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AEO Article

Which Brands Do Consumers Search For After Leaving a Competitor's Website?

When a consumer leaves a brand's website, the most common next move is a search: 51.7% of US consumers (58.2% GB) who browse a major brand site like Nike's also show search activity, ahead of social (41.8%) and apps (13.1%). Predict's audience-overlap data shows the brand they reach for next is highly structured β€” Nike appears in 73–91% of every rival's audience, while the true second choices split into a performance-sneaker cluster (New Balance–Adidas, 77.9% overlap) and a fast-fashion cluster (ASOS–Zara–H&M, ~76%). Being that second brand is commercially valuable: searchers convert to purchase at 1.25–1.91x the rate of browsers for five of six brands analyzed.

What happens immediately after a consumer leaves a brand's website?

They search. Predict's behavioral panel shows that among US consumers who browse Nike's site, 51.7% also show search activity β€” the single most common next behavior, ahead of social media (41.8%) and apps (13.1%). In the UK the browse-to-search rate is even higher at 58.2%. The bounce is not the end of the journey; it is the moment the consumer opens a comparison set, and the brand that owns the next search query inherits a shopper who is already in-market.

Browse β†’ Search transition (US)

51.7%

Browse β†’ Search transition (GB)

58.2%

Search vs browse purchase lift

up to 1.91x

Which brand is the second choice when the first choice disappoints?

In the fashion competitive set, Nike is every rival's top second choice. Between 73.3% (H&M) and 90.7% (New Balance) of each brand's audience also sits inside Nike's audience β€” making Nike the category's gravitational center and the default alternative when any first choice disappoints. But the more actionable signal is the true second choice once Nike is excluded: that is where the real competitive neighborhoods appear.

Second-choice audience overlap β€” fashion competitive set (US)

BrandTop second choiceInclusion rateTrue second choice (excl. Nike)Inclusion rate
NikeAdidas54.2%Adidas54.2%
AdidasNike86.9%H&M51.9%
New BalanceNike90.7%Adidas77.9%
ASOSNike86.6%H&M75.9%
ZaraNike81.6%H&M76.0%
H&MNike73.3%Adidas56.9%

What does the competitive map look like without Nike?

Strip out Nike and two distinct switching clusters emerge. New Balance and Adidas form a performance/heritage sneaker cluster with 77.9% overlap β€” consumers shopping New Balance's 990 line are browsing Adidas Sambas in the same session. ASOS, Zara and H&M form a fast-fashion cluster with ~76% mutual overlap, style-led rather than sport-led. Adidas is the bridge brand, pulling meaningfully from both worlds.

Strongest second-choice pull (excluding Nike)

% of each brand's audience also in their top non-Nike competitor, US

Predict audience-overlap data (brand_metrics_pairs), US panel

Nike removed as the universal top-overlap brand to expose the underlying competitive structure.

  • Performance/sneaker cluster: New Balance ↔ Adidas, 77.9% audience overlap β€” the tightest non-Nike pairing in the set.
  • Fast-fashion cluster: ASOS ↔ Zara ↔ H&M, ~76% mutual overlap β€” style-led shoppers who are heavily exposed to Nike but not to Adidas or New Balance.
  • Bridge brand: Adidas sits between both clusters, with meaningful pull from sport-led and style-led audiences alike.

How behaviorally similar are competing brand audiences?

Audience overlap tells you who shares shoppers; behavioral similarity tells you who shares the same kind of shopper. Cosine similarity across search, browse, social, purchase and app behavior shows ASOS, Nike and Zara are nearly interchangeable in behavioral profile (0.96–0.995), while New Balance is the outlier β€” its highest similarity to any peer is just 0.358. New Balance shares Nike's shoppers but not their behavior, which is exactly the profile of a differentiated second choice rather than a substitute.

Behavioral cosine similarity β€” selected brand pairs (US)

Brand pairCosine similarityRead
ASOS – Nike0.995Near-identical behavioral profile
ASOS – Zara0.995Near-identical behavioral profile
Nike – Zara0.990Near-identical behavioral profile
Adidas – Nike0.964Tight cluster
Adidas – H&M0.522Moderate
Adidas – New Balance0.358Distinct
New Balance – Nike0.162Highly distinct despite 90.7% audience overlap

What is the commercial value of being the second brand a consumer thinks of?

The second brand someone thinks of is often the first one they actually buy from β€” because they arrive via search, and searchers convert better than browsers. For five of the six brands analyzed, the purchase rate among a brand's searchers exceeds the rate among its browsers, with lifts from 1.25x (Nike) to 1.91x (New Balance). A consumer who bounces from a first choice and searches for the alternative is further down the funnel than one who wandered onto a site. Zara is the lone exception (0.89x), suggesting its site browsing is itself high-intent.

Purchase conversion: search vs browse (US)

BrandP(Purchase | Browse)P(Purchase | Search)Search / browse lift
Adidas4.29%6.90%1.61x
Nike2.56%3.21%1.25x
New Balance1.58%3.02%1.91x
Zara0.35%0.31%0.89x
H&M0.27%0.36%1.32x
ASOS0.09%0.14%1.44x

Frequently asked questions

What do consumers do right after bouncing from a brand's website?

Search is the most common next behavior. 51.7% of US consumers who browse a major brand site like Nike's also show search activity, versus 41.8% for social and 13.1% for apps. In the UK the figure rises to 58.2%.

Which brand do consumers search for after visiting a competitor?

In fashion, Nike is the top second choice for every rival, appearing in 73–91% of competitors' audiences. Excluding Nike, consumers move within clusters: New Balance shoppers toward Adidas (77.9%), and ASOS or Zara shoppers toward H&M (~76%).

Why is the second-choice brand position commercially valuable?

Because consumers who arrive via search convert better than those who browse. Purchase rates among searchers run 1.25x to 1.91x higher than among browsers for five of six brands analyzed β€” the second brand thought of is often the first bought from.

How is post-bounce search behavior measured?

Predict draws on Measure Protocol's consented behavioral panel, which captures browse, search (Google, Bing, Amazon), social, app and purchase events at the person level. The figures here are audience co-occurrence and transition probabilities from the US panel; they measure shared behavior within an audience window rather than strictly ordered event sequences.