Mother of all Attribution Guides.
Understanding your customer journey is crucial to optimizing your marketing strategy, and selecting the right attribution model can make all the difference. Attribution models determine how credit for conversions is assigned across various touch points, helping you understand which efforts drive results. Here’s a straightforward guide to choosing an attribution model that aligns with your business goals.
What Are Attribution Models?
Attribution models are frameworks for assigning credit to marketing channels based on the customer’s journey. Each model answers a simple question:
Which channels or interactions deserve recognition for driving a conversion?
Common attribution models include:
First-Click: Gives full credit to the first interaction.
Last-Click: Assigns all credit to the final touchpoint before conversion.
Linear: Distributes credit evenly across all touch points.
Time-Decay: Awards more credit to recent interactions.
U-Shaped: Allocates majority credit to the first and last touch points, and the remaining across middle interactions.
Key Considerations When Choosing an Attribution Model
To select the right model, start by clarifying your business objectives and understanding the nature of your customer journey. Here are some key factors to consider:
1. Marketing Goals
Your marketing objective defines which attribution model is most suitable. Here's how different goals align with attribution models:
Brand Awareness:For campaigns focused on drawing attention and sparking initial interest, First-Click Attribution is ideal. It emphasizes the channel or interaction that introduced your audience to your brand.
Example: A customer discovers your product through a Facebook ad but takes weeks to convert. First-Click Attribution highlights the importance of that initial awareness.Conversion Optimisation:When closing the deal is your priority, Last-Click Attribution helps identify which channels or interactions seal the conversion.
Example: A retargeting ad on Google drives a customer to finalise a purchase. Last-Click Attribution ensures this critical touchpoint gets the credit.Holistic Customer Journey Insights:For a complete understanding of how multiple touch points work together, Linear Attribution or Data-Driven Attribution offer balanced or algorithmic insights.
Example: A campaign using email, paid ads, and social media shows how each channel contributes to nurturing and converting customers.
2. Sales Cycle Length
The length of your sales cycle determines how many interactions happen before a customer converts. Choose attribution models that match this complexity:
Short Sales Cycles (E-commerce):Customers make decisions quickly, often influenced by one or two key touch points. Use models like Last-Click Attribution to focus on what closed the sale, or First-Click Attribution to identify what brought them in. Example: A customer sees a social media ad, clicks, and purchases within hours.
Long Sales Cycles (B2B or high-value products):Customers engage over weeks or months across multiple channels. Models like Time-Decay Attribution or U-Shaped Attribution capture how various interactions contribute, with greater emphasis on the final and initial steps. Example: A business prospect attends a webinar, reads whitepapers, and responds to an email campaign before making a purchase.
3. Available Data and Resources
Your data quality and analytics capabilities play a key role in choosing an attribution model:
Limited Data or Tools:Stick to simple models like First-Click or Last-Click Attribution, which don’t require advanced tools or large datasets. Example: A startup with basic website analytics can still track which source initiated a customer journey.
Rich Data and Advanced Tools:With access to CRM systems and marketing analytics platforms, you can explore Data-Driven Attribution or Algorithmic Models like Markov Chains. These models dynamically assign credit based on channel performance and user behavior. Example: A SaaS company using predictive analytics can identify which touchpoints are driving lifetime value.
4. Channel and Campaign Mix
The diversity of your marketing efforts impacts how you should assign credit:
Single-Channel Campaigns:For campaigns focused on one channel, like paid search, simpler models like Last-Click Attribution provide clarity on which keywords or ads convert best. Example: A single Google Ads campaign directing traffic to your product page.
Multi-Channel Campaigns:For complex campaigns using email, social media, and paid ads, Linear Attribution or Position-Based Attribution captures contributions from each touchpoint. Example: A customer clicks a social ad, opens an email, and converts through a retargeting ad.
5. Analytics Granularity
The depth of analysis required also influences your attribution model choice:
Transactional-Level Insights:Use Heuristic Models like First or Last-Click for straightforward insights into individual transactions. Example: Tracking a direct conversion from a single ad click for a flash sale.
Cohort-Level Insights:For broader trends and predictive insights, go for Algorithmic Models or Data-Driven Attribution. Example: Identifying how repeat purchases from loyalty program members correlate with specific campaigns.
Take the Quiz to Find Your Best Fit
Not sure which attribution model suits your needs? We’ve designed a quick quiz to guide you through the process. Answer a few simple questions about your goals, sales cycle, and data resources, and we’ll recommend the best model for your business.
Try the attribution quiz
Conclusion
Attribution models are not one-size-fits-all. Align your choice with your business goals, sales cycle, and available data. By starting simple and iterating as you grow, you’ll unlock deeper insights to refine your marketing strategy.
Ready to find your perfect fit? Take our quick quiz to uncover the attribution model best suited for your needs!
📖 Want to explore more?
Check out our previous article: A Deep Dive into Attribution Maths — Part 3
🔗 In our previous article, we explored Shapley and Markov models—two key examples of Algorithmic Attribution Models—alongside Heuristic Models.
