing various marketing attribution models, from basic models like First Touch and Linear to more advanced ones like Multi-Touch, Algorithmic, or Unified Measurement, can enable you to attribute proper resources to the right marketing channels.
In the long haul, this empowers you to optimize your marketing efforts, aligning them more effectively with your customer’s journey and maximizing your return on investment.