DataWorks
B2B Marketing Data, Attribution & Analytics
Without visibility, you're flying blind. Without correlation, you're guessing.
Most marketing teams are rich in dashboards and poor in answers. DataWorks covers attribution, measurement infrastructure, and the intelligence layer that makes every other marketing investment legible.
Without visibility you are flying blind; without correlation you are guessing — this section is about replacing both with evidence.
LinkedIn Ads Conversion Tracking: Insight Tag, CAPI, and the B2B Attribution Gap
Your LinkedIn Campaign Manager shows 300 demo requests while your CRM shows 14 opportunities, and neither number tells the whole story. Here's why the B2B attribution gap isn't a technical problem, it's structural, and what you can actually do about it.
The Attribution Reckoning: How Enterprises Actually Measure Marketing Automation ROI in 2026
Seventy-five percent of companies now use multi-touch attribution, yet most still can't explain which campaigns actually drove revenue. The gap between 'we have an attribution model' and 'we trust our attribution model' has never been wider, and the enterprises winning in 2026 are the ones honest enough to admit what they can and can't prove.
The Confidence-Readiness Paradox: What TransUnion's AI Study Means for How We Sell GEO
Eighty-nine percent of marketers are planning to increase their AI investment, but only 36% say their data is ready to support it. If that gap doesn't make you pause before your next GEO pitch, it should, because visibility without attribution is just vibes, and vibes don't survive budget season.
Google's AI Search Data Is Growing, But The Gaps Remain
Sixty-eight percent of Google searches now end without a click, and the gap between impressions and traffic is the AI Overview eating your CTR. The data keeps arriving, but the measurement gaps remain, and the teams that close them first will have a forecasting advantage that compounds.
The Conversion Counting Problem Nobody Wants to Model
Your Meta dashboard shows 50 conversions, Google claims 32, and your CRM logged 42 actual sales. Three numbers, zero agreement, and spoiler: everyone's numbers are right by their own rules. The question is whether you've built a model that reconciles them.
The Funnel Lied to You: What Dreamdata's Data Reveals About How B2B Buyers Actually Buy
Eighty-eight touchpoints. Ten stakeholders. Two hundred seventy-two days. The comforting fiction of your linear funnel just got buried by Dreamdata's latest research, and the implications should make every CMO reconsider everything they thought they knew about attribution.
The 83% Accuracy Play: Why Your SEO and Paid Teams Need to Stop Forecasting in Silos
Here's a stat that should make every CMO sit up: forecasting SEO and paid search together lifts revenue accuracy to 83%. If you're still running separate forecasting models, you're essentially flying a plane with two pilots who refuse to talk to each other.
When Your Product Is the Marketing Funnel: What Barrière's Vitamin Patches Teach Us About Attribution in 2026
Someone asks about your tattoo. You explain it's actually a vitamin patch. Congratulations: you've just become an unpaid brand ambassador, and Barrière's marketing team has no idea how to credit you for the sale that might follow.
The End of "Trust Me, It Worked": Why Analytics Hubs Are Finally Giving CMOs the Receipts
Every CMO knows the nightmare: scrambling through spreadsheets when the board asks what marketing actually contributed to revenue. Analytics hubs are finally solving this with instant, traceable answers that connect every touchpoint to actual deals.