Search functionality plays a much bigger role in ecommerce performance than many retailers initially realise.
As product catalogues grow, navigation becomes more complex and customers become less patient, onsite search often becomes one of the highest leverage areas for improving product discovery and conversion rates.
Platforms like Algolia and Klevu have become increasingly popular because they offer significantly more advanced functionality than the default search experiences provided by most ecommerce platforms.
While both platforms aim to improve ecommerce search relevance, filtering and merchandising, they approach the problem quite differently operationally.
Having worked with ecommerce search implementations across both Shopify and Magento stores, this guide breaks down some of the main differences between Algolia and Klevu, where each platform tends to work best and what retailers should consider before implementing either solution.
What Are Algolia and Klevu?
Algolia and Klevu are both advanced ecommerce search and product discovery platforms designed to improve onsite search experiences, filtering, merchandising and conversion rates.
Both platforms support features such as:
- Autocomplete and instant search
- Typo tolerance
- AI-driven search relevance
- Merchandising controls
- Product filtering and facets
- Search analytics
- Personalised product discovery
However, the philosophy behind each platform differs quite significantly.
Algolia is heavily focused around flexibility, API-driven architecture and customisation. It is often used on more technically complex ecommerce projects where retailers want significant control over search behaviour and frontend experiences.
Klevu, on the other hand, positions itself more as a managed AI-powered ecommerce search platform, with a stronger focus on automation, merchandising and ease of operational management.
Algolia vs Klevu: Key Differences
Flexibility and Customisation
Algolia is generally the more flexible platform from a technical perspective.
It allows developers to build highly customised search experiences across both Shopify development and Magento development projects, making it particularly attractive for larger ecommerce stores with more advanced frontend requirements.
For businesses investing heavily into custom product discovery experiences or headless ecommerce architectures, Algolia often provides greater long-term flexibility.
Klevu still offers customisation, but the platform tends to feel more operationally managed and structured out of the box. Many retailers prefer this approach because it reduces the amount of custom search logic and manual configuration required internally.
AI and Search Relevance
Both platforms use AI-driven relevance and behavioural data, although Klevu leans much more heavily into AI-led merchandising and automation within its positioning.
Klevu’s self-learning search functionality adapts over time based on user behaviour, search interactions and conversion data.
Algolia also offers AI-driven functionality, although retailers and developers often have more direct control over how search logic and ranking are configured.
In practice, both platforms can deliver excellent results when implemented properly. However, one thing retailers often underestimate is how heavily search relevance still depends on catalogue quality, product attributes and merchandising structure.
Even the most advanced ecommerce search platform cannot fully compensate for inconsistent product data.
Merchandising Controls
Merchandising functionality is one of the most important areas to evaluate when choosing an ecommerce search platform.
Both Algolia and Klevu allow retailers to:
- Boost products
- Prioritise categories
- Influence search rankings
- Promote products strategically
- Manage filtering behaviour
Klevu tends to provide a slightly more retailer-friendly merchandising experience operationally, particularly for teams without extensive internal technical resources.
Algolia often provides greater flexibility overall, although this flexibility can come with increased implementation and management complexity.
Ease of Implementation
Implementation complexity varies quite significantly between the two platforms.
Algolia implementations can become highly customised depending on frontend architecture, catalogue complexity and integration requirements. For larger ecommerce stores this flexibility can be extremely valuable, but it also typically requires stronger development involvement.
Klevu generally feels more streamlined operationally and can often be implemented faster, particularly for retailers looking for an advanced search platform without extensive custom frontend work.
That said, implementation quality still matters heavily for both platforms. Search projects are rarely entirely plug-and-play once larger catalogues and merchandising requirements are involved.
Shopify Compatibility
Both Algolia and Klevu integrate well with Shopify, although the ideal choice often depends on the scale and complexity of the store.
For many mid-sized Shopify stores, Klevu provides a good balance between functionality, AI-driven search and ease of management.
Larger Shopify stores or businesses investing in heavily customised frontend experiences may benefit more from Algolia’s flexibility and API-first approach.
Retailers evaluating search improvements for Shopify should also consider how search ties into broader collection structure, filtering and ecommerce conversion rate optimisation.
Magento Compatibility
Magento stores often have more complex catalogue structures and merchandising requirements, which is where both Algolia and Klevu can become particularly valuable.
Algolia is often well suited to larger Magento implementations requiring custom search experiences, advanced filtering or headless frontend architectures.
Klevu works well for Magento retailers seeking stronger AI-powered search functionality with a more managed operational approach.
For many Magento stores, the right choice ultimately depends on internal technical capability and how much ongoing control the business wants over merchandising and search configuration.
Analytics and Reporting
Search analytics are often overlooked but can provide extremely valuable commercial insight.
Understanding:
- what customers search for
- which searches convert
- where users hit zero-result pages
- which filters drive engagement
can highlight both merchandising opportunities and catalogue weaknesses.
Both platforms provide strong reporting capabilities, although Klevu’s reporting often feels slightly more accessible for non-technical ecommerce teams.
Cost Considerations
Both Algolia and Klevu sit within the premium ecommerce search category.
Algolia pricing tends to scale based on usage, indexing and infrastructure requirements, particularly on larger ecommerce stores.
Klevu is also positioned at the premium end of the market, although retailers sometimes find the platform operationally easier to manage internally.
The right choice is rarely about software pricing alone. Retailers should also factor in:
- implementation costs
- development overhead
- merchandising resource requirements
- ongoing optimisation
- internal technical capability
Performance and Scalability
Both platforms are capable of supporting high traffic ecommerce stores and large catalogues.
Algolia is particularly well known for speed and scalability across technically demanding ecommerce environments.
Klevu also performs strongly at scale while placing greater emphasis on AI-driven automation and merchandising simplicity.
For larger retailers, performance differences are often less important than operational fit and long-term manageability.
Algolia: Pros and Cons
Pros
- Extremely flexible and customisable
- Strong API-first architecture
- Excellent performance and scalability
- Well suited to headless ecommerce
- Advanced search configuration options
- Strong support for custom frontend experiences
Cons
- Can require more technical resource
- Merchandising and tuning may require ongoing management
- Implementation complexity can increase quickly
- Costs can scale significantly on large catalogues
Best suited for
- Enterprise ecommerce stores
- Complex Magento implementations
- Custom Shopify storefronts
- Retailers with internal technical teams
- Businesses investing heavily into custom search experiences
Klevu: Pros and Cons
Pros
- Strong AI-driven search functionality
- Easier operational management
- Good merchandising controls
- Streamlined implementation experience
- Strong reporting and analytics
- Well suited to growing ecommerce brands
Cons
- Less flexible than fully custom Algolia implementations
- Premium pricing
- Some retailers may outgrow platform limitations over time
- Still requires strong catalogue structure for best results
Best suited for
- Mid-sized to enterprise ecommerce retailers
- Businesses prioritising AI-powered search
- Stores wanting easier operational management
- Retailers without large internal development teams
Which Ecommerce Search Platform Is Better?
There is no universal winner between Algolia and Klevu because the right platform depends heavily on the operational requirements of the business.
Algolia is often the stronger choice for retailers prioritising flexibility, custom frontend experiences and deep technical control.
Klevu tends to work particularly well for businesses wanting advanced AI-driven search functionality with a more managed operational experience.
In practice, the decision usually comes down to:
- catalogue complexity
- internal technical capability
- merchandising requirements
- frontend customisation needs
- operational resources
- long-term ecommerce strategy
Retailers often focus heavily on feature comparisons, but implementation quality, product data structure and ongoing merchandising tend to have just as much impact on search performance long-term.
FAQs
Is Algolia better than Klevu?
Not necessarily. Algolia generally offers more flexibility and customisation, while Klevu often provides a more streamlined AI-driven operational experience.
Is Klevu easier to implement?
For many retailers, yes. Klevu often requires less custom frontend work and operational management compared to more heavily customised Algolia implementations.
Which platform is better for Shopify?
Both platforms work well with Shopify. Klevu is often attractive for mid-sized stores seeking easier implementation, while Algolia suits more customised Shopify experiences.
Which platform is better for Magento?
Magento stores with large catalogues or complex filtering requirements can benefit from either platform. Algolia is often preferred for highly customised implementations, while Klevu offers a more managed operational approach.
Does Algolia use AI?
Yes. Algolia includes AI-driven relevance and search functionality, although the platform is generally positioned more around flexibility and developer control.
Does Klevu use AI?
Yes. Klevu places a strong emphasis on AI-powered search relevance, behavioural learning and merchandising automation.
Final Thoughts
Both Algolia and Klevu are capable ecommerce search platforms that can significantly improve product discovery, filtering and onsite conversion rates when implemented properly.
Algolia tends to suit retailers requiring flexibility, scalability and highly customised search experiences, while Klevu often appeals to businesses looking for strong AI-driven search functionality with easier operational management.
Ultimately, ecommerce search performance depends on far more than software selection alone. Product data quality, merchandising strategy, filtering structure and ongoing optimisation all play a major role in delivering a strong onsite search experience.
If you’re currently reviewing ecommerce search platforms or improving onsite product discovery, I can help. I’m an independent ecommerce consultant with hands-on experience working across both Magento and Shopify ecommerce projects.
Feel free to get in touch if you’d like to discuss your ecommerce search setup or broader ecommerce optimisation strategy.