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In a recent episode of “Marketing from the Source”, Chris Sell welcomed Scott Brinker - VP Platform Ecosystem at Hubspot, Editor at chiefmartec.com, and popularly known as the Godfather of MarTech. They talked about the explosive growth of MarTech solutions and how generative AI could be a game-changer for the global marketing landscape. In today's blog, we're diving into the key insights from their conversation.
“With the rise of the cloud data warehouse, data is flowing back and forth between the warehouse and marketing tools. And it’s phenomenal - it’s connecting marketers to the rest of the organization in a much broader way.”
The martech landscape has seen 7000% growth over the last 12 years with over 11,000 solutions currently on the market. In terms of broader growth trends, there are three main themes Scott is focusing on:
The shift towards a universal data layer - While most MarTech tools had their own siloed databases earlier, universal data exchange and public storage is on the rise thanks to the growth of the cloud data warehouse.
More composability - With more APIs and cloud solutions, marketers can compose their own channel tools and add-ons whenever they need to.
Generative AI - The industry as a whole is reaching an inflection point with AI, opening up unprecedented scope in terms of customer conversations and content creation.
And as more and more martech solutions re-architect around the data cloud, Scott emphasized that this makes the most sense overall in the long term, even if some companies choose to maintain separate operations for now.
The two discussed a recent observation from Scott, wherein the old model of marketing operations as a funnel to data warehouse is being replaced by a circular flow between the two.
Instead of the conventional funnel approach leading to a data warehouse, they are envisioning a circular flow between the two. According to Scott, this transformation will eventually become the norm in marketing operations, though he points out that its adoption curve will likely be a lengthy one.
The reason behind this slow adoption is that marketers are just beginning to grasp the full potential of their data assets. Previously, data was primarily utilized for visualization in analytical reports. However, there is now a realization that data can be leveraged for active decision-making through iterative experiments and discovery projects aimed at understanding customer needs better.
As this understanding grows, marketers will feed the insights gained from these experiments back into the central data hub. They will continuously experiment with, modify, and refine the data, creating a continuous loop of improvement and adaptation - thus setting the circular flow into motion. Ultimately, this circular approach promises to revolutionize marketing operations, empowering businesses to make better-informed decisions and cater more effectively to their customers' requirements.
“With the growth of AI-powered content, buyers will plausibly come up with their own AI tools. Think algorithms designed to serve the customer, not the seller.”
Generative AI has emerged as a powerful tool for sellers, enabling them to quickly create content and personalize it extensively for each individual customer. However, a downside to this advancement is the potential inundation of customers with an abundance of seller-generated content. To counteract this, Scott foresees the rise of buyer-specific AI as a response. These buyer-specific AI tools would scan the customer's inbox, among other data sources, and condense the day's emails and information based on the customer's preferences and interests.
Looking ahead, sellers will shift their focus from traditional SEO strategies and instead concentrate on optimizing their content to align with the preferences and criteria of the buyer AI. It's essential to recognize that it may not be feasible to perfectly cater to every individual AI, prompting Scott's suggestion for the establishment of universal standards for the type of content that sellers can use to connect with their customers. These standards would ensure that content remains relevant, engaging, and compliant with the requirements of various buyer-specific AI systems, enhancing the overall customer experience and effectiveness of marketing efforts.
“With this kind of disruptive innovation in AI, anyone will be able to take an idea from brainchild to living, breathing status. This is excellent news for so many creative spirits.”
In the near future, as generative AI becomes integrated into various apps and tools, marketers will start to view these applications as a simple and intuitive way to request and receive exactly what they need. Similar to how we conduct searches on Google without much thought, marketers will rely on generative AI to quickly bring their ideas to life with unprecedented speed and ease.
However, this newfound ease of creation comes with a potential drawback. Scott acknowledged that there might be an increase in the amount of low-quality content, often referred to as "junk," being produced due to the accessibility of generative AI. Despite this concern, he remained optimistic about its overall impact, emphasizing that it will significantly enhance access for individuals with innovative ideas who wish to experiment with them.
To address the issue of content quality, filters will play a crucial role. Trusted influencers and peer groups can take on the responsibility of championing valuable content worth consuming. Customers can then opt for content recommended by these reliable sources, ensuring they receive high-quality and relevant material.
During their discussion, Scott and Chris also noted that different companies will have varying levels of technological maturity, leading to a diverse range of MarTech architectures being adopted in the industry. This diversity of approaches will likely shape the marketing technology landscape in the future. “It’s going to be diverse - at least for the rest of this decade,” said Scott.
You can check out the entire conversation here.
