SocialScore's E-commerce Customer Intelligence Layer turns a single email or phone number into 300+ real-time signals for marketplaces, electronics retailers, fashion brands and luxury e-commerce. Pricing starts at about €1 per verified profile, with volume pricing above 10,000 checks a month. A free demo and 500 free identity checks are available from SocialScore (DSNTech LTD, Sofia, Bulgaria).
You know your tech better than
you know your customers.
The Customer Intelligence Layer that hands back the knowledge Google and Meta have been monetizing for years — better marketing, lower risk, real personalization. Without the enterprise price tag.
You pay for the click.
They keep the customer.
Every euro on Google or Meta teaches their algorithm something about your buyer. They keep that knowledge and monetize it forever. You get a session, a CAC bill, and a blank slate for the next campaign.
Acquisition, fraud screening, marketing, and support usually run on different knowledge of the same shopper. SocialScore gives every one of your systems the same signal — one customer, understood the same way everywhere. You take the ad platform's data. We hand you the context.
What that costs, sector by sector
Thousands of new buyers a week, no way to tell a bargain-hunter from a repeat premium spender at session one — every hour spent manually segmenting them is an hour not spent acquiring the next cohort.
High AOV, high fraud exposure — one stolen card wipes out a week of margin, and every order held for manual review is a delay the marketing team then has to smooth over.
Same homepage for a bargain hunter and a full-price loyalist — discounts get handed out that were never needed, and campaign budget chases the wrong lookalikes.
Can't tell a genuine high-net-worth visitor from window-shopping — VIP treatment never reaches them in time, and concierge hours go to the wrong sessions.
Everyone wants AI.
Nobody has context.
This isn't only an e-commerce problem — it's the problem underneath every AI tool you've bought. Your chatbot, your recommendation engine, your pricing logic all guess, because none of them know who's actually on the other side of the screen.
Everyone chases lower CAC
Without identity signals, "optimization" means paying more to find the same answer by trial and error.
Everyone is adding AI
A chatbot with no context greets a first-time browser and a returning VIP the same way. That's the default, not a bug.
Everyone wants personalization
But nobody knows who's behind the screen. Over 50% of internet traffic today isn't even human.
The same signal ad platforms use on you —
now working for you.
SocialScore enriches an email or phone into the same kind of digital-footprint intelligence Google already holds — except the output belongs to you.
Data & Signals Engine
Email + phone + country → 300+ signals, under 5 seconds. Your own platform data can feed it too — not just email and phone.
Software & Capabilities
Works on our signals — or entirely on your own data: orders, channels, addresses, your own segments. Use us purely as software, if that's all you need.
Your GA4, CRM, checkout and ad accounts stay exactly where they are. SocialScore feeds the tools you already run with the context they were missing.
From an email address, phone, or web visit to a
buying decision
Define the group
Top buyers, cart-abandoners, new visitors — any audience you choose.
Enrich & profile
300+ signals per identity, under 5 seconds. Batch mode for full lists.
Segment & predict
Behavioral clusters computed automatically from external signals.
Act in real time
Every new visitor scored against your segments before the form is done.
No devs required —
this is the actual product
Everything below is live in the SocialScore dashboard — no integration needed to see it working.
Integration takes about 10 minutes. One API call returns every signal — as JSON for your systems, or CSV for a straight upload into a spreadsheet.
One call returns
six different kinds of answers
Verification & Health Scores
Data: deliverable/disposable/breach-exposed email, valid mobile/WhatsApp-reachable phone, plus Social/Email/Phone/Fraud/Buyer Power scores.
Value: at least 20% of a typical database is invalid or fake — that tanks sender reputation and sends the whole campaign to spam, on top of paying to reach contacts that don't exist. This catches it before you hit send (see Case 1 ahead).
Interests
Data: 15 categories, benchmarked vs. your country's average, not a global one.
Value: powers the actual content and creative direction, not a guess at what to put on the homepage.
Digital Footprint
Data: where they actually live online, which platforms, how active, how established.
Value — cookieless-ready: built on 1st-party data (email/phone) plus public OSINT, never third-party cookies. It works exactly the same the day cookies disappear for good, because it never depended on them.
AI Customer Persona & Human-or-Bot
Data: a ready-made persona plus confirmation of active human, bad bot, or legitimate AI shopping agent.
Value — the pre-emptive context promise: know who this shopper is before you've spent a cent on retargeting or handed them a 20% code they never needed. That's the Holy Grail in marketing.
Funnel & Purchase Stage
Data: registered only, cart started, cart abandoned, or repeat buyer.
Value: know exactly where they stand before you message them, not after you've already guessed wrong.
Predictive Matching
Data: scored against every segment you've defined, automatically — 80+ is a strong match.
Value — zero integration, no code: push straight into Klaviyo, Meta Ads, or Google Ads. No IT ticket, live the same day (see Case 2 ahead).
Six answers.
Six signals, tied to real numbers.
Fraud & Risk Savings
Data: which orders are real, reachable, and safe to ship. You optimize: screen before shipment, not after the chargeback. Money: fraud losses drop 55–57% (Case 1 & 3 ahead).
Content & Creative Direction
Data: which Interest segment this visitor matches. You optimize: homepage and copy per segment, not a guess. Money: a message that fits converts higher than one that doesn't.
Google Ads & Meta Export
Data: your best-converting segment, hashed-email ready. You optimize — zero code: push straight into Klaviyo, Meta Ads, or Google Ads, no IT ticket. Money: live this week, not next quarter.
Precision Targeting — the CAC Lever
Data — pre-emptive context: who this shopper is before they've clicked a single retargeting ad. You optimize: stop paying to re-discover shoppers you could have known from message one. Money: CAC drops 22–25% in every case ahead.
Smart Discount Engine
Data: loyalist vs. deal-hunter segment. You optimize: full price to loyalists, the code only to who needs it. Money: €15K–35K/mo protected margin (Case 2 ahead).
Channel & Timing — Cookieless-Ready
Data: 1st-party signal (email/phone) plus public OSINT, zero cookies required. You optimize: right channel, right moment — still works the day third-party cookies are gone. Money: retargeting keeps converting when cookie-based targeting breaks.
€500K/month revenue,
mixed-category store
~3,500 new customers enriched per month at checkout. Segment-based targeting replaces blanket discounting; Fraud Score screens every order before it ships.
Why: the CAC drop comes from shifting ad budget away from broad match toward the ~27% of visitors who score 80+ on Predictive Matching — spend stops going to people who were never going to convert. That's the same lever behind ROAS: same budget, more of it lands on buyers, not browsers. Fraud drops because every order with a Fraud Score above 40 is screened before shipment, not after the chargeback. Notice what's not needed: no persona work on all 3,500 checks — the system runs entirely off applicants who registered or reached checkout, then feeds look-alike audiences back into Google/Meta from there. Cost basis: ~3,500 checks/month × €1. Fraud benchmark: Europe averages ~3.0% of e-commerce revenue lost to payment fraud (Statista/LexisNexis, 2026).
€300K/month revenue,
DTC apparel brand
~2,500 new customers enriched per month. The Smart Discount Engine replaces the site-wide promo code with a Fashion-score-based segment: full price for loyalists, the code only for genuine deal-hunters.
Why: the promo code used to go to the entire list; the Fashion + E-commerce interest scores now separate the ~55% who would have bought at full price from the genuine deal-hunters, so margin stops leaking and ROAS on the promo budget goes up without cutting reach. CAC drops the same way as Case 1 — spend follows the Predictive Score, and the same loyalist segment becomes a look-alike seed for Meta/Google, improving retention on repeat sends instead of just acquisition. Persona work only ran on the ~2,500 who registered or reached checkout, not the full site traffic. Cost basis: ~2,500 checks/month × €1. Fashion CAC benchmark scaled from 2026 apparel-vertical DTC data (Mobiloud/Ringly) for the SEE ad-cost environment.
€1.2M/month GMV,
multi-vendor marketplace
~15,000 new buyers enriched per month — volume pricing applies above 10,000 checks/month. Two-sided fraud (buyer + seller) is the sharpest pain point marketplaces report.
Why: at marketplace volume, the segmentation happens at session one instead of after the first order — new buyers are matched to "will convert" or "needs nurturing" before the first click, so CAC and LTV both move: cheaper acquisition and a clearer read on who's worth retaining. Fraud drops because both buyer and seller identities get the same real-time screening. The persona and look-alike work only runs on the ~15,000/month who actually register or check out, never blind on raw traffic. Cost basis: ~15,000 checks/month, volume pricing applies above the 10,000/month threshold. Fraud benchmark: European merchants lose an average of 2.8% of revenue to fraud (Sift, 2025); marketplaces sit at the higher end due to two-sided buyer/seller risk.
Same 5,000 registrations.
Same €7,500 budget. Very different outcome.
A worked example, from the e-commerce merchant's side — what changes, step by step, when SocialScore sits between your CRM and your marketing spend.
Why: the 45 vs. 180 recovered orders come from the same €7,500 ad budget, plus the €5,000 SocialScore identification pass — the only thing that changed is knowing WHO to spend the €7,500 on and HOW to reach them. Once that €5,000 is included, cost per buyer still drops from €167 to €69, and the 135 incremental buyers cost just €37 each to acquire — still far cheaper than the blind baseline. That's the CAC lever. Separately: each of the 930 buyers now carries a predicted long-term segment (loyalist, deal-hunter, browser), so content, channel, and next offer are personalized from their very first order — that's the LTV lever, and it compounds every month after this one.
Same product page. Same call.
Three completely different shoppers.
This is what the signals actually look like on real shoppers — and what each one means for the offer you show.
More than half of today's web traffic isn't human, and some of what's left is browsing blind to your best offer. Nobody, not even your own product recommendations or chatbot, knows if they're serving a loyal buyer, a deal-hunter, or a bot. We hand your systems that context on the first call — so the right offer, channel, and price reach the right shopper, and more of that traffic becomes revenue.
The Customer Intelligence Layer
vs. what you have today
| Comparison | SocialScore | GA4 / Meta (what you see today) | In-House Build | Traditional CDP |
| Cost to start | €0 | Already in ad spend | €500K+ | €300K+ |
| Unified profile per customer | Yes, 300+ signals | No — aggregated, per-platform | Internal only | Internal only |
| Can you export the profile out? | Yes, anywhere | No — walled garden | Yes, if you build it | Yes |
| Time to first result | 1 day | Immediate, limited | 6+ months | 4+ months |
| Prediction basis | Real-time data | Aggregated history | History only | History only |
GA4 and Meta show you behavior inside their own walls — SocialScore builds a portable profile and lets you push it into Google Ads and Meta yourself, whenever you want.
Marketing today, in one sentence: everything is automated except knowing who the customer is
Built to
improve what you run, not to replace it
SocialScore was designed as an enrichment layer from day one — one API call, live in about 10 minutes, gives you enterprise-grade predictive software without disturbing your checkout, CRM, or ad stack.
Your own Data Science team, on call
Every account includes access to our data science team — for signal interpretation, custom scoring logic, and model integration.
Customized to your exact stack
Proprietary or headless checkout? We build a custom module to your specification — same enrichment, embedded into your flow.
AI Tools
Chatbots, recommendation engines, pricing logic — connected via MCP, so your AI gets the same context a human agent would.
CRM / CDP / E-commerce
Beyond the five above — any platform with a webhook or an import can pull SocialScore signals through the API.
Handling identity data means
compliance isn't optional
We process signals on your instructions, for the purposes you set. We provide signals, never scores or verdicts — we don't decide what happens to the shopper.
You decide why the data is processed and what happens with the result. Every actual decision is yours.
The person the signals describe. Their GDPR rights — access, erasure, objection — route through you as controller.
What We Process For
Two purposes only: identification (verifying who someone is) and marketing (understanding what they might want) — never anything else without your instruction.
Where Your Data Lives
Pass-Through (default): we return the signals, keep no copy. Storage Mode (opt-in): we retain the profile for you to re-query, deletable on request — both covered by the same DPA, signed before production use.
SocialScore commits to signal transparency and strict compliance: we operate purely to help merchants with identification and marketing, reducing risk and improving personalization while cutting the spam and wasted spend that come from bad data. We never output scores or verdicts, only signals for your own systems to weigh. Because the Controller — your business — makes every actual decision, SocialScore sits outside GDPR Art. 22's automated-decision rules and outside the EU AI Act's high-risk (Annex III) category — both apply to the system that decides, not the one that informs it.
GDPR — Standard Tier
Public digital-footprint data, never Art. 9 special-category data — the standard risk tier, not the enhanced one.
ISO/IEC 27001:2022
Our security program is aligned to this standard, so you don't have to audit our infrastructure yourself.
EU-Based Entity
DSNTech LTD, Sofia, Bulgaria — subject to EU law, not a third-country transfer.
Never Resold
Your enriched data is yours — never sold on to advertisers or other clients.
Get an expert read on your shoppers,
not just another data feed — free.
Bring your own customer list. Our team enriches it live, in front of you, walks through what it means for CAC, retention, and personalization, and shows you exactly what your audience looks like today.
Already live with e-commerce companies across Europe — retailers, fashion brands and marketplaces using SocialScore today to cut CAC, protect margin, and grow.
office@socialscore.io · dimitar@socialscore.io · DSNTech LTD, Mladost 2, Sofia, Bulgaria