Today on the Demand Gen Pod, Episode 25, The podcast episode delves into the impact AI has on marketing and sales alignment, emphasizing the benefits of integrating AI for improved efficiency and personalization. It also raises challenges, including ethical considerations and the need to verify accuracy in AI-generated work. Leveraging AI for lead generation, personalization, and enhancing collaboration between teams is highlighted, along with the importance of discerning analysis insights while maintaining vigilance on data quality.
Ethical aspects such as transparency, consent, and compliance with regulations like GDPR are also discussed concerning the use of AI. The discussion underscores the significance of training in AI skills and knowledge to effectively leverage its potential. By considering AI for lead generation, personalization, and facilitating teamwork, the conversation points out the value of ethical practices and rigorous data quality checks to optimize the benefits of AI implementation.
In wrapping up, the conversation stresses the importance of staying vigilant about data quality and ethical considerations when using AI for marketing and sales alignment. Emphasizing the need for training in AI skills to maximize its potential, the talk concludes by advocating for a balanced approach that focuses on reaping the benefits of AI while addressing challenges such as ensuring transparency, consent, and compliance with data regulations like the GDPR. By focusing on effective utilization of AI for lead generation and collaboration, the podcast aligns with the broader theme of ethical and accurate AI implementation.
Summary notes from Episode 25:
Chapter 1: Integration of AI in Sales and Marketing (00:01 – 03:25) 00:19: AI
reshaping sales and marketing alignment, improving efficiency,
personalization, and collaboration. 01:34: Challenges of integrating AI
include ethical considerations, privacy concerns, and the need for training.
02:11: Advancements in AI technology like natural language processing and
predictive analytics. Chapter 2: Leveraging AI for Lead Generation (03:25 –
06:30) 03:39: AI-powered tools analyzing data, identifying valuable leads, and
enhancing lead generation. 04:48: Key capabilities of AI adoption include
automation, integration with current workflows, and data analysis. 06:02:
Driving personalization through AI, utilizing chatbots, recommendation
engines, and dynamic content. Chapter 3: Improving Sales and Marketing
Collaboration (08:00 – 09:54) 08:23: AI enhancing collaboration between sales
and marketing through data-driven insights and workflow automation. 09:00:
Importance of assessing the accuracy and effectiveness of AI-generated
results. 09:54: Ethical considerations in using AI, transparency, consent, and
compliance with regulations. Chapter 4: Data Analysis and Insights with AI
(10:14 – 12:50) 10:29: AI empowering sales and marketing with data analysis,
understanding consumer behavior, and market trends. 11:08: Optimizing sales
and marketing strategies with AI-generated insights. 12:05: Providing training
to sales and marketing teams for AI skills and knowledge. Chapter 5: Future of
AI in Sales and Marketing (13:25 – 14:08) 13:25: Advancements in AI technology
automating routine tasks and enabling predictive strategies. 14:04: Staying
ahead by adopting AI early, testing, and ensuring expected behavior. This
outline provides a structured overview of the key points related to the
integration of AI in sales and marketing discussed in the transcript.
Full Transcript:
00:01
Welcome to the demandgen pod. My name is Ryan. Today we’re talking about AI, marketing and sales all getting together, loving each other. It’s kind of weird. Let’s get going. Listen, like it or not, AI is reshaping the landscape of sales and marketing alignment by automating these processes and providing data driven insights across the board and in ways that we never really could have before, at least certainly not efficiently. But also, with that said, it’s also creating new ways that maybe we haven’t thought of. And I guess that can be cool. Some potential benefits of integrating AI, like I mentioned, improved efficiency. But you can also improve your personalization. You can increase collaboration between sales and marketing teams. But some challenges, some ethical considerations, privacy concerns, and additional need for training and upskilling.
01:02
And I think that there’s one other point here that I just want to make too, is that along with all of these, is checking your damn work. So if you’re using AI to design something for you, or to write scripts, or to write emails, or to write basic copy, wherever that copy is being inserted, check, they’ll work. And I think that’s sort of one of the drawbacks, that in some ways AI is good enough, in other ways it’s most certainly not. And one of those ways is that it can sometimes just make stuff up. Like, just make stuff up. And if you’re using AI, let’s just use a really specific example.
01:43
You could theoretically, I think we’ve talked about this before, but you could theoretically use a tool like zapier chat GPT and your database, your marketing automation database or Salesforce database to send some piece of information over to chat GPT to get some sort of information back, to write some sort of, say, opening email sentence or something like that. I assure you’re already getting emails that are like this. They are all like the cold call emails. Some are way better than others. They started out like the weakest of them, I think, and I still see them and it’s just like an immediate, they’re all pretty obvious to me, I guess, but the worst ones, I think are, oh, hey Ryan, I saw that you had this really great review recommendation from Matt and I’m like, yeah, in like 2015.
02:35
Like why are you telling me this now? Or, oh, I really liked your recent post on X and not the platform X on Topic X and this is what I took away. I thought that it was really interesting. I think that when you’re looking into things like this, you need to make sure that it’s current and have some sort of way to leverage that. Now, some recent advancements in AI technology, natural language processing and machine learning, predictive analytics, I mean, some of this has been around for a long time, but I mean, even the AI companies are admitting that it’s kind of crap and so you really need to be careful with it. And AI powered tools and platforms are really changing.
03:25
Lead gen by analyzing data, identifying the most valuable leads, they’re able to look in all these nooks and crannies of the Internet that we wouldn’t even know to look to. And that’s all really helpful, again in bytes. I think some of those key capabilities that you want to be looking for when you’re thinking about adopting AI, think about automation. How can you integrate, so might Zapier example is probably a good one here. How can you integrate AI with your current workflow? How can you implement it with your current databases? How do you get information too the platform? How do you get information from the platform? And what about your data analysis and personalization opportunities? Integration within all of those existing systems and beyond.
04:11
You can also improve lead gen by automating processes, which we can certainly leverage AI for, analyzing customer data and identifying high quality leads. And then you can also use techniques like predictive analytics, scoring and customer segmentation to prioritize them. And then in terms of automation, we can use lead nurturing and pipeline management to streamline our processes and save time. So all these can be really helpful if you can identify where people are supposed to go based on different behavior points. But a lot of that AI can also be integrated, or has been integrated into various tools that we’re using. I get these emails all the time from different vendors that we use, or integrating AI in to do this, that, or the other thing. And I think that I found, because it’s not that I don’t use AI or chat GPT, I definitely do.
05:01
But I found that when you set up bumpers for it, and they’re very specific and you keep a focus, that you can generally get pretty decent results. It’s when you don’t really have a process in place that you’re following and you haven’t vetted that process that you can run into the problems. But what I found is that with chat GPT, it stays very consistent. So if you ask a question one way and you just change maybe the specific topic of the question, but the question is still framed in the same way, then you’ll get really similar results from chat GPT, and that can be really beneficial when you’re testing for these things and you want to make sure, like, can I trust you? If I turn around? If I turn around, you’re still going to provide the same results or the same consistency.
05:48
And that can really help with that. While I’m thinking about it, if you have an opportunity, I’d love if you guys could subscribe to the channel, whether that is on Spotify or Apple Music or wherever you listen to your podcasts or also on YouTube and TikTok. And I appreciate that. Thanks very much. So what about personalization? So we can really drive personalization forward by analyzing customer data, delivering some different tailored content and experiences, you can leverage AI powered solutions like chatbots, which can be helpful, I think depending on the complexity of the questions that are going to be asked on your sites, recommendation engines, dynamic content to help deliver personalized experiences at scale. We can do that certainly within email, for example.
06:30
So again, if we knew a contacts company, we knew their name, maybe some other piece of data about them, maybe that you can scrape from LinkedIn or something like that, or Dun Bradstreet or whatever. And if you have this value, these values in your database, you could create a prompt to AI to be able to say, write an opening paragraph for a sales email for person X at this company who has been in their role of X for the last x number of years, something like that. And if you are just swapping out the person, the company, the role and the number of years, you will get a very similar answer. But it will be personalized for every single person. And again, as long as the data is accurate, going in, the output will most likely be pretty accurate.
07:24
So that’s what I found so far. It’s not really something that we do, but it is certainly possible, even with the tools that we currently use. And the other thing that you can do is predictive analytics, so it can really help you to understand customer behavior and preferences for better engagement. And at the end of the day, I think that if you are able to leverage AI to improve somebody’s experience, and that’s a good thing, if you’re leveraging AI because you’re lazy and you just couldn’t possibly be bothered to do it yourself, that’s not like such a good thing. I think you got to recognize your limits there. How does it improve sales and marketing collaboration?
08:02
Well, we can bridge some gap between sales and marketing, and there always seems to be one by providing data driven insights and automating workflows, just like were front facing, we can do it on the backend, too, and you can leverage collaboration tools and strategies. We can leverage shared dashboards and regular communication channels, and all of these things enhance alignment. The nice thing about streamlining workflows and data sharing and reporting all of these through AI driven systems is that we can allow AI, I suppose, again, big caveat, sometimes with accuracy, regarding accuracy, to provide additional context that we may not be able to provide upfront or certainly not in real time, and that’s where that difference is. So again, I really think that it’s the difference and the middleman between speeding up your workflow and improving your workflow, but also actually providing good results.
09:00
So are the results as good or better as you could provide, and is it faster? If yes, I mean, how could I possibly make another argument against it? If no, you really got to step back and start thinking about how am I using this? And does it really make sense how much of it is customer facing, how much of it is actually believable? How much of it, let alone believable, is even real? Because we’ve seen, there was a lawsuit recently where one of the lawyers went to chat GPT to ask it about related cases that it could use, and chat GPT made one up and then the lawyer submitted it, an absolute idiot. So, you know, does it make you faster? Well, it made the lawyer faster. Did it make the lawyer better?
09:45
Well, it clearly wasn’t that good of a lawyer to begin with. Did it do a better job than the lawyer could have done if the lawyer just done it himself, or herself? I don’t even know. No. The answer is no. Like hard no. So, you know, great example of something that theoretically solid idea, but as we’ve learned, chat GPT, when it doesn’t actually know something, it rarely really tells you it just make stuff up, or can make stuff up. So with that, let’s think about analysis and insights. So because we can collect all this data and we can load it into a database, we can empower sales and marketing with AI to manage some data analysis by collecting and organizing and interpreting customer and market data. And you can do it on a much grander scale, that’s for sure.
10:29
So while it can help us understand consumer behavior and market trends and competitor insights and inform decision making, again, we just need to be careful with how we’re actually leveraging it. But again, in theory, AI generated insights will optimize your sales, it’ll optimize marketing strategies, and it will help to target the right audience and drive better results with the caveat that you’re putting the right data in. So good data in, hopefully good data out, bad data in, definitely bad data out. Nobody’s fixing your own mistakes before it goes into AI. AI certainly isn’t. What about some ethical considerations? We were talking about this last week when were talking about psychology. We can certainly talk about it again this week, too. We need to be transparent.
11:18
We need to request consent and include things like the use of AI and the fairness of use for AI technologies in our consents. And you also need to be sure that you’re not sharing anything that might be HIPAA related. Make sure that you’re in compliance with security regulations like GDPR. You know, anytime that you are taking data that somebody has given you and you’re sending it somewhere else, you need to make sure that it’s going to a place that is safe. And, you know, I think that ultimately, making sure that you are checking your work, making sure that you understand where these things are being sent to, making sure that you are accounting for all of that in your agreements, so be it.
12:05
But don’t let it stop there, because we’re also using this, which is a new tool, and we have to be able to provide training to equip sales teams and marketing teams with AI skills and knowledge. So sort of like some of these things that I’m kind of imparting on you that I’ve learned is important to know and it took me time and to mistakes to learn them. Luckily, I’ve never used AI for anything really like customer facing or consumer facing. I really just use it internally and then kind of like check its work. And it’s a good jumping off point, for example, especially if you don’t necessarily know how to approach something, it can help you there, too. But there are online courses and workshops and access to AI has never been more easy. Just go online, it’s all right there.
12:54
And then, you know, you could always consider hiring for some sort of AI expertise as well. This is where we’re going. I mean, it’s just the reality, I don’t think that AI is ever going to be like taking over. I just really don’t. I think it’s just, it’s as smart as it is. I think it’s too dumb. And the reality is that I don’t know when it will ever get smart enough to outsmart all of us, I guess even the majority of us. But with that said, I do think that there are going to be advancements in AI technology and lots of experts have envisioned the AI is going to play a larger role in automating routine tasks. That’s certainly not very surprising, driving some hyper personalization. I can definitely see us going that way and enabling predictive strategies, and that’s certainly already happening.
13:47
I mean, it’s already even built in to things like Salesforce, for example. And you can really stay ahead of this by adopting them early, trying them, see how they work, testing, and then again making sure that everything behaves as you expect it to behave. So I hope this has been helpful. It’s a really interesting topic and always happy to chat further if you would. So like, you can reach out to me straight through any of where you’re listening. Spotify. There’s a question box that you can type a question. It comes straight to my inbox, so love to hear it. Thanks for listening and watching and we will see you next week.