QUICK ANSWER
One of the most difficult questions for a brand manager: 'Did we get our money's worth from the budget we spent on this influencer campaign?' Being able to answer this question with data rather than intuition is possible through correctly establishing attribution modelling.
One of the most difficult questions for a brand manager is this: “Did we get our money’s worth from the budget we spent on this influencer campaign?” Being able to answer this question with data rather than intuition is possible through correctly establishing attribution modelling — conversion attribution. A large proportion of brands investing in influencer marketing in Turkey have either not built this infrastructure at all, or are keeping it at a very primitive level. Yet an attribution system that links influencer spending to business outcomes is a critical tool not just for reporting but for improving budget decisions.
What Is Attribution and Why Is It Not Just an ROI Calculation?
An attribution model defines in a mathematical framework which of the touchpoints a customer passes through on their way to a purchase decision contributed to what extent. In influencer marketing specifically, this means: a user saw an influencer’s content, then a few days later searched on Google, then saw a retargeting ad, and finally made a purchase. Who should the credit for this conversion be given to? The influencer? The Google ad? Retargeting?
The wrong attribution model also misdirects budget decisions. A model that gives one hundred percent credit to the last click makes the upper-funnel awareness created by the influencer invisible and feeds the mistake of “let’s cut the influencer, we can’t show ROI.” Conversely, a model that evaluates each touchpoint with equal weight also obscures real performance.
The Last-Click Model: Why Insufficient on Its Own?
Last-click attribution gives one hundred percent credit to the touchpoint immediately before conversion. Still the most widely used model in digital marketing, but it creates a structural blindness for influencer campaigns.
Why? Influencer content most often comes into play in the discovery and consideration phase. The user sees the influencer, records the product in their mind, then reaches the purchase decision through a different channel at a different time. In this scenario, the last-click model attributes the conversion to the search ad or direct visit; the influencer’s upper-funnel contribution is completely erased.
There is an additional factor in Turkey that triggers this problem: multi-device switching. The user watches the influencer content on their phone but completes the purchase on desktop. A last-click model without cross-device tracking completely misses this scenario.
Multi-Touch Attribution Models
Attribution models evaluating more than one touchpoint provide a more realistic picture. Commonly used models:
Linear model: Gives equal credit to every touchpoint on the purchase path. Simple and democratic; however, since not all touchpoints have equal impact in reality, it can sometimes be misleading.
Time decay: Gives heavier credit to touchpoints closer to the purchase. Logical for e-commerce, because the trigger at the last stage is generally more decisive. However, upper-funnel content (like an influencer awareness video) can still be undervalued.
Position-based (U-Shape): Gives forty percent to the first and last touchpoints, and distributes the remaining twenty percent equally across the middle. This model is quite suitable for influencer marketing: the first touchpoint (influencer discovery content) and the last touchpoint (conversion trigger) are evaluated with weighted consideration.
Data-driven model: This model, offered by Google Analytics 4 and some DMPs, calculates the marginal contribution of each channel with real user data. It requires large data volumes, but provides the most realistic result. Applicable for brands in Turkey with more than one hundred thousand monthly visits and more than tens of thousands of conversions.
Influencer-Specific Attribution Tools
In addition to general web analytics infrastructure, attribution tools specific to influencer campaigns can also be activated:
Custom UTM structure: A unique URL containing source (influencer name or code), medium (campaign name), and content label for each influencer. This structure enables full funnel conversion reporting on an influencer-by-influencer basis in Google Analytics 4.
Promo code system: Influencer-specific promo codes are the most practical method for capturing in-app and offline sales that UTM cannot reach. Code usage rate directly shows influencer contribution.
Pixel-based view-through attribution: The view-through window offered by Meta Pixel and TikTok Pixel (usually one day) tracks conversions performed in subsequent days by users who saw influencer content but didn’t immediately convert. This window reflects the influencer’s real impact much more accurately.
Branded search increase: The organic increase in brand name searches during the influencer campaign period is an important indicator measuring the awareness effect without creating direct conversion. Google Search Console and Google Trends can be used to track this change.
Building the Attribution Infrastructure Before the Campaign
The attribution system is not built after the campaign starts. This infrastructure must be ready before the campaign starts: UTM template created and assigned to each influencer. Meta Pixel and TikTok Pixel on landing pages must be active and triggering the correct events (PageView, AddToCart, Purchase). Conversion tracking and attribution window settings in Google Analytics 4 must be configured. Promo codes entered into the system, single-use or influencer-based restrictions applied. Starting a campaign without this infrastructure is like opening a storefront where the sales connection cannot be established.
How to Interpret an Attribution Report?
When attribution data is ready, the next challenge is interpreting this data correctly. Interpretation mistakes to watch out for: sticking to a single model, selecting a short time window (especially for high-value products, the customer decision process can take weeks), and combining view-through and click-through data (these two metrics should be kept separate). An effective attribution report should answer not just “which influencer made the most sales?” but also “which influencer created the most value at which funnel stage?” Some content creators generate excellent upper-funnel awareness but don’t create direct conversions — this profile is valuable in awareness campaigns but the wrong choice for direct response campaigns.
Kara Talent’s Attribution Framework
In influencer campaigns managed within Kara Talent, attribution infrastructure is planned simultaneously with the campaign brief. A unique UTM and promo code for each influencer is part of the standard deliverable. Throughout the campaign, UTM data is transferred to weekly reports, and the funnel contribution beyond last-click is also covered as a separate heading in the report. At the end of the campaign, an influencer-based attribution comparison feeds the next period’s selection decision: which content creator produced only visibility, and which was able to be associated with real sales?
Part of the legitimacy of influencer marketing comes from being able to answer this question consistently and reliably. Budget decisions made without an attribution model are largely left to chance. Eliminating this uncertainty, for both brand and agency, ensures that the long-term business relationship sits on solid ground.
Practical Consensus Points in Attribution Discussions
One of the most frequently occurring tension points between brand and agency is this: the brand looks at the last-click report and cannot see the influencer contribution, while the agency argues that the upper-funnel effect is real. The way to resolve this tension is to mutually agree on the attribution framework in writing before the campaign starts. Which model will be used, which window (attribution window) will be adopted, whether view-through and click-through conversions will be reported separately or together, how promo code sales will be accounted for — these decisions should be determined before the campaign. Changing the model afterward doesn’t resolve the argument; on the contrary, it creates trust erosion. Kara Talent guarantees expectation alignment between brand and agency from the start by adding these items to the measurement framework document prepared before each campaign.
Incrementality Testing: Beyond Attribution
The attribution model determines which channel the existing conversions should be attributed to. However, there is a deeper question: if the influencer campaign hadn’t happened, would some of these conversions have occurred anyway? To answer this question, incrementality testing — incremental impact testing — is applied. The test group is exposed to influencer content while the control group does not see it; the conversion difference between the two groups shows the real incremental impact of the campaign. The number of brands in Turkey applying this test methodology is still very small, but when done correctly it definitively resolves attribution discussions and proves the legitimacy of influencer investment with data.
