With so many marketing channels and touchpoints (like ad types and unique campaigns), plus an abundance of data pouring in, it's important to know your customer’s journey and understand why they’re purchasing.

Polar Analytics and the Polar Pixel give you a suite of attribution models designed to highlight this path, making sure you have a clear vision of which elements of your marketing strategies are working.

Here’s a look at why attribution models matter and what we offer.

Attribution models are key to unlocking the full potential of your marketing efforts. Here’s why:

At Polar Analytics, we use our Polar Pixel to leverage first-party data and achieve accuracy by tracking customer journeys and conversions that ad platforms don't see.

Our methods are designed to navigate the challenges posed by privacy regulations like iOS 14.5’s ATT framework — ensuring your data is reliable and compliant with current privacy standards.

First Click attribution: Best for top-of-the-funnel, awareness campaigns that aim to identify how potential customers first discover your brand or product.

First Click is Ideal for gauging the initial interest generation effectiveness of various channels.

🎯 This model attributes the conversion solely to the first interaction a customer has with the brand.

Last Click attribution: Best for campaigns focused on driving immediate actions or conversions, such as sales promotions or limited-time offers, where understanding the final push that leads to a purchase is crucial.

🎯 It assigns all credit for a conversion to the final interaction before the purchase.

These models assign credit to every touchpoint within the user's journey, distributing the credit among all interactions.

Linear Attribution: Great for comprehensive marketing strategies where every touchpoint is considered equally important in nurturing customer relationships and driving conversions across the entire customer journey.

🎯 This model distributes credit equally across all touchpoints in the customer journey.

U-Shaped: Ideal for campaigns that emphasize both the introduction of the brand or product and the final decision to purchase, such as launches or rebranding efforts where initial and last impressions are critical

🎯 40% credit to both first and last touchpoints + 20% given evenly among the remaining touchpoints.


Time Decay: Works well for longer sales cycles and retargeting campaigns where the focus is on gradually increasing engagement and convincing the customer over time, with more value placed on interactions closer to the conversion.

🎯 It gives more credit to touchpoints closer to the conversion and less to earlier interactions.


Paid models only consider and give credit to paid touchpoints within the user's journey.

Paid Linear: Useful for analyzing the overall impact of paid advertising efforts by equally valuing all paid campaign touchpoints, helping to assess the performance of paid marketing channels as a whole.

🎯 This model allocates equal credit to all paid touchpoints in the customer journey.


Full Paid Overlap: Best for evaluating specific paid marketing efforts or campaigns by attributing full conversion credit to each paid channel encountered in the customer journey, useful for ROI calculation and optimization of paid strategies.

🎯 Full Paid Overlap distributes full conversion credit to each paid channel in the customer journey. 


Full Impact: Unlike traditional methods that mostly look at clicks, this statistical model looks at all customer journeys to determine the real contribution of each paid channel.

Full Impact looks at every paid touchpoint to understand what helps make a sale and uses advanced learning algorithms to assign attribution credit by impact.

This model’s goal is to keep improving by learning from new data. It’s great for forward-thinking brands looking to leverage advanced analytics and machine learning to measure the comprehensive impact of their marketing efforts.

🎯 Full Impact only accounts for paid marketing channels and assigns credit by impact.

If you'd like to adjust your attribution model in Polar, you can easily do so by editing the "Attribution Model" filter either within your Channel Performance table or within a Custom Report.

Note: Keep in mind that by default, the Polar Pixel metrics (that are automatically added to your Key Indicators section when you first install the pixel) are calculated using the First-Click model.