Sponsored Brands and Sponsored Products often bid on the same queries for the same products. When they do, you can end up paying twice to reach one shopper, or paying SB prices for a sale SP would have won anyway.

The word "cannibalisation" gets used loosely. This playbook is about establishing whether it is actually happening, because the answer is frequently no.

**Time: about 90 minutes. Do it twice a year, or after any SB expansion.**

[Watch the walkthrough](https://kb.trackiq.com/kb-assets/kbvideo-cannibalisation-explainer-5060c91a.mp4)

*Prefer to watch? Seventy-eight seconds on what cannot be measured, and the test that can.*

## **Step 0 — Know what you cannot measure**

Be clear about the limit before you start, because it shapes every conclusion below.

**Amazon does not tell you when two of your ads appeared on the same search for the same shopper.** There is no report for it, in TrackIQ or anywhere else. What you can do is find the **overlap in queries and products**, measure the two formats against each other, and reason carefully about the difference.

Anyone claiming a precise cannibalisation figure is estimating. So will you be — just knowingly.

## **Step 1 — Find the overlap**

**Amazon Ads → Search Terms**, with [**Aggregated Search Terms**](https://kb.trackiq.com/hc/knowledge-base/articles/search-terms-and-aggregated-search-terms) on.

![Search terms, aggregated across the account](/kb-assets/shot-adv-terms-view-2cadd4.png)

Aggregation matters here for a specific reason: it collapses the same customer search across every keyword and ad group it came from, which is exactly the view you need to see one query served by two formats.

Sort by spend and look for queries that appear in **both** an SB and an SP campaign. Those are your candidates. Everything else is not a cannibalisation question at all.

**A large SB budget with almost no query overlap is not cannibalising anything** — it is reaching different searches, and this exercise ends here for those campaigns.

## **Step 2 — Check whether they are chasing the same products**

Overlapping queries only matter if they lead to the same ASINs.

**Amazon Ads → Product Ads** shows ASIN-level performance across formats. If your SB campaign drives a category page or a range of products while SP drives one hero ASIN, they are doing different jobs on the same query, and that is usually fine.

If both formats point at the same single ASIN on the same query, you have a genuine candidate.

## **Step 3 — Compare the two on that query**

**Amazon Ads → Campaigns**, filtered to the overlapping campaigns.

![Campaign performance with the comparison toggle](/kb-assets/shot-adv-campaigns-view-77ace2.png)

For each overlapping query, compare the formats on:

**CPC.** Sponsored Brands typically costs more per click. If SB is paying materially more for the same query and converting no better, that is the clearest signal in this whole exercise.

**Conversion rate.** If SB converts better, it may be earning its premium — brand-led creative can qualify the click before it happens.

**New-to-brand share.** This is the one that settles most arguments, and it needs AMC.

## **Step 4 — Read the NTB split**

**AMC Cloud → NTB Purchases.**

![New-to-brand share by ad product type](/kb-assets/shot-b27-purch-top-7fa12d.png)

Sponsored Brands frequently shows the **highest NTB rate** of any format, and that changes the conclusion entirely.

**If SB's NTB share is well above SP's**, the two formats are not competing for the same customer — SB is reaching people who do not know you and SP is converting people who do. Cutting SB to save money on overlap would remove your best recruiter to save a small amount on duplicate exposure.

**If SB's NTB share matches SP's**, they are reaching the same population, and the overlap is real. Now the CPC comparison from step 3 decides which one should hold the query.

Watch the volume trap: SB often has the best NTB **rate** on a tiny **share** of your new customers. Both facts matter. See **NTB Customers: New vs Repeat, Counted as People**.

## **Step 5 — Test it, do not assume it**

The only honest way to size the effect is to change one thing and watch.

**Pick your three or four clearest overlaps.** Not the whole account.

**Reduce, do not remove.** Lower the SB bid on those queries by 25–30% rather than pausing. Pausing tells you what happens with none of it; reducing tells you about the margin, which is what you are actually deciding.

**Watch total sales for that product, not the campaign's sales.** This is the crucial instrument. If SB spend falls and SP sales rise by roughly the same amount, the traffic simply moved — that is cannibalisation, and you have just saved the difference. If SB spend falls and **total** sales fall too, SB was bringing something SP was not.

**Give it three weeks.** Attribution lags 7–14 days depending on format, so a two-week read is mostly noise. See [**Why SP, SB and SD Numbers Don't Add Up**](https://kb.trackiq.com/hc/knowledge-base/articles/why-sp-sb-and-sd-numbers-dont-add-up).

## **Step 6 — Decide**

| What the test showed | Do |
|---|---|
| SP sales rose to match SB's fall | genuine overlap — keep SB reduced on those queries |
| Total sales fell with SB spend | SB was incremental — restore it |
| Nothing moved either way | the spend was small; leave it and move on |
| SB fell, NTB users fell | **restore it** — you cut acquisition, not waste |

The last row is the one to watch for, and it is the reason step 4 exists.

## **What not to do**

**Do not pause Sponsored Brands wholesale** to "stop cannibalisation". You will remove a discovery format and attribute the resulting decline to something else three months later.

**Do not test across the whole account.** You will not be able to read the result.

**Do not judge on campaign-level sales.** Both campaigns' numbers will move; the product's total is the honest measure.

**Do not conclude from one week.** Two formats with different attribution windows need three.

**Do not run this alongside a bid-strategy change.** One variable.

## **Related**

- [**Search Terms and Aggregated Search Terms**](https://kb.trackiq.com/hc/knowledge-base/articles/search-terms-and-aggregated-search-terms) — step 1, and why aggregation matters.
- [**NTB Purchases: New Business by Campaign**](https://kb.trackiq.com/hc/knowledge-base/articles/ntb-purchases) — step 4, the deciding evidence.
- [**Why SP, SB and SD Numbers Don't Add Up**](https://kb.trackiq.com/hc/knowledge-base/articles/why-sp-sb-and-sd-numbers-dont-add-up) — the attribution differences behind the test.
- [**Product Ads: ASIN-Level Ad Performance**](https://kb.trackiq.com/hc/knowledge-base/articles/product-ads) — step 2.
- [**Create a Sponsored Brands Campaign**](https://kb.trackiq.com/hc/knowledge-base/articles/create-a-sponsored-brands-campaign) — how the brand banner is set up in the first place.