Predictive, Relevant & Personalized Search Results
Our AI builds a deep user pattern by observing all interactions between users and site content. We build a deep network that will predict the next move and give the most personalized search result.
We put your business first by considering your business goals when ranking the search results. Our AI also creates experiments based on specified KPIs and goals.
Personalized search results using AutoML for known users and Markov Chain attribution model for all users (known and anonymous).
How is SearchBoost.ai better?
Most search engines rely on keywords to rank the search results, SearchBoost.ai is user centric. We rank the results based on what your users expect and respond to. This is why access to your data source is pivotal to our algorithms. SearchBoost.ai creates a deeper connection between the search keyword and displayed results.
What your users see?
Predictive search results using Auto Suggest mechanism through suggesting search terms and recommending results in the search bar.
Relevant search results rooted in document quality using Pairwise and Listwise ranking. SearchBoost.ai uses AutoML for its relevancy models which uses 15 ML algorithms with 14 preprocessing methods yielding a total of 110 hyper-parameters. This approach ensures the most optimal set of results based on the highest confidence levels.
Personalized search results using AutoML for known users and Markov Chain attribution model for all users(known and anonymous).
- Markov Chain attribution model is also utilized for optimal scoring for conversion attribution to provide the proper set of search results that yield that highest potential of conversion!
SearchBoost.ai utilizes machine learning to provide the most relevant, predictive and personalized search results for every user. In that spirit, we have ensured that SearchBoost.ai follows these pillars of responsibility and ethics.
Pillars of Responsible AI
SearchBoost.ai models do not have written rules that will cater to discrimination towards any one user. All rankings are calculated based on observing user patterns and web behavior.
SearchBoost.ai has implemented a mechanism that ensures underpopulated (small) clusters of similar users are not discriminated from more populated (big) clusters of users.
SearchBoost.ai doesn't negatively impact the existing accessibility measures of any site's search experience like WCAG 2.0 compliance. Further, within our product roadmap, we plan to include voice search that can help visually impaired people.
SearchBoost.ai have implemented fully encrypted communication between different layers of the AI. All sensitive data is securely stored and encrypted.
There are no safety measures that are compromised by SearchBoost.ai.
SearchBoost.ai does not store personal identifiable information that can be back tracked to a private individual, thus no negative impact on user privacy.
SearchBoost.ai offers full transparency on how it forms rank by providing model visualizations where user can understand on what base ranks are calculated.
Machine Learning and Advanced Search Algorithms
Download our white paper on how we leveraged machine learning to power SearchBoost.ai into the most advanced smart search platform. Fill out the form and we will email you a copy of our white paper.