One piece of marketing technology you think most teams could stop paying for tomorrow
- Part 1Why Your Data Isn’t Changing Your Business Decisions
- Part 2By 2028 the AI tools developers could cost more than the developers themselves?
- Part 3Changes to how you’ll spend a marketing budget
- Part 4One metric acquirers scrutinize that most marketers completely overlook
- Part 5 One piece of marketing technology you think most teams could stop paying for tomorrow
- Part 6Is AI more like a tool or an operating system?
Episode Chapters
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01:00: Canceling a competitive intel tool
An AI-driven agent system replaced a costly subscription-based competitive intelligence application, automating research collection and delivering real-time, interactive updates to the field team.
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02:30: UI-based tools losing relevance
As data access and manipulation become easier through AI, polished dashboard interfaces and manual reporting tools are increasingly seen as u ecessary overhead.
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Episode Summary
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The MarTech Subscription Your Team Could Cancel Tomorrow
Introduction
Katrina Wong, Chief Marketing Officer at New Relic, has spent more than 20 years building go-to-market and community-led growth engines at enterprise technology companies — including Twilio Segment, Hired, Zuora, Salesforce, and SAP. Asked to name one piece of marketing technology most teams could stop paying for tomorrow, she didn't reach for a category. She reached for a line item her own team had just killed: a competitive intelligence platform that, on inspection, turned out to be a database wearing a login screen. -
The Software You're Paying For Might Just Be a Database
Wong's realization was less about one bad vendor than about a pattern hiding inside the stack. "I didn't realize how many applications we had where it's just a data repository with maybe a light interface for everyone to log into," she said. That's a useful audit question for any marketing leader staring down a renewal cycle: strip away the interface, and what is this tool actually doing that your team couldn't do another way? -
In the competitive intelligence case, the answer was thin. The workflow required Wong's competitive intel team to manually input the latest intel, and the sales team to log in and read it — through an interface she diplomatically described as not the easiest to use. The subscription wasn't buying insight. It was buying storage, plus the friction of getting people to visit it.
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What Replaced It: Roughly 85 Agents and a Shared Gem
Her head of competitive intelligence built what Wong estimated at around 85 agents that go out and gather competitive intel automatically. The output lands in two places: static one-pagers for the field, and an interactive Gemini gem the sales team can query directly. The distinction matters — the one-pagers serve the rep who wants a briefing before a call, and the interactive layer serves the rep who has a specific question mid-deal. -
The operational payoff showed up in two places. Updates are now real time rather than gated on a human entering them, and the field stops pinging the competitive intel team over Slack for answers. That second effect is the one most teams underprice. The vendor invoice is visible; the internal labor spent answering the same questions repeatedly is not.
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Why the Interface Layer Is Losing Its Value
The broader pattern here is that the interface used to be the product. Historically, data was hard to reach, so vendors earned their price by putting it behind a dashboard with filters, pivot tables, and drag-and-drop reporting. When accessing and manipulating data becomes trivial, the polished front end stops being the differentiator — it becomes the thing you're overpaying for. -
That reframes the buying question for marketing leaders. The durable value in a MarTech contract now sits in proprietary data you can't source elsewhere, in workflow that spans teams and systems, or in a system of record with real governance requirements. If a tool's primary contribution is presentation, it's a candidate for replacement rather than renewal.
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How to Run This Audit on Your Own Stack
Three practical filters come out of Wong's example. First, look for tools where your own team is the primary data source — if you're paying a vendor to host information you produce, you're paying for a container. Second, check adoption honestly: a tool people have to be required to log into is signaling something. Third, count the Slack tax — the recurring internal questions a tool was supposed to eliminate but didn't. -
Key Takeaways
The cancelable subscription isn't usually the expensive one; it's the one whose job description quietly shrank to "place where we put things." Wong's team didn't cut competitive intelligence as a function — they cut the software layer sitting between the intel and the people who needed it, and got faster in the process. For marketing leaders heading into renewals, the test is simple: separate what a tool stores from what it actually does, and price it accordingly. -
--- One sourcing note: this segment was short, so the guest-attributed material — the canceled competitive intelligence subscription, the ~85 agents, the one-pagers plus Gemini gem, the real-time updates and reduced Slack load — is everything Wong said on the record. The "interface layer is losing its value" thesis is Benjamin's, stated in the exchange. The audit checklist in the final body section is a framing extension, not something either speaker said; cut or flag it if you want the post strictly limited to spoken content.
- Part 1Why Your Data Isn’t Changing Your Business Decisions
- Part 2By 2028 the AI tools developers could cost more than the developers themselves?
- Part 3Changes to how you’ll spend a marketing budget
- Part 4One metric acquirers scrutinize that most marketers completely overlook
- Part 5 One piece of marketing technology you think most teams could stop paying for tomorrow
- Part 6Is AI more like a tool or an operating system?
Up Next:
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Part 1Why Your Data Isn’t Changing Your Business Decisions
AI is helping marketers move faster, but not always smarter. Katrina Wong, Chief Marketing Officer at New Relic, explains how her team turns raw data into decisions leadership can trust. She covers using AI to analyze recorded sales calls for unbiased win-loss insights, deploying real-time in-product signals to personalize the self-service funnel, and building a human-in-the-loop fact-checking process to catch AI drift before it erodes trust in the data.
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Part 2By 2028 the AI tools developers could cost more than the developers themselves?
AI development costs won't outpace developer salaries by 2028. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years of enterprise marketing leadership and AI-driven go-to-market expertise. She predicts market competition and open models will keep AI tooling affordable, while token costs won't scale to $250,000 per developer per year. Wong also points to one-to-one personalized marketing and selling as the next frontier AI will unlock.
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Part 3Changes to how you’ll spend a marketing budget
AI adoption is upending marketing budgets. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years leading marketing and go-to-market strategy across enterprise tech companies including Twilio Segment, Hired, Zuora, Salesforce, and SAP. She discusses experimenting with OpenAI's ChatGPT app program despite unproven ROI, treating emerging AI platforms as a budget hypothesis rather than a guaranteed channel, and rethinking SEM investment as LLMs become a default search interface.
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Part 4One metric acquirers scrutinize that most marketers completely overlook
Rising AI costs are quietly eroding marketing's bottom line. Katrina Wong, Chief Marketing Officer at New Relic, has led seven successful exits and now factors AI spend directly into cost of goods sold. She breaks down the buy-versus-build decision for AI agents, explains why New Relic won't automate end-to-end campaigns yet, and shares how her team is orchestrating agents across marketing handoffs to control costs.
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Part 5One piece of marketing technology you think most teams could stop paying for tomorrow
Marketing teams keep paying for tools they no longer need. Katrina Wong, Chief Marketing Officer at New Relic, explains why AI is replacing entire categories of MarTech software. Her team canceled a competitive intelligence subscription after building roughly 85 AI agents to gather and organize the same data. The output now feeds one-pagers and an interactive Gemini gem, giving sales real-time answers without waiting on a team or logging into a clunky dashboard.
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Part 6Is AI more like a tool or an operating system?
Clean data beats clever algorithms in AI marketing. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years of enterprise go-to-market experience to the data-versus-AI debate. She argues AI functions as an operating system, not a standalone tool, becoming the intelligence layer powering interconnected agent workflows. Wong stresses that AI output quality depends entirely on data hygiene, making clean data infrastructure a prerequisite for effective AI-driven decision-making.
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