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AI-powered martech releases and news: July 11

Martech

You might want to hold off on using AI for customer service: 64% of customers don’t want companies to replace people with bots, according to Gartner. More than half (53%) would consider switching to a competitor if they found out a company used AI for customer service. They’re serious about this, too.

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Enterprise SEO: 11 keys to success in 2024 and beyond

Search Engine Land

SQL With GA4 and the push to create data lakes via BigQuery with your own historical data rather than Google retaining it, you may hit a point in your year-on-year analysis in Google Analytics now within the interface where you may hit a wall, specifically with conversion events. Dig deeper: Why server logs matter for SEO 5.

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Where to deploy AI for maximum martech impact

Martech

Utilize natural language queries : Ask natural language questions to your datasets and let AI generate the necessary SQL queries. They have ad campaigns across all the big ad platforms, email service providers, cloud accounts, journey management, cloud providers and standalone data science providers, all frequently part of their stacks.

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GTM in The Age of AI: The Top 10 Learnings from ICONIQ’s 2025 B2B SaaS Report

SaaStr

SQL-to-Closed Won Rates Drop 5-6 Points YoY While Top-Funnel Stays Flat The Funnel Breakdown : Marketing teams can breathe a sigh of relief—lead generation and early-stage conversion rates have remained relatively stable. This could include automated customer communications, self-service onboarding flows, and AI-powered support.

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The Ultimate Guide to Building a Lead List

Hubspot

How to Build a Lead List My Tips for Building a Sales Lead List A prospect may have shown interest in a product or service by responding to an online offer, visiting your company’s booth at a conference, or engaging with social media posts. Tip #2: Subscribe to sales lead enrichment services. Table of Contents What Is a Lead List?

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What the composability revolution means for CDPs

Martech

The warehouse was great for running SQL queries; the data lake was good for more complicated stuff, especially AI. He explained: “Ten years ago we were building data lakes and consolidating data. Then there was the rise of the cloud data warehouse. ‘Lakehouse’ seemed pretty close. .

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The fatal flaw killing your customer data initiatives

Martech

They completed onboarding in 30 days with four live use cases—total cost: under $100,000 in software and professional services. The team embedded a natural language AI assistant, enabling business users to run complex SQL queries and create fresh user segments.