AudienceLab vs DataShopper
We ran the tests. See our analysis of data from DataShopper and how it compares to AudienceLab.
US Consumer Profiles
Data Accuracy
Behaviours Scanned Weekly
Agencies & Advertisers
*This is based on 98% of US households which currently sits at approx 127,482,865 according to the US Census Bureau.
What Is It Really Costing You?
DataShopper's data isn't verified.
To make it usable, you'd need to clean it yourself.
Here's what that actually costs.
Catch-all Email Validation
$0.00255 per record
$2,550.00
Phone Validation & Skip Trace
$0.02 per record
$20,000.00
NCOA Validation for Accurate Addresses
$0.05 per record
$50,000.00
$72,550.00
just to make DataShopper's data usable
AudienceLab includes all of this — verification, skip tracing, and NCOA — built into the platform.
How Data Decays with Probabilistic Matching
A promised 60% match rate sounds great.
But after probabilistic IP matching and accuracy decay,
here's what you actually get.
Expected Match Rate
60% of matched records
60,000
Probabilistic IP Matches
70% of matched records
42,000
Accuracy
20% of matched records
8,400
8.40%
actual usable matches from probabilistic data
AudienceLab uses deterministic matching — no probabilistic guessing, no inflated match rates.
Consumer Database Accuracy
DataShopper uses unverified data from a generic co-registration dataset. Co-reg data comes from online form fills — information that can be made up, fake, or severely out of date.
Example: Someone fills out a form on CreditRepair.com in July 2024. That email, mobile, and name could still be sold in 2026 and beyond. These datasets typically test below 40% accuracy.
Every 30 days, AudienceLab's core consumer file goes through a NCOA database verification update — every single address is verified against official post office data.
Roughly 11-12% of the US population moves every year, meaning a database even 1 year old could have up to 20% data decay. Most co-reg datasets are never NCOA verified to begin with.
No Email Verification
DataShopper uses a commonly known email file — an assortment of historic personal and business emails. The data is not verified; instead it has "ESP Valid" which just means the email has existed before.
This means up to 40% bounce rate and emails that are out of date or no longer belong to that person. Their own deliverability data shows ~46% "Risky" and ~8% "Bad."
AudienceLab owns and operates DEEEP (deeepverify.com) — a full email verification engine responsible for cleaning over 10 million emails every 24 hours.
The entire database is fully verified every 2-3 months. This means dramatically lower bounce rates and emails that actually reach the right person.
IP-Based Matching Without Accuracy
DataShopper claims up to 70% match rate, mostly through IP-based matches. IPs are places, not people. Without proper quality control, they frequently match the wrong identity.
Example: If John Smith is at Starbucks using WiFi and visits a website with an IP-resolution pixel, he — and everyone else at the coffee shop — gets classified as a match. That's 50-100 people matched at once, skewing rates and matching wrong identities.
AudienceLab uses Geo Frame Resolution — the process of assigning a recently logged-in IP address to the latest longitude and latitude of the household.
If John Smith is at Starbucks on public WiFi, we identify it's really him away from his core residence and only match his identity. This can only be achieved by having the most recently updated coordinates of an address through continuous NCOA verification.
Mobile Number Accuracy
DataShopper uses mobile numbers likely sourced from co-reg/co-op databases. When you call someone, they either won't answer or it's the wrong person entirely.
The co-reg data is out of date or contains wrong information. Choosing the right number is a hit and miss — destroying your clients' trust and campaign performance.
AudienceLab runs a skip tracing service to match all data across 10-20 other offline datasets to confirm it's the actual number that belongs to that person.
This means high connectivity rates, better pick-ups from clients, and more deals closed. Your phone data actually works.
Intent Scoring Via Third-Party API
DataShopper uses an intent feed via third-party API — meaning there's no closed-back feedback loop to train false positives or hard negatives on any intent list.
This creates a lack of accuracy in the "distance" from a topic to the original source. Example: People classified with intent for "Metal Sheet Roofing" may only be on generic blogs that mention "roofing" — no actual context, just noise.
AudienceLab's intent model is powered by a continuous feedback loop which identifies false positives and hard negatives to create stricter rules for intent.
We tested across other generic feeds (including DataShopper) and found massive "noise" — URL-to-HEM pairings that are either unrelated or too distant from the actual topic. Our system filters this out.
*Bright red blob represents HEM <> URL pairings that have "far distance" and not relevant intent
See the Difference
A side-by-side comparison that speaks for itself. Signal vs. noise.
Database Accuracy
Email Deliverability
Identity Resolution Precision
Mobile Connectivity
Intent Accuracy
Consumer Profiles
Database Refresh
Email Verification
Email Bounce Rate
Identity Resolution
Mobile Verification
Intent Model
Intent Accuracy
Behaviours Scanned
White Label
True Data Ownership
| Feature | AudienceLab | DataShopper |
|---|---|---|
| Consumer Profiles | 308M+ (NCOA Verified) | 280M+ (Unverified Co-Reg) |
| Database Refresh | Every 30 Days via NCOA | Unknown / Stale |
| Email Verification | DEEEP Engine (10M+/day) | ESP Valid Only |
| Email Bounce Rate | <8% | Up to 40% |
| Identity Resolution | Geo Frame Resolution | Basic IP Matching |
| Mobile Verification | Skip Traced (10-20 sources) | Co-Reg / Co-Op |
| Intent Model | Closed Feedback Loop | 3rd Party API Feed |
| Intent Accuracy | Continuous Training | No Feedback Loop |
| Behaviours Scanned | 60B+ Weekly | Not Disclosed |
| White Label | Full White Label | White Label |
| True Data Ownership |
You're Not Paying for Data.
You're Paying for a Moat.
With AudienceLab, you're not paying for third-party access to an API or co-reg data that your competitors can duplicate. You're investing in infrastructure that can't be replicated.
NCOA-Verified Identity Spine
Consumer data verified every 30 days via NCOA — the gold standard for address accuracy.
Proprietary Email Engine
DEEEP cleans 10M+ emails daily across the entire dataset. Not a third-party API — we own it.
Geo Frame Resolution
IP-to-household matching using real-time longitude/latitude coordinates. No more coffee shop false matches.
Closed-Loop Intent
Continuous feedback loop trains out false positives and noise. Real evidence for real intent.
This is how DaaS agencies aren't just winning — they're working with real enterprise clients and even exiting.
Ready to See the Signal?
Stop paying for noise. Schedule a demo and see exactly why 1,000+ agencies and advertisers chose AudienceLab as their data infrastructure.
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