If AI can amplify every employee’s reach ten-fold, how ready is your organization to harness that network effect?
We are here at Forrester CX in Nashville, TN and hearing all about the latest insights and ideas for brands to create better experiences for their customers.
Agility isn’t about adding more tech; it’s about multiplying human impact.
Today we’re exploring the network effect of AI and how it helps employees create powerful experiences with Jay Pattisall, VP & Principal Analyst at Forrester.
About Jay Pattisall
Jay’s research focuses on marketing services (creative, media, digital, in-house agencies); AI marketing (applications of generative and predictive AI to media and content); and genAI for visual content technologies. Jay helps CMOs and business leaders make sense of the complex and ever-changing marketing services landscape as it embraces AI and automation technologies as part of media management, creative services, and the future of agencies.
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Transcript
Greg Kihlstrom (00:00)
If AI can amplify every employee’s reach tenfold, how ready is your organization to harness that network effect? We’re here at Forrester CX in Nashville, Tennessee, and hearing all about the latest insights and ideas for brands to create better experiences for their customers. Agility isn’t about simply adding more tech to solve challenges. It’s about multiplying human impact to find new opportunities. Today, we’re exploring the network effect of AI and how it helps employees create powerful experiences with Jay Pattisall, VP and Principal Analyst at Forrester. Jay, welcome to the show.
Jay Pattisall (00:31)
Thanks, Greg, it’s great to be here with you.
Greg Kihlstrom (00:32)
Yeah, looking forward to talking about this with you and a great job yesterday with your talk. I’ve really enjoyed it. Thank you. Before we dive in though and share a little bit of takeaways from that, why don’t we start with you giving a little background on yourself and your focus at Forrester. Sure.
Jay Pattisall (00:46)
I am a vice president principal analyst at Forrester and my responsibility is our marketing services coverage. I sit on a team that serves the B2C marketing executive and my responsibility is to cover marketing services and help brands make the right selection and considerations to take into the right consideration for their partnerships with agencies or systems integration companies or consultancies.
We also work for the providers, the agencies, SIs that I just described, and we help them understand the needs of the marketer and how they can best position and develop their propositions and their offerings to meet those needs. And of course, we also work with ad tech and martech companies and we help them to understand just the ecosystem of marketer and marketing partner and how the technology can best serve that.
So that’s my role prior to coming to Forrester. I was agency side for a number of years as a strategist and planner.
Greg Kihlstrom (01:48)
Nice, great. Yeah, definitely. a lot of, as you described, lot of dots to connect there. So it’s definitely good to have somebody that understands all of those pieces. Before we get into talking about this network effect concept, just wanted to get your, you we’re last day of Forrester CX Summit here in Nashville. What’s been, you know, something that’s been particularly insightful so far at the conference?
Jay Pattisall (02:11)
Wow, I mean, I think a number of things. First of all, I really appreciated my colleague Angelina Genis’ point of view about it’s not about the actual journey map, it’s about the understanding of the customer and being able to serve their needs. And I think that’s a great point for us to focus on. Shar van Boskirk, another one of my colleagues made a similar point in that the goal is not about customer obsession, but rather the actions that you take to serve your customers’ needs. And I think this is a really, it’s a great point that they’re both making in different ways in their subject matter domain about customer focus is the point, not the actions that we take or the constructs that we create. it’s really, stay focused on the goal. And the goal is serving your customers the best way that you can.
Greg Kihlstrom (03:04)
Yeah, yeah, I love that. And that’s actually a great segue into talking about this topic. you know, a lot of the talk about AI in a lot of companies is framed as cost efficiency, know, productivity, things like that. And certainly there’s lots of that to be had by by automating and things. But what mindset shift is required to move kind of beyond that from only thinking about efficiency and cost effectiveness to elevating employee experience and customer experience?
Jay Pattisall (03:34)
Yeah,
that’s a great question. As I was saying in part of my keynote and in the research that backs this keynote up, that efficiency is a tremendous focus of marketing organizations and brands and companies across the board. The question that I get most frequently is how can we use AI to save and cut costs? And it’s a legitimate question to ask because there are efficiencies to be had. we see that there are other things that can also be delivered in addition to just overall efficiency or cost efficiency or cost reduction. We see that the productivity jumps significantly with the amount of time that’s saved. And in that time that is saved, you can do more. And so it really becomes a question back to brands and back to companies, what do you want to do with the time and the value that is produced with increased productivity? Do you want to capture that time saved and just move to market faster? Do you want to reallocate that time to produce more content and reach audiences or reach segments or reach channels that you simply couldn’t afford to place content in prior? I think that’s one of the steps that I think that is necessary for brands to think through. And then of course, the performance of it all, know, the measurement of the work that’s produced and its impact in the marketplace. so we see increasingly, we’re seeing more examples of yes, cheaper, but faster from productivity and better from performance. And the better comes
from being able to create content that is more relevant and appropriate to the customers and the audiences. Back to what I was saying before, stay focused on serving your customers. And when you stay focused on serving your customers best, it’s not about necessarily reducing your costs, but improving their experience with more relevant and tailored and personalized, may it be content or communication or advertising or overall marketing experiences and serving them things that are relevant to the region that they live in, down to the zip code of the neighborhood that’s relevant to the context of their lives based upon the data and the signals that you acquire. that type of value, this stair-step value of saving some through efficiency, improving
overall speed and the volume of work and then producing better, more relevant work, I think is a great stair step to like a triad of value that AI can help deliver for marketers. And so, as I said, we used to look at cheaper, faster, better as pick two because you can’t do all three. We’re starting to see the opportunity to, with time and with the right maturity to be able to achieve all three.
Greg Kihlstrom (06:28)
Yeah, I mean, think that that was something that really stood out to me from your talk was just that that paradigm shift because we do we take that, you know, cheap, fast or good thing for granted. It’s it’s the accepted wisdom, so to speak, that, you know, has been around at least for a couple of decades, at least in my career. But to be able to turn that that paradigm around and be able to have all three again, you know, there’s things required to be able to do that. But the fact that all three are possible through this network effect. How do you explain that to the execs, the stakeholders, the potential there when, again, they’re probably stuck in a paradigm as well. They’re probably thinking, given whatever’s going on with the economy or this or that, they’re thinking about cost cutting and savings. How do you make that case to an exec of, no, we can actually have it all?
Jay Pattisall (07:19)
Yeah, I think that that case is made through at least as it pertains to the network effect of AI. It’s made through improving and transforming your workflows internally so that your talent and your employees can deliver the value and the brand promise, if you will, to your customers and to do it more efficiently and to scale that promise, know, and to scale the brand. So we’re really deliberate in the way that we think about customer versus consumer or prospect. Your customers are your most valuable addressable audience, but it’s not your full addressable audience. AI can help you scale and create the breadth that you need to address a majority of your addressable audiences, both customers and prospects. And the value that’s
created from that in the form of efficiency, but in the form of scale and being able to do more and to be able to address them in a more relevant and accurate manner creates the business return that’s necessary. And you can tie that return from the work that’s produced right back to your efforts to change and improve the workflow for your employees.
So, know, employees create value, value creates happy customers and more customers. And so that’s the thinking.
Greg Kihlstrom (08:45)
And so employees are often, some of their time is freed up or some of those repetitive tasks that no one wants to do are automated and things. There’s also, when we’re talking about this network effect, at least in my mind, this is tying perhaps teams together that aren’t used to working together or don’t, they may know each other, but in a large enough org, they may never.
Never, you know, an email team and a social media team may not ever even talk with each other. How does how does this work when, you know, it’s at the talent level, perhaps it’s introducing the opportunity for new skills and even new roles. And then at the organizational level, it’s how do we do we break down silos like the cliche always says, or do we just find new ways of mapping those are all of the above?
Jay Pattisall (09:31)
think there’s a little bit of all of the above involved in this, but it’s definitely breaking down the silos. The organizational silos with distinct objectives and budgets and leaders and teams creates a scenario where the experiences that you’re creating for your customers and consumers start to feel those silos. And so…
From an organizational standpoint, I mean, we’re talking about the way that the company works and we’re talking about changing the way that the company works, but that helps improve the overall experience. So it’s definitely about removing some of the silos, but it’s also about accessing ideas and accessing expertise that you wouldn’t normally have at your disposal, but you suddenly do because…you can in a large organization, you can tap into the expertise that exists in other parts of the company or other parts of the world for that matter. And so a little bit of it is kind of like getting out of your own box, so to speak, and bringing in a diversity of ideas from other experts inside the company that are now accessible through a network, an AI enabled human network.
and the technology facilitates that connection and it creates exposure to things that you haven’t thought of or questions that just weren’t asked by the core team or a pushback on an idea and assumption that just helps things get better. And this can happen quickly now because technology is instantaneous and except for the know, the time zones, of course, that may delay it. We’re talking about pretty immediate response. breaking the silos, creating a diversity of thought, and tapping into expertise that isn’t otherwise immediately available to you is, I think, of the, is kind of the elements that help comprise the benefit of a network effect.
Greg Kihlstrom (11:31)
Yeah, yeah. So for those leaders that are maybe even think they’re a little bit further along the maturity curve, you could say, than they may even be. A lot of times, technology is thought of as the silver bullet. It’s going to solve everything. But to everything that you’re saying, it takes people and it takes ideas to create that network effect. It’s not just AI in a corner doing all the work for us. How do leaders kind of get a sense of
where they are and based on where they are, obviously there’s a set of considerations based on their stage, but how do they get a handle on where they and their teams are in the curve and try to find some ways to move forward a little bit.
Jay Pattisall (12:11)
Sure. mean, I think this goes back to the value that we were talking about a few minutes ago. And if you look at efficiency, productivity, and performance, not only as the types of value, but as almost like a maturity curve, a simple way for organizations or leaders to look at their situation is to look at what are the use cases that you’re using AI for and what is that delivering? If these are basic use cases,
that are removing things like studio or production resources out of the equation and automating that and providing you cost efficiency, I think that’s the first step. It’s the first benefit. It’s the easiest benefit to achieve, but it’s also the first step in the maturity curve, if you will. The use cases get a little bit more sophisticated when you’re pursuing productivity because
It’s assisting the way that you work. So, you know, some marketing examples, know, creating personas, helping to ideate initial concepts, helping to create storyboards in a rapid succession so that you can communicate these ideas, conducting competitive analysis to give you a sense of what strategy and messaging should be. Those types of use cases, a bit more sophisticated.
So a little further along in the maturity journey, if you will, and designed to deliver speed to market or productivity benefits of getting to an answer faster and then being able to execute that with some more scale. Then performance, think, is the next stage in that, where you’re using the systems that you’ve put into place, and your use cases are more about
personalization and scaled personalization. mean, it’s a bingo word, right, in that regard. more relevant advertising, more relevant marketing is a way to articulate personalization that’s designed to improve the response and improve the overall outcome. And this is a data exercise. This is a measurement exercise.
It’s more of a loop in terms of the use cases where you’re taking feedback and you’re understanding what impact it’s had. And that’s a more mature use case. And so to answer the question, if leaders look at the use cases and the value that they’re extracting, they’ll get a very good sense of where they are in the maturity curve. Is it early on with efficiency? Is it a little bit more advanced with productivity? Or is it more advanced with performance?
Greg Kihlstrom (14:42)
Yeah, I love that. That’s great. So then as far as measuring this, mean, obviously when we’re talking about performance, there’s marketing performance metrics and there’s various metrics that are probably already in place in the org or at least should be. Are there other ways of measuring this growth? I I love that maturity curve or journey that you described as a way of determining some of that, but.
Are there other KPIs that the leaders should be looking at in terms of growth?
Jay Pattisall (15:11)
Yeah, it’s a really great question. And the first part of the answer is at this stage, no. At this stage, we’re talking about affecting the work as we know it and the metrics as we understand them. So in my research and in my presentations, I was talking about click-through rates. click-through rate is a very conventional KPI that has been around for the better part of 20 plus years, Working on 30 years at this stage. And so we have benchmarks, of course, for click-through rates and other advertising engagement metrics, for example. And you can compare non-AI use cases and what you were seeing in terms of the KPIs with non-AI use cases versus AI use cases and directly see the contrast between the two.
Where this goes is as the consumer experience changes as a result of AI, then I think the metrics are going to have to start to change. And an example of that would be search. Like we look at traffic, directed traffic and inbound traffic as one of the metrics that’s associated with search engine optimization, SEO, SEM. As more and more answers are being given by AI on the search engine platform or new platforms like OpenAI’s chat GPT or Perplexity, then we’re going to need to shift metrics from the amount of traffic to the amount of attention could be an alternative. attention metrics are not a new thing necessarily, but that’s just one, you
available example to refer to, but I think there could be things that we haven’t even thought of yet. But it’s contingent upon the advancement of the technology and the change in consumer behavior and the consumer experience. So I think that’s more to come.
Greg Kihlstrom (17:03)
Yeah, and I mean, it seems to me like that’s one of those additive things where the old stuff isn’t going to go away. It’s like print advertising, like they said it was dead, you know, 50 years ago or whatever. you know, it’s not going anywhere. There’s just new things. You know, there’s going to be there’s shopping agents now. So like now we’re talking about all types of other types of interactions and stuff. So in other words, to me, that.
That means even more so what you’re saying. Like we’ve got to get the foundational stuff. We’ve got to get the efficiency to productivity to effectiveness because we don’t necessarily know what’s next. We just know that there will be more and the old stuff probably won’t go away, right? Yeah. Yeah. Well, Jay, thanks so much for joining today. One last question before we wrap up here. What do you do to stay agile in your role and how do you find a way to do it consistently?
Jay Pattisall (17:50)
I stay busy and I probably take on more work than I should, but I like the constant stimulation and it keeps me on my toes. able to multitask is at times a struggle, but I think it helps. While you’re working on multiple projects simultaneously, what you’re learning in one project helps inform the other.
And it also is a way to kind of keep yourself in check. you know, so multitasking some projects simultaneously is my go-to for staying agile. it works, you know, it works for me. May not work for everyone, but I’m able to manage the chaos a little bit.
