Systems of Record in the AI Age

Data is everywhere. It is the fuel which powers modern marketing. Marketers have spent years building complex tech stacks to make the most effective use of customer profiles and campaign activity history. Marketing technology is the decision-making engine that drives marketing ROI. It turns data into revenue through proprietary vendor workflows or bespoke AI models built into each app. That technology takes the disparate insights collected across the tech stack and uses them to optimise ad spend, identity nurture audiences, or generate leads.

Information Overload

As a result of all this technology, enterprise marketing teams have more information than they know what to do with. It's not just the classic customer profiles found in every CRM system. AI has expanded the scope of useful information to include internal notes, customer communications, and even the marketing content that prospects consume. All those things are data, but they are managed very differently.

Over time, specialised SaaS platforms have been developed to manage each dataset. Budgets are often controlled in specialised finance tools such as Anaplan. Reporting data is increasingly centralised in dedicated BI tools owned by the analytics team. CRM data remains locked in Salesforce or Dynamics. The CMS increasingly acts as an asset management tool, as well as a website hosting platform. Vendors develop their products to fit the specialised workflows needed to manage data and activate content within a specific set of use cases. Tech teams mix and match vendors to fit the specific business needs each platform must address.

Core Competencies

Some vendors do cover multiple categories. Salesforce and Adobe both offer solutions across all areas of marketing. However, specialisation matters. The most mature and well designed features from each vendor fit the dataset and use cases that the vendor knows best. That's often the market in which the vendor has the highest pedigree and the deepest institutional knowledge. Despite owning multiple best-in-class customer activation platforms, Adobe's strongest offerings remain those related to content production and content management workflows. Salesforce remains the market leader for CRM platforms.

It's no coincidence that the core competence of Salesforce is CRM data and customer engagement workflows. That's where the company started. They’ve been able to expand that strength by developing enterprise grade customer service and cross-channel marketing capabilities. The backend data and content management products have struggled though. Instead, it is Adobe who have become the thought leader in digital asset management systems. While their primary growth driver is built around the related content production tools.

The two vendors compete directly, but they still operate in very different worlds, often answering to different marketing stakeholders. That's because they arrive at the same challenges from very different angles, looking to solve critical marketing challenges through the most effective use of different types of information. Perhaps the biggest impact of AI is the ability to link these disparate data types together in a structured way. Adobe look to generate leads from the best use of content. Salesforce from the best use of customer data. Yet, why not do both?

Value Add

Expectations about technology have changed. Marketers don't want unused technology lying around doing nothing. It needs to be always on, constantly powering the customer journey. Mere campaign execution is not enough. Marketers want technology to improve campaigns. The successful vendors have relevant expertise and insight into a specific channel or marketing workflow. That expertise is the moat upon which the vendor’s offering is built. Without it, a technology product cannot survive in a saturated martech marketplace. Complex applications can now be developed using in house solutions. A new technology needs to add value not found in the existing tech stack. That value that is not measured through capabilities, but instead is measured in experience.

However, vendor expertise is no longer enough on its own. AI or agencies can provide it. Marketers want bespoke solutions. Each technology needs to work within the customer’s own industry. Vendor capabilities need to be adaptable to the campaigns that users need to run. Marketers expect to overlay their context and their strategy on top of vendor provided capabilities. That linkage requires manual guidance and human insight into the most relevant connections. Technology then allows the resulting strategy to be executed quickly and optimised efficiently, but only if the underlying data has been appropriately tagged, stored and cleansed. Dirty data leads to bad AI. Good data requires the right governance processes for each dataset.

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