Explore the differences between custom and standard attribution models to optimize your marketing strategy and gain valuable insights.
Custom and standard attribution models help businesses understand how marketing efforts lead to conversions. Here's a quick breakdown:
Feature | Standard Models | Custom Models |
---|---|---|
Setup Complexity | Quick and easy | Time-intensive, requires expertise |
Flexibility | Fixed rules | Fully customizable |
Data Integration | Limited | Comprehensive |
Best For | Simple customer journeys | Complex, multi-channel journeys |
Choose standard models for simplicity and speed. Opt for custom models if your business needs detailed insights and can allocate the necessary resources.
Let’s dive deeper into standard attribution models. These are ready-made frameworks designed to help track and analyze marketing touchpoints.
Standard attribution models are generally divided into two categories: single-touch and multi-touch. Single-touch models focus on one interaction, while multi-touch models distribute credit across multiple points in the customer journey.
Model Type | Credit Distribution | Best Used For |
---|---|---|
First-Touch | 100% to the first interaction | Campaigns focused on brand awareness |
Last-Touch | 100% to the last interaction | Short sales cycles or impulse purchases |
Linear | Equal credit to all touchpoints | Analyzing a balanced customer journey |
Time-Decay | More credit to recent touches | Long sales cycles or relationship-based sales |
Customer journeys are rarely simple. For instance, B2B buyers typically engage with 8 touchpoints, B2C buyers with 6, and retail customers may interact with as many as 56 touchpoints . These variations highlight the need for choosing the right model based on the journey's complexity.
Standard attribution models come with a few standout advantages:
"There is no wrong answer. It depends on your business needs and one model isn't better than another. As we've discussed, finding data-driven insights that help you drive revenue is the most important part of building a marketing attribution model." - Craig Jordan, Founder and CEO at SaaScend
Despite their convenience, these models have some limitations:
These limitations mean standard models work well for straightforward cases, like retail purchases with 4-6 touchpoints. However, for more complex journeys - such as B2B scenarios with 12-20 interactions - a custom model may be more effective .
Custom attribution models give marketers the ability to fine-tune how credit is distributed across marketing touchpoints, aligning the approach with specific business goals.
These models often begin with a standard framework, like linear or position-based attribution, and are then adjusted to meet unique business needs. Marketers can tweak credit distribution, apply channel-specific rules, and even include offline data for a more complete picture.
For instance, Campaign Manager 360’s linear model might assign 25% credit to each touchpoint. However, custom rules could redistribute this, giving search interactions 40% and other channels 20% each . These adjustments make the model more relevant to specific strategies.
Custom models provide a range of advantages that go beyond standard approaches:
Benefit | Description | Impact |
---|---|---|
Precise Control | Adjust weights based on factors like channel importance or timing | Better revenue attribution |
Channel Integration | Combines online and offline touchpoints for a full customer journey view | Deeper marketing insights |
Flexible Rules | Customize based on specific conditions or interaction types | Aligns with business objectives |
Data-Driven Insights | Leverages analytics to refine credit distribution | Smarter decision-making |
Creating a custom attribution model requires a solid foundation. Here’s what you’ll need:
While setting up a custom model takes effort, the payoff is a clearer understanding of marketing performance and return on investment. A structured setup ensures more reliable insights for future strategies.
Custom and standard attribution models differ in their capabilities and the resources they require. These differences play a critical role in guiding analytics decisions. The comparison below breaks down their core features, focusing on setup, flexibility, and resource needs.
Feature | Standard Attribution Models | Custom Attribution Models |
---|---|---|
Setup Complexity | Quick and straightforward with pre-built frameworks | Requires significant resources and extended setup time |
Maintenance | Minimal ongoing effort | Needs continuous updates and adjustments |
Flexibility | Fixed rules with limited customization | Complete control over credit assignment rules |
Resource Requirements | Basic analytics knowledge | In-depth understanding of audience behavior and touchpoints |
Data Integration | Restricted to standard data sources | Supports multiple, customized data sources |
Model Types | Includes 8 pre-built options like last-click, first-click, linear, etc. | Unlimited possibilities for customization |
Credit Distribution | Predefined distributions (e.g., 40-20-40 for position-based) | Fully adjustable based on business goals |
Implementation Time | Can be done in hours or days | Requires months of development and testing |
This table outlines the main distinctions. Let’s dive deeper into these aspects to help you decide which model fits your needs.
Standard attribution models are ideal for those seeking simplicity and speed, offering eight pre-built options. These include popular approaches like last interaction and linear models. As Himanshu Sharma of OptimizeSmart.com explains:
"No attribution model is good, bad, the best, or flawed. We select an attribution model on the basis of our business model, advertising objectives, and the hypothesis we want to test"
On the other hand, custom models are tailored for businesses with complex customer journeys. However, they require significant effort. Melissa Yap from MNTN emphasizes:
"Setting up a custom attribution model requires significant time and research. You must understand how your audience values each touchpoint so you can assign credit accordingly. Overemphasizing the wrong touchpoints could lead to budget mishaps and underperforming ad campaigns"
For straightforward setups and faster implementation, standard models are a reliable choice. However, if your business needs deeper insights and a tailored approach, custom models are worth the investment .
Choosing the right attribution model depends on aligning it with your business goals and advertising strategy.
Your decision should be guided by your business structure and advertising needs . A few key factors to consider include:
Once you've assessed these factors, it's time to look at where each model performs best.
If your business has a simpler sales journey, a standard attribution model might be all you need. These models are ideal for businesses with straightforward customer paths.
"Ultimately, the best attribution model is the one that's in line with your business goals, customer journey, and resources"
Standard models are particularly effective for:
Research indicates that even basic attribution models can improve marketing efficiency by 20-30% .
"Advanced attribution and marketing mix modeling promise greater fidelity of spend analysis and optimization, but bring their own cost and additional complexity"
Custom models are a better fit for businesses with more intricate needs, such as:
These models shine when you need to track multiple touchpoints across different channels and gain deep insights into customer behavior. While they require more effort and resources, the detailed analysis they provide can be worth the investment.
This section highlights the main differences and practical uses of each approach discussed earlier.
Standard models rely on fixed rules, making them easy to set up and implement. On the other hand, custom models use advanced analytics to provide more accurate credit allocation .
Custom models allow for flexible lookback windows and tailored credit rules based on metrics like session duration and page views. These features are particularly helpful when dealing with complex, multi-channel customer journeys .
Regardless of the model you choose, success depends on maintaining high-quality data, clearly defining conversions, and regularly updating your approach to align with your business goals. The key takeaway: choose an attribution model that fits your marketing strategy and the resources you have available.