MarTech 09月29日
MarTech大会:充分利用现有数据,而非追求更多
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在MarTech大会上,营销专家们探讨了为何即使数据充裕,许多洞察仍未被挖掘。他们强调,营销人员需要的不是更多数据,而是更智能、更协作地利用现有数据,并关注数据卫生。会议指出,第三类数据、直接流量和第一方互动数据常被忽视;数据孤岛和集成是主要障碍。同时,AI驱动的环境下,网络分析和邮件数据变得复杂,开放率等指标不再可靠。专家们呼吁重视零方和第一方数据,并以谦逊的态度对待AI,回归数据使用的基本原则,如明确问题、关注数据质量和向上游解决数据卫生问题。

📊 **重新审视被忽视的数据源**:第三类数据、直接网站流量以及第一方互动数据(如应用内信号)蕴含着丰富的用户行为和意图信息,常被营销人员低估。尽管第一方数据备受推崇,但第三类数据提供了更广泛的客户画像,而直接流量则揭示了用户真实的行为模式,这些都被证明是实现精准细分和个性化营销的关键。

🔗 **打破数据孤岛与集成障碍**:数据访问本身已不是主要问题,关键在于数据的质量和集成。营销团队面临的主要挑战是数据孤岛和系统间的集成鸿沟,导致数据无法有效整合和使用。解决这些问题需要统一的系统和强有力的数据治理,才能充分释放数据潜力。

📉 **适应变化的分析与邮件指标**:在AI和隐私保护的时代,传统的网络分析和邮件营销指标(如开放率)已变得不可靠。营销人员需要接受不完整的归因数据,并更多地依赖转化和跨渠道的互动信号来理解用户意图。邮件营销尤其需要与其他多渠道信号结合,而非依赖单一渠道数据。

💡 **善用零方及第一方数据**:零方数据(客户直接提供偏好)和第一方数据是建立个性化和AI应用的基础。但前提是必须建立清晰的价值交换,让用户看到提供信息的益处,并透明地告知数据用途。同时,需要确保CRM等系统能够及时更新以反映现代的购买周期。

❓ **回归数据使用的基本原则**:在拥抱AI和新技术的同时,营销人员应首先明确自身需要回答的问题,并关注数据卫生。解决数据质量问题应优先考虑在数据仓库或CDP等上游环节,确保数据的准确性和一致性。选择工具时,应基于自身数据需求、技术栈和行业特点,而非盲目追逐最新概念。

At the September MarTech Conference, MarTech Editorial Director Mike Pastore gathered three seasoned practitioners to tackle a deceptively simple question: if marketers are swimming in data, why are so many insights still being left on the table? Joining him on the panel were: 

The conversation ranged from overlooked data sources like direct web traffic and CRM rules, to the challenge of channel silos, to the shifting reliability of email and web analytics in an AI-driven environment. What emerged was a clear message: marketers don’t need more data — they need to use what they already have more intelligently, more collaboratively, and with better hygiene.

MarTech Conference September ’25: Now On-Demand
Six panel discussions on data and AI, available on-demand when you log in or register. Watch now for free.

The most overlooked data sources

The panel began with a lightning round. Each expert named the most underutilized data point in modern marketing:

That opening set the tone: valuable signals exist everywhere, but organizational silos and old assumptions prevent them from being harnessed.

What’s blocking data use?

The audience poll revealed two top challenges: silos and integration gaps. Access itself was less of an issue — marketers generally have the data — but without integration and quality, it’s unusable.

The consensus: the tools exist, but without unified systems and governance, data potential goes unrealized.

Web analytics in an age of noise

Harris described the radical shift in web analytics: attribution has shattered.

“In 2007,” she said, “the funnel was neat: submit a lead, get a call, close in five days. Now? There are 65 touchpoints in many purchases. In automotive alone, over 20 touchpoints per sale. We need to stop pretending attribution is a straight line.”

Her advice: accept incomplete data. Use what you have. “It’s okay that you can’t see it all. Make decisions anyway.”

John Heywood added that clean, centralized data — often in cloud warehouses — makes this complexity manageable. Braze, he noted, is investing in zero-copy integrations so data doesn’t need to be constantly copied and synced across tools.

Phelan recalled the early days of “guiding” website visitors hand-in-hand. That predictability is gone. “Today, one shopper goes through every step; another impulse-buys in a minute. Web analytics must adapt to unpredictable, fragmented paths.”

Email data: Also disrupted

If web analytics has been upended, so has email. Apple’s Mail Privacy Protection and Gmail’s changes have made open rates unreliable—once everyone’s favorite metric.

The takeaway: email data alone can’t carry segmentation. It must be combined with multichannel engagement signals.

Zero- and first-party data: Still underused

The panel agreed: marketers consistently underutilize the most permission-rich data they own.

Zero- and first-party data should be the foundation for personalization and AI. But without governance and reciprocity, marketers risk misuse.

Customer journeys: Fragmented beyond control

If attribution was messy before, AI and multichannel customer paths make it nearly impossible to script journeys.

Data hygiene: where to start?

The Q&A turned to data hygiene — a recurring theme across the September 2205 MarTech Conference.

The panel resisted naming a “best tool.” The key, they stressed, is first assessing your data needs, stack, and industry context before shopping solutions.

A hot topic: generative engine optimization (GEO). Is it hype or real?

The consensus: the names change, but the fundamentals endure.

AI personas: Useful or hype?

An audience member asked whether AI personas are being used for stakeholder insights.

Verdict: promising, but unproven. Useful as a supplement, not a replacement.

Key takeaways for marketers

    Revisit neglected data. Direct traffic, CRM rules and third-party data still hold insights.
    Fix silos and integrations. Access isn’t enough — data must be unified, cleaned and accessible.
    Accept messy attribution. Stop chasing perfect paths. Use what you have and act anyway.
    Use zero- and first-party data wisely. Create clear value exchanges and keep systems updated.
    Treat AI with humility. Everyone is a beginner; focus on practical use cases.
    Ask better questions. Define what you need from data before diving into AI or new tools.
    Invest in hygiene upstream. Clean, accurate data multiplies value across every channel.

The bottom line

Marketers aren’t short on data. They’re short on discipline, integration and confidence in messy realities. As Harris put it, “Not all the data will always be there — and that’s okay.”

The opportunity isn’t chasing the next acronym, but unlocking overlooked assets already in the stack, cleaning them, integrating them and applying them with humility in a world where journeys are consumer-led, not brand-led.

MarTech Conference September ’25: Now On-Demand Six panel discussions on data and AI, available on-demand when you log in or register. Watch now for free.

Listen to an audio overview of the September 2025 MarTech Conference

Use the player below to listen to an AI-generated overview of the September 2025 MarTech Conference sessions.

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MarTech Conference Data Utilization Marketing Insights Data Silos Data Integration AI in Marketing Zero-Party Data First-Party Data Data Hygiene Web Analytics Email Marketing
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