Agility today means adapting your marketing playbook at the speed of AI—experimenting fast, learning faster, and never assuming yesterday’s tech advantage still applies.
Today we’re going to talk about how B2B marketers should be thinking about AI in the months ahead—and how to know if you’re already behind.
To help me discuss this, I’d like to welcome Victoria Blackwell, Sr. Program Manager of Research Insights at G2.
About Victoria Blackwell
Victoria Blackwell is a Sr. Program Manager for Research Insights at G2, specializing in marketing and digital advertising software. She brings a strategic mindset, analytical depth, and a strong track record of cross-functional leadership to the B2B tech space. Victoria began her career on Capitol Hill before transitioning into the private sector, where she developed expertise in program management and stakeholder engagement. Her journey took her through high-growth B2C startups and global app platforms in Chicago and London, where she led innovative brand and marketing initiatives. Today, she leverages her cross-industry experience to deliver strategic insights and thought leadership that help shape the future of marketing technology. RESOURCES G2: https://www.g2.com https://www.g2.com
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Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com
Transcript
Greg Kihlstrom (00:00)
Agility today means adapting your marketing playbook at the speed of AI, experimenting fast, learning faster, and never assuming yesterday’s tech advantage still applies. Today we’re going to talk about how B2B marketers should be thinking about AI in the months ahead and how to know if you’re already behind. To help me discuss this, I’d like to welcome Victoria Blackwell, Senior Program Manager of Research Insights at G2. Victoria, welcome to the show.
Victoria Blackwell (00:25)
Hi, Greg. Thrilled to be here. So happy to be on.
Greg Kihlstrom (00:28)
Yeah, looking forward to talking about this with you. Before we dive in, though, why don’t we start with a little background on yourself and your role at G2?
Victoria Blackwell (00:36)
Yes, of course. So I am our senior program manager for our research insights team here at G2. And I specialize in marketing and digital advertising as like an industry. So I’m a former practitioner in brand marketing for B2C brands. Then I transitioned to G2 and was immersed in all things B2B. So my goal kind of having those two parts of my brain and being a practitioner myself is to kind of bring this strategic mindset, analytical depth, and kind of maintain like a strong track record of not only cross-functional leadership, but publication.
to not only kind of entice, but to also enjoy for fellow marketers to make sure that getting the information out there is as easy as possible without it being like a thousand pages, a bunch of graphs, just really adding kind of context and color to the industry.
Greg Kihlstrom (01:20)
Great, great. So yeah, let’s start by talking about AI driven content. you know, lots of people talking about it, writing about it, making videos about it. They’re making content about content. so, you know, let’s talk about that and as well as personalization. you know, I kind of say like AI is kind of the loudest or content is the loudest AI use case.
You cite Jasper’s data showing 57 % of marketers use generative AI for content creation. I feel like that’s low, but
Victoria Blackwell (01:54)
You know, right? I thought so too when I was first researching. I was like, there’s no way maybe someone who’s bold enough to admit it.
Greg Kihlstrom (02:01)
Yeah, I think there’s a lot of people that, yeah, may not be 100%. And they use 55 % or 55 % of them use AI for idea generation, but, you know, warn that authenticity can suffer. So how can B2B teams keep scale from sounding synthetic?
Victoria Blackwell (02:20)
Sure, and I think this is a really common problem when it comes to especially like novice users of AI content creation. But I think to simplify it, it’s very much in a single phrase that you’ve got to use AI to amplify human creativity, not replace it. And I think that is contextual in many ways. I think when it first came out, it was very like, this is going to take my job. Like, this is going to replace me. Like, copywriters galore were, this is it. This is how I go. But.
It’s really not. And I think that when you think about what AI content creation really is, you have to let AI handle repetitive and generate drafts. So first tasks, getting just that idea generation, getting it out there. And while people shape, tone, context, and emotional nuance, that’s something that AI, crossed, will hopefully never be able to do as well as a human.
And for right now, ideally, when we talk about human creativity, that is what brings life to a brand. That’s what brings life to text and that’s what brings life to content. So kind of when we talk about like tone and authenticity and all of these different aspects of content creation, that is something that AI will never be able to kind of match at a human level. Cause it’s just, you can tell nine times out of 10, like we’re even seeing kind of even the content creation like video to this day, like on reels, on TikTok.
it immediately you see in the comments, you’re like AI, like you didn’t get me this time. It’s like that can also translate into B2B as well. And like when something doesn’t feel authentic, your customer, your potential customer, they know. And kind of with that like focus on personalization, it really feels to not only just not being generic, but it’s tailored and it creates real and very, I think, genuine interaction.
Greg Kihlstrom (04:06)
Yeah, well, and to that end, a recent report from G2 ⁓ predicts that adopters of AI-driven personalization will see a 50 % jump in B2B buyer engagement. So real, tangible engagement. ⁓ What are some practical moves that marketers can make to move beyond? ⁓
There’s personalization that’s like, call it substitution. It’s like, hi, Greg, you know, your offer or whatever, but like to move beyond that kind of substitution to real personalization.
Victoria Blackwell (04:41)
Totally. And I think that this is something when I initially made that prediction in my report, it was a bit of a shock and stun. think, well, honestly, all three predictions that I made in my report, my team was kind of like, what? What is this? Are you sure? I was like, well, that’s a beautiful prediction. Like, you know, we’re reading the data. We’re looking to see where it makes sense. And I feel like, especially with AI-driven personalization, all of these kind of like…
I call them like sparkles basically of like, we could like, that looks good. Or like, like this looks nice. And to be kind of like practical when it comes to making this personalization go beyond the high first name, I would say probably my first one would be to kind of tap into your signals, you know, like using behavioral and intent to like tailor messaging based on what buyers are actually like interested in instead of like just making content to make content is probably one of the worst ways of time.
and your customer won’t have any value in it. So when they like the content, they engage with it. And when they visit pages and when all of these little sparkles of data and sparkles of real-time view of your customer, that needs to be not only timely but relevant. And then the second I would say is probably to personalize the journey, not just the message. And I think that that’s sometimes where it can get lost, where it’s like, OK, well,
How do I look at the full journey and how can I make it personalized to every single customer who walks in the door? And you can kind of do that by adjusting your channels, timing, offers, based on each kind of accounts, like role, stage, pain point. That’s a lot of information that you can really use to help craft something really incredible. And this just creates a smarter and more human experience that goes kind of far deeper than just knowing someone’s name.
Greg Kihlstrom (06:27)
Yeah, yeah. And to that point, you can send the personalized message to someone at the wrong time. Absolutely. You know, who cares that it was personalized, right? If it’s not hitting them on the right channel at the right time and stuff. Absolutely. Yeah. So, and you mentioned, you know, alleviating some of those pain points. And let’s talk about analytics as endpoint prevention here. Absolutely.
And that’s another thing from the report, know, framing analytics as the difference between reacting to preventing churn. so the report states SAS firms with 100 % net retention grow 43.6 % annually versus 13.1 % when retention slips below 60%.
What are some of the early warning metrics that marketers should be tracking to spot turn risk before it bites?
Victoria Blackwell (07:26)
plain and simple engagement, engagement across the board. Like this is, I would say, often the earliest and strongest indicator and just kind of like looking out for like drop-offs, like declining, like open rates or content interactions, site visits, any changes in kind of like product, like patterns or like engagement patterns, because patterns are probably your best indicator of what is to come as well as how to adapt. So,
kind of like understanding those like usage patterns, sentiment shifts in feedback, that’s a really big one as well. And we see that a lot kind of like in my days in like G2 truly, when you kind of really look into a product profile and you see kind of either the avalanche of review sentiment change or really like the buildup of review sentiment change. Like it really does create a very strong indicator of how people are perceiving.
that perception is something that you can’t really get from a lot of analytics right as they come in. It’s really like live feedback, you know? So I would say those are definitely some of the early warning signs of churn, and just kind of watching your engagement on every channel. That paints a picture, and that picture really is a pattern.
Greg Kihlstrom (08:41)
Well, and I think that’s also an area where AI, as opposed to just, you know, a human looking at charts all day, like AI can really play a strong role here, right? are so many things that you could look at as far as trends go, or, you know, there’s just too much for a human to do themselves to look at. Yeah.
Victoria Blackwell (09:00)
Absolutely.
Yeah. And it’s just crazy because you have to be so reliant, I think, on so many channels. It can be overwhelming. And that really is where that AI can come in and be like, if you put in raw data to an AI tool and you’re like, hey, listen, need, what are some patterns that you’re seeing from this? That’s using AI for pain point prevention. It can be as simple as that.
Greg Kihlstrom (09:23)
Yeah, definitely. so this works best when everything’s seamless and connected and, you know, there’s no silos and all of those things. But as we all know, and probably most of us have at least have experienced, there are a lot of not only we talk often about team silos that, one person doesn’t talk to the other or whatever, but data silos are real and also
just as, you know, can prevent some of the stuff from being done as well as it could, as well as just some teams, you know, from a digital or data maturity standpoint, you know, some teams being a little bit ahead of other areas. ⁓ How do you ⁓ do something like piloting predictive analytics without waiting for that ideal perfect scenario where everybody’s on the same page and singing kumbaya and all that stuff?
Victoria Blackwell (10:16)
Yeah. ⁓ so I will say this. I feel like there is no kind of perfect data area unless it has been from immediate adoption when the company was founded. So like, don’t feel bad everyone. This is like a very common problem, very, it’s which is why tools are being created to help solve it. So you don’t really kind of need this like perfect data lake, if you will, like, you know, like a single silo right from the get, but
If you want to start kind of like piloting predictive analytics, you just have to start with the data you trust. So that is kind of like one of my first and best like use cases for it. It’s like, what data do you rely on? What data has proven true? What data do you feel has a high impact of use cases? Like if you’re identifying at-risk accounts or like surfacing likely buyers and you apply like a simple predictive model or a scoring system to it.
Based on your existing engagement signals, you’ll be able to find kind of like what makes the most sense to make and continue pilot programs off of it. And a lot of this data can be different for everyone. So there isn’t one single source of truth. I think that you really have to look at where it makes the most sense for your team, your objective, what you’re trying to accomplish from a product perspective. It could be a variety of different things, but whatever data that you find, not only most like
It’s really truly that you trust the most, but the most accurate in what you’re trying to achieve, that is probably where I would say that you can lose and have a really solid predictive analytics use case without kind of just waiting for the silos to merge.
Greg Kihlstrom (11:54)
Yeah, yeah, because that’s, you know, hopefully everybody’s working on that, it’s, it’s, it’s always a work in progress even when it’s being done well absolutely. really is. And that’s why I said that in the beginning, because just take a breather and take that load off because you are not alone. This is a very common problem. it’s something that I know I’m sure engineers are up at night thinking about it. So don’t worry.
Greg Kihlstrom (12:21)
Yeah.
Definitely. Well, and I think that’s a good segue to the next thing I wanted to talk about and certainly ⁓ a topic near and dear to my heart, the marketing operations part of this and how automation plays there as well. And certainly, think marketers and marketers aren’t alone, marketers look at AI as a great way to automate and thus create efficiencies. And you’ve argued that know, aggressive adopters of AI in these areas can cut marketing operating costs by 30 % through AI powered automation. I completely agree there. For a resource strap team, where are some of the highest impact areas where automation can prove some quick ROI?
Victoria Blackwell (13:10)
Okay, well have having been on many resource strap teams Over the course of my know right? over the course of my career I came up in my marketing career came up in startups and I Live and breathe by that I feel like if you want to be the scrappiest marketer out there like you got to start with some startups and I think that it proves very quickly what works what doesn’t so when you have like and you’re wearing like 17 different hats so for like resource strap teams, would say
kind of like highest impact automation, like lead, nurture, and follow up workflows. Like truly like automating responses to key triggers, like content downloads, demo requests, page visits, like that saves times, but also keeps like leads warm and insurance, like nobody is kind of like left in the dust, which is something I think when I think just starting a new business, engaging with new business, or just trying to like…meet that retention growth, all of these things. It doesn’t matter what level you’re at or what your business goals are. It’s not only relevant, but it’s key to kind of like really just also from a data perspective, like you got to see what works, you got to see what’s resonating.
Greg Kihlstrom (14:21)
Yeah. Yeah. And mean, it’s kind of just leaving money on the table if you don’t. And maybe, you know, to that example, I mean, you know, I’ve, I’ve worked everywhere from fortune fifties to startups as well. You know, you may hire us an enterprise sales team to follow up and do the white glove service or whatever at a, the enterprise level, but a startup can set automation and do lot of this stuff in a really meaningful way.
Victoria Blackwell (14:24)
Exactly, yeah.
For sure. it kind of like, whenever you are thinking about automation with AI, I think it is a little scary because like you have to like really take the time to set up these workflows. But it really is like no risk, no reward, like in these cases, because AI is truly meant to be a help and not a hindrance, especially when it comes to like automating tasks and like really kind of like setting the scene of what you want it to do and how you can help it learn to become something so
like truly like sometimes life changing for some cases, like it creates just the opportunity to do more with less. And that I think is why we’re going to see this like for aggressive users, at least like an aggressive adopters, this huge just like operating cost save because it’s, really is, I think something I would probably say in the next six months, I would encourage everyone to really take a deep dive at where they could implement it because it really is like such a lifesaver.
Greg Kihlstrom (15:45)
Yeah, yeah. Salesforce found that 39 % of marketers don’t know how to use Gen.ai safely and 43 % don’t know how to extract value. It seems like with all the content being created to our earlier point, how can you not like at least have a vague notion of how to extract value, but it is what it is. But from, you know, from the safety standpoint, what guardrails, you know, it could be
Victoria Blackwell (16:05)
Yeah.
Greg Kihlstrom (16:12)
process policy training, all of the above. What have you seen that works to boost some of the confidence in using these tools in meaningful ways while mitigating risk?
Victoria Blackwell (16:24)
Yeah, for sure. So I think with AI being this brave new world, right, I think you kind of have to think of these as not only like continuous education, but I think like cautious approach as well. So I would say for larger companies, especially clear usage policies, like define where and how AI can be applied in what context, what you know, is maybe crossing a line, what is unethical, like all of those things play a really big part into these usage policies, number one.
Number two, would say human in the loop review processes. Like AI can’t just be like left alone. it’s, you got to think about it like a toddler at the beach. can’t be like, let them walk into the ocean, you know? Like you gotta be like making like sure you have like a very like human and watchful eye on it. Like it has to very much be like oversight in a way that isn’t, you know, too daunting, but especially for anything that’s customer facing content, messaging, all of that fun stuff.
And then I would say the third is probably regular team training, regular team updates, kind of focused on prompt best practices or data ethics. And especially when it comes to like content or messaging brand voice alignment. This is something that can get a little tricky. And I talk about this in kind of the first part of my report in our first focus area around content creation that no matter what tool you use, no matter what kind of makes like the most impact in terms of efficiency, if your brand, your voice, your messaging is skewed.
and you’re using AI, that’s one of the first indicators that you are untrustworthy. As a company, as a business, as a brand, whatever it may be. So having these three little pieces in place to make sure that AI can not only boost that confidence, but also mitigate that risk is going to be crucial.
Greg Kihlstrom (18:11)
Yeah. So last topic I want to talk about with you, something I’m watching pretty closely myself and is search engine optimization is, you know, it’s been a thing for decades and now we’ve got AI and it’s changing things, right? So you’ve noted that, you know, traditional SEO rules don’t map clearly to AI answer engines. How should B2B brands be thinking about
discoverability and things like that when it’s not just the Google search spiders and stuff like that that are crawling the web anymore.
Victoria Blackwell (18:49)
Yeah, so I think this is something that is not only going to be changing the game for 2025, but just years beyond. Like the evolution in it has been so quick in a sense that I don’t think that there was preparation on like the business’s end to be like, oh my God, like, well, how do I become like searchable? Because I think it was such like an idea for so long and the use cases that were more like public and national.
where kids using it to like write papers or in some of the more heinous cases, like doctors using it to like take notes and you’re like, my God, like this will never touch my area of business. Like we’re here, like this is it. So I think that one of the big pieces, like when it comes for like, especially B2B brands, when like we think discoverability and when we rethink that shift from traditional SEO.
to AI optimization, I think the focus on creating really high quality, structured and trustworthy content that LLMs can easily interpret in site, that is huge. When I’m looking for a specific something, I don’t go to Google anymore, I go to chat. And that is something that I think is so relevant and it could be truly anything. I live in New York City, so I very much don’t like…
If I need something or if I’m looking for a restaurant or a place like I had to get a pair of shoes fixed, I use chat for that. Like the application is above and beyond just like single like simplified searches. It’s for everything. And when I was looking for a couple, actually I had a girlfriend who, I have a G2 user, she uses the compare and contrast of G2’s compare pages with chat’s findings.
To see kind of like where and how like that she literally I think just bought a for her company. She’s like she’s in social media. She just bought a social media tool like a software tool to kind of like help like amplify like brand presence and brand Intel and she used chat and g2 to figure that out and she didn’t even she didn’t even tell me until after she was like my god by the way I used you guys the other day but like that is truly like a buyer taking a journey through using an LLM
where they would have otherwise used traditional SEO, which is crazy. I think if you’re a business trying to figure out how you can do this, I think if you double down on just clear, authoritative, semantic relevance, that’s the other thing too. And having that consistent brand presence across every piece of the internet is what’s going to set you apart when it comes to LLM search.
Greg Kihlstrom (21:34)
Yeah. Yeah. Yeah. I mean, it’s it’s one of those things where it was hard to imagine something supplanting search, right? Like, you know, let’s say, mean, it was like what I mean, Google is a verb and ⁓ a name, right? So but now it’s changed. I mean, still at the end of the day, mean, good content is good content, right? I mean, what I guess what’s what’s what should be the same that
Victoria Blackwell (21:43)
I know, right?
Greg Kihlstrom (22:00)
You in in this scenario, I mean, you know, you talked about some of the differences, but you know what? What should brand still keep doing? I guess.
Victoria Blackwell (22:07)
I think you have to have a true knowledge of your brand value and how you come across in messaging. When I first started at G2, I was doing a lot of product additions, basically. Every single product that comes through on G2 that’s submitted is checked by a human. Because we want to make sure that there’s integrity behind the products that are going on our site. And you would not believe some of the product links and websites.
that I would see that would have no clear brand messaging whatsoever, where I would have to dig deep and Google and research these companies that had no clear brand messaging, but their site looked like something that they had created with a developer. So it’s like, only really keep up the facade for so long, other than like, well, it looks good, so I must trust them. No, it’s beyond that. Brands who have longevity, brands who have really solid brand integrity from
literally like toe to tip, like can really like understand why it’s so important to have these like really incredible and solid like messaging pieces that tell you what you do, how you can help, what’s like the best way to use me, how can, how much am I, like all of these different things that I think a lot of people don’t really think about when they’re creating a business from like behind like a screen. And that I think is like,
some of the best and most genuine ways to keep like longevity in success for a brand, for a business. And you can see that with like Salesforce, you know exactly what they do. Like, you know, that’s like a legacy software brand, Microsoft, you know what they do. Like there’s very much brand trust behind being as clear as possible.
Greg Kihlstrom (23:53)
Yeah, yeah. Love it. Well, Victoria, thanks so much for joining today. One last question for you before we wrap up here. I like to ask everybody, what do you do to stay agile in your role and how do you find a way to do it consistently?
Victoria Blackwell (24:05)
Oof. Agility, one of my favorite words. literally on my, one of my first tech resumes, I described myself as that in a, in a, in my like opening a paragraph of like who and what I’m about. And I had one recruiter, she was like, ⁓ my gosh, agility. I never thought that would be a tool that like, I could like rely on for someone. I was like, hell yeah, it is. So I would say probably, I think just always being like a constant student.
That is something like you will never know everything. You will not always be right. You will never, like I think, sometimes not know the answer. Like all of those things, I think like having that forever student mindset and the humility to know that you’re always going to be a student, I think is what keeps like people agile. And especially for me, I want to kind of just very much, I know this sounds so lame, but it’s very much like a student of like life is probably one of the best ways because in order to really get to know people and brands and messaging and what resonates, what doesn’t, you just gotta be out there. You gotta be learning, reading, listening, all of these different things. And I think one of the ways that I do it consistently is that I really do carve out the time to make sure that I do do that and I’m not just focused on a single sector or a single area of interest. That I think is probably what has made me most agile and definitely helped me be consistent doing it.
