The AI Q&A Series: Victoria Samways, Marketing & Brand Manager at Major Tom Uncovers the AI-Powered Future of Digital Marketing
Welcome to the second edition of our AI Q&A series, where we continue our exploration into the dynamic world of artificial intelligence and the ever-evolving digital marketing landscape.
We are thrilled to collaborate with Victoria Samways, Marketing & Brand Manager at Major Tom, a cherished member of our agency community. Together with her, we unveil the latest insights and innovations shaping the future of digital marketing through the lens of AI.
1. How has the role of a digital marketer evolved with the integration of AI technology? What skills or knowledge areas are becoming essential for digital marketers to excel in this changing landscape?
As it turns out, AI is not drastically changing the roles and responsibilities of digital marketers, but it is evolving their processes. To use a familiar phrase, it allows them to work smarter, not harder — if they are leveraging AI correctly.
To do that, marketers are quickly becoming familiar with a variety of AI tools across just about every discipline in our industry. That includes those created specifically for generating content and images, along with tools that speed up both data collection and analysis. But whichever tools you use, the key to mastering all of this is understanding the nuances of data requests.
Marketers need to know both what to ask for and how to ask for it, ensuring that they can get the right, valuable output. That means having the insight and skills necessary to know how to phrase a request or question. You need to understand both the tool itself and your areas of expertise.
After all, it is “artificial” intelligence, not “autonomous” intelligence. You may know the old bit of computer science wisdom that garbage in = garbage out. It still holds true today.
2. “Hyper-personalization” is a term used to describe the impact of AI on delivering customized content and recommendations to individual customers. Could you elaborate on the techniques and benefits of AI-driven hyper-personalization?
For most marketers, the benefits are self-explanatory. The more something is personalized to an audience’s needs, the better the experience and outcomes they are going to have. Even before our current era of AI, customers expected brands to know and anticipate their needs as well as exceed them — and that is true whether it is with a piece of content, a product, or a service.
We already use dynamic content on websites to serve our visitors more relevant content, and those capabilities should only become even more sophisticated as time goes on. AI lets you lean into that in a big way.
The only thing to be wary of is not making the consumer feel uneasy. After all, we have all had moments where we are served an ad or piece of content that feels a little too close to the mark.
So hyper-personalization needs to be done carefully, in a way that will improve the customer experience without creeping them out. For example, use it to serve up the right content for a specific user or audience, without over-personalizing the content itself. Say, by using their personal information or highlighting their behaviours.
Also, remember that when someone receives a great, personalized experience, it sets a new benchmark for their expectations. It is crucial that brands remain competitive and at the top of their game with this for if they do not, their customer experience will quickly feel outdated and un-personalized in comparison.
3. Automation is a key feature of AI. How is marketing automation evolving with AI, and what advantages does it offer in terms of campaign management and customer interaction?
We have already seen a number of platforms, such as Salesforce and HubSpot, incorporate new AI features that help on this front. For example, the “HubSpot AI” initiative includes both new and upcoming tools like generative AI assistants for content (think email and webpage copy), automation for customer service and chat support, and analytical tools to help with lead reporting and forecasting.
This highlights one of the key ways that marketing automation is evolving. More and more, the tools and platforms marketers already use are rushing to add AI functionality directly into their services. Think Adobe Firefly, or Zoom’s new in-house meeting summary tool. For paid media buying, platforms like Google have been incorporating automation and optimization driven by machine learning for years.
Much like our client brands, these platforms have a vested interest in staying at the cutting edge of AI automation. They want to make sure that the efficiencies we expect are available through their tools. That will hopefully mean more and more of the AI benefits we have discussed become available through the familiar user experience of platforms that are already connected to your campaigns, websites, and content.
For example, what if, instead of asking ChatGPT for drafts of paid search copy, you could leverage Google’s Bard chatbot from within Google Ads itself? Expect to see more of this kind of service integration as AI technology becomes more commonplace. For now, you will need to do the legwork and learn for yourself.
Generally speaking, the more menial work that you are able to automate, the more time your team has available for strategic thinking, insights, and adjustments.
4. What are some specific AI-driven techniques that you employ to analyze your clients’ campaign performance, behavior, and market trends for better decision-making?
As we mentioned, AI and Google Ads go back for some time. Their optimization and bidding has been running on machine learning and AI for years. It allows us to analyze data much quicker than we could otherwise. We input the data, asking for it to provide key insights, and so on. Google also offers multiple bidding strategies and campaign types to better match your goals with its machine learning optimization.
5. Could you elaborate on a recent client success story where AI technology took a prominent role in achieving remarkable results?
We have been recognized as a top industry-leading agency by Google for our use of AI and machine learning since 2020 as shown in this case study. However, with where AI is today and looking outside of Google, our team is constantly finding new ways to work smarter, not harder to help improve the quality and speed of providing deliverables.
One such example was when our UX designer could not attend an in-person workshop with our client and the rest of our team. Instead of manually going through 12 hours worth of video recordings to extract the information he needed, he leveraged the tools he had to get the information in an hour. How so? With the workshop being recorded using Gong, he downloaded the entire transcript and uploaded it to ChatGPT using a temporary URL (more on that later). With the URL only live for an hour, our UX Designer began asking very pointed and probing questions in ChatGPT in order to extract the right information he was looking for.
How successful was this? When sharing his insights and solutions with the team who had attended the workshop, they agreed that these were spot on. With some innovative thinking, our UX designer managed to cut the time of a tedious task by 90%.
Yes, this is just AI being used for a small part of a project rather than a “prominent role”, but we are okay with that. A lot of small wins add up to big wins, and we know that it still takes our team of experts to create remarkable results and AI is simply their powerful sidekick.
6. Given the potential for AI to shape the future of digital marketing, what are your key considerations while incorporating AI into any marketing strategies? How did you ensure a successful implementation?
While our main questions and considerations will continue to evolve alongside the technology, they are probably a pretty recognizable list for now.
How accurate is the output of AI? What are its data sources? In other industries, older sources might still offer valuable insights, years after they are first available. In digital marketing, however, data from 2021 is already considered outdated. While some insights are timeless, pairing sound strategic thought with an old picture of the digital landscape and its tech can still lead to bad decisions. So, how are marketers asking ChatGPT for information? How are we making sure that its responses are relevant and up-to-date?
Another big consideration is how to combine AI and human intelligence. Marketers should never simply be taking AI’s output as-is without critiquing it and adding their own insights, wisdom, and empathy. This is especially true of generative AI, which might give you the broad strokes of worthwhile content, but will usually need at least some polishing from a relevant member of your team.
Of course, we cannot forget that AI has been known to exacerbate issues surrounding diversity and inclusion. There has been ample proof that AI can highlight stereotypes and repeat or amplify racist assumptions. Again, what are its sources? Does it critique the data it finds, or take it at face value? Given these questions, it is our duty to review both AI processes and outputs to ensure that we’re not undoing crucial DEI progress across the industry through a lack of proper diligence.
Then, there is security. Can any information you upload to an AI tool be tracked? Since there’s no universal answer to how different AI tools handle data security, we need to take the initiative and create processes that minimize risk and exposure. For example, when we ask AI to review documents or transcripts, we upload that content to a temporary URL that automatically gets deleted in an hour or so. This helps protect any data summarized.
Perhaps most important of all is coming to the understanding that AI is not a trend like digital glasses were. It is here, it is staying — and it is quickly evolving. Treat it like a passing fad at your peril.
Instead, knowing that it will drastically reshape the future of digital marketing, we need to consider how to use it correctly, and to what extent. That is what will keep us competitive and working efficiently.
7. Can you provide examples of AI-powered tools that you are using to streamline processes, and how do these tools improve efficiency and effectiveness?
Naturally, ChatGPT is high on the list. Whether we want to produce summaries of information, reframe and reorganize information, generate the skeleton of new content, or produce brainstorming prompts for future content, ChatGPT can significantly speed up the process — or help power through stubborn moments of writer’s block. HubSpot’s content tool (which we discussed above) provides similar benefits, as does Jasper.ai. At this stage of the game, it does not hurt to experiment with multiple AI options to understand their advantages and drawbacks relative to one another.
Adobe Firefly is another useful tool for creative ideation. Its expanding capabilities can help quickly adjust not-quite-there creative assets (changing details, smoothing over stubborn pixelation, etc.), or generate elements for different designs. Fun fact: if you are one of the millions of users pulling images from Adobe Stock, it is possible that you have already used AI-generated content without realizing it, as the platform allows for AI submissions within certain constraints.
We have already mentioned Zoom’s new summary feature, which can be helpful for producing skimmable summaries of critical meetings. After all, you will not always have time to watch a full recording to review a handful of details. This tool does come with some caveats — and definitely is not perfect — so think of it as producing a useful index to help you navigate your notes and other records, or catch information you might have otherwise missed.
SEO staple Semrush has also introduced some invaluable generative AI templates that help keep SEO top-of-mind when planning content for a site. These SEO Content templates can help you collaborate with clients when creating, say, new blog posts, and ensure that relevant keywords aren’t lost during rounds of revision.
You can read up on more marketing AI tools here.
8. Among the services you offer, in which areas do you harness AI technology’s potential the most? Could you elaborate on instances where AI has been a game-changer in enhancing the delivery and effectiveness of these services?
It is hard to overestimate AI’s impact on marketing campaigns. After all, as we have mentioned, AI and machine learning are not new in paid media. Google’s automated bidding and optimization features have been leveraged by marketers for years, and have radically changed our industry’s approach to budgeting and targeting across campaigns.
Just look at our work with Zolo, where automating keyword targeting, listing uploads, and bidding strategy using Google’s machine learning reduced cost per acquisition by 60%. Never underestimate the difference automation can make compared to manually managing your campaigns.
We have also found AI particularly useful for creative work across our services, with some qualifiers. For example, we may use AI to create or modify images. However, we have found that you still get a pretty clear feeling when something is exclusively AI-generated. We need to be mindful of that since we do not want our clients’ audiences to be unnerved by their brand. The images we use should always positively impact that relationship.
If you are using AI to create quick content with no oversight or revision, your audience may get that slight feeling of unease. Not something you want associated with a brand. Simply put, either keep that type of uncanny image away from your public-facing assets or ensure it is properly reworked by your team beforehand. If you are quickly generating mood boards or concept work earlier in a project? That’s a much better fit.
AI has also saved the team significant time when it comes to preparing SEO deliverables for website builds. On-page elements like titles, descriptions, headings, and image alt text can all be generated using your target keywords much faster than working manually.
9. What do you think about emerging “AI Automation Agencies”, are they a goldmine or another bubble that will pop soon enough?
We do not think that these agencies will pop up. More likely, they will have to evolve. Just as you have specialized marketing automation agencies and so on, AI Automation Agencies will likely still exist no matter what the technology looks like years from now. They will just adjust their focus and skillsets accordingly. However, other agencies may step up the competition — buying them up or creating in-house teams of specialists that can do similar work.
If you are evaluating whether an AI Automation Agency is worthwhile now? The main thing is to ensure that they are providing value, rather than acting as an unnecessary middle man between your team and the tools. Do they have a proven level of insight and experience? Are they filling gaps in your team’s knowledge? You should approach these questions the same way you would when vetting any agency partner.
10. What potential challenges and obstacles might arise when integrating AI into marketing campaigns, and how can agencies address these challenges effectively while leveraging AI to maintain a competitive edge in the evolving role of digital marketers?
Copyright is always something to watch out for with AI. After all, the ethical and legal boundaries surrounding generative AI, in particular, are still being drawn. Look no further than the recent high-profile lawsuit targeting ChatGPT, launched by a group of prominent authors (including Game of Thrones’ George RR Martin) and claiming that it relies on training data from copyrighted works. Since these legal boundaries are still in flux, you have to know when AI is likely to butt up against copyrighted content and avoid it accordingly.
As we mentioned above, security is also always a concern, especially if you are working with clients who rely on confidential or privileged information. For now, it is not wise to rely on these AI tools alone for data security, so you should have your own processes in place, and keep your team in the loop.
Similarly, we have already mentioned that you should have a process in place to ensure you are not undermining your DEI efforts with AI-generated racism. This is true across the board, but always be diligent. At the absolute minimum, anything produced by AI should be checked by a set of human eyes before it is published.
That segues into our next consideration. While automation and efficiency are some of the most appealing aspects of using AI tools, do not overly automate any live or public-facing work without checking it. Even if your AI output is solid 99% of the time (an optimistic figure), a prominent typo, uncanny art, or incorrect information can all undermine trust in a brand.
Similarly, do not embrace AI at the expense of your project strategy. Make sure all campaigns are tightly tied back to the brand’s goals, tone of voice, purpose, audience, and so on. This is where knowing how to write the correct prompt is critical. No matter how quickly you are generating content, if it does not use the research and insights you have built about a brand and its audience, it is missing value.
Most importantly, continue to learn and share within your agency. As with any new technology, there are going to be both exciting wins and frustrating misses. Share both, and your full team can learn and improve together. You should also have guidelines in place when using AI for campaigns. No one wants that painful AI learning experience to happen on a high-profile project.
The point of staying competitive by using AI is to speed up your data analysis and content creation. But it will always be the skills and ideation of marketers that propel a business forward. Embrace AI, but do not abandon your team’s expertise and insight.
11. How will companies address data security and privacy concerns in the near future? What strategies and best practices can be adopted to ensure ethical AI usage?
As mentioned earlier, you should always be aware of the possibility that any information you upload may be tracked — and put the appropriate processes in place to avoid exposure.
In terms of ethical usage, we have already recommended avoiding AI in cases where you may unintentionally rely on or parrot copyrighted material. Similarly, using generative AI as one step in the process of content creation, but not for final content, ensures that you are not unintentionally reusing other work.
When the state of AI is changing constantly, it is also important that you learn and evolve your approach accordingly. Continue to stay up to date with the latest news and insights regarding AI security and privacy, as today’s best practice might be hopelessly out of date tomorrow.