Coming Soon

We're expanding our execution pipeline to support more channels and deeper account-level intelligence. Stay tuned for the next release.

TikTok Ads Assistant

From a confidence interval to a live change in TikTok, sized to match

Pangolin's model is built for a channel with limited history, and shows the uncertainty rather than hiding it. Once you approve a budget move, Pangolin executes it directly in TikTok Ads Manager, sized to how confident the model currently is.

Book a Pangolin demo

1. Bayesian Sizing recommendation Shift £1,800/wk to Top-of-Funnel Prospecting (84% Confidence Interval)

2. Awaiting Human Sign-off Performance lead review pending APPROVE

3. Direct TikTok Deployment Budget re-allocated dynamically inside TikTok Ads Manager

The Critical Gap

The problem with manual TikTok Ads management

New channels don't have years of spend and revenue history to model against, so any recommendation should come with real uncertainty attached - and that uncertainty should affect how much changes, not just what's reported.

In practice, teams either wait for a certainty that a data-sparse channel will never quite deliver, or manually resize TikTok budget test-by-test, logging into TikTok Ads Manager each time evidence shifts, while the account runs on outdated settings in between.

This delay means campaign dollars sit stagnant in non-performing sets during crucial high-momentum testing windows.

The Testing Disadvantage

Average time elapsed awaiting absolute modeling certainty 12-18 days

Typical delay in manual TikTok campaign adjustments 5.1 days

Average budget wasted on sub-optimal trial bids 38%

The Mechanism

How Pangolin's TikTok Ads Assistant works

Pangolin's Bayesian model uses informed priors where TikTok data is sparse, and narrows the confidence interval as more data accumulates.

1. Informed Priors Bayesian Modeling Establishes performance expectations early where history is sparse, bypassing standard data voids.

2. Confidence Sizing Adaptive Moves Smaller, conservative budget adjustments early on, larger and bolder moves as confidence accumulates.

3. Human Approval Human in the Loop Every budget shift proposal is routed to you for approval first - no changes deploy untracked.

4. API Deployment TikTok Ads API Integration Approved recommendations instantly deploy in TikTok Ads Manager with zero manual execution.

Capabilities

What the assistant does today, and what it recommends

Pangolin surfaces a confidence-weighted budget recommendation for TikTok, routes it for approval, and executes approved changes directly in TikTok Ads Manager.

1. Monitoring Headroom Flagged

Spark Ads - Creator Amplification

Current spend £1,200/day

Low Saturation Yield optimization potential

2. Sizing Uncertainty-Weighted Change

Targeted Reallocation

Daily Budget £1,200/day → £1,550/day

Sized conservatively based on active 62% confidence interval parameters.

APPROVE REJECT

3. Deployed Live in TikTok Ads Manager

ToF Prospecting UK

New daily limit £1,550/day

Deployed Confidence Level: 84%

Budget adjusted +£350/day · API confirmation code 8d2c-f9 · Completed automatically

The Difference

Why this is different

Versus treating all channels the same Data-Sparse Sensitivity

A channel with three months of data gets smaller, more cautious executed changes than one with three years. Pangolin handles uncertainty natively.

✓ Custom Bayesian prior mapping✓ Prevent high-variance budget spikes

Versus manual test-and-adjust No Platform Logging Lag

No one has to log into TikTok Ads Manager each time the evidence shifts. Approved budget adjustments sync to the native API dynamically.

✓ Auto-reallocations within minutes of signoff✓ Immediate capture of performance windows

Versus waiting for "enough data" Active Bayesian Testing

Bayesian priors let Pangolin start executing sensibly-sized changes sooner, rather than waiting for a certainty that may never arrive.

✓ Accelerate testing on sparse channels✓ Scale safely with shrinking intervals

Business Value

What it means commercially

Sized to Evidence Scale TikTok spend through changes sized directly to the active statistical evidence, executed the day they're approved. No delayed opportunity windows.

Right size risk Avoid the two classic failure modes: over-committing budget to TikTok because it's new and exciting, or leaving it under-resourced because no one gets around to adjusting it.

Unbroken Audit Log A complete, timestamped record of every executed change and the confidence behind it, so the decision can be revisited and audited as the interval narrows.

Clear Cognition

Frequently Asked Questions

How much TikTok spend history do I need before Pangolin will execute a change?

Some estimate is possible from early data; executed changes are simply smaller and more conservative until the interval narrows and the model collects more data.

Will Pangolin execute changes automatically, or does someone need to approve first?

Every change is routed for human approval before execution. You always hold absolute control over budget deployment.

Does this work the same way for any new channel, not just TikTok?

Yes - the same confidence-weighted approach applies to execution on any channel with limited history. It ensures you test safely and scale responsibly.

Can Pangolin manage TikTok spend across multiple ad accounts?

Yes, recommendations and executed changes are visible and actioned across every connected TikTok Ads account from a single view.

How does Pangolin decide how big a change to make?

The size of every executed change is tied to the width of the model's confidence interval at that moment. Wider intervals, typical in the first weeks on a new channel, produce smaller, more conservative moves. As the interval narrows with more data, Pangolin sizes larger changes using the same underlying process.

Ready to automate TikTok Ads execution?

Free consultation for brands spending >500k / month.