Platinum Sponsor Webinars

🎉 Coming Soon 🎉
We’re super excited to announce a fresh perk for you: our amazing Platinum Sponsors will be hosting exclusive webinars both before and after the event! scroll for full list

✅ Why is this awesome?

• It’s a bonus for YOU – more chances to learn cutting-edge analytics from industry pros.
• It’s a bonus for THEM – a little extra love for the sponsors who make this event possible!

(Seriously, without their support, tickets would cost at least £200 per person. So let’s give them a virtual high five! 🙌) ✨ The webinars look fantastic, so don’t miss out. Reserve your spot and get ready to level up your analytics game!

Topic: Making AI Reliable for Business Decisions

You’ve probably already used AI to analyse data or support an important decision. And you’ve probably experienced that unsettling moment when its answer sounded completely confident—but was completely wrong. The good news? This isn’t simply a model or prompting problem. It’s usually caused by gaps in the organisation—and those gaps can be fixed.

For AI to deliver answers your business can genuinely trust, it needs three essential layers:

• Connected, reliable data it can query
• Clear business and data context
• Workflows that reflect how decisions are actually made

The Coupler.io team has developed a practical framework that brings these layers together, helping thousands of customers incorporate AI into business decision-making in a reliable, transparent and auditable way.

It works across different tools, team sizes and data destinations—and fits around the technology you already use.

You’ll learn:

• How to give AI access to better data so your business can make faster, more confident decisions
• How to build a trustworthy and auditable AI system that your team, clients and leadership can genuinely rely on
• How to move from impressive AI outputs to dependable business decisions

Register here

Why Most Experimentation Programs Plateau — And What Actually Moves Them Forward

You’ve probably run plenty of A/B tests. Some win. Some lose. But somewhere along the way, the results stopped compounding, and the program started feeling like it was just running in one place.

This isn’t a testing volume problem. It’s rarely even a tool problem. It’s usually caused by gaps in how experimentation programs are structured, and those gaps can be fixed.

For an experimentation program to deliver lift consistently, it needs three things working together:

• Behavioural evidence that tells you why visitors aren’t converting, not just where
• Hypotheses grounded in that evidence, not instinct or stakeholder requests
• A feedback loop that closes — from insight to test to decision, without the program losing momentum between each step

The Zoho PageSense team works with experimentation teams across industries and has seen what separates programs that keep improving from ones that flatline. In this session, we’ll walkthrough what actually moves programs forward — with real examples you can take back to your team the same day.

You’ll learn:

• How to diagnose why your program has plateaued — and which gap is costing you the most
• How to connect behavioural data, funnel analysis, and user feedback into one coherent testing story
• How to build and ship experiments faster without sacrificing the rigour that makes results trustworthy

Register here

Register here

Closing The Measurement Gap with Data Manager API

1. Why Data Manager API, why now?

• The problem: conversion loss caused by browser restrictions (ad blockers, ITP, cookies)
• Google’s answer: a unified server-to-server API, successor to the Offline Conversion API and the GA4 Measurement Protocol, available to all Google Ads accounts since October 2025
• Key benefits: more complete measurement, better attribution…

2. The use cases and what it actually solves

• Sending offline conversions to Google Ads and GA4 (in-store, phone, CRM)
• Enriching existing online tracking as an additional source (recovering lost conversions, deduplication via Transaction ID)
• A simple visual on the deduplication logic (update / ignore / create)

3. How to do the set-up

• The “one API, multiple destinations” concept
• The 6 steps at a high level
• A concrete example (GTM Server preview with the payload)
• A quick note on Consent Mode (adUserData / adPersonalization)

Register here