Why Beauty and Wellness Brands Are Outgrowing Shopify Recommendations
For many beauty and wellness DTC brands, Shopify’s built in recommendation tools are a sensible starting point. They are easy to enable, require limited configuration, and can surface basic suggestions like related items.
But as catalogs expand, customer intent diversifies, and discovery becomes increasingly AI assisted, these systems begin to show structural limits. What once felt helpful starts to feel repetitive, shallow, and misaligned with how beauty and wellness customers actually decide.
NavOut was built for this next stage.
This article explains where Shopify recommendations tend to plateau and why NavOut offers a stronger discovery approach for beauty and wellness brands that care about trust, relevance, and long term retention.
The Limits of Traditional Shopify Recommendations
Shopify’s own documentation describes recommendation strategies that depend on patterns like purchase history, similar product descriptions, and related collections. It also notes that merchants cannot edit the generated recommendations, beyond adding manual recommendations.¹
That structure matters.
In beauty and wellness, shoppers frequently arrive with high context intent that is not visible in transactional patterns alone, such as sensitivity, routine compatibility, ingredient preferences, or changing goals. When a recommendation layer is mostly derived from purchase patterns and surface similarity, the system tends to over repeat bestsellers and under serve nuanced intent.
This creates friction in categories where confidence matters as much as speed.
Beauty and Wellness Discovery Is a Decision Problem, Not a Browsing Problem
Beauty and wellness shoppers are not just choosing items. They are managing uncertainty. They often need to answer questions like:
Will this irritate my skin?
Does this fit my routine?
What pairs well together?
What should I avoid?
When discovery does not help customers resolve uncertainty, they keep scrolling, abandon the session, or buy with low confidence.
This is not a small problem at the market level. Large scale UX benchmarking shows that many ecommerce experiences still struggle with core discovery usability. Baymard’s 2025 benchmark reports that 58 percent of desktop ecommerce sites and 78 percent of mobile ecommerce sites have product list experiences rated poor to mediocre.²
In a category like beauty and wellness, where product differences can be subtle and outcomes can be personal, weak discovery has an outsized impact.
The Shift That Matters Now: AI Assisted Discovery Is Growing Fast
Discovery is also changing outside the storefront.
Adobe Analytics reports that traffic from generative AI sources to US retail sites rose 4,700 percent year over year in July 2025, with strong growth earlier in the year as well.³ Adobe also reports that in a survey of 5,000 US consumers, 38 percent said they have used generative AI for online shopping, and 52 percent planned to do so this year.³
That means beauty and wellness brands should assume a growing share of customer journeys will involve AI assisted research and recommendation before a shopper reaches a brand owned experience.
Reuters, citing Adobe Analytics holiday data, also reported a 693.4 percent jump in traffic tied to AI powered shopping assistants and chatbots during the 2025 holiday season period.⁴
The direction is clear. AI assisted discovery is moving from novelty to normal.
NavOut vs Shopify Recommendations: A Structural Comparison
1. Intent Modeling vs Behavioral Guessing
Shopify recommendations largely infer relevance from historical patterns and surface similarity.¹ NavOut is designed to model real time intent more directly.
For beauty and wellness, this matters because intent shifts frequently, even for returning customers. Seasonal changes, routines, sensitivity, pregnancy, lifestyle changes, and new goals can all alter what a shopper needs. A discovery system that can adapt to present intent reduces cold start friction and shortens the path to relevance.
2. Semantic Understanding vs Surface Similarity
Beauty and wellness shoppers often describe needs in human terms, not catalog terms.
Nielsen Norman Group notes that too many choices can lead to fatigue, dissatisfaction, and abandonment, and that people can feel mentally exhausted when comparing many options.⁵ In high consideration categories, relevance is not just about showing similar products. It is about narrowing toward what fits.
NavOut is designed to operate at the meaning level, helping brands retrieve and rank products based on semantically aligned intent rather than only behavioral similarity. This supports decision clarity, not just recommendation volume.
3. Controlled Discovery vs Fixed Logic
Shopify documentation is explicit that merchants cannot edit generated recommendations, beyond manual additions.¹ That is workable for basic cross sells, but limiting for categories where brand safety, ingredient rules, and routine compatibility shape what should and should not be recommended.
NavOut is designed for controlled autonomy. Teams can adjust preferences, constraints, and objectives through a low code dashboard, without requiring an internal ML team. This makes discovery a managed system, not a black box.
4. Decision Quality vs Short Term Click Optimization
Adobe reports that AI driven shopping behavior is still more research oriented, with conversion rate differences narrowing over time. In July 2025, Adobe reported generative AI traffic was 23 percent less likely to convert than non AI sources, improving from larger gaps earlier in 2025.³ Adobe also reports AI driven revenue per visit increased 84 percent from January 2025 to July 2025, indicating rapid improvement in the quality of AI assisted shopping traffic.³
The takeaway for beauty and wellness brands is that the discovery layer should be designed for the consideration stage. That means helping customers decide with confidence, not just driving extra clicks.
NavOut is built for that decision layer.
Preparing Beauty and Wellness Catalogs for AI Mediated Discovery
As AI assistants increasingly mediate shopping journeys, visibility depends on whether products and content are legible to modern retrieval systems.
Shopify recommendations mainly improve on site browsing.¹ NavOut is designed to make catalogs more machine interpretable and retrieval ready, improving performance inside owned experiences and strengthening compatibility with AI mediated discovery environments that may sit upstream of the click.
Final Thoughts
Shopify recommendations are a useful baseline. They help brands start recommending quickly.
But beauty and wellness brands compete on trust. Trust comes from relevance, clarity, and confidence. As AI assisted discovery grows rapidly in the US market, the winners will be brands that treat discovery as a strategic system, not a widget.
NavOut is built for that shift.
Citations
Shopify Help Center. Customize product recommendations with Shopify Search and Discovery. Shopify Inc.
Baymard Institute. (2025). Product list UX benchmark: Usability performance across ecommerce sites.
Adobe Analytics. (2025). Generative AI–powered shopping rises with traffic to U.S. retail sites. Adobe Inc.
Reuters. (2025). U.S. online holiday spending hits record levels as AI shopping assistant traffic surges.
Nielsen Norman Group. Simplicity wins over abundance of choice.
