Communicating The Impact Of AI On SEO To C-Level via @sejournal, @TaylorDanRW

2 weeks ago 4

AI has emerged as one of the most transformative and disruptive forces in marketing as an industry in a long time, probably the most impactful since the mass adoption of the internet.

It will continue to evolve and change search as a practice for years to come.

While brands are working on AI adoption at an organizational level, the benefits and applications to most departments within the business are clear to the C-level.

When it comes to SEO, the opportunities and threats are less clear.

As an industry, we’re still deliberating how we classify ChatGPT (and other large language model tools). Are they search engines or discovery engines?

If we don’t have clear definitions of what is happening in the industry, we can’t expect our C-level stakeholders to understand – and this can breed uncertainty.

There are enough headlines surrounding AI from various mainstream publications that the perception of, and application capabilities of AI can vary greatly depending on your field of view.

To best explain and communicate how worried – or excited – your C-suite stakeholders need to be with the impact of AI on your SEO program, you need to be able to make it relatable.

This often comes down to the potential impact on website traffic (all channels), and the measurable impact on conversions (and the ROI/CPA stemming from specific channels). But also includes how it affects your audience.

AI Adoption In Your Audience

Before, we look at how to assess your SEO opportunities and threats with AI. A key part of this is understanding how your target markets perceive AI, their planning on adopting AI in their daily lives, and what opportunities AI has to enter their lives seamlessly.

Depending on your target markets, you’ll find active AI adoption rates differ.

Adopting any new technology relies on its ability to provide value by either enhancing user experience or solving a disutility. To do this, it has to achieve ARC:

Accessibility.
Reliability.
Cost.

Only by achieving these three things while providing value can a new technology gain mass market adoption.

Different demographics are adopting AI at different rates.

Looking at consumer surveys and reports, we see Gen Z and Gen Alpha embracing AI and actively utilizing platforms other than Google as the first port of call to discover information and content.

This is supported by a recent data release by Ofcom (Online Nation 2024 Report), which identified that those aged 18-24 are the highest adopters of AI technologies.

It is reported that 1 in 4 (27%) uses ChatGPT at least monthly, with 1 in 3 of this age segment using it.

Another notable data point from this report is that men are more likely to adopt AI, with 50% reporting using AI tools, compared to only 33% of women.

Adoption rates don’t tell the full story.

Threads reached 100 million users in less than a week, but quality issues have seen demand and daily active users (DAU) drop substantially.

A key part factor in this has been Threads’ algorithm capabilities to return satisfying and relevant content to users, and this same challenge is facing LLM tools such as ChatGPT.

The Ofcom Online Nation 2024 Report found that only 1 in 5 (18%) of adults found the information on ChatGPT to be reliable, but this rose to 33% among young adults.

Passive AI Adoption

ChatGPT and the other LLM tools fall under the banner of active AI adoption. Using these tools is a conscious adoption of AI, as you don’t accidentally log in to Claude or Perplexity.

In my opinion, the greater “softening” of the mass market and normalization of LLM tools and AI in the mainstream will come from the passive AI touchpoints that our target audiences are subjected to.

These include things like:

The appearance of Google AI Overviews and Bing Generative Search frequently appearing as part of routine internet usage.
Additional prompts to use AI tools such as virtual try-ons.
Phone manufacturers promoting AI-driven features such as Gemini and Circle Search as product unique selling points (USPs).
Apple’s integration of Intelligence.
Spotify’s AI DJ.
Meta AI’s integration into their suite of products.

These non-invasive touchpoints will, over time, soften attitudes towards AI and build trust, leading to increased adoption elsewhere.

This means that we need to understand where our users spend their time, and the potential exposure to passive AI interactions.

To do this, we need to understand which channels have higher than average term usage, and this helps us identify which platforms our audience over-indexes on.

For example, the topic of “eyeliner” over-indexes on Facebook and Instagram and under-indexes on Reddit and LinkedIn, which is the same channel indexing patterns as “Adidas Samba”.

Understanding which channels your audience is actively engaging with also aids buy-in from other internal marketers and agencies handling the non-SEO channels, and reaches closer to a collaborative integrated communications strategy.

This is a great opportunity to get buy-in from other marketing stakeholders, but if your success metrics are bound to metrics such as directly attributable organic traffic – this is a threat.

Adapting To AI-Origin Users

AI introduces opportunities, but also raises the bar for channel performance.

As mentioned earlier in the article, this means a better understanding of your product and which channels are the right fit, in addition to visibility in organic search.

One way we can do this, in addition to data from third-party tools, is to utilize the Kano Model. The Kano model is a framework traditionally used to categorize and prioritize customer needs and can be effectively applied to assess and enhance product-channel fit in marketing.

For marketing product-channel fit, think of the channel (e.g., email, social media, SEO, paid ads) as a “feature” and map how well it satisfies user expectations.

To adapt and reach our target audiences as they adopt AI tools, or AI product features in existing tools, we as marketers need to:

Shift from Broad Channels to Intent-Driven Channels: Focus on channels that align with customer intent, as AI improves its ability to match consumer needs in real-time.
Embrace AI-Native Platforms: Platforms like ChatGPT or AI-powered discovery engines require new strategies for delivering benefit-focused, concise, and conversational content.

Monitoring AI Traffic

Another key part of communicating your exposure to LLMs and AI chatbots is the accurate tracking of AI traffic to your website.

This also informs your marketing strategies and adaptation to cater to shifting user behaviors within your target audience.

Traffic from LLMs can be easily monitored through Google Analytics 4 Explore reports, or through Google Looker Studio.

The method for segmenting data depends on the objective, who needs data access, and to what depth.

Tracking LLM traffic via Looker Studio. Image from author, December 2024

GA4 Explore Reports are effective for routine updates, such as monthly reporting, and provide clients with direct access to data through their Google Analytics accounts.

Looker Studio offers two distinct approaches. The first focuses on detailed, client-specific reports that track granular data, such as landing pages and events triggered by LLM traffic, tailored to individual needs.

The second is a quick overview dashboard, which is less customized but allows easy navigation through GA4 accounts, making it useful for ad hoc analysis and monitoring.

Marketers Must Adapt And Align

AI is transforming marketing, offering new opportunities and challenges across all marketing channels. To adapt, marketers must align strategies with evolving user behaviors and clearly communicate AI’s impact on traffic, conversions, and audience engagement to the C-suite and wider business stakeholders.

By focusing on clear communication, measurement and simple visualizations, and strategic adaptation of AI technologies into existing processes, brands can successfully navigate and take advantage of opportunities presented by AI while transforming and future-proofing the marketing function.

More Resources: