Ever feel like you’re throwing marketing dollars into a black hole? You run marketing campaigns across multiple channels, but can you confidently say which marketing efforts yield real returns? This is where marketing attribution models become essential.
Figuring out which marketing touchpoints influence a customer’s buying decision provides invaluable insight. It helps marketers invest wisely. Marketing attribution models show which marketing channels are performing best.
Table Of Contents:
- Why Marketing Attribution Matters
- Understanding Your Data for Marketing Attribution Models
- Collecting The Right Information
- Data Connectivity is Required
- Business Optimization
- Types of Marketing Attribution Models
- Getting into The Process
- Conclusion
Why Marketing Attribution Matters
Today’s customer journey is rarely a straight line. Customers interact with brands 20 to 500 times before finally making a purchase.
It could start with a social media post, leading them to a blog post, and perhaps an in-store visit weeks later. Knowing how each interaction influences the final purchase allows you to double down on effective methods. It’s powerful information.
Without understanding how each interaction contributes to the buying decision, you might overlook what’s working. For product-led growth companies, where conversations might not be central to the customer journey, this gets tricky. Tracking what’s most critical for driving conversions and allocating resources becomes your responsibility for marketing strategy optimization.
Understanding Your Data for Marketing Attribution Models
Consider two users. Each might sign in from multiple devices, complicating their identities.
Even if signed in, their home office or VPNs might use varying IP addresses. Connecting the dots becomes tricky. There’s inherent difficulty in accurately identifying individuals.
Shared IPs or family members using similar computers for research add further challenges. Is this a minor issue? What if your audience signs in but doesn’t use the app like a website visitor?
Without this knowledge, correlating actions is harder. Challenges mount if connections are weak. Incorrectly linking factors can disrupt everything, demanding careful mapping.
Breaking Down Marketing Attribution
Data collection begins with gathering information. Without this foundational step, further action is impossible.
Once you have data, connect it. Analyzing it requires technological proficiency.
The goal is driving critical business decisions. Making sense of data is the core objective. This clarity is highly desired by business professionals.
Collecting The Right Information
Collecting information requires gathering insights from diverse sources. Ideally, you gather a wealth of data from many different places.
Collecting blog content data can answer crucial questions. Consider gathering everything from client browser inputs to server information.
Ad networks also factor in and shouldn’t be dismissed. The platforms, while offering a broad overview, can provide detailed insights.
Review Your Server Logs
Checking logs helps pinpoint where users clicked. These logs are often more valuable than Javascript scripts.
Analyzing site activity provides key metrics on user behavior. You must:
- Monitor every action on a web or app.
- Track inputs from users and responses from your technology stack.
- Comply with regulations, respect user preferences, and document everything.
- Collect data across all digital assets, including documents.
Tools like Segment, Rudderstack, and Snowplow excel at these tasks. These platforms are popular among marketers globally.
Third Party Sources
Various companies and ad networks, like Google Ads, collect vast amounts of data. Though analyzing these datasets individually is challenging, they contain valuable information.
Pulling data from networks where you run marketing campaigns will likely clarify things significantly. Export raw data by connecting datasets using tools like Big Query and Google Ads connectors.
Gather information from Google Cloud or Amazon Web Services. Delve deeper by using your CDN provider.
Data Connectivity is Required
Having everything correctly located is crucial for connecting the dots. Setting it up for centralized analysis is highly beneficial.
You want your tools working together and organized. Start by choosing where and how to do that. Popular methods include leveraging data warehouses like Snowflake, or you might choose a different path.
Once you’ve decided on collection and sorting, proceed to the cleaning phase. Your datasets likely contain irrelevant information requiring attention. Cleaning this up will be the beginning of the user engagement connection. Ultimately, the goal is to achieve useful insights. This gets realized through reporting software that helps with assigning credit where it’s due.
Capturing it All
- Track down anything important, keep gathering details.
- Centralize everything using databases and engineering software.
- Decide on your approach for proper planning and building an incredible dataset.
Data Structuring
- Select methods for tying your dataset using IDs.
- Connect datasets that might have trouble connecting.
- Model data to visualize for improved understanding and channel attribution.
Enable The Insights
Simplifying insights in reporting is beneficial. A tool can visualize different views or reports on engagement. Modeling this information correctly is powerful.
Not everything connects seamlessly. User roadblocks, tech glitches, and bugs can affect results. There’s always something that could disrupt.
However, a solid strategy can address many of those concerns. The right attribution tool will model helps users to find the most success.
Business Optimization
With standard user engagement, analysis quickly becomes valuable. It clarifies which marketing channels are effective. For instance, a customer seeks what your technology offers.
The prospect finds your company and signs up. Conversions always count. Right?
But what’s the actual business impact? Perhaps the person sought task management software for work.
Your app primarily serves consumers, not large teams. A disconnect arises if you don’t grasp conversion motivations. Someone might need business intelligence software beyond dashboards.
Real-World Results
Data points on volume only provide basic details. Marketing attribution uncovers more for optimization.
Tracking leads identifies which campaign type, like free trials, converts effectively. Conversely, discover how gated content affects future business income.
Leads from gated content might become top converters. Studying lead acquisition trends reveals this. Connecting revenue sources and MRR identifies user behaviors impacting income.
Changing lead handling significantly alters customer activity and revenue. Decide how attribution modeling fits business use cases. Specify the desired insights from analyzing marketing attribution.
Channel diversity can help you learn more. Consider how analysis aligns with marketing channels.
Types of Marketing Attribution Models
Attribution modeling provides ways to analyze core aspects influencing marketing outcomes. These approaches can be categorized to fit business needs. Leadership must choose the appropriate model.
Single-Touch Attribution
Simple concepts begin with recognizing conversions from a single influencing touchpoint. This model is straightforward and best for short sales cycles.
There are various examples of the single-touch attribution model.
First-Touch Attribution
This straightforward concept attributes everything to the customer’s starting point. Using a first-touch attribution model simplifies things. Many companies focus on this area.
Last-Touch Attribution
The last-touch attribution model tracks the ending point. Credit is given where a sale occurs.
However, this approach has a major weakness: it ignores other influences. Interactions impacting results aren’t considered.
Multi-Source Attribution
Going beyond a single influencing factor provides a deeper understanding. Each factor carries equal weight in this model.
Explore the many available multi-touch attribution models.
Linear Attribution
The linear attribution model is a simple multi-sourced approach. It identifies valuable information at various points in the customer journey.
Linear approaches are straightforward because you evenly weigh multiple data points. They also separates the various touchpoints for clarity.
Position-Based Attribution
Also known as “U-shaped attribution,” this model focuses on first touchpoints and conversion points. Using position-based marketing can help provide insights about marketing and the attribution model assigns credit to those areas.
Remaining weight is split evenly across other touchpoints. This method can feel generalized. U-shaped concepts might begin with ad touchpoints but extend further.
Time Decay Attribution
Time decay modeling prioritizes interactions closest to conversion. This method organizes data logically for technology use cases. It leverages exponential rates, suitable for in-depth analysis.
W-Shaped Attribution
W-Shaped modeling weights several key areas. Influence is distributed among remaining touchpoints.
Top-of-funnel, core funnel, and conversion points each receive 30% of the total weight. Any leftover value is distributed among the rest of the interaction attribution.
Choosing the Right Path
Consider several factors when exploring what your company should leverage. Think about the following as you consider:
| Marketing Approach | Great For | Problems |
|---|---|---|
| First Touch | Knowing the First Entrypoint | Not analyzing beyond the start of conversions |
| Last Touch | Tracking sales outcomes from clicked ad | Omits areas influencing customers before a conversion action |
| Position Based | Sorting by conversions and early-funnel interactions influence | Doesn’t consider that first versus final clicks could be the biggest influence |
| Time Decay | Studying the things that work to cause the customer to convert | Google Analytics may not accommodate all requirements, particularly with earlier touchpoints |
Attribution models impact all marketers by clarifying questions. Always consider this when deciding which to use. The model helps determine how to allocate resources, too.
Mistakes When Modeling Attribution
A major concern is overlooking elements within the sales funnel impacting income and journeys. Failing to recognize this is problematic. Ignoring a factor overlooks channel value.
Multi-channel recognition offers benefits, though many marketers only use attribution models across channels. Analyzing channels reveals how engagement leads to conversions. Review sources to understand the customer story.
Getting into The Process
Begin using business analysis reports to identify channels supporting revenue. The goal is aligning online channel investments. Data collection from multiple marketing channels is key.
Measuring software could integrate reporting or connect different data components. Tracking offline sources, like advertisements, improves insights. Modern marketing can involve many channels so a multi-touch model could be beneficial.
Tools assist in taking action based on attribution reports. Google Analytics’ multi-channel feature offers comparisons. Consider using it with Windsor.ai to study data across platforms like Google, Bing, Facebook, and LinkedIn. Custom reports can further enhance reporting with this added information. All of this combines the marketing strategy of assigning credit to various efforts to know how to achieve higher conversion rates.
Conclusion
The objective is always to identify what works through proper reporting. Your process becomes clearer as channels align with actions. Continuously study marketing attribution models to empower marketing teams with valuable insights for future marketing campaigns.
