Full Score is an extremely lightweight (3KB gzip) library, providing serverless behavioral analytics with real-time security monitoring and AI insights.
This site showcases Full Score’s live performance. Your real-time browsing journey appears at the bottom, analyzed by Edge as it happens. It flows naturally, like music in resonance.
Here are the orchestrated capabilities. Click to explore each movement.
- 🧭 Serverless Analytics with No API Endpoints & 90% Cost Reduction
- 🔍 Complete Cross-tab User Journey Without Session Replay
- 🧩 Bot Detection & Human Personalization via Real-time Behavioral Layer
- 🧠 BEAT Flows into AI Insights as Linear Strings, No Parsing
- 🛡️ GDPR-Conscious Architecture with Zero Direct Identifiers
All while achieving a decentralized paradigm using browsers as auxiliary databases.
This demo focuses on live performance. For technical details on how this works, see the 🔗 GitHub repository and code comments.
1. Serverless Analytics with No API Endpoints & 90% Cost Reduction
Traditional analytics platforms built for web traffic analysis, session replay, and cohort tracking excel at their tasks. However, gaining user insights typically requires heavy and complex infrastructure.
They rely on bulky data formats such as JSON events and DOM snapshots, all transmitted to centralized servers for storage and processing. This results in script payloads of tens of kilobytes, millions of network requests, and monthly infrastructure costs in the thousands.
Full Score doesn’t try to solve this complexity. It removes it entirely, proposing a new paradigm.
- Traditional Analytics
Browser → API → Raw Database → Queue(Kafka) → Processing(Spark) → Processed Database → Archive// ⛔ 7 Steps, $1,000 – $5,000/month
- Full Score
Browser ~ Edge → Archive// ✅ 2 Steps, $50 – $500/month
// No API endpoints needed
// No Queue & Processing needed
// No Origin access required
It begins with a simple realization. Gaining insight into a user’s complete browsing journey doesn’t always require transmitting data elsewhere.
Every browser already provides storage like first-party cookies and localStorage. What if insights were recorded there first, and interpreted only once, at the moment a user’s browser performance is deemed complete?
By turning each browser into infrastructure, the need for complex, centralized systems disappears. A billion users become like a billion decentralized databases, each holding their own raw data.
Of course, few would have embraced this approach because data transmission protocols are extremely limited. JSON events and DOM snapshots are too heavy, so even sending data once still requires Queue and Processing layers.
That’s why Full Score created BEAT, a new data format. BEAT is 60-75% lighter than JSON and requires no Queue or Processing. By recording user behavior as linear strings, raw data becomes music, naturally readable to both humans and AI.
And the resonance with Edge computing completes the story.
(Video introduction)
As the video shows, Edge transforms Full Score into a real-time analytics layer, with no API endpoints required. Edge reads the request headers from each browser.
Because browser and Edge are so close in space and time, their connection resembles resonance more than transmission, like listening to music flowing through the air.
For sites spending $1,000–5,000/month on analytics, Full Score typically runs at around $50/month for Edge computing and cloud archiving combined. With AI insights preprocessing at the Edge, costs can scale up to roughly $500/month. This is a conservative estimate and actual costs may vary depending on your environment. Its decentralized, Edge-based design keeps costs stable as traffic scales.
Full Score doesn’t replace traditional analytics entirely. It specializes in behavioral analysis and works best alongside traditional platforms like Cloudflare Analytics.
2. Complete Cross-tab User Journey Without Session Replay
Traditional analytics makes cross-tab analysis complex and incomplete. It requires a complicated pipeline including identifier collection, sessionization, data ingestion, joins, post-processing, and real-time synchronization.
Full Score uses browsers as storage, so complete journeys including cross-tab navigation are recorded immediately. With a single prompt, AI can interpret this data directly, and the process of loading into BigQuery for visualization is simpler than traditional approaches.
Click the button below to open a new tab and test it yourself.
In the demo’s RHYTHM data, you can see tab navigation in the (___N) format.
Full Score uses up to 7 cookies (default). If an 8th tab opens, it automatically archives existing data and restarts. All sessions share the same timestamp and hash, allowing later consolidation into a single journey.
However, opening 8+ tabs simultaneously is rare. This likely indicates abnormal bot behavior patterns.
Full Score elegantly addresses this challenge. 🔗 When resonating with Edge Runner, it enables real-time security and personalization.
3. Bot Detection & Human Personalization via Real-time Behavioral Layer
Let’s start with a simple test. Tap the button below either at bot pace (rapid, mechanical taps) or at human pace (imperfect, natural taps).
This test may briefly trigger a Managed Challenge that clears in about 30 seconds.
See how the Score field changes from (0000000000) to (1000000000), (2000000000), or (0100000000), (0200000000)? That’s Full Score working with Edge Runner to analyze behavior in real time.
If rapid taps aren’t recognized well on mobile, try enabling TEMPO. It refines touch timing and accuracy by tuning out event-loop delays, creating a smoother mobile UX.
Traditional bot detection relies on IP blocking, CAPTCHAs, and fingerprinting. But smart bots bypass these. Full Score takes a different approach, watching behavior patterns to catch bots that try to act human but give themselves away through unnatural actions like clicking without scrolling.
For real users, this provides personalized user experiences. Someone clicks add to cart three times quickly? Show them a help message. Someone spends a long time browsing? Show them a discount.
Using Full Score solely for real-time security and personalization is also a valid choice.
4. BEAT Flows into AI Insights as Linear Strings, No Parsing
BEAT (Behavioral Event Analytics Transform) is a domain-specific language (DSL) that transforms multi-dimensional behavioral data into linear sequences. It captures when actions occur (time), where users navigate (space), and what they do (actions with depth). This compression transforms complex user journeys into single strings that both humans and AI can read. While serving as RHYTHM’s core data format, BEAT maintains versatility for use in other systems.
🔗 For detailed explanations of the BEAT format, see the GitHub README.
- rhythm_1=2___1_5_32_8_12497_!home~237*nav-2~1908*nav-3~375/123*help~1128*more-1~43!prod~1034*button-12~1050*p1___2~6590*mycart___3
- rhythm_2=2___1_1_24_7_12093_!p1~2403*img-1~1194*buy-1~13/8/8*buy-1-up~532*review~14!review~2018*nav-1___1
- rhythm_3=2___1_1_0_0_12503_!cart
// Serialized to NDJSON for BigQuery compatibility and faster AI understanding
// Simple format conversion (no structural parsing or data interpretation)
- {„device“:1,“referrer“:5,“scrolls“:56,“clicks“:15,“duration“:1250.3,“beat“:“!home ~23.7 *nav-2 ~190.8 *nav-3 ~37.5/12.3 *help ~112.8 *more-1 ~4.3 !prod ~103.4 *button-12 ~105.0 *p1 ___2 !p1 ~240.3 *img-1 ~119.4 *buy-1 ~1.3/0.8/0.8 *buy-1-up ~53.2 *review ~14 !review ~201.8 *nav-1 ___1 ~659.0 *mycart ___3 !cart“}
Human Interpretation
„Let’s see… homepage to cart, but no purchase. What went wrong? This user really took time with the reviews.“AI Interpretation
[CONTEXT] Mobile user, direct visit, 56 scrolls, 15 clicks, 1872.8 seconds
[SUMMARY] Confused behavior. Landed on homepage, hesitated in help section with repeated clicks at 37 and 12 second intervals. Moved to product page, opened details in a new tab, viewed images for about 240 seconds. Tapped buy button three times at 1.3, 0.8, and 0.8 second intervals. Returned after 660 seconds and opened cart but didn’t proceed to checkout.
[ISSUE] Cart reached but purchase not completed. Repeated buy actions may reflect either intentional multi-item additions or friction in option selection. Long delay before checkout suggests uncertainty.
[ACTION] Evaluate if repeated buy or cart actions represent deliberate comparison behavior or checkout friction. If friction is likely, simplify option handling and highlight key product details earlier in the flow.
Traditional data formats, including JSON, are like dots. They’re great for organizing and separating individual events, but understanding what story they tell requires parsing and interpretation.
BEAT is like a line. It’s the same raw data level as JSON, but because user behavior flows like music, the story becomes clear right away.
So BEAT is raw data, but it’s also self-contained. No parsing needed. This sounds grand, but it’s really not. BEAT just mimics the most common data format in the world. The oldest data format in human history. Natural language.
And AI is the expert at understanding natural language.
(VIDEO)
Data resonating from Full Score to Edge becomes real-time insight reports through lightweight AI (e.g., GPT OSS 20B-class models). LogPush then archives this data to cloud storage, organized by date.
All this accumulated daily data flows to your AI assistant. This creates an AI-to-AI collaboration system where lightweight AI creates reports for each session and advanced AI synthesizes comprehensive insights from all reports. No need for humans to analyze dashboards. As AI evolves, Full Score evolves with it.
Start a conversation.
“Which user journey patterns are driving conversions?”
“Any notable ISSUEs today?”
“Can you suggest UX improvements?”
5. GDPR-Conscious Architecture with Zero Direct Identifiers
Full Score’s primary implementation uses first-party cookies as its data storage. While a localStorage version exists, cookies offer a functional advantage since they’re automatically included in HTTP request headers. This allows Edge to read them immediately.
First-party cookies are fundamentally different from the third-party tracking cookies commonly flagged in analytics. Full Score stores data only in users‘ browsers and resonates naturally with Edge without API endpoints, actually reducing exposure compared to traditional analytics approaches.
Attacking this architecture would require compromising users‘ browsers at scale, a highly impractical scenario. Even if such an attack succeeded, the data stored in cookies contains no personally identifiable information (PII), only behavioral strings. Additionally, cookies are designed to expire automatically, leaving no trace, like a performance that ends.
For detailed GDPR and ePD compliance guidance, see the FAQ section below.
FAQ
Q1. Why does Full Score use the term „resonance“? Isn’t HTTP header transmission still transmission?
A. Understanding this requires looking at data ownership. Here’s an illustration to explain.
The first image shows traditional transmission. The two sides are completely isolated from each other. For B to hear A’s performance, protocol transmission becomes inevitable. During this process, data ownership shifts from A to B and gets stored on the server. Without storing it, there’s simply no way for B to hear A’s performance.
The second image shows resonance between Full Score and Edge. There’s still a wall between them that can’t be physically crossed, but B can listen to A’s performance in real time. Throughout this entire process, data ownership stays with A.
This is exactly what Edge computing enables as a serverless architecture. Edge doesn’t need to receive and store data like a traditional server does. Instead, it interprets and responds immediately at the network layer closest to users. Put simply, Full Score creates a structure where data ownership remains with the user (browser) while enabling near-instant interaction.
That’s why Full Score chose „resonance“ as its musical metaphor. Rather than focusing on physical mechanics, it centers on the logical architecture shown above.
Q2. Do I need cookie consent for GDPR and ePD compliance?
A. This is a topic that requires legal consultation depending on jurisdiction and site policies. Please understand that this answer is based on personal experience and judgment.
The answer depends not on Full Score itself, but on the custom configuration of Edge Runner that resonates with it.
GDPR requires legal grounds when collecting or processing identifiable personal data. The ePD requires user consent when storing information in or accessing browser storage, including cookies. However, it recognizes an exception called „strictly necessary“ for cookies that are strictly required for functionality.
As explained earlier, Full Score uses first-party cookies where data ownership stays with the user (browser), fundamentally different from third-party cookies. When combined with Edge Runner, it operates as a security and personalization layer at the serverless level.
Therefore, if Edge Runner maintains data ownership with the user (browser) without even keeping logs, this approaches the green zone. Full Score doesn’t collect identifiable personal data covered by GDPR, while meeting the ePD’s strictly necessary cookie criteria.
However, if the Edge Runner configuration sets (LOG: true) to collect and process behavioral data for analysis, this decision should be made carefully.
Full Score is designed to maintain complete anonymization without any personally identifiable information (PII). However, GDPR covers not only direct identification but also data with potential for indirect identification. When matched with other Edge records like IP addresses or User-Agent strings, some level of identification potential may exist.
That’s why Edge Runner includes options to remove timestamp and hash records before logging. This way, even when matched with other Edge records, indirect identification potential effectively disappears. This puts it in a gray zone closer to green.
Keeping the hash enabled remains in the gray zone, but enabling timestamps may enter the red zone and warrants legal consultation.
Q3. Can Full Score be used standalone without resonance with Edge?
A. Yes. Full Score provides detailed customization options and can operate independently of Edge through custom endpoints. For details, see the code comments in the GitHub repository.
Q4. Is there a dashboard for analysis?
A. No. Unlike traditional analytics tools, Full Score performs analysis through natural language conversations with AI. In other words, your favorite AI assistant serves as Full Score’s analytics tool. As AI evolves, Full Score evolves with it.
For those preferring traditional dashboard analysis over AI, it’s also possible to implement this directly by storing NDJSON in Cloud Storage and using BigQuery. Since the BEAT format contains storytelling elements, user journeys could be visualized as 🔗 tree-structured flowcharts like Detroit: Become Human’s. It might be interesting to explore someday if time permits.
Q5. Is Full Score really 3KB?
A. Yes, based on minified and gzipped size. The three versions come in at 2.73KB, 3.18KB, and 3.33KB.
- Basic (2.73KB): https://cdn.jsdelivr.net/gh/aidgncom/fullscore@main/fullscore.basic.min.js
- Standard (3.18KB): https://cdn.jsdelivr.net/gh/aidgncom/fullscore@main/fullscore.standard.min.js
- Extended (3.33KB): https://cdn.jsdelivr.net/gh/aidgncom/fullscore@main/fullscore.extended.min.js
The demo site you’re viewing uses the Basic version. This version includes only BEAT (core) and RHYTHM (engine), without TEMPO (auxiliary module). It operates without issues on most sites.
If clicks or taps register incorrectly when testing the Basic version, this typically indicates problems with your site’s event handling or coordinate setup. The Standard version includes TEMPO, which resolves these issues elegantly.
For Power Mode activation or scroll depth tracking, consider the Extended version with addon features. Most sites won’t need this. Use it only when your specific situation requires these features.
Start with either the Basic or Standard version. The script runs smoothly even when placed in your site’s footer, with setup examples as shown in the image below. See the code comments for specifics.
Full Score performs in richer harmony when resonating with Edge Runner. See the YouTube video for detailed setup instructions.
Contact
Full Score is a personal project by Aidgn. Please understand that responses to every inquiry may not always be possible.