The Boring Al Side Hustle Making People $10,000/mo

Okay, listen, there is a side hustle right now paying people anywhere between $2,000 to $10,000 a month. No, it's not dropshipping. It's not selling prompts. And no, you don't have to become an influencer. It's boring. And that's exactly why it works. And here's the thing. A lot of you guys are already doing some version of this work at your job right now for free, but you don't realize that someone else will pay you a whole bunch more money for it. So in this video, I'm going to break down what this side hustle actually is, pays for it, how to land your first client, and how you can use AI to scale your business past $10K a month. So let's start with what this side hustle actually is. It is called fractional data analytics consulting. You are a part-time on-retainer analyst for a business that needs answers from its data, but doesn't need or can't afford a full-time hire or a full-time team. Now ignore the word fractional for a second because it makes it sound way more complicated than it actually is. Here's the easiest way to think about it. Every small business already pays someone part-time to own their numbers. It can be called an accountant, for example. But the accountant's job is to tell the IRS what happened last year. No one's job is to tell the owner what to do next month or what happened last week. That is the empty chair you are filling. Here's an example. Imagine a dental group with 4 locations. Every month, the owner wants to know which location is growing, where collections are slipping, and which providers are underutilized, how many patients aren't showing up, and whether labor costs are starting to get out of control. The problem is that business owner has no idea where to even start. One number may be in a practice management system, another may be in some random spreadsheet, another billing may have its own report and numbers, and their accountant may be looking at something else entirely. So whenever the answer simply wants to know why were collections down last week, 3 people are sending 3 different numbers. And at the end, no one is completely sure which version is right. That is a real problem that you're solving. And that is a real painful problem where companies are losing money. And you're not going to be showing up saying, I know a dashboard software. You're going to be saying, every Monday you're going to know exactly what's happening in the business without chasing 5 people for 5 different spreadsheets. The work itself isn't complicated to understand. You build and maintain dashboards that the business actually uses. You connect messy data systems that they already have, and you clean up their numbers so revenue in one report actually matches revenue in another. And then once a month, you can explain what changed, why it changed, and more importantly, what the owner should look at next. And when they have a random question like, hey, which products are actually profitable? Or why did sales fall last week? You're the person that they call. Now, once a quarter, you can also go deeper. Maybe it's a pricing analysis, a customer churn breakdown, or a staffing forecast. It is a kind of project that sits on someone's to-do list for 6 months because no one inside the company actually owns it or even knows how to get started. And this is where people make their first mistake when they get into the space. They think their client is just paying for dashboards and spreadsheets and numbers. They are not. A dashboard itself is just a picture. The client is paying to trust that picture. They are paying for someone to maintain the data behind it, define the metrics, notice when something is wrong, and explain what the number actually means, because there's a lot of money behind those numbers. And every single day a business runs, it creates brand new mistakes in its own data. Research published from the Harvard Business Review found that almost half of newly created records have at least one serious error. So a dashboard or spreadsheet isn't something you just build once and just forget it. It is something that you keep true. This is why this is a recurring income opportunity instead of just a one-time freelance project. And the system needs to keep working each month or each week and every day. Now, pricing depends on how much involved that you are. At the lower end, you could just do a dashboard and a monthly report. That can be anywhere between like $1,000 to $2,000 a month. And once the system is running, that could be as little as 5 hours of work. In the middle tier, you can be doing weekly check-ins, answering questions throughout the month, and doing more analyses. Now you're closer to a $3,000 to $5,000 a month retainer. And at the high end, you're basically their part-time head of data. You're forecasting, helping leadership decide which numbers matter, and you're sitting on their leadership meetings. That can move you into the $6,000 and $9,000 a month range. All right, quick pause. Now, if you want to land your first job in data analytics and avoid the lengthy mistakes that I did, click the link in the pinned comment where you can find the exact steps that my students use to land their job in data analytics without going back to school. All right, now let's get back to it. Now, I know what some of y'all are thinking. Kedisha, no one is going to be paying me $9,000 for a spreadsheet. That is correct. They're not paying you $9,000 for a spreadsheet. They're paying you because they're making decisions about payroll, inventory, marketing, pricing, and hiring, sometimes tens of thousands or hundreds of thousands of dollars in revenue on the line. Nobody they trust owns the numbers, and those are very different things. Think about it from their side. A full-time analyst costs a business maybe $7,000 plus a month once you add on salary, benefits, and taxes. You're giving them most of that value back for a fraction of the cost and zero hiring risk. That is why they say yes. But here's what I really want to the seat. This isn't just a side hustle. It is a completely different way of using data skills than most career changers are doing. Now, here's the thing. I know a lot of you guys probably want to become a data analyst and work a data analyst job, but many of you don't really want to get into tech. You just want to make more money. And tech may just be a vehicle, but data analytics is your mechanism. And the people with the most money to pay for data skills aren't always posting jobs on LinkedIn. Think about how most people approach a career change. You learn spreadsheets, then you learn to work with databases, you learn how to build dashboards and some programming. Then you open LinkedIn, search data analyst, and now you're competing with everyone else who did the exact same thing. But there's a whole new market sitting right next to that one. I'm talking about, again, the businesses doing a few million dollars a year, maybe 20 employees, maybe even less than that. Startups even. They make enough revenue where bad decisions hurt, but not enough to justify building an entire data analytics department. Let's use an independent physical therapy group as an example. They may have 5 local locations and they know revenue is up. But one clinic seems to be busier than all the others and somehow not making as much money. Their no-show rate looks very high. They just added another physical therapist, and their marketing company keeps telling them that leads are great, but the owner has no clean way to answer whether any of this is improving the business. The owner doesn't wake up thinking, man, I really need a data analyst or a business intelligence professional. They wake up thinking, man, we've been busier than ever and we're not making more money. We're actually bleeding money. That is your opportunity. And that problem is not just in clinics. It's in online stores that don't know which ads actually make money, restaurant groups trying to compare locations. It's in trucking companies trying to understand fuel costs, late deliveries, marketing agencies wasting hours building reports for clients, and startups whose investors suddenly want proper metrics. Businesses have more data than ever, but having data and being able to use it to make money and save money are completely different things. What usually triggers them to look for help and hire is pain. I'm spending $20,000 a month on ads and I have no I have no idea what's working. My investors want numbers on Friday, or even worse, the one employee who understands this report is leaving. And notice who feels that pain. It's not HR. It isn't the IT department. It's the person responsible for the entire business result. The founder, the COO, the head of marketing, the owner. It's the person losing sleep because the number looks wrong and no one can explain why. And again, that's who you talk to. And here's the part most people actually miss. You might understand that person's problems better than someone with twice your technical skills. Now, for this side hustle, your current or past career is your most valuable thing that you bring to the table. And here's why. When you apply for a job, the employer is judging your tools because tools help them decide whether you can do the work. A business owner is completely different though. They're not hiring for your tools. They're hiring for someone who understands their business well enough to just fix the problem. And that's something most technical people just don't understand or comprehend. So let's say you've been working operations for 10 years. You are the person who's been tracking weekly performance and building reports for your boss. You understand schedules, track inventory, and you can notice when costs suddenly jump before anyone else does. And whenever the numbers just don't look right, someone asks you to figure out what happened. And you might look at all of that and think, you know, it's just my job. But no, those are the exact problems businesses pay someone else to solve, maybe even 2x your hourly salary right now. You already know what the questions sound like. You know which numbers people actually care about and where things actually go wrong and what the person making the decision needs to hear. Now compare that to someone who knows more programming than you, but has never worked a day inside a real business. Who do you think understands the problem faster? Exactly. What When I worked at a warehouse, I could see exactly where inventory data broke because I was physically around the inventory. I understood what happens when the system says one thing, but the box in front of you says something else. You cannot learn that from some certification or some degree. That's domain knowledge. And it's what lets you charge more than someone with the same technical skills and no context. And context is expensive. So here's what I want you to do before you go any further. Grab a piece of paper and write down 3 problems from your current or past job that involve numbers. It could be a report that you build, a cost that you know is creeping up, or a question your boss just kept asking you that no one else could answer. Those 3 problems are the start to your offer. Okay, so now you know your edge and your competitive advantage. Let's turn that into your first client. Now, the fastest way to land your first client is going to be cold outreach, and that means emailing or messaging business owners who don't even know you yet on LinkedIn or again email. But most people do this completely wrong. They will send strangers something like, hey, I noticed your company is scaling and wondered if you'd be interested in leveraging data-driven insights. That goes straight into the trash because it's all about you and not their problem. Also, your leading with leveraging data-driven insights. People don't care about that. There's only 2 things people care about with data. They want to know how data can, one, make them earn more money, and 2, help them save more money. They don't care about data-driven insights. So here's how to do it right. So step 1, pick one industry and build one proof asset. And it doesn't have to be an industry you've worked in. Once you pick one, you want to build a proof asset for it. If you're going after dental groups, build a simple dashboard showing collections, no-shows, and provider schedules across multiple locations. Step 2, build your list. Find 50 to 100 local businesses. You can use Google Maps, search dental office plus your city, and look for the ones with multiple locations. Find the owner or practice manager on their website or LinkedIn and use a free email tool finder like Hunter or Apollo to get their email. Put it all in a spreadsheet. Then step 3, reach out on email and LinkedIn. Keep your message short and to the point about their problem, not your tools. Here is an example of what it will look like. Again, it names one problem that they actually have and it doesn't ask for a meeting or a sale. It just asks if they want to see an example, and that's an When they reply, you send your proof asset and offer a quick call to walk them through it. Step 4, follow up and play the numbers. Most people send just one message, hear nothing, and then quit and just say nothing works. Do not be that person. Follow up 2 to 3 times over the next couple of weeks and make sure you're sending 10 to 20 messages per day to multiple businesses. Out of 100, you might get a handful of replies and maybe 1 or 2 calls. That is normal. You only need one yes. Alex Hormozi has a rule of 100 that I love to follow. You want to send 100 cold outreach messages a day. And the more volume you're doing that, the higher your probability of successes. Now, once you get on a call, you can start small with either a paid pilot, or if you have no experience, you can do like maybe a week or so trial. Whatever you do, make sure you have a clear scope. In your first month, you want to map out where their information lives, build one useful view, and find something that they didn't know. Maybe one location is busy but not profitable at all. Maybe their best product has terrible margins. Now you're not selling a dashboard anymore. You're showing them what better information And then when the owner asks, hey, can you keep this updated every month? Congratulations, that's the retainer. Now, getting your first client, it might take a few weeks, right? It may not happen tomorrow. You're going to hear a lot of nos and not right now, or maybe a lot of nothing. That is normal. Every consultant making over $10,000 a month started with one client who just said yes after a bunch who said no. And once you land your first client, everything's going to get a whole lot easier. And once you land your first client, you're going to run into a whole brand new problem. Time management. Here's what happens, right? You find one or two clients and then you hit a wall because you only have about 10 or few hours a week. If every client eats 10 hours, you didn't really build a side hustle. You just gave yourself another job. And this is where you can use AI to scale your business and also save you time. Here's three ways you can do it. Number one, data cleanup. Every client's data is messy. One report can have different spellings, different formats, all of that stuff. And all it does is creates problems where the numbers don't add up. Instead of fixing it all by hand, you can use AI to help clean it and also create some. Automation to clean it every month. After a while, you're going to have data cleaning templates or data cleaning recipes where next month or next week, whenever new data comes in, you just run the same recipe and it cleans it in minutes instead of 4 hours of manual work. Number 2, recurring revenue systems. This is what keeps clients paying every month. Instead of just downloading reports and rebuilding the dashboard every time, you can connect the dashboard directly to wherever the data lives so the numbers update on their own. And then you can give AI this month's numbers. Last month's, and then ask it to write in plain English a summary of what changed. You read it and then you make sure you add your own twist of what AI can't do. Like, hey, revenue is down because the North location was closed for 4 days. And then set it up with simple alerts. So if no-shows jump, the owner gets an email that same week instead of finding out a month later. That is how 10 hours of client work can go down to 3 hours. Number 3, AI-powered solutions where you charge more. Now, once a client's data is clean, you can start building things. Picture the owner typing which location has the most cancellations last week and getting the answer from their own numbers in seconds, or AI reading every customer review each month and then telling the owner the top 3 things people complain about. That's not a report anymore. That is a new capability. That is how you move from the $2,000 tier to a $5,000 tier. Just make sure you're using tools that the client actually approves because this is their private data. Now, if you're sitting there thinking, Kedeisha, I don't know how to build any of that yet. That is okay. You don't really need to do all of this on day 1. You start with number 1 and then add the next one whenever you land the next client. But just remember, when it comes to AI, you are always the pilot. AI AI is your copilot. It drafts and you check. Okay, so that's the boring side hustle where you can easily add $10,000 a month to your paychecks. And remember, step 1 is finding businesses that can't afford a full-time analyst using your past career or your current career as your edge. You land your first client with cold outreach and then you use AI to scale. And I know this isn't sexy, but boring businesses pay real money. And while everyone else is chasing the next shiny thing that's going to crash and burn tomorrow, you could be quietly building your next $10,000 a month starting today. If you wanna get started on the exact skills to actually become a data analyst and build data analytics skills, watch this next video here. I'll see you in the next one.