Nội dung
- Open-source has brought MMM closer, but it has not made it easier
- Digital video enters a new competitive era: targeting rises, AI moves into operations
- Before the next budget cycle, audit AI instead of just counting tools
- Why are industry conferences still worth attending in the AI era?
- A perspective for the Vietnamese market
- References
AI is moving from “experimentation” to “scaling” in marketing, but the pace of maturity still varies widely across businesses. While some groups have already started using AI to run campaigns and measure performance, many organizations are still stuck at the level of disconnected tools, lacking processes and methods to assess effectiveness.
- Key points:
- Open-source has made marketing mix modeling (MMM) more affordable to access, but it has not made the measurement problem any easier from a technical standpoint.
- Digital video continues to accelerate, with targeting becoming the new competitive advantage and agentic AI beginning to enter campaign operations.
- Many marketing teams are using AI, but the number of organizations with truly automated workflows or clear business results remains low.
- Industry conferences still hold value thanks to human connection, shared experience, and opportunities to learn beyond the screen.
Open-source has brought MMM closer, but it has not made it easier
MarTech says marketing mix modeling is becoming more accessible thanks to open-source platforms, but the biggest barrier is no longer the upfront cost — it is implementation capability. In other words, businesses can get started sooner, but to produce reliable and actionable results, teams still need a deep understanding of data, methodology and how to interpret models.
The article emphasizes that the emergence of open-source libraries has changed MMM’s “starting point.” This is especially important as MMM is increasingly seen by marketers as a more reliable measurement method for budget allocation, rather than relying entirely on surface-level metrics.
The core message here is clear: better tools do not automatically mean better results if analytical capability and validation processes are missing. With MMM, the value is not in which software you can install, but in the ability to turn input data into better budget decisions.
Source: MarTech — “Open source made MMM cheaper, not easier”
Digital video enters a new competitive era: targeting rises, AI moves into operations
Data from IAB, cited by MarTech, shows that digital video ad spending in the U.S. is projected to reach $81.9 billion in 2026, up 11% from the previous year and accounting for 61% of total TV and video spending. This is a sign that digital video is no longer just a “growth channel” — it has become a central competitive battleground for the advertising industry.
The most notable point in the report is the shift in media-buying priorities: targeting has overtaken content quality as the top criterion. At the same time, social video is still growing faster than connected TV, reflecting how user behavior continues to move toward social platforms and short, continuous viewing experiences.
MarTech also notes that agentic AI is gradually entering campaign operations, but has not yet reached spending decisions. This points to a very practical transitional phase: AI can support optimization tasks and automate workflows, but strategic decision-making still belongs to humans and internal control systems.
Source: MarTech — “Digital video enters a new era of competition”
Before the next budget cycle, audit AI instead of just counting tools
In the third story, MarTech raises an issue many marketing leaders are facing: they know their teams have “made progress” with AI, but they cannot clearly say where they are on that journey. Familiar metrics such as the number of licenses, tool usage rates or hours saved only reflect activity levels; they do not show true maturity.
The article cites several comparative figures to show that the gap between “using AI” and “achieving business results from AI” remains very large. From there, the author suggests that before entering a new budget cycle, managers should conduct an internal AI audit to determine which stage the team is in: experimentation, partial integration, workflow automation, or measurable impact on business outcomes.
This is a very useful suggestion for Vietnamese marketers, because many businesses still evaluate AI based on intuition or on the list of tools they have purchased, rather than on the real change in workflows and output performance.
Source: MarTech — “Run this AI audit before your next budgeting cycle”
Why are industry conferences still worth attending in the AI era?
MarTech’s final article returns to a topic that may seem familiar, but remains highly relevant: why marketing conferences still attract attendees even though everyone says they are busy, tired and overloaded with information. According to the article’s argument, the greatest value of conferences is not the stage or the venue, but human connection — something that is difficult to fully replace with digital platforms or AI tools.
In the post-COVID work environment and amid saturated digital communications, face-to-face meetings still help marketers build relationships, exchange experience and create deeper conversations than linear interactions on a screen. Conferences, therefore, are not just places to hear keynotes, but also places to “read the market” through how industry people discuss, challenge and look for collaboration opportunities.
From this perspective, AI does not reduce the value of industry events; on the contrary, as digital content becomes increasingly dense, live experiences become even more meaningful as a pause for connection, validation and network expansion.
Source: MarTech — “Why marketing conferences are still worth it”
A perspective for the Vietnamese market
These four stories point to a common denominator: AI in marketing is no longer a race to see who has the newest tool, but a race in organizational capability. If Vietnamese businesses want to use AI effectively, they need to look at three layers at once: data, processes and people.
At the data layer, MMM can be a worthwhile direction for brands with multiple channels and budgets large enough to require more precise allocation. At the process layer, AI should be audited regularly to identify which tools truly create value and which only make reports look better. At the people layer, in-person activities such as seminars, workshops or industry meetups remain very important for hands-on learning and faster trend updates.
In short, AI will help Vietnamese marketing move faster, but only teams that know how to combine measurement, operations and connection will be able to go further.
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This article focuses on AI marketing trends with a perspective for the Vietnamese market.
References
- Open source made MMM cheaper, not easier
- Digital video enters a new era of competition
- Run this AI audit before your next budgeting cycle
- Why marketing conferences are still worth it
