MarTech (Marketing Technology) has become an essential tool for businesses aiming to improve marketing efficiency and optimize customer experiences. However, if MarTech challenges are not properly addressed, it can have the opposite effect—wasting valuable resources and harming a business’s reputation.
By understanding and tackling these MarTech challenges, companies can unlock the full potential of their technology investments and drive sustainable growth.
This insight was highlighted by Mr. David Lapetina, VP of Engineering & Technology at Kyanon Digital, during the Vietnam MarTech Day 2024 event held on November 1st. Centered around the theme “Fusion to Future,” the event emphasized the power of technology integration in shaping the future.
1. Avoiding Common Challenges in Technology-Driven Marketing
While MarTech has the potential to elevate marketing strategies and optimize customer experiences, MarTech challenges can quickly arise if not managed carefully. For MarTech to be both efficient and accurate, it must rely on three foundations:
- Artificial intelligence (AI)
- A sound technical architecture
- Data
These elements are crucial to building a MarTech system that supports growth rather than hinders it. When any one of these pillars falters, the impact can be severe—leading to resource waste, brand damage, and diminished customer trust.
Navigating these MarTech challenges and ensuring these foundations are maintained effectively is key to turning MarTech into a true asset for your business.
2. MarTech Challenges: How Small Errors Can Cost Big Opportunities
In the world of MarTech, several challenges can arise if key elements aren’t managed properly.
2.1. Wrong data leads to wrong decisions
For example, imagine a chatbot representing your brand but misfiring with inaccurate or irrelevant responses.
Or marketing automation designed to engage customers, but instead, it floods inboxes with what feels like spam. Then there’s the risk of relying on outdated data—wrong data leads to wrong decisions.
2.2. Poor inventory management data
Take a brand using poor inventory management data, unaware of how outdated stock information could trigger a crisis.
Without real-time updates, they miss the opportunity to capitalize on trending products, leading to stockouts just when demand peaks. The result? Lost revenue and frustrated customers who quickly turn to competitors.
2.3. AI gone rouge
One of the most alarming MarTech challenges is when AI goes rogue.
Imagine a brand launching a chatbot to assist with customer service, only to have poorly trained AI suggesting illegal services. In one extreme case, the AI might even offer adult content advice to underage customers or provide responses violating company compliance rules by promoting services in regions where they’re illegal.
The impact of such AI failures can be catastrophic—resulting in legal repercussions, negative press, and a social media backlash that could severely damage the brand’s reputation.
2.4. Wrong email to wrong people
One common MarTech challenge businesses face is poor email segmentation, which can lead to embarrassing and costly errors.
Imagine a company using faulty MarTech to segment their email lists and targeting the wrong audience. In this case, emails are mistakenly sent to 20-somethings offering senior citizen discounts—an obvious mismatch. The result? Frustrated recipients, high unsubscribe rates, and a damaged brand image.
The impact of such targeting errors goes beyond lost engagement—it can lead to a loss of credibility, a decline in customer trust, and negative press that tarnishes the brand’s reputation.
2.5. Silos destroy brands
One of the most damaging MarTech challenges brands face today is the creation of data and software silos.
Data silos fragment customer insights, making it difficult to achieve a unified understanding of your audience. Software silos arise when each department uses its own tool for specific functions without integration across teams.
This disconnection can create confusion, especially when the same data is represented differently across platforms
2.6. Poor data quality, poor results
One of the biggest MarTech challenges businesses face is poor data quality, which leads directly to poor results.
Without real-time updates, it becomes nearly impossible to personalize customer experiences or anticipate trends effectively. Low-quality or inaccessible data can cause marketing teams to make costly mistakes—whether it’s targeting the wrong audience or misjudging customer preferences.
The impact is significant: marketing decisions based on bad data can alienate customers and erode trust in your brand.
According to Mr. David Lapetina, in the context of rapidly advancing technology and increasing competition, businesses globally, including those in Vietnam, have largely adopted MarTech solutions to manage their marketing activities. One significant trend he highlighted is the growing use of chatbots and virtual assistants to support customer service operations.
However, Mr. Lapetina cautioned that improper use of MarTech can create opportunities for competitors. He emphasized that while Vietnamese businesses have been quick to embrace MarTech, improper execution can result in significant setbacks.
He provided an example: “Imagine an ad banner for a beautiful pair of shoes, but when customers click it, the product is out of stock. Worse, the system suggests similar products from competitors right below. Not only does this result in a lost customer, but it also inadvertently promotes a competitor.”
Such errors in inventory management on e-commerce platforms can lead to significant losses for businesses, affecting their brand image and, in some cases, promoting competitors for free.
Chatbots are also a growing trend in automating customer support, increasing interaction, and reducing labor costs. However, as Mr. Lapetina noted, if chatbots are not used correctly, they can have a negative impact on brand image and harm revenue. For instance, Air Canada faced a major issue when its chatbot automatically issued inappropriate refund policies, leading to customer complaints and a hefty fine.
These examples underline the importance of properly managing MarTech to avoid costly errors and ensure it adds value rather than creating problems for businesses.
3. How to overcome MarTech Challenges
To tackle the MarTech challenges of poor data quality, software silos, and slow decision-making, businesses must implement strategic solutions like data governance, composable architecture, and AI for real-time insights.
3.1. Data Governance
Effective data governance is a critical foundation for overcoming the MarTechchallenges and ensuring that your marketing strategies are built on reliable, actionable data. At its core, data governance relies on a well-defined organizational structure that outlines clear responsibilities and processes for data management.
By establishing guidelines for data accuracy, security, and accessibility, companies can ensure consistent, high-quality data across the board. Furthermore, data governance plays a pivotal role in AI explainability—allowing businesses to better understand and trust AI-driven decisions. When data is properly governed, AI can offer transparent insights, making it easier to explain how certain predictions or recommendations were made.
This transparency fosters trust, improves decision-making, and enables companies to leverage AI for smarter, more efficient marketing operations.
3.2. Composable Architecture
One of the most significant advantages of composable architecture is its ability to break down software silos, which are common barriers to efficient operations in many businesses. By offering modular and flexible systems, composable architecture allows different tools and technologies to integrate seamlessly across departments.
This modular approach enables all teams to work with their preferred tools, yet still collaborate within a unified ecosystem.
The result? Real-time insights are made available across departments, operations become streamlined, and cross-department collaboration becomes more efficient. With a unified yet flexible system, businesses can eliminate the bottlenecks caused by software silos, ensuring that teams are working from the same data, improving decision-making and driving business growth.
3.3. AI For Real-Time Insights
AI for real-time insights is a powerful tool for overcoming MarTech challenges, but its effectiveness hinges on the quality of the data it processes.
AI can only deliver valuable insights if it’s fed with clean, unified data. Without proper data governance and composable architecture, businesses risk poor data management, leading to inaccurate insights and missed opportunities. These two components ensure that data is integrated, accessible, and trustworthy, giving businesses full control over their information systems.
Data Governance and Composable architecture gives you back control on your information system and your data, without these two components it will be a guarantee for failure at scale.
4. The future of MarTech
The future of MarTech lies in the convergence of three key trends: AI-driven, governed, and unified.
As businesses continue to embrace AI-driven solutions, they will harness the power of real-time data insights to make faster, more informed decisions. However, to ensure that AI delivers value, it must be backed by strong data governance—ensuring that data remains accurate, secure, and accessible across systems. Finally, the trend toward unified systems is critical for eliminating data silos, fostering cross-department collaboration, and streamlining marketing operations.
By integrating AI, data governance, and unified architecture, businesses can create a future-proof MarTech ecosystem that not only overcomes existing challenges but also drives long-term growth, efficiency, and customer satisfaction.
Kyanon Digital is a top MarTech consulting and integration company in Vietnam, empowering businesses with innovative solutions to harness the full potential of their data and marketing technologies. Contact Kyanon Digital today to connect with our team of professionals who can guide you through the complexities of MarTech and data management.
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