WeShareAI Behavioral Signal Layer

For consumer insights platforms, FMCG analytics teams, and market research firms.

Tagline: Behavioral signals that reveal demand before it appears in data. — We don't track users. We read the signals they leave behind.

What We Capture

WeShareAI is installed across 10,000+ publisher websites in 194 countries. Every time a user shares content, we capture a structured behavioral event — recording the destination platform, content category, geography, and timing. No PII. No cookies. No cross-site identifiers.

The result is a behavioral signal layer that may provide early indication of emerging consumer interest patterns — potentially weeks before that interest becomes visible in retail sales data, search trends, or social media analytics.

The core insight: When a user stops reading an article and sends it to ChatGPT or Perplexity instead of sharing it on Facebook, that's not social behavior — that's active research. It's a fundamentally different signal, and no other platform captures it at scale.

Why This Signal Is Different

Traditional Signals	WeShareAI Behavioral Signals
Retail sales data — what already sold	Share-to-AI behavior — what is being researched now
Search trends — after awareness forms	Research-oriented sharing — before awareness becomes search
Social listening — public broadcast intent	Intent taxonomy — social vs. research vs. save behavior
Consumer panels — declared, not behavioral	Organic, anonymized interactions — real behavior at scale

The window between research behavior and retail visibility is where WeShareAI operates. We call it the pre-demand signal layer — designed to capture early-stage behavioral signals before traditional data sources pick them up.

Intent Taxonomy

We classify every share event by destination type, producing a four-category intent model that goes beyond raw share counts.

Social Sharing

Facebook · Viber · WhatsApp · Messenger · Twitter/X · Telegram

Broad distribution intent User wants others to see this. Passive sharing behavior.

Research Intent ← the signal we monetize

ChatGPT · Perplexity · Claude · Grok · Gemini

Active exploration — highest purchase signal User is investigating, comparing, evaluating. Pre-purchase research behavior.

Action-Oriented

Email · Gmail · Outlook · Teams

Deliberate handling User is forwarding to a decision-maker or saving for action. High engagement depth.

Save for Later

Pinterest · Pocket · Instapaper · Bookmarks

Future-oriented interest User wants to return to this content. Long-cycle purchase consideration signal.

Why this matters for FMCG: When Research Intent signals for a product category increase over 2–4 weeks, that pattern tends to precede measurable uplift in search volume and retail demand. This is the layer we deliver to data partners.

Network & Proof Points

WeShareAI is not a concept. The infrastructure is live, the data is real, and the signals are already being generated.

10K+

Active publisher websites

194

Countries in network

2.98M

Active users/month

40M+

Behavioral events/month

113K

Greek active users/month (#3 globally)

8,300+

AI-destination share events (GR, Jan–Apr 2026)

Consistent upward trend: AI-destination sharing has grown steadily since January 2026, across all markets. This is an emerging behavior category — and WeShareAI is the first platform to instrument it at scale. This behavior category is not widely captured or productized in existing data platforms.

Top Markets by Network Volume

Rank	Country	Active Users/Month	Notes
#1	Japan	191K+	High LINE + AI-tool sharing
#2	Singapore	114K+	High engagement rate
#3	Greece	113K+	Beachhead market for FMCG pilot
#4	India	102K+	High key events rate
#5	United States	67K+	Growing AI-destination behavior

Sample Output

This is the type of insight a data partner would receive from a WeShareAI behavioral signal dataset. The example below is illustrative — based on real signal patterns observed in the Greek publisher network.

          WeShareAI Signal Report — Sample

          Category: Health & Wellness

          Market: Greece (.gr network)

          Period: Jan–Apr 2026

          Finding:

          Research-oriented share events (AI-destination) in the Health & Wellness category have increased +34% over 6 weeks, while social sharing in the same category remained flat.

          Signal interpretation:

          Consumers are actively investigating health & wellness products — comparing, evaluating, seeking deeper information — before this interest becomes visible in search trends or retail data.

          Lead time over retail data: 4–6 weeks (indicative — subject to validation with partner client data)

          Note: This is an early behavioral indicator, not a confirmed purchase intent signal. Predictive value is to be validated through pilot engagement.

What you receive: Structured dataset with category-level signal summary, temporal trend analysis, intent classification breakdown, and geographic segmentation — delivered in CSV or via API. Format and delivery method agreed with each partner.

Use Cases for Data Partners

1. Client Reporting Enhancement

Add an early demand indicator layer to existing FMCG intelligence reports. Deliver forward-looking signals alongside traditional retail and search data — helping clients act weeks earlier than competitors.

2. Consulting & Strategic Advisory

Identify categories where consumers are transitioning from passive content consumption to active research. Use this to advise brand clients on when to accelerate media spend, product launches, or promotional campaigns.

3. Portfolio Differentiation

Offer a data product that no competitor currently provides. The AI-destination behavioral signal category is genuinely new — first instrumented by WeShareAI and not available from ShareThis, Nielsen, or any existing signal provider.

4. Research Product Development

Use WeShareAI signal feeds as a foundational layer for new research products — demand forecasting tools, trend detection dashboards, or category intelligence APIs for FMCG brand clients.

Who This Is For

Primary ICP: Mid-size consumer insights platforms (such as Convert Group, Netquest) that already sell FMCG intelligence to brand clients but lack access to pre-demand behavioral signals. These platforms have existing client relationships, budget authority, and the commercial infrastructure to resell or integrate a new data layer — without needing to build the underlying signal capture themselves.

Fits well if…	Less relevant if…
You sell FMCG or consumer goods intelligence	You focus on B2B or enterprise GTM signals
You have brand clients who want forward-looking data	You need person-level contact intent data
You're looking to add a differentiated signal layer	You need large-scale validated datasets today (we're in pilot phase)
You operate in Greece, Southern Europe, Japan, or Singapore	You need US-only coverage at scale

Pilot Program

WeShareAI is currently accepting 1–2 pilot data partners in the Greek FMCG market. The pilot is designed to validate the commercial value of behavioral signals with a real client use case — before committing to a paid subscription.

1
Partner scoping call (30 min) Define the FMCG category and client use case together. No commitment required.
2
Pilot dataset delivery (6 weeks) WeShareAI delivers a structured behavioral signal dataset for the agreed category and market. Complimentary for the first validated partner.
3
Value assessment Partner tests the signal in a real client reporting or consulting context. Feedback shapes the next iteration.
4
Paid engagement (if validated) Pricing defined per partner based on scope, category, and use case. Available upon request.

What we're trying to answer together: Can this behavioral signal be embedded into a real client deliverable as a meaningful early indicator? That's the question the pilot is designed to validate — not a sales process.

Request a Pilot Conversation

If you work at a consumer insights or FMCG analytics platform and want to explore whether this signal has value for your clients, we'd like to hear from you.

Privacy & GDPR Compliance

WeShareAI is built privacy-first. All behavioral signals are fully anonymized, aggregated, and GDPR/CCPA compliant. There is no PII, no cookies, and no cross-site user identification in any dataset we produce.

What we collect	What we never collect
Share destination (platform category)	User identity or email
Content category (aggregated)	Browsing history or cross-site tracking
Country (coarse, ISO code)	IP addresses stored by WeShareAI
Timestamp (aggregate patterns)	Device fingerprints or persistent IDs

TL;DR for compliance teams: WeShareAI does not create or sell user profiles. All signals are aggregated at the category and geography level. No individual can be identified from any dataset we produce. Fully GDPR and CCPA compliant.

WeShareAI is recognized by the GAIA-X Accelerator — a European data infrastructure initiative focused on privacy-sovereign data products — as well as the EGG Accelerator (Eurobank/Corallia) and the Greek Ministry of Digital Governance.

FAQ — Data Partners

Q1: How is this different from intent data providers like Bombora or 6sense?

Completely different use case. Bombora and 6sense track company-level B2B purchase intent — identifying which companies are researching enterprise software. WeShareAI tracks consumer-level research behavior at the category level — identifying which product categories are attracting increasing research interest among general consumers. Different buyers, different signal, different market.

Q2: How is this different from ShareThis or social listening tools?

ShareThis and similar platforms track what users share socially (Facebook, Twitter). They measure broad distribution behavior. WeShareAI goes further: we classify where content is shared — and shares to AI tools (ChatGPT, Perplexity, etc.) represent a fundamentally different, higher-intent behavior than social sharing. No existing platform captures or monetizes this classification.

Q3: Is the data validated? Do you have proof that the signal predicts demand?

We have consistent behavioral patterns from the network. Correlation with downstream demand has not yet been formally validated — that is precisely what the pilot program is designed to establish, together with data partners who have access to retail or client data. We are transparent about this: the pilot is a validation exercise, not a proven product claim.

Q4: What is the delivery format?

For pilot datasets: structured CSV with category-level signal summary, temporal trend data, and intent breakdown. For ongoing subscriptions: format and delivery method (CSV, API, dashboard) agreed with each partner based on their workflow.

Q5: What geographies are available?

The strongest signal density today is in Greece (#3), Japan (#1), Singapore (#2), India (#4), and the US (#5) by network volume. The pilot program is initially focused on the Greek market for FMCG categories. International expansion to Japan and Singapore is planned for H2 2026.

Q6: What does the pilot cost?

The first validated partner pilot is complimentary — we provide the dataset at no cost in exchange for feedback and validation of commercial value. Post-pilot pricing is defined per partner based on scope, category, and use case. Available upon request.

Q7: Who is behind WeShareAI?

WeShareAI is built by Nikitas Georgopoulos (Founder & CEO, 20+ years in UX and social sharing infrastructure) and Spyros Kallonis (Co-founder & CTO, two decades of software engineering). Strategic advisor: Ilias Sousis, former Google executive. The platform evolved from E-MAILiT (2008), which generated €40,000 in data partnership revenue within 12 months. Currently participating in EGG Accelerator Cohort 2 (Eurobank/Corallia) and GAIA-X Accelerator.

Questions? Contact nikitas.georgopoulos@weshareapp.io — WeShareAI Data Partners Program · weshareapp.io