Videos
TikTok Data Literacy Lab
A strategic training program designed to transform how TikTok Sales and Client Solutions teams engage with data—from fragmented sources to client-ready narratives that drive revenue growth.
5-Session Program
Sales & Client Solutions
Data → Narrative → Revenue
Program Overview
This program follows a deliberate progression that mirrors real-world team operations: understanding the ecosystem, extracting signal, telling persuasive stories, and driving next actions. The structure reflects how teams actually work with fragmented data sources, varying tool fluency, and constant pressure to translate numbers into compelling client stories.
Data Literacy
Sessions 1–2 establish shared data literacy and TikTok tool context
Strategic Narratives
Sessions 3–4 focus on transforming TikTok data into strategic narratives
Live Application
Session 5 applies everything to live client scenarios
Session 1
The Client's World: Data Capture, Attribution & Why Numbers Disagree
Build a shared mental model of how advertising data is captured, attributed, and reported — across TikTok and the client's stack — so that every data conversation starts from credibility, not defensiveness.
Core Topics
  • Pixel, Events API, and SDK: how TikTok captures data
  • iOS 14+ impact on signal loss and attribution accuracy
  • Attribution windows and why they create discrepancies
  • MTA (Multi-Touch Attribution) vs. MMM (Media Mix Modeling)
  • First-party vs. third-party data: what TikTok sees vs. what clients see
  • The broader measurement ecosystem: MMPs, Google Analytics, Adobe, Rockerbox, Tealium, Nielsen, Comscore, IRI
  • The Source-of-Truth Conversation: how to navigate discrepancies without being defensive

Key Insight: TikTok frequently over-indexes on performance internally relative to client MMP reporting. The goal is to explain this confidently — not defend it reactively.
Outcome
Understand where TikTok fits inside a client's full measurement stack, why numbers don't always match, and how to proactively frame those differences in any client conversation.
Homework
Audit one live or past account. Identify the client's source of truth for measurement. Map TikTok data sources, client MMP data sources, and document where and why discrepancies appear.
Read the Data: The TikTok Data Ecosystem + Data Manipulation Foundations
Build hands-on fluency with TikTok's actual data — TTAM exports, Market Scope views, and measurement study readouts — so participants can find signal in the numbers, not just read what's on screen.
TikTok Ads Manager (TTAM)
Campaign, ad group, and ad-level reporting across 22 columns of raw data. Events Manager, attribution analytics, experiments, lift studies, Audience Insights, and creative diagnostics. Metric selection by objective: LPV, conversions, reach, video views.
Market Scope
Audience Asset: sizing, demographics, funnel positioning. Brand Perception: awareness and consideration signals. Organic-to-paid connections. Decision framework: when to use Market Scope vs. campaign data.
BLS Deep Dive
Understanding Brand Lift Studies end-to-end. Interpreting results and communicating lift to clients. Common misreads and how to avoid them.
Data Manipulation Foundations
Pivot tables for campaign analysis using real TTAM exports. Calculated fields: CPM, CTR, CPA, VCR, ROAS, Cost per LPV. VLOOKUP / XLOOKUP for data matching. Every formula applied to real TikTok data.
Session 3
Find the Signal: From Numbers to Opportunities
Develop the analytical instinct to look at TikTok data strategically — identifying patterns, gaps, and opportunities — instead of jumping from high-level data straight to individual accounts. This session addresses the "data secretary" problem head-on.
1
The Diagnostic Framework
A repeatable method: (1) What's the client's stated objective? (2) What does this data say about progress toward it? (3) What does this data say that the client hasn't asked about? That third question is where Level 3 thinking lives.
2
The 'So What' Framework
A four-step model: Data → Insight → Implication → Recommendation. Moves every conversation from "here are the numbers" to "here's what this means and what to do next."
3
Signal vs. Noise in TikTok Reporting
Not all metrics matter equally. Signal changes behavior. Noise fills a slide. Traps look good but mislead. Metric selection by vertical: commerce vs. leads-and-services.
4
Market vs. Campaign Data
Campaign data answers "how did we do." Market data answers "what should we do next." The upsell lives in the gap between them.
"Their analysis jumps from overall data to account. There is no strategy. They're not looking at the data strategically — what angles they can look into it." — Wenxin

Think First, Prompt Second: The right way to use AI with TikTok data — form a hypothesis first, then use AI to test it, visualize it, or find what you missed. Never lead with "analyze this for me." Always verify the output against what you know.
Outcome
Apply the Diagnostic Framework and "So What" model to read TikTok data strategically — identifying opportunities the client hasn't asked about and mapping performance signals to product recommendations.
Homework
Write a one-page QBR-style narrative: (1) Here's what we did and how it performed, (2) Here's what the data tells us about where the opportunity is, (3) Here's what I recommend we do next and why. Tailor one version for a CMO and one for a manager.
Session 4
Tell the Story: Audience-First Selling & The Upsell Conversation
Transform analysis into clear, defensible, client-ready narratives that drive spend decisions — for QBRs, office hours, upsell conversations, and pitch meetings. Shift client conversations from reporting what happened to shaping what happens next.
CMO
Strategic, outcome-focused. Lead with category insight, end with investment recommendation. Address Day 7 ROAS on their BI dashboard directly.
Manager
Tactical, efficiency-focused. Optimization narratives tied to performance signals. Upsell and incremental growth motions.
Analyst
Granular, data-focused. Connecting mid-funnel signals to future investment. Metric-level precision and methodology transparency.
Sales Track
  • Pre-sale storytelling with audience data
  • Market-led opportunity identification using Market Scope
  • Pitching incremental reach and new audiences
Client Solutions Track
  • Optimization narratives tied to performance signals
  • Upsell and incremental growth motions
  • Connecting mid-funnel signals to future investment
Handling Objections with Data
"TikTok is too expensive." → Reframe with reach efficiency and CPM benchmarks
"We don't see the ROAS." → Shift to full-funnel attribution context
"Meta performs better." → Use Market Scope to show incremental audience

Signal-to-Action Framework: Map performance signals directly to product recommendations. Use Market Scope audience data to anchor every pitch in market reality — positioning TikTok as indispensable within the client's media mix.
ession 5
Practicum & Panel
The final session applies the full progression — Industry context → TikTok tools → Strategic narrative. Participants deliver live QBR-style presentations scored on a 100-point rubric, with feedback from a panel intentionally composed to mirror real accountability structures.
20%
Data Accuracy
Correct use of TikTok metrics and measurement context
20%
Narrative Strength
Clear story arc from data to recommendation
20%
Persona Alignment
Tailored delivery for the right audience
20%
Upsell Quality
Compelling, data-anchored growth recommendation
20%
Objection Handling
Confident, data-driven responses under pressure
Session Structure
01
Live QBR-Style Presentations — 5 minutes each, strictly timed. Real sales pitches or optimization stories built in Session 4 homework.
02
The Messy Data Round — Facilitated group exercise with deliberately contradictory metrics. Build the skill of presenting honestly without losing the room.
03
Peer & Facilitator Feedback — Structured debrief on narrative structure, data usage, client positioning, and objection handling.
04
Personal Action Plan — Three 30-day commitments: one tool used differently, one conversation approached differently, one habit stopped. Shared with managers for follow-up accountability.
Panel Composition
CS Leader
BPM Sales Lead
Facilitator

Panel composition intentionally mirrors real leadership accountability — signaling organizational commitment to the program's outcomes and driving real behavior change.
The program doesn't end when the session ends.