Speaker 1 0:00

Music. Welcome to the aim podcast, where we bring you actionable insights on AI and how to best apply it in your business, across marketing, sales, customer service and more, hosted by helpflow.com this is your guide to staying ahead in the world of AI for business. And just to blow your mind a little bit, our hosts are literally AIS talking to each other. Enjoy the show.

Speaker 2 0:29

Welcome back for another deep dive. Looks like you sent over some pretty interesting articles this time around about using data more effectively, especially with this whole idea of a data analyst virtual assistant? Yeah,

Speaker 3 0:41

it seems like you're really trying to get a handle on how to move past just collecting data and start actually using it

Speaker 2 0:49

right, like maybe even using data to make smarter decisions or even boost your bottom line. It's

Speaker 3 0:54

a really common challenge. I mean, tons of people in businesses these days are just swimming in data, yeah, but they haven't really figured out how to turn it into, like, actionable insights. You know what? I mean, it's

Speaker 2 1:07

true, and one of the articles even said that, like the majority of CFOs out there are feeling pressure to get a faster return on their digital investments, yeah, but they just don't even know where to start. Yeah. So with that in mind, I think it's time for us to really dive into these articles and see what we can find. Right there seem to be a few key themes, like simplifying data collection, zeroing in on the right metrics, and then using AI to turn that raw data into those actual insights we were talking about,

Speaker 3 1:35

right and then ultimately using all that to make better decisions, yeah, which should then lead to all sorts of good stuff, like more revenue and growth or more efficient marketing and sales, all the good stuff everyone wants

Speaker 2 1:46

exactly all the benefits. Yeah, so let's start with that first one, this idea of simplifying data collection. Okay, I think it was the first article that had this analogy about drinking from a fire hose. Oh, yeah, trying to describe the feeling of collecting every single bit of data.

Speaker 3 2:00

Yeah, yeah, it's a great analogy, yeah? Because if you're trying to track every single data point, you're gonna get totally overwhelmed and probably be no closer to understanding what really matters for your business, right?

Speaker 2 2:12

You're just gonna have all this data and not know what to do with it. Yeah, exactly.

Speaker 3 2:16

So the real trick is to identify which metrics are the ones that really have the biggest impact on your bottom line,

Speaker 2 2:23

right? And they actually had a really interesting example in one of the articles about this coaching business that was tracking over 20 different data points, but they saw a 20% jump in their revenue when they just narrowed their focus down to three key metrics, website traffic, conversion rates and lead quality. Oh, wow. Do you think that's because those three metrics give them a much clearer picture of how effective their marketing and sales efforts actually are, compared to say something like just looking at their social media engagement, which doesn't tell you as much?

Speaker 3 2:58

Yeah. I mean, it's highly likely by focusing on those three specific metrics that coaching business was finally able to make a direct connection between their actions and their revenue, which I know that's so important, and let them actually prioritize those activities that were really moving the needle, instead of just getting bogged down with all these vanity metrics that at the end of the day didn't really matter.

Speaker 2 3:18

Yeah, I get that. Okay, so it makes sense that you need to narrow it down. But even when you've done that, just collecting the data can still feel like a chore. Oh, for sure. And I know the articles spend a lot of time talking about the importance of streamlining data entry and making sure everything is standardized.

Speaker 3 3:34

Yeah, absolutely. I mean, especially if you've got multiple people entering data manually, you really need to have a clear system in place right to make sure everything's consistent and accurate. Makes sense. One article even mentioned a real estate client who saw a 15% improvement in their lead nurturing cycle just by standardizing how they input their leads. Wow,

Speaker 2 3:54

that's a huge difference. So do you think standardizing and streamlining data entry frees up your team to work on more important tasks, like high level stuff. Oh yeah,

Speaker 3 4:05

definitely. By auto making data entry and making sure everything is consistent, you're reducing the chance of errors, saving a bunch of time, and then your team can focus on what really matters, which is analyzing the data and using it to drive, you know, like strategic decisions. Okay,

Speaker 2 4:21

that makes sense, but I think that even with Streamlined data collection, the sheer volume of information can still be really overwhelming, and that's where AI starts to play a role, right? And I know the articles mentioned AI powered tools that could help with data analysis. One of them even talked about using machine learning to identify trends and anomalies. I have to admit, though, when I hear machine learning, I always think of robots taking over the world. What does it actually mean? In this context? It's not

Speaker 3 4:50

quite as dramatic as Hollywood makes it seem. Okay, good. In this context, machine learning basically refers to these algorithms that can learn from data and make predictions or. Identify patterns, okay, without actually being specifically programmed to do so, okay? So instead of having to manually sift through spreadsheets, you could have an algorithm analyze all your data in real time and highlight any interesting trends or red flags. So

Speaker 2 5:13

it's kind of like having a little data detective on your team always working in the background to find those hidden insights.

Speaker 3 5:18

Exactly. And that brings us to the next stage, which is actually using AI to identify those high value opportunities that are often buried within all that data. So

Speaker 2 5:29

we've simplified our data collection, and we're starting to see some patterns. But how do we turn those insights into actual opportunities? There's that saying right data without action is just trivia.

Speaker 3 5:41

I totally agree. One of the articles even said something similar, and they really drove home this point of finding those high value opportunities, figuring out which customers, channels and offers have the biggest potential. And I feel like AI can be a huge help with this. Oh

Speaker 2 5:53

yeah for sure. They talked about using AI for lead scoring instead of chasing after every single lead. You could use AI to predict which ones are most likely to convert. It's like having a crystal ball for your sales funnel. But how does that even work? It sounds kind of like magic to me. Yeah,

Speaker 3 6:08

it might seem like magic, but really it's all based on data and algorithms. So think of it this way. Let's say you're running an online store, an AI lead scoring system could analyze tons of data about your website visitors, like their browsing history, their past purchases, demographics, even how long they spend on certain pages. And then, based on all that information, the AI can give each lead a score that shows how likely they are to actually make a purchase. Okay? And this lets your sales team prioritize the hottest leads and really tailor their approach for each one. So it's

Speaker 2 6:41

not just about predicting individual behavior, then it's also about understanding those bigger trends and patterns, right? Like in that example, with the real estate company, they discovered a whole new profitable niche just by analyzing the demographics of their leads. Right?

Speaker 3 6:55

Exactly? They realized that they were attracting tons of families, but all of their marketing was focused on like, single bedroom rentals. So by adjusting their properties to better match their actual audience, they were able to tap into this whole new revenue stream. That's

Speaker 2 7:09

awesome. It's like data can help you see your blind spots and find all these new opportunities. But it's not just about attracting new customers, is it? The Articles also talked about using data to really get the most out of your existing marketing? Oh yeah,

Speaker 3 7:23

definitely. One of the biggest takeaways, for me was the power of data segmentation. Instead of sending the same generic message to everyone, you can actually tailor your communication based on all sorts of stuff, like demographics, user behavior, purchase history. It's all about making sure your message really resonates with the right people at the right

Speaker 2 7:41

time, like they have that example of that E commerce client who segmented their email list based on how often people were buying things, and they saw a 35% increase in their click through rates. So I guess it's not about blasting everyone with the same email. It's about being way more targeted with your message

Speaker 3 7:58

Exactly. And this applies to all your marketing channels, not just email. By analyzing your data, you can see which channels are giving you the best return on your investment, and then you can focus your marketing budget where it's actually working. Are you spending a ton on paid ads? But maybe finding that organic social media is driving more conversions, data can really help you make those tough decisions and make sure you're getting the most bang for your buck. So we've

Speaker 2 8:22

talked about simplifying data collection, identifying those high value opportunities, and then even using data to refine your marketing strategy. But how do we actually turn all these insights into concrete actions? I feel like this is where people get stuck. It's one thing to have all this data, but it's totally different to actually use it to make decisions. Yeah,

Speaker 3 8:40

that's a really good point. Data driven insights are only valuable if you actually do something with them. It requires, like, a whole shift in mindset, from just relying on your gut feeling or intuition to making decisions based on evidence and data. One

Speaker 2 8:54

article even called data driven decision making, the moment where the rubber meets the road. What are some ways that we can actually use data to inform those decisions.

Speaker 3 9:03

Well, for starters, data can be super useful for making pricing adjustments. Let's say you notice a trend where people are always buying the premium bundles, or maybe they're more willing to buy during certain times of the year. Data can help you really fine tune your pricing strategy to get the most revenue without alienating your customers. So

Speaker 2 9:20

instead of just guessing what price might work best, you can use data to make a way more informed decision, exactly.

Speaker 3 9:27

And another example is using predictive analytics to kind of anticipate demand and plan out those seasonal promotions. One of the articles mentioned an E commerce company that used AI to predict this big surge in demand during a holiday sale, and by increasing their inventory beforehand and really ramping up their marketing, they ended up boosting their revenue by 40%

Speaker 2 9:49

Wow, that's amazing. It seems like these AI tools are getting so much more advanced, but I bet it takes a certain level of expertise to use them correctly, right? I mean, not everyone has a data scientist on their team. That's

Speaker 3 9:59

true. But the good news is that a lot of these tools are becoming way more user friendly and accessible, even for small businesses and individuals who don't have a technical background.

Speaker 2 10:07

So it sounds like we're moving towards a future where anyone can use data analysis and AI, which is really cool, but I imagine it could still feel pretty overwhelming if you're just starting out. Where do you even begin? Yeah, I

Speaker 3 10:19

get that. It's totally normal to feel a little intimidated at first, but the key is to start small and just focus on answering some really basic questions, like, what data do you already have? What are you actually trying to achieve, and what specific problems are you facing? Once you have a good grasp on your goals and those obstacles, then you can start looking into the different tools and resources that are out there to help you

Speaker 2 10:41

that makes sense. Don't try to do everything at once. Just focus on one specific problem you want to solve. And I know the articles mentioned something called a smart staff virtual assistant that's powered by AI. It sounds like it could be a total game changer for businesses that don't have the budget to hire a full time data analyst.

Speaker 3 10:59

Oh, yeah, absolutely, like virtual assistant like that could take care of so many of those routine data collection and analysis tasks that we've been talking about, things like tracking your website traffic, monitoring your conversion rates, even generating reports. It's basically like having a dedicated data analyst on your team, but without having to pay a full salary. So

Speaker 2  11:19

it's not just about crunching numbers, it can actually help you figure out those key insights and even make recommendations Exactly.

Speaker 3 11:26

And because these virtual assistants use AI, they can learn and adapt over time so they get more and more sophisticated and fine tuned to your specific business needs, they can even help you pinpoint those high value opportunities or forecast demand or even suggest ways to improve your operations. It's like having

Speaker 2 11:45

a consultant at your fingertips. 24/7, that's wild based on all the articles that we talked about. What do you think is the most impactful way to use data? I

Speaker 3 11 :54

think the biggest thing for me is how data can really help businesses make smarter decisions at every level, whether it's figuring out your pricing or personalizing your marketing or even coming up with new product ideas, data can give you the insights you need to stay ahead of the competition and do really well in today's world,

Speaker 2 12:10

it seems like data isn't just a tech problem anymore. It's something every business needs to think about strategically, and AI is making it so much easier for everyone to use.

Speaker 3 12:19

Totally agree, data is like the fuel that drives growth and innovation. The people who learn how to use it effectively are going to have a big advantage. So

Speaker 2 12:28

as we wrap up this deep dive, what's the one piece of advice you would give to someone who's feeling overwhelmed by data or doesn't know where to start?

Speaker 3 12:37

I'd say, just be curious. Don't be afraid to try things out and experiment. Start by asking questions. Find one specific problem you want to fix, and then look into the tools and resources that can help you. The world of data is always changing, so there's always something new to learn that's

Speaker 2 12:53

a great point to end on. Thanks for joining us for this deep dive into data and AI. We hope you learned a lot and feel inspired to try some of these things yourself until next time, keep learning, keep experimenting and keep pushing the limits of what's possible with data. We'll see you soon.

Speaker 1 13:10

Thanks for listening to the aim podcast. If you found today's episode impactful, be sure to check out help flow.com where we help businesses maximize AI across marketing, sales, customer service and more. Visit helpflow.com today you.

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