Fixing Business Bottlenecks with AI to Go Further, Faster w/ Liza Adams
A practical framework for using AI at the constraint that matters most, from faster execution and better analysis to focused market choices and new possibilities.
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AI is most useful when it addresses the thing slowing a business down. That sounds obvious, but many teams start with a tool, a prompt, or a productivity goal instead of asking where the real constraint is. In a conversation with Liza Adams, I explore a more practical progression: use AI to move faster, produce better work, and eventually do something different.
Start with the constraint
Marketing teams usually feel the pressure first as overload. There is more research, writing, analysis, and execution than the team can reasonably finish. AI can help with repetitive work and give people more capacity. That is the faster stage.
The next stage is better work. A team may not have enough time or resources to analyze customer interviews, market data, or reviews deeply. AI can help structure information, identify patterns, and create a stronger starting point for decisions. The final stage is different work: using the new capacity and insight to imagine an approach that was not practical before.
The best place to begin is the bottleneck that matters most. Ask what would change if the team fixed one constraint. That question keeps AI connected to business value instead of turning experimentation into another task.
Narrow the market with evidence
One example involved a company considering expansion into additional segments. The natural instinct was to pursue more markets, but spreading the product, budget, and team across too many segments could weaken the business. The better question was which few segments the company could serve exceptionally well.
The team used AI to compare segments across criteria such as market size, market growth, competitive intensity, partnership strength, and product fit. They used non-sensitive data, gave the model one criterion at a time, and created force rankings and a color-coded matrix. The goal was not to let AI choose the strategy without oversight. It was to make the assumptions visible enough for executives to debate.
That debate was essential. Leadership had different views about the strongest segments, and the matrix gave the team a shared object to examine. After the discussion, the team validated the hypothesis with customers, prospects, partners, and market information. Only after that validation did the company align on the segments, personas, and budget priorities.
AI made the analysis easier to perform, but the value came from combining data with executive judgment and market validation. A report alone would not create alignment.
Work in small steps
Large prompts can look efficient, but smaller steps make the work easier to inspect. Ask AI to read and understand the source material first. Then ask for a ranking on one criterion. Review the result. Apply the next criterion. Add weights only after the individual comparisons make sense.
This process creates checkpoints. If the model misunderstands a document or makes a bad assumption, the team can correct it before the error spreads through a long analysis. The same approach works for campaign strategy, positioning, customer reviews, and other marketing work where the output needs to be both useful and defensible.
Make AI part of the operating system
Once the bottleneck is clear, AI can support more than content production. It can help a team analyze reviews, identify patterns in customer language, develop campaign options, build a custom assistant around a repeatable workflow, and pressure-test its own output.
The human role remains central. Teams still need to decide which problem matters, which data is trustworthy, how the result should change the business, and whether the recommendation survives contact with customers. AI can accelerate the work, but alignment and judgment are what turn analysis into action.
The practical sequence is simple: find the constraint, improve the process in small steps, validate the result, and then look for the new possibilities that become available. That is how AI helps a business go further and faster without adding more unexamined work.
In this episode of AI-Driven Marketer, host Dan Sanchez speaks with Liza Adams, an AI Advisor and Fractional CMO at GrowthPath Partners. Liza shares how AI can help businesses identify and resolve operational bottlenecks to go further, faster. From her experience advising CMOs to leveraging AI for real-world challenges, Liza breaks down how marketers can use AI to streamline productivity, improve output quality, and foster innovation. Tune in to hear practical AI-driven solutions that will elevate your marketing and business strategy.
Resources Mentioned:
Timestamps:
- 00:01 – Introduction to Liza Adams and the topic of using AI to fix business bottlenecks
- 01:20 – Common bottlenecks in businesses and how AI can help
- 03:42 – Tackling productivity and quality challenges with AI
- 06:59 – Case study: Using AI to focus on key market segments
- 11:31 – How to leverage AI for market sizing and forced ranking
- 14:45 – The importance of executive alignment and validation
- 20:41 – Using AI to develop campaign strategies and improve messaging
- 26:00 – Creating custom GPTs and enhancing sales processes with AI
- 32:04 – Leveraging customer reviews and data for more effective marketing messages
- 41:00 – Validating AI outputs and ensuring quality with AI tools
- 44:00 – Final thoughts and where to find Liza Adams online
welcome back to the AI driven marketer I'm Dan Sanchez my friends call me danz and we are on a journey in 2024 to master AI so we can make the most of marketing because we all know that marketing always has more to do so with AI we're hoping to leverage it so that we can do more with less uh in order to catch up today I'm excited to talk to Lisa Adams who is going to be helping us break down our bottlenecks and using AI to fix the things that are slowing us down in marketing so welcome to the show thanks I'm I'm so excited to be here thank you for having me absolutely I someone recommended you on LinkedIn and after checking out your feed and what you were talking about I was really impressed I'm like oh my gosh got to have her on the show after we had our pre-interview I was like even more impressed I was like no wonder why you're speaking at meon like I'm like she H you have the goods and I'm excited about this episode and ready to get started thank you so much learn from many people and I try to apply them where I can and and you know I love the AI Community with a lot of sharing we're able to use AI responsibly and and learn from each other so if it's okay with you let's dive into the deep end and see where it goes I'd love to know like as you're advising Consulting a lot of different companies as as a fractional CMO as a AI adviser what are the kind of issues you're usually coming up against are they usually marketing strategy issues tactical issues Tech issues like what kind of bottlenecks are you usually coming across as an adviser yeah so my work spans fractional CMO work so with fractional CMO work you are essentially the CMO of the business right so you are in charge of everything from strategy all the way to execution and leading that team and ALS Ely representing that team to the board on the other end of the spectrum I am an AI adviser so as an AI advisor I advise CMOS and their marketing teams and that could be a wide gamut of of challenges right it could be very simple as Inspire our teams with what's possible with AI yeah so you know that might be hey we're simply using it for Content creation to create blogs or summarize reports is that it Lisa you know is that all we we we should think AI for to help us on this journey we need to scale with AI and we need to go from exploration to integration how do we do that as a team and how do we ultimately not just do this for the sake of marketing but also for the sake of the business because we are the growth engine for the business so I see a wide range of of challenges that AI can address and as a fractional CMO it keeps me real because the the use cases that I tend to talk about on LinkedIn or in in podcasts like this one they're real right we're addressing true challenges that marketers and businesses are going through and then we take those best practices and and takes a lot of that experience and apply it into my advising Workshop s and and and and roles it's interesting when I'm talking to people it is a pretty common question of like well what what can I be doing with this and usually I'm like well where are you stuck right now and then we'll start there kind AI is this General tool that can cover so many different problems so you might as well just start with the problem that's slowing down the most right because that's where you're G to get the most bang for your buck out of it like uh if we can fix this one thing how would that change your business right is kind of how it goes that's right that's right yeah do you see any Trends as far as what businesses are running into the most or is it just kind of depend it's different from business to business it's it's it's different by business however the natural inclination is to go straight into productivity like how do we get more things done or how do we make this thing go faster my team is overburdened is there a way for AI to help and take on some of these mundane and repetitive tasks so there's a group of use cases and a set of problems that tend to address productivity challenges and then there's another set of problems that tend to address we need better quality because of lack of time lack of resources we don't have the bandwidth nor the time to really think deeply right you know when we do research when we have to do interviews we don't have time to do all the data analysis we don't have the tools to do that we need new insights to inform decision making so just better outputs and then the last one is now I see less of this because there's so much focus on you know the productivity aspect of it and then making things better I do hope that more will start to lean in on making things different so now we're in Innovation H aspect of this it's not just making what we currently have better in terms of faster or better quality it's now thinking about things in a very different way so those are the the three buckets if you might you know that that you could think about it um in it's like faster better and then different or inative it seems like that's a natural progression like You' probably if you're starting to get an AI and train your whole team in it naturally the easiest thing to do is just to be able to do things faster faster that's right and then of course as you get better at dealing with AI and I think everybody goes through this cycle with AI where they actually prompt enough to begin knowing how to prompt in a way that you can get better outcomes than you would have gotten naturally not only that faster but you move quick you get better and then and then of course once you really start to master the faster and the better you start to think of like I don't know you start getting eyes to see like oh I wonder if and you start asking bigger questions of like now this whole new things possible we couldn't have done before that's right but you wouldn't have got there unless you had learned how to go faster gotten better and then that's kind of the training you need in order to be Innovative with it that's right that's right what are some case studies that you're proud of that you've addressed with teams now that you've seen all the way through you guys found the problem uh found how AI could become a solution to the problem and implemented it and it worked remarkably well yeah I'm going to share with you a use case that we did my team and I did when I was a CMO for um a company that had significant growth during Co because a lot of their customers went obviously many of us you know started working from home and their business was one of those that really thrived during covid because it enabled remote capabilities and things of that nature but postco it was really tough right and the company started to think about what do we need to do to to grow this business to identify more opportunities and the natural inclination of the business was to expand into new markets you know go into more segments identify new personas and pursue them but the challenge is when you start going into more markets you now start to spread yourself so thin and you risk not being able to serve all those markets super well there's a danger and that right you spread your resources you spread your budget so thin that you can't serve any one or two well and there's a risk of you know uh increased risk of uh um uh turn yeah so yeah the the idea really is to not expand into new segments it's to pick your top two or three segments that you can serve the best because nobody else can do what you do you have exceptional product Market fit and because you're so good at it you could do it profitably so we actually use AI to determine which top segments of the market we should go after rather than identifying new market segments in addition to what we have right we were actually narrowing the number of segments that that um we should pursue so we we use AI by I've explained this um in one of the newsletters that I launched uh in just last couple of weeks you know we have this framework by which we evaluated the segments across a number of criteria it could be market growth Market size competitive intensity strength of Partnerships a fitw road map and evaluated each one of those segments by each one of the criteria so you came up with all these segments did you give each one a score of how to rank them okay did AI help you come up with the segments and the scoring factors so we came up with the segments because we we had an idea of which segments we wanted right and let's just say there were eight of them Y and then we had our criteria and then what we did let's just say the market size was one of the criteria we used uh Market sizing data you know analyst reports data to to do that evaluation and we did a Force ranking scenario with chat GPT so basically fed uh non-sensitive data we had to redact some of the market sizing information fed it into chat GPT and we asked it to do a Force ranking so largest market size gets an eight because we were evaluating eight market segments lowest Market size gets a one and ultimately you um we asked it to do a heat map so the eight got a red and and the one got a blue kind of thing and you kind of do that same thing for each of the criteria right you did so lowest score wins then yep and then ultimately at the bottom it had a total yeah which allowed us to to see across multiple criteria which one was the best so let me just pause there just to make sure that that was Landing with you yeah no so um did you have I'm seeing it you put you just uploaded a chat gbt these reports redacted some information probably you probably upload them as PDF yep and then you just write like one long Mega prompt that said like okay here's what we're doing here's what we want to know here's the context the information here's the CR here's the categories the criteria and the and the segments no now go and do it and just get report report back one Mega promp it's multiple little promps okay so you CH prompted it to go step by step and to think through it step by step and you know there's value in going step by step in in in smaller bite-size prompts right because you can uh course correct if it doesn't understand it is also a good way to check ai's work because you're only checking little things versus checking a whole heck of a lot of things right y so definitely step by step like for for example that first prompt was is I'm going to give you the market size for these eight segments read this document or read this um Excel spreadsheet understand it well then I will give you further instructions okay first pro second prompt now that you understand all of that do a forc ranking based on Market size and show that to me in a table that and I told it you know I want the segments on the um column and the market size is the row so it gave me basically a row with with the forc ranking then I said all right color code this thing and create a heat map just for that row then it just did that right yep so that now we have one and I said now I'm going to go to the second criteria yeah now we're going to go to market growth and then did the same process after criteria I said put them all together put all the rows together in a table so now we have a table a matrix that is colorcoded based on all the force rankings and then I said give me a total with weights that are equal across the different criteria so now you have at the bottom a total an aggregation and you can see which one one out across all of the different criteria you can also say oh by the way I want to apply different weights because it's more important to me market growth is more important to me than um number of reference customers right so you can actually play with the weights and then it will give you a different result so let me pause there this is such a fantastic process and I feel like it's one of those things that probably need to be shouted from the rooftops because I feel like the Decay or the the killer of many businesses is operational complexity right because line I mean you you're successful on one thing but naturally line extension comes in you're you're serving way too many products to way too many markets and it slows down and kills many companies which is why when consultants and fractional CMOS like yourself get in one of the first things we see is kind of like hey like the easiest way to profit is just by eliminating work that you're currently doing not even launching new stuff just stop doing the stuff that's killing your profit and you win but this actually gives people a way to I don't know about you but like I've recommended that many times that people are like well yeah but we need more Revenue you're like you don't understand by doing less serving less people is the is the path to revenue and you've this process is essentially given other there is a way to prove it empirically or at least give show like hey no like it's not just me guessing it's like here's a here's a path you can take that proves empirically that there are better segments and if you focus on these segments we can grow it so once you're able to kind of prove that these segments are better than these segments what steps do you take yeah it to your point the reason we did it is you know we could decide to add more segments and and we would Now peanut butter and we were just not convinced that we were going to get to the re to the revenue goals right so we said hey there's no harm trying this let's Nar narrow the aperture and figure it out but that was only the First Step Dan you know that was product marketing doing our little table you know using data to to craft this table we needed to get alignment right we can't just say hey this is what chat GPT created for us here's the heat map therefore these top three segments are the segments we're going to go after we we went to the executive team right because the executive team had different views on which segments were the top ones and you know their hypothesis may have been right in one or two dimensions but not right across eight Dimensions now that they saw the Matrix let's have a conversation right let's have a conversation around the different weights the different Force rankings you know let's debate these things and that is where I would argue that that was the most valuable part of the process the the framework was foundational for them to have a conversation but that debate debate within the executive team to ultimately Drive some alignment was the most valuable thing in there but even after that debate you know healthy debate let's say we came up with like the top three the the next phase of the process wasn't all right let's tell everybody in the company that these are top three and let's pivot to these three no we took another two to three weeks and said let's validate our hypothesis and our data with the market right let's talk to stakeholders to Partners let's ensure that we got the competitive information right let's talk with customers and Prospects did some of that work and then ultimately came back again as an executive team you know um changed some things based on what happened in the validation process and then ultimately aligned and then once we get alignment I would you know I would argue it it was probably one of the most strategic things that marketing can do because it avoided you know the not a whole company from CEO to Frontline managers know exactly the segments that we're going to go after if somebody has a wild idea about another segments no we all aligned on these three segments right and then from a marketing perspective we knew exactly how to allocate our budget and where to allocate it these are the three segments that we're going to go after this is our ICP Iden ify personas Within These segments and we will craft campaigns specifically for these segments because they are the ones that we can serve the best from the criteria that we chose it makes it so much easier for marketing to prove its worth rather than having to guess or having to peanut butter its money across the board I feel like marketing always has good insights to what products to go with or kill but I usually find that marketing is not usually the one in the Executive Suite to actually make choices around that and I don't know I think it's just because there's probably just not enough empirical evidence that marketing brings but with this process it actually makes it possible to bring the empirical evidence you need to drive the conversation in a really productive and profitable way so I love that you're using AI in order to make this process simpler because certainly you could do it by hand but gosh it's a lot of work to create that one report doing this manually is exhausting but AI is actually able to go through read it and actually do analysis and explain why so that you know you can double check it to make sure it actually gives you a good report and I'll make sure to link to you said this was a newsletter I think you have a blog post on this now yeah uh I have a blog post on it but the newsletter goes more specifically into the process that I um that we went through well I'll share a link to this uh case study if anybody wants to break it down and replicate it I know I will be because this is such a common problem I've run into and I'd love to know exactly step by step we just heard it but I'm like H but I want I'm going to need to reference it later so I'll be linking back to that yeah what else have you found AI to be useful for yeah so so once we got down to the three segments it got super easy because now we have alignment so we actually used AI to develop our campaign strategy so you know if if we let's just pick one of the segments right you know we we said all right for for this segment help us brainstorm with us so we used it as a thought partner in that thought partnership there's there's there's a collaboration you know it it needed to understand our Market it needed to understand our positioning our messaging it needed to understand our personas so all of that work that we did we we had to feed into AI again redacting it and taking out sensitive information people always say hey you're feeding it competitive information and messaging I'm like they would find it on our website anyway yeah and in fact if AI wants to learn that that's our positioning and that's our messaging and that's our value prop awesome you know feed it to the market right so like you know I I understand that the competitors might see that but they will anyway because that's what they will see on websites or on customer review sites so feeding that that information around your Market strategy your positioning your messaging your value props your personas is so critical in helping AI in giving it context of what you want it to do right and then really thinking about all right AI let's brainstorm on what the campaigns might look like in support of this the segment and here are the three goals that we're trying to achieve and given all that context it begins to give you some ideas right sometimes it it it's not quite right but then you guided to to give you the ideas and we actually came up with three campaigns one of them was one that we never thought about that came from AI from from that discussion from that we used it as a thought partner in essence it it it this is where I feel like AI made it better you know that the first process It sped it up right but it also made it better this why sped It Up made it better again and then ultimately once we had that idea now we use AI again all right help us to further craft this campaign what does it look like here's the buyer's Journey what the how would you design this campaign so what AI does for us Dan is it helps us get started quickly right it like gives us a first draft once you give it a lot of context a lot of really good insights and information good first draft and often times that's the hard part like just getting it lifted off the ground so rather than lifting it off the ground now we're lifting it from our knees because AI helped helped us to lift it off the ground a little bit right and then now what we need to do it's easier to edit than to start from scratch AI allows us to not start from scratch I find that the Strategic documents are actually useful for the first time how many times have we written marketing plans or Persona guides or positioning statements that just sit in a folder in Google Drive somewhere be seen once and never again right until we're like who don't we have some personas oh yeah we did that as an exercise eight months ago you're like oh gosh but nobody's looked at it since AI keeps it front and center though do you use custom gpts to attach it to or do you just upload it most of the time no we use H we're starting to use a lot of custom gpts so thank you for ask asking about that we actually did a custom GPT for the Strategic one that I talked about where uh we created a heat map because we wanted to be able to use the custom GPT when the executives were having a debate while they were having a debate a debate the force rankings were changing so we were doing it in AI in the custom GPT as they were changing the force rankings right so the the executives were seeing how the Matrix was changing so that's one custom GPT um the other custom gpts are a bit more tactical you know like yeah for copyrighting for um you know to your point like copywriting you put brand tone and voice in there you put Persona information in there right okay hey we have this Persona Dan we're going to do an email for him this is the goal and then we don't need to explain what the day and Persona is because it's in knowledge right here's the goal and I need three emails to Dan at the top middle and bottom of the funnel please draft it now again lifting it off the ground for us all we need to do is edit from there yeah I love loading I just did this for a client just yesterday and I loaded it I actually did an intake interview with this client just to ask them all the basic information they were like what why are you asking I'm like what industry are you in who's your target audience what's your story what's your mission what are the brand elements that make you weird like just I probably asked 50 questions unloaded it all into Excel sheet and then I upload it all to a custom GPT with some other basic information about their business and their products and different things and now I just query that all the time it's a great starting point because like you said and now I can go and take things like hey I love this email from a totally different industry email but I want one like it in this client's industry but use this as an example it's like you constantly have all the Strategic docs and everything then you could take inspiration from totally other places and be like hey Mash these two together and it just it just does wonderfully with that I I I love that because Dan I I've said that AI will force us to be more strategic yeah and it will for us Force us to be more authentically human right this example that you're just talking about it's forcing us to really be strategic because absent those strategic documents well AI is just going to give you average information you're just going to be creating content that's a result of what it can find on the web it it's not truly personalized and and relevant to the market that you're going after that you know you can serve the best because of who you are so I think it's such a gift to marketers it will highlight our strategic value and if we're not doing that it will force us to be strategic I love that it AI gives away for strategy to actually be utilized because you often find that there's a diff there's a disconnect between strategy and tactics and this actually Bridges the Gap in a way because you don't have to depend on just people's memory of the strategy now I'm I'm pretty sure like I will I won't force people but like I'll just be like hey always start with this custom GPT when writing anything that way I know all the objectives are taken into account each time at least by AI because AI will always remember right yes I mean it hallucinates sometimes but as long as you're giving Crystal Clear context I'm like it's it doesn't forget easily it humans are humans hallucinate way more than AI does it's a human problem so I love that you're using this to like guide strategy and bring strategy back to the Forefront of the Tactical side of Mark I don't think we have a choice yeah it's I I don't know it just it's somebody who I I jump I jump between these two Fields all the time between the the clouds and the dirt of marketing so it's fun to find a process to pull it pull it together with everybody and I I love the way you framed it that how many times have we seen these strategy documents be created we spend a lot of time and a lot of money doing them and sometimes we bring in outside Consultants right they they do tons of interviews and then they do Persona development and they identify our ICP we we spend tens and even hundreds of thousands of dollars it gets presented and then it sits yeah in one drive or Google drive right and never to be seen again but now I have so many clients where we are feeding that into the work that we do consistently and in the case of custom gpts that's the Benchmark right like it's in there without that what does AI have to go by nothing so I think it's such a good call out you know I didn't realize it until you said it you said it how many times have these documents just sat there almost every being now they're front and center without them it it's bad marketing yep I'm a producer for a different AI show around sales and they they have even worse problems because they'll make quarterly objectives of things they want sales to push but of course you want it to be pushed well two weeks ago usually but they have issues where they just can't even because you know you got a you got a whole Salesforce and you got to coach them you got to train them and then you got to reinforce it it's not enough to do a dayong training with all the sales people on the new thing they they need to know you have to reinforce it and then Coach it like it it's like six nine 10 months before it's actually being done which is so slow in today's market so now ai is making it possible to bring It Forward for them and that's that's something the sales people are working on but I'm like it's working for marketers too because we set objectives we set standards and it's just not it just wasn't happening without repeated training and reinforcement which most of us never did because there was always some fire to put out with marketing but now it's actually it's possible and it's just exciting because like strategy will actually be useful again that's right that's right tell me a little bit more like do you have any other case studies these these are two fantastic ones what else have you done and seen so far that people should know about yeah so let's let's just keep going down right so okay we've got our strategy we have our Target segments we got our personas we've got our campaign so let's create some assets so what I love about creating assets is talking in the language that customers use and leveraging data that we have where they're actually talking to us or talking to the masses so what I'm referring to is you know customer reviews on review sites these are customers or prospects that are reviewing us and our competitors there's a lot of good insights in there and they're using language that they use in in those reviews um in they us in their business any kind of sales call call transcript right like from gong yeah like take that any kind of customer review from creating testimonials or case studies uh you know when we do customer success calls or customer support calls there's a lot of insights from all those things right and let's just say you've got your your messaging for Persona Dan Persona Dan has these three pillars because there are three pain points and let's just take let's make this example simple yeah let's take some reviews from G2 review site right and we take all of our customer reviews and we say here's a table for Persona Dan with is three pain points in our value propositions create the messaging that we would need for Dan um and give me proof points for each one of messages based on what you can infer from the customer reviews and use exactly the language and the words that that customer that the customers are using do not make it up do not paraphrase fill out this table now there there might be 177,000 reviews right yeah but this thing is gonna comb through it it's gon to look at our pillars it's G to try to match up one might be around efficiency quality or Roi then it's going to start matching it up right yeah then we'll see what comes up with you know we need to double check its work and then we could say all right for those proof points see if you can find qualitative proof points or qualitative improvements that we could include in our message so pull it out right yeah it's all public information it's G2 like anybody can go in there you know cap Tera or trust radius so see what we can find and then use that I think we get so enamored in marketing Dan where you know we we speak we we like the itties and the Ables flexibility scalability you know all sort highly scalable Aid driven all sorts of things when the customers don't talk that way and then when we look at the customer reviews and we just use their language we're mirroring them you know there's the saying that if the customer doesn't understand or they see language that they don't use then the automatic impression is oh it must not be for me right and we don't want that right so mirroring the language is going to be super important and there's no better place to find it than actual customer speak actual customer reviews and interviews and transcripts and and it could give you a really good Head Start I feel really dumb I'm like how have I not done this already I knew this kind of stuff I literally did a podcast just on grock and don't know grock 2 just came out which is kind of like a GP it's almost gp4 level but it's attached to X AKA Twitter right and it it it's I don't know it's it's probably a combination of some old algorithm Tech and AI because you can ask it like hey what's currently trending with insert target market and its ability to go and find it and then analyze it to find out what's trending and it'll bring the receipts it'll bring the tweets that it's pulling from for you to understand the market what the Market's talking about in real time is really good but it hadn't occurred to me yet to just scrape all the reviews from something like G2 and then have a do analysis on pain points and then to bring examples with it it makes me want to like do that immediately after this interview actually because I can think of like three clients that I'm like how have I not done that already it's such a quick and easy thing that you can do you don't even have to copy and paste it you can literally just go to hey do a search on Bing for G2 for this company and report back uh because it can do web searching through Bing and find it well and and then if you just take that use case one step further into sales because you were going down that path right taking customer reviews you could say based on the customer reviews what are the top objections about our product heck that's your template for your objection handling yep yep document for sales right and then you feed it your value propositions your positioning your your messaging your differentiation and you say all right take a stab at answering those objections based on on what we've got yep again gets you started on a draft for crafting your objection handling AQ for sales Yeah question when you're feeding it something like it's GT reviews are just long and extensive there's usually only dozens of them per company sometimes very popular product you have hundreds when it comes to companies that might have like hundreds of reviews and they're like short maybe Amazon reviews how do you validate the AIS doing a good quantitative analysis because some of the problems might be coming up more frequently than others versus it like just hovering down on like maybe the first or the last one that they might give a special attention to even though it was only mentioned a few times yeah do you check to see if that's consistent yeah I I try not to give it too many because because uh at least in today's versions of the AI and I'm not deep in the technical reasons why it can and can't right but there's also this notion of the context window and how how big it is so you know Gemini's got like two million right so but I've not tried to use Gemini for this I'm I'm using cha GPT right so 12 um K tokens the other aspect of this is um it's not very good at math so once I start needing very precise information then I I really don't trust it so I try here here are a couple things let's just say there's 177,000 reviews I don't give it 17,000 reviews I Pro I probably will narrow down the window to all right instead of the last year just give me the last three months okay now we don't have 177,000 reviews now we only have 2,000 right yeah you maybe take the most recent ones most is always pretty big good way to you know in capar G2 you can also say I only want the Enterprise ones I only want the healthcare ones start narrowing it down right because we we do have an ICP because if you took everything this thing's huge so start you know really go down to the segmentation to see if you could narrow it down and if you still can't narrow it down small enough then then what I do is like chunking it down into pieces like do do the do the first 500 I want to get insights from that do the second 500 give me insights on that and then see if you can combine them you know insights from the first one insights from the second one and then combine if that makes sense that's yeah no that's how everybody gets around the context Windows you have to do it in chunks and then summary and then combine the chunks it helps for checking it too right because I can't check like something super big but I can check something that's you know maybe one or two pages of a spreadsheet yeah and that is a way to actually quantify it because if it's giving a summary of highlights of whatever you're looking for whether it's pain points or uh high like things that they liked about the product doesn't matter whatever you're looking for and it gives a summary and then you have it do maybe five sets of summaries well now it can it can quantitatively look to see like well which which pain maybe if you went like three months and then three months back and then three months back and three months back you could see what's trending across the year and actually quantitatively know like hey like this this Insight is coming up in each summary therefore this is a thing yeah and it's it continues to Trend you know the other way to check this and and we've done this fairly consistently now is same prompts same data do it with ch GPT same prompt same data do it with Claud see if there's a vast difference in what they're recommending in terms of value propositions and what they're inferring from the reviews if there's a vast difference somebody is hallucinating somewhere right and that gives you a kind of a mental check but if they're relatively similar you know same Trends same value props then you could feel a little bit more confident because now you've got two AIS you know checking each other yeah no that's a good way to do it I I tend not to ever use Claud or any of the other AIS I'm pretty committed to chat GPT just because I find learning how to use one is like learning how to use them all I just don't want to pay for them all so I just I just stick with chat GPT I'm hoping eventually it'll be Microsoft co-pilot because then it'll integrate with more stuff I don't feel like co-pilot's ready for Prime Time quite yet but it's getting close well Dan I I will tell you that for as much as I use it I I would say that um at least for my purposes Claude is a better thought partner yeah it's a bit more collaborative a bit more uh Analytical in my mind I I I truly just like the way it thinks about strategy right like if I ask it for different perspectives it it it challenges me actually right yeah chat GPT kind of um uh it's less collaborative it it just answers a question rather than Claude tends to ask me questions and I like that you know before I answer your question it it it asks for clarification so anyway you might want to I hear I keep hearing that claud's like a step A step above I just expect that Chad GPT would be launching number five or it's fifth version soon so I'm just like I'm just gonna stick with that just wait yeah because I'm G to move over to Claude and have to move all my custom gpts over to like the new thing and I'm like nah I'm just gonna leave them because like dozens of them and I'm like I ain't moving them that is the problem I that Claude you can't do custom gpts with Claude right you now I thought they released a mechanism for that didn't they call it Gems or something Gems or maybe that was Gemini thing I think they do I think they do have a custom GPT thing with Claude now at least that's what I heard yeah fantastic whether you can do all the other little tiny things I don't know like can you upload PDFs can you have it scrape the web can can it do excel sheets I I don't know but I've heard it do gbts at least today as far as I know Claude still can't browse the web so if it's doing a custom GPT but it can't browse the web we got a little bit of a challenge yeah well thank you so much for coming on this episode I've learned a lot and I feel like I've been unloaded like like a full course meal like a five course meal with like how to really unpack a whole strategy from beginning to middle to end and this is one of my favorite episodes so far I think you've really challenged me on how to use CH how to use AI on a strategic level and not just a tactical level which is what I usually tend to gravitate towards I like the strategy but you've really given me a framework for how to like fit it together to actually use it to really speed up and quantify and do better strategy um so thank you so much for coming on the show and sharing that yeah my pleasure this was so much fun and you've given me like little new analogies little tidbits that kind of crystallize it for people and make it more relatable and half the time it it's really just that right like you know when you say something different and then now the ideas crystallized and like ah okay I didn't realize that that's what you're talking about so I really like this notion of no strategy document will now sit and and and collect dust right it is now the the the the guts of what powers AI to deliver personalized and highly relevant responses and content for us so where can people to go to learn more from you to find some more about these the case studies that you've mentioned and connect with you online yeah so I post liberally on on LinkedIn and and the reason I do that is I'm so passionate about elevating strategic value of marketing and like I said initially I do feel that this is the gift that will turn perceptions on its head that marketing is primarily a tactical function we are a strategic function we our Nord star is deeply understanding the customers and absent that it's just marketing for the sake of marketing right so um that that is my passion and that's why I'm sharing um more broadly the other thing is this AI Community I I'm indebted to it you know I learned so much from so many people like what you hear from me is as a result of learnings from so many like you just gave me a bunch of key learnings today right and this is one of those where the AI companies are building to create God when it comes to technology but no one is really teaching us the best practices because there are no best practices it is up to us users to determine how to apply AI responsibly so you know when when when I share this is like part of my gratitude you know I'm sharing because so many people have shared with me um so LinkedIn is one the other one is my website growth. net and you know my work is to inspire people with what's possible and if I can help reach out to me and of course all the links to these will be in the description if you want to jump over to them and learn more thank you so much again for joining me thank you Dan thank you so much for listening to the AI a marketer if this show was any good please give it a fstar or whatever star rating you think it deserves on the podcast app that you're listening to and tap that thumbs up button on YouTube and if you want to dive deeper into Ai and you're still not sure if you've mastered the fundamentals go to my free AI course at Aid driven marketer.com and take a look learn the fundamentals and you will never have to look for a prompt cheat sheet again five video series and you'll even find that I've customized the course so it's hyper personalized for you your role and the people you're marketing to take a look at it and let's get started so we can do more with AI today