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TIKTOK SHOP → AMAZON

Halo calculator

Understand the relationship between your TikTok activity and Amazon sales.

Measure the relationship between TikTok views and Amazon sales. We use daily history to estimate sales with and without the measured TikTok exposure. This is a preliminary model estimate.
STEP 1 OF 4

What are you measuring?

Use the same brand and products on both platforms.

Update an existing analysis or restore a workspace

Your weekly update

Daily data · weekly routine

Start with 210 daily Amazon outcomes plus 28 earlier days of TikTok views when available. The minimum remains 140 + 28 days; it is a software floor, not a guarantee of accuracy. Never turn a weekly total into seven invented daily values.

  1. First run: upload the full history for one brand/product scope. Whole-account Amazon data is the simplest manual option when the account contains only that brand.
  2. Every Wednesday: restore your workspace. Re-export the last 28 days through the preceding Saturday from both sources, retaining daily rows. Review replacements so late corrections are included.
  3. Check and run: verify the same scope/day boundaries, record promotions or stock issues, advance the cutoff and run. Review the latest complete week and trailing 28 days.
  4. Save: download the updated workspace and full analysis. Monthly, replace both histories with fresh complete exports to catch older revisions.

The suggested cutoff allows three full days after the reporting day closes. This is a ShopOS operating buffer, not a provider finalization guarantee. If either source is incomplete, choose an earlier date. A selected-product Amazon backfill can require one export per day; use a verified daily warehouse extract when that is impractical.

Workspaces contain source CSVs and settings, not approved results. They stay on your device unless you share the file.

Leave unchecked to replace the entire file. Pasting always replaces the full history. Both weekly files must keep the same columns, controls, product scope and metric definitions.
THE MEASUREMENT

What these numbers mean

In plain language

Upload daily Amazon sales and daily TikTok video views for the same products. The model uses their historical relationship, weekday patterns, trend and delayed views to estimate an Amazon sales contribution for the period you choose.

The amount is a period total of ordered product sales. The range describes uncertainty under the model’s assumptions. It does not prove that TikTok caused individual Amazon purchases or account for every other business change.

Calculation methods and technical requirements

Quick calculator

Scenario gap = actual Amazon ordered product sales − your supplied expected sales without TikTok. Lift = gap ÷ expected sales. The baseline drives this answer; the calculator cannot verify it from two sales totals.

If you enter a baseline range, the gap range is actual − high baseline through actual − low baseline. It is a user-defined scenario range, not an 80% or 95% confidence interval. Previous-period sales alone do not establish a counterfactual.

Daily data model

A signed linear model uses trend, weekday effects and one delayed TikTok view series. It evaluates 12 prespecified kernels with lags 0–28 days, decay 0.5/0.7/0.85 and peak 0/3/7/14. At 730 Amazon outcome days, annual Fourier terms are included. Optional control_ columns are standardized and held fixed under the comparison.

The point estimate uses the lowest-AIC candidate. The counterfactual removes all measured exposure, including warmup. It is a whole-program comparison, not a campaign effect. Fitted sales and actual sales differ by the model residual; the contribution is fitted actual-condition sales minus fitted zero-exposure sales.

Each of the 12 candidates receives 1,000 HC2-adjusted block-wild bootstrap replicates, with 14-day calendar blocks and seed 41017. Aggregate 80% and 95% ranges are the union of candidate percentile ranges. They describe uncertainty conditional on these modeling assumptions; they do not cover all omitted causes or establish real-shop causal validity.

Requirements and limits

At least 140 complete outcome days plus 28 exposure warmup days; continuous daily inputs; exposure CV ≥0.3; selected exposure VIF ≤5; at least five observations per parameter. This simple runner requires 100% complete outcomes and limits input to 1,096 outcome days. A block choice of 7 or 28 days can be run as sensitivity after the main result.

Predictive validation holds out three consecutive 14-day periods. Each fold chooses its lag from training outcomes only and compares against an otherwise identical no-TikTok model and a last-week seasonal baseline. Lower error does not prove causal attribution. Price, stock, other marketing and seasonal changes can explain the same sales movements. Causal support, placebo/negative-control tests, broader simulation validation and independent review are not completed by this tool. Daily model results are internal draft estimates, never automatically approved customer claims.

What to upload

Amazon: date and ordered product sales in one marketplace and currency. TikTok: date and verified daily total views, starting 28 days earlier. Use the same approved products and source-day boundaries. If data is missing, leave it blank; it won’t become zero.

The upload screen includes exact export paths for Amazon Seller Central and TikTok Shop Seller Center. Platform downloads must be reshaped into the ShopOS template; they are not accepted unchanged.

No customer names, order addresses, payment data or private creator contact information are needed. Every export retains inputs, scope, method and result status. Program-return scenarios require matched costs; they are not media iROAS or profit.