Marketing goals must serve customers before internal preferences

Marketing goals must serve the customer’s purpose

An email can preserve a brand’s typography and still stop a customer from reading its offer. The design may pass every internal review, yet the communication fails because the customer cannot use it. Similar problems arise when Google visibility, campaign engagement, or distinctive copy defines success: a team can meet its own goal while making discovery, access, or customer relationships harder.

A marketing commentator explains this problem through advice from his wife, a leader at a Boston hospital who counsels colleagues, team members, and sometimes him. Getting someone to take a useful action can matter more than getting them to accept your reasoning; insisting on both can undermine the action. For marketers, her distinction raises a practical question: do professional preferences still serve their intended purpose? His four examples concern email design, search discovery, performance measurement, and messages processed by AI agents.

Brand consistency depends on usable messages

Email makes the conflict concrete because preserving a preferred appearance can change who can read a message. The commentator reports that some brand stewards turn almost the entire email into images to preserve their typography. The lettering looks right in an internal review, but subscribers can find the message harder to read, enlarge, or use with assistive tools. Visual consistency comes at the expense of access.

The desire for control comes from an earlier publishing environment. When magazines, newspapers, and billboards dominated marketing, brands could tightly specify how their material appeared. Digital distribution put that material inside software and settings controlled by other organizations and by customers. The commentator sees attachment to print-era control as one reason marketers resist variation, even when it helps a message work.

Email exposes these limits through rendering, the process by which an inbox turns email code into an on-screen message. The commentator describes email as lacking common coding standards, with font support varying across inbox providers. Some inboxes display custom brand fonts, while others require fallback fonts. Subscribers’ choices about how to open and use messages add further differences.

A fallback font keeps the words readable when the preferred typeface is unavailable. Some brand stewards resist that visible change and put the words into images, leaving little HTML text, which an email application can directly process and display. The inbox then receives a picture of the lettering. Preserving its appearance changes how both people and software can access the information.

Screen readers and voice assistants need access to those words to convey the message to a subscriber. Image-heavy emails complicate that task, while subscribers who need larger text can struggle to enlarge words embedded in pictures. People who block images face another obstacle because the information depends on content they have chosen to hide. The commentator also includes subscribers sorting through spam folders, where image-dependent content makes messages harder to assess, and describes the affected population as substantial.

The same design choice creates problems for AI email summaries because an agent must extract a message’s information before summarizing it. This extends an existing accessibility problem to another way customers receive information. The commentator expresses the change in goal as moving from “Deliver identical brand experiences everywhere” to “Deliver functional brand experiences everywhere.” A different font can therefore be a successful outcome when the subscriber can read and act on the message; approval needs to account for the environments in which it will be received.

Discovery strategy must follow customers across destinations

A usable message still needs to reach its audience, which makes discovery the next test of whether a familiar goal serves its purpose. In the commentator’s account, many brands treated appearing on “page 1” of Google Search as the condition for being found. Search engine optimization, or SEO, became a major industry around that assumption. He proposes moving from “Get visibility in Google Search” to “Get visibility in the places your customers frequent most.”

The case for that change begins with how search now answers questions. Large language models, or LLMs, are AI systems that generate responses from learned language patterns; they and Google’s AI Overviews increasingly provide answers within the discovery experience. The commentator links these changes to a sharp fall in referral traffic, particularly for publishers, as fewer searches lead to visits to their sites. He sees no indication that previous traffic levels will return, making dependence on those visits a strategic concern.

Some SEO firms have responded by presenting themselves as AI search specialists. The commentator argues that this can carry the same dependence into a new environment because visibility still rests on another company’s changing selection process. He describes LLM discovery rules as shifting “with every new model release.” For example, he points to Reddit’s recent move from a prominent source of AI references to a much less emphasized presence in ChatGPT.

That instability leaves room for AI-search optimization as a tactic while strengthening the case for a broader discovery strategy. The commentator recommends considering relevant social media platforms, Amazon, YouTube, and customers’ inboxes. The choice depends on where a particular audience gathers. His concern is that confidence in existing SEO expertise can make marketers reluctant to broaden their approach even as referral traffic falls.

Reaching customers across those destinations serves a different purpose from helping them once they arrive. For that interaction, the commentator proposes brand-operated AI systems or agents that address customers’ needs and reduce their reasons to consult outside AIs. He separately recommends obtaining permission to contact customers through email, SMS text messages, push notifications, and loyalty programs. Platform presence supports discovery, brand-operated assistance supports an interaction, and permission-based contact gives the business a way to maintain the relationship.

Customer relationships should guide performance measures

Maintaining that relationship requires measures that extend beyond a single contact. The commentator proposes moving from “Maximize campaign and channel KPIs” to “Maximize customer relationship KPIs,” with KPIs meaning the indicators used to judge performance. Opens and clicks describe an interaction, while customer lifetime value concerns the value of a relationship over time. Changing the governing measure changes what teams are encouraged to improve.

The need for a broader view coincides with declining visibility into individual behavior. Brands want more data-driven decisions, yet the commentator describes social platforms as providing limited transparency and questions their reporting. Privacy laws also restrict tracking, especially in Europe, where tracking pixels, small embedded elements used to record activity, are a current regulatory target. These constraints limit what marketers can observe about particular interactions.

Technology providers impose further limits through privacy protections. The commentator points to browser, inbox, and mobile operating-system providers introducing measures including App Tracking Transparency, Mail Privacy Protection, and Link Tracking Protection. These changes affect the information available to marketers even when the teams themselves have changed nothing. As organizations seek more evidence for decisions, increasingly detailed campaign reports become harder to produce.

Incomplete reporting becomes harder to manage when customer activity is also divided across teams and systems. Separate channel teams and marketing-technology, or martech, stacks assembled from individually selected specialist tools can fragment information about one relationship. The commentator reports that many brands are overhauling customer data and marketing technology in response. They need to connect interactions managed through different processes and responsibilities.

His proposed overhaul follows four steps. First, centralize customer information in a customer data platform, a system that brings customer data together, or an equivalent system. Second, change KPIs and optimization strategies to center on customers. Third, consolidate marketing technology to support omnichannel messaging, meaning coordinated communication across channels, and fourth, use AI to carry out those efforts at greater scale.

The second step gives the other three their purpose because performance measures direct how teams use the technology. Centralized information can support better-informed decisions, consolidation can enable coordinated messaging, and AI can expand execution. But if teams retain campaign-level objectives, those capabilities can make the same short-term approach more efficient. The commentator sees familiarity with campaign measurement as one reason changing the objective can be difficult.

Campaign measures still help teams understand individual communications within the longer relationship. Opens and clicks describe what happened in a particular contact; customer lifetime value provides a longer time horizon without accounting for every customer need. These measures require judgment rather than offering a guaranteed performance formula. The choice matters when a campaign’s immediate result conflicts with the relationship, because the organization must decide which outcome governs its response.

Messages must be understandable to customers and their AI agents

A relationship-centered approach also has to account for agents that process information on a customer’s behalf. The commentator describes this shift as moving from “Give customers the information they need” to “Give customers and AI agents the information they need.” Agentic commerce, in which AI agents perform shopping-related tasks for people, makes those intermediaries part of the interaction. Gartner predicts that mobile app usage will decline by 25% by 2027 in connection with that change.

Gartner’s forecast concerns how people may interact with businesses; the commentator’s advice about wording addresses how an agent interprets a message. In a recent conversation with Russ Macumber, host of the Beyond the Search Bar podcast, he advocated direct descriptions and avoiding creative phrasing that could confuse an AI recipient. A person may recognize playful or distinctive language that an agent misunderstands. The wording needs to preserve the intended meaning as the agent processes it.

Understanding the message adds a second requirement to the email-access problem. An AI email summary depends first on extracting the words, then on interpreting them correctly. Readable text supports extraction, while clear descriptions support interpretation. A message can therefore be technically accessible and still leave an intermediary uncertain about what the brand offers.

The commentator sees a historical precedent in the 2000s, when publishers and bloggers moved toward SEO headlines containing relevant keywords instead of more creative headlines. He captures his concern with the rhetorical line, “RIP creativity. Long live clarity!” Enjoyment of quirky brand copy can make this adjustment uncomfortable, just as attachment to typography can complicate email design. His recommendation is to balance human appeal with straightforward information so that a customer’s agent can understand the offer and act on the customer’s behalf.

Key takeaways for leaders

• Make email usable across inboxes: Brand and email teams need approval standards that prioritize readable text, fallback fonts, and accessibility. Image-heavy designs can block access for subscribers, assistive tools, and AI summaries.
• Diversify customer discovery: Marketing teams need a presence where their customers spend time, including relevant social platforms, marketplaces, and inboxes. Permission-based channels help sustain relationships as search referrals become less dependable.
• Align measurement with customer relationships: Marketing leaders need relationship-level KPIs to guide investment in centralized customer data, coordinated messaging, and AI. Campaign metrics remain useful for assessing individual interactions within that longer relationship.
• Write for customers and AI agents: Content teams need clear descriptions that help people and their agents understand offers. Readable text supports information extraction; straightforward wording supports accurate interpretation.