The Enterprise package is for businesses that want the whole toolbox.
Building an effective custom content recommendation system from scratch can take years. You need something that you can make your own but that works from day one.
With Bibblio's support you're provided with everything you need, from an out-of-the-box solution to a modular self-build.
The API makes indexing your content simple by either automatically scraping your site or you sending us URLs. If required you can also segregate content into catalogues.
Our algorithms optimize based on context, recency, interaction and user preference. Use them individually or blend them to suit your needs.
During output, you can choose a predefined look and feel for your recommendation modules or easily design your own.
Monitor effectiveness by incorporating our analytics data into your own dashboards.
Drop a code snippet on your pages to scrape your content and display recommendations.
Use our proprietary algorithms individually, blend them together or use them with your own.
Use catalogues to promote revenue-generating sponsored content in specific modules.
Choose from 150 module design combinations that can be further adapted to match your site.
Monitor click tracking and analytics to see how your recommendations are performing.
Download advanced metadata for your content to improve your SEO and internal tagging.
Draw up a custom SLA so we're clear on our expectations.
The Bibblio team is on hand to assist you.
Advanced machine learning algorithms optimize on-page engagement.
A content item is any article or page within your catalogue that you want to provide recommendations from and to. Sets of metadata are collected for each content item, which are then stored.
An API call occurs when a set of recommendations is served to your web page. (Technically put, this is achieved via a request to the recommendation endpoint of the Bibblio API.)
If you have a Bibblio pre-designed recommendations module on your site, the number of API calls will equate to your number of page views. So 1M page views = 1M API calls per module.
The Enterprise package gives you the option to recommend content on your platform based on a user's historical interactions with your content. Our personalization algorithm combines anonymized user and content IDs to generate highly meaningful connections using inputs such as history of clicked items, time, device, recency, and popularity.
Bibblio also supports a fully customizable data schema for users, allowing you to pass us your most valuable user data to personalize the recommendations even further.
Bibblio's API endpoints give you unrestricted access to the product so you can tailor the integration to your use cases and make it work with your own stack. You can send both structured and unstructured data about your content or use our catalogue functionality to match your own internal taxonomy.
As an Enterprise customer you receive full implementation instructions and onboarding assistance from a designated Bibblio expert who guides you every step of the way.
Once you're up and running you will receive feedback, optimization guidance, performance monitoring and more from our customer success team.
We can produce recommendations for all languages using the Latin alphabet, and we can generate in-depth semantic analysis for Dutch, English, French, German, Italian, Mandarin, Polish, Portuguese, Russian, Spanish and Swedish.
Yes we are. We do not process any personal information from visitors on a customer's page, and we only process personal information from our customers when strictly necessary to provide our services. We are committed to being fully transparent regarding our processing of customers' data. We are happy to provide a compliance statement upon request.
Bibblio does not drop any cookies on the page. All user tracking is carried out from within the related content module itself, or is sent to us directly by our partners.
Lea is on hand to answer any questions about our Enterprise package and how we can set up a trial together.