How To Detect Branded Search Cannibalization
Detect branded search cannibalization by analyzing attribution overlaps and conversion shifts from paid to organic branded channels.
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By Joris van Huët, Founder & CEOUpdated 2 min read
What is Branded Search Cannibalization?
Branded search cannibalization occurs when paid search ads for your brand keywords divert traffic and conversions that would otherwise come from organic branded search results. This leads to inefficiencies as you pay for clicks that do not generate incremental sales.
Why Detect Cannibalization?
Understanding cannibalization allows you to sharpen your ad spend by identifying if paid branded campaigns truly add incremental value or merely capture existing organic traffic.
Step 1: Collect Data from Paid and Organic Channels
Use your marketing attribution tool to pull conversion data separately for paid branded keywords and organic branded search traffic. This requires granular channel tagging.
Step 2: Analyze Conversion Trends
Plot conversion volumes over time for both channels. Look for inverse relationships where increases in paid branded conversions correspond to decreases in organic conversions.
Step 4: Calculate Cannibalization Rate
Define cannibalization rate as:
Cannibalization Rate = (Organic Conversions Lost) / (Paid Branded Conversions Gained)
A cannibalization rate approaching 1 means paid ads mostly shift existing organic conversions rather than generate new ones.
Step 6: Refine Accordingly
If cannibalization is high, consider reducing paid branded bids or reallocating budget to non-branded channels with better incremental ROI.
Related Resources
Your Google Ads ROAS Is Dropping: The Attribution Problem
Paid Search Refinement Template with Attribution Data
Your Retargeting ROAS Is Inflated: Here Is the Math
Frequently asked questions
What causes branded search cannibalization?
Branded search cannibalization happens when paid ads for brand keywords attract clicks that would have come from organic branded search, resulting in paid spend without incremental sales.Is some cannibalization acceptable?
A low level may be acceptable if paid branded ads protect against competitor clicks or maintain brand presence, but high cannibalization indicates inefficient spend.Can cannibalization affect other channels?
Yes, paid branded search cannibalization can overlap with multiple channels.How often should I check for cannibalization?
Regular monitoring, ideally monthly, ensures timely detection and budget optimization based on current channel dynamics.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- Ad SpendAd Spend is the total amount invested in advertising campaigns. It is measured against Return on Ad Spend (ROAS) to evaluate campaign effectiveness.
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- ClickClick is the action a user takes to interact with a digital advertisement, redirecting them to a website or landing page. Clicks are a fundamental metric for measuring ad engagement and a primary input for click-based attribution models.
- ConversionConversion is a specific, desired action a user takes in response to a marketing message, such as a purchase or a sign-up.
- Google AdsGoogle Ads is an online advertising platform where advertisers bid to display ads, service offerings, and product listings.
- Marketing AttributionMarketing attribution assigns credit to marketing touchpoints that contribute to a conversion or sale. Causal inference enhances attribution models by identifying true cause-effect relationships.
- RetargetingRetargeting is online advertising that targets users who have previously interacted with your website or content. Attribution analysis shows the causal role of retargeting in driving conversions and improving ad spend.
- TaggingTagging labels or mentions another user, page, or location in a social media post. It creates links between entities, which helps analyze influence and attribution.