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Holistic Measurement

When a user views an ad on TikTok, it's not always a simple click and convert. TikTok ad views frequently serve as the starting point for further exploration and purchases across platforms. Therefore, a holistic measurement approach involving the right solutions and partners is essential to showing TikTok's true impact.

Your Path to Measurement Success Scale Bundle more tools to understand complex consumer behavior on and off TikTok and identify growth levers for your business

Improve Prove Measure TikTokʼs true value beyond last click or ad attention metrics to inform key budget decisions

Optimize channel performance with test & learn frameworks designed to improve ROI to get more for your dollar

Measurement Solutions Overview

Accessible for all

Unlock business outcomes

Understand impact across the funnel

Split Test

Conversion Lift Study

Unified Lift Study

TikTok

TikTok

TikTok

Media Mix Modelling

Multi Touch Attribution

TikTok

TikTok data UI, API, 3P Partners)

Fospha, KLAR!

Brand Lift Study

Multi-Cell Conversion Lift Study

Sales Lift - Geo Lift

Attribution Analytics

TikTok, Kantar)

TikTok

Post Purchase Survey PPS

Store Visits Lift

TikTok, KnoCommerce)

Circana)

(new partner in testing)

TikTok Measurement Partners

Key takeaways

1

Know the limitations of web analytics by leveraging Attribution Analytics to understand how TikTok drives conversions, whether thatʼs through view-through or click-through attribution

2

Measure beyond last click to capture TikTok's channel value (including view-through impact) for key investment decisions across channels.

3

Determine the most effective TikTok touchpoints by calibrating attribution with CLS or PPS results or leveraging robust cross-channel measurement (MTA, MMM)

This document is the property of TikTok Inc. and is intended solely for informational purposes. The recipient shall not distribute, exhibit or otherwise use this document for any other purpose. TikTok undertakes no obligation or responsibility to update any of the information contained in this document. Past performance does not guarantee or predict future performance.


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