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"It’s easy to lie with statistics, it’s hard to tell the truth without statistics.” – Andrejs Dunkels Reflecting on when I first started in digital marketing, this quote perfectly captures my journey. I was overwhelmed by a sea of metrics—conversion rates, ROAS, CPL—it was hard to know where to focus. Over time, I realized metrics alone are misleading. Leaning into statistics, specifically Z-scores, allowed me to uncover the truth behind the numbers, pinpointing exactly when and where to optimize my campaigns and making data truly work for me. Using Z-scores as part of my process has helped me scale revenue volume by over 51.4% for 7 figure business and generate upwards of $21,000 in revenue from organic content. What are Z-scores? Example of Z-scores for a marketing campaign How and why should you use Z-scores? What are Z-scores and how to use them? Statistics was never my favourite subject—I avoided it throughout high school and university. It wasn’t until I saw its value in marketing that I decided to dive in. Don’t worry, I’ll keep this simple so you can easily replicate the process I use. So, what are Z-scores? Simply put, they measure how far a data point is from the average in a dataset. What if a data point is far from the average?   That data point is considered an anomaly . What if a data point is close to the average? That data point is considered normal . But how do you know when a data point is close or far enough to be normal or an anomaly? This is where the bell curve comes in handy. A bell curve, shaped like a hill, shows how values are distributed: most are clustered in the middle (the average), while fewer appear at the edges (the anomalies). For example, if we analyzed the volume of conversions across campaign channels, most channels would likely fall in the middle, generating a typical amount of conversions assuming you have tracking and everything else set up correctly. However, channels with extremely high or low performance would stand out as less common, appearing on the edges of the curve. It doesn't matter whether you are comparing Facebook Ads to Performance Max, or any combination of channels. You can mix in any number ads or campaigns from any platform, the framework is designed to standardize the results for the simplest comparison. I recommend using Google Sheets or Excel when you give this your first try. Example of Z-scores for a marketing campaign Below is an example of a campaign I created to outline the steps for conducting a Z-score analysis and provide optimizations insights. The process consists of three main steps: the Raw Data Table , the Average and Standard Deviation for each metric , and the Z-score Data Table . Each step builds on the previous one, and by the end of this section, you’ll have the needed steps to make construct your own Z-score analysis using your campaign data and make informed decisions. Raw Data Table Channel Leads Budget Spent Cost Per Lead Facebook Audience 8 $2,000.00 $250.00 Facebook Retargeting 15 $1,500.00 $100.00 Google Search 20 $3,000.00 $150.00 Performance Max 17 $2,500.00 $147.05 For this example, I focused on three metrics, but you can include as many as you need. Additional metrics worth considering are clicks, impressions, CTR, revenue, ROAS, and more. To begin building the framework, you’ll need to calculate the standard deviation and average for each metric. These values serve as the foundation for our Z-scores: Standard Deviation : measures how much the data varies from the average. Average : the sum of all values divided by the total number of results in the dataset. Average and Standard Deviation for each metric Z-score components Leads Budget Spent CPL Standard Deviation 5 $645.50 $63.13 Average 15 $2,250.00 $161.76 If your data is in an Excel sheet, I recommend using built-in formulas to calculate the standard deviation and average for each metric. Calculating standard deviation manually can be quite complex, so leveraging these formulas will save time and reduce errors. Feel free to use the values from the Raw Data table to practice creating your own version of the Average and Standard Deviation for each metric . Below are the formulas to use: Standard Deviation : in Google Sheets or Excel, use "=STDEV(B2:B5)" Average : in Google Sheets or Excel, use "=Average(B2:B5)" Z-score Data Table Channel Leads Budget Spent CPL Totals Facebook Audience -1.37 -0.39 1.40 -0.36 Facebook Retargeting 0.00 -1.16 -0.98 -2.14 Google Search 0.98 1.16 -0.19 1.96 Performance Max 0.39 0.39 -0.23 0.55 Totals 0.00 0.00 0.00 0.00 We’ve reached the final step of the process: calculating the Z-score for each channel and metric. Below, I’ve outlined a step-by-step guide to show how it works and how each value can inform your decision-making process. Follow the steps below: To calculate the Z-score, use the formula : (X - Metric Average) / Metric Standard Deviation X : The raw data value for a specific channel and metric (e.g., Facebook Audience and Leads). Metric Average : The average we previously calculated for the metric (e.g., Leads). Metric Standard Deviation : The standard deviation we calculated for the metric (e.g., Leads). Example : For Leads and Facebook Audience: (8 - 15) / 5 = -1.37 As you calculate Z-scores, the totals at the bottom rows and right columns will provide valuable insights: Totals Row : The sum always equals zero because the positive and negative deviations from the mean balance out. Totals Column : While not traditionally used in statistics, calculating column totals offers insights into what influences campaign performance, making it a useful addition for marketing analysis. Here are three actionable insights from the example table: Facebook Retargeting: Total Z-Score : -2.14, primarily due to low budget allocation and CPL (-1.16-0.98) Recommendation : Increase the budget by one standard deviation ($645.50) to improve performance. Facebook Audience: Total Z-Score : Indicates poor performance due to fewer leads and a high CPL. Recommendation : Reduce the budget by 1 standard deviation ($645.50). Google Search: Total Z-Score :   Indicates strong performance with CPL below the overall average. Recommendation : Maintain the current budget or increase it by 0.19 standard deviations ($645.50 x 0.19 = $122.64). Take some time to analyze the Z-score table yourself and explore additional insights. This framework allows for tailored recommendations to optimize campaign performance. How and Why should you use Z-scores? If you got this point, I hope that my explanation of what Z-scores are and how to use them proved useful for you and your campaign analysis. It's a neat framework that is standardized, easy to communicate with, and from my first hand experience it has helped scale results for clients. There is so much more to explore with this concept that I didn't expand on here but I will in future blogs and tutorials. As to why you should be using Z-scores, I recommend using the step by step process I provided and as you get more familiar with it add other metrics or reorganize the data. After all, it's hard to tell the truth without statistics so I strongly believe that this framework is a tool to help anyone gain additional insight that would otherwise be difficult to reach by analyzing raw metrics alone. More importantly it's a tool that has proved key in my ability and my teams ability to scale results.

" Given a 10% chance of a 100 times payoff, you should take that bet every time. " - Jeff Bezos As a business, marketing campaigns can sometimes be the tool that takes a 10% opportunity and turns it into a 100 times payoff. ROAS (Return on Ad Spend) is one of the key metrics to help you get there. But it’s not always easy to know when to start, keep going, or hit pause on your ad campaigns based on revenue alone. That’s why I put together this piece—to break down what ROAS is, when to use it, and how you can use it to push your results even further. ROAS (Return on Ad Spend ) is exactly what it sounds like—it's a simple ratio between the revenue generated and the amount you spent on your ad campaign. Basically, it's your return on investment. For example, if you spend $20,000 on ads and make $40,000 in return, your ROAS would be 200%. Here's a quick formula: Revenue from Campaign / Amount Spent on Campaign = ROAS So, if you spent $20,000 and made $40,000 in revenue: $40,000 / $20,000 = 200% ROAS Using ROAS to measure the return on your investment is a great way to understand and manage whether your campaign is meeting, under-performing or exceeding your expectations. When Should You Care About ROAS? How Should You Use ROAS to Measure Success? Final thoughts on ROAS When Should You Care About ROAS? If you're running any sort of ad campaign and want measure results by the amount of revenue generated , ROAS is one of the best metrics to track alongside revenue. It gives you a clear picture of how much money you're making for every dollar you spend on your campaign. So, if you spend $10,000 and get $20,000, $30,000, or $40,000 in return, your ROAS would be 200%, 300%, or 400%, respectively. So you should care about ROAS if you want to quickly figure out when your campaign is losing money, breaking even, and turning a profit! Remember, ROAS Fluctuations are normal - especially on a daily basis When I first started in digital marketing, I used to panic whenever ROAS fluctuated, especially during the first week of a campaign. That anxiety would peak as the end of the month approached. Here’s some advice that helped me manage those nerves and improve my campaign management— your ROAS won’t always be static . One day it might hit 300%, the next it could drop to 200%, or land somewhere in between. Performance marketing naturally has its ups and downs. Just remember that so as long as you're staying within the 200% to 400% ROAS range, your campaign is doing well and generating a solid return. Plus, you can always optimize your audiences, ads, and settings to push those results even higher. I’ll dive deeper into that in a future piece. Here's a general ROAS benchmark you can use, but be sure to make adjustments based on data, unit economics and results you have available: 200% ROAS and beyond - You're generating a positive ROI. 100% to 200% ROAS - You're breaking even on your investment. O to 99% ROAS - You're spending more than you're getting in return. How Should You Use ROAS to Measure Success? Think of your campaign like a flight—it takes off, rises, adjusts, and lands. Some days your campaign will soar, and other days it’ll dip. So how do you know if your ROAS is too high or too low, and what should you do about it? The answer depends on a few factors: The seasonality of your market or target audience. The supply and demand of your product. Your brand's promotional calendar. There are plenty of other factors that can impact your ROAS, but these three should help you get a sense of when fluctuations are likely to happen and how to react. For example, running a Black Friday campaign on Google Ads or Meta Ads is a great way to boost revenue for an e-commerce brand, but the same strategy might not work as well for a real estate agency focused on lead generation. Make sure you’re setting expectations based on real time data and upcoming events that might affect your campaign’s performance. Final thoughts on ROAS If you're looking for a good way to measure how well your campaign is turning ad spend into revenue, ROAS should be the metric that is at the top of your list to track. Other useful metrics to use alongside ROAS are POAS (Profit on Ad Spend), MER (Management Expense Ratio), total revenue generated, and AOV (Average Order Value) to name a few. Just remember, when it comes to ROAS, some factors are within your control, and some aren’t—so prepare as best you can to navigate through those fluctuations. In a future piece, I’ll share how you can calculate and predict these fluctuations using key metrics.

"Stopping advertising to save money is like stopping your watch to save time." - Henry Ford Ever finish watching the NBA playoffs, the Premier League, or anything entertaining and wonder how you’ll get by without it? Or maybe after reading a great book, watching a Christopher Nolan movie, or enjoying an amazing meal, you immediately start thinking about when is the next time you can experience it again. Whatever niche you’re into, you’re part of a market, and the choices you make as a fan or consumer place you squarely within a target audience. One of the most crucial aspects of structuring a marketing funnel is understanding your market, and more importantly, the decision-making process of your target audience. Take Starbucks and your local coffee shop—they both sell coffee, but people choose them for different reasons. The same goes for fine dining versus McDonald's, or people who run versus those who lift weights. They may all exist within the same broader market—beverage, food, or fitness—but each niche attracts a distinct audience, and sometimes, there’s even crossover between them. That’s why structuring and timing your marketing funnel correctly is key to gaining as well as maintaining a foothold in your market and reaching your audience. I’m here to help you do just that—by explaining the different stages of the funnel, how to time your campaigns, and choosing the right channels so you can avoid being in a position where cutting back on advertising to save money feels like the only option. The Stages of the Marketing Funnel Think back to the first time you heard about one of your favorite brands. Maybe it was through word of mouth, or while scrolling through TikTok, YouTube, Facebook, or Instagram. When you discovered that brand, it was exciting—you likely resonated with it and maybe even started considering a future purchase. This is known as the awareness stage or top of funnel (ToFu—just like the food!). It’s the moment when you’re casually watching TikTok or YouTube, and suddenly your screen is interrupted by an ad. You might not think much of it at first, but the next time you see it, the brand will feel familiar. The awareness stage is essentially your first impression of a brand. The first time you visited your favorite brand’s website, followed them on Instagram, or liked their content was the moment you moved from simply being aware of the brand to considering what they offer—this is known as the middle of the funnel (MoFu). It’s when you start comparing it to other brands, maybe you’re even researching and taking notes if it’s a big purchase or something you care about a lot before making a decision. Essentially you want to take your time to make a conclusion, and marketers are aware of this. That’s why it’s a priority to engage as much as possible with people who are at this stage of the funnel.  After finding a brand that sells what you want and researching and comparing it to other products, the day finally comes to make your purchase. You’ll likely head to Google Search, type in the brand name and model of the item you want, click the first link that pops up, complete your purchase, and wait for it to arrive. At this point, you've reached the Conversion Stage, also known as the bottom of the funnel (BoFu). And who knows—depending on the information you’ve shared on the website or at checkout, you might start receiving emails or social media ads suggesting other items to purchase from that brand or products commonly bought with your purchase. Or maybe you didn’t even go through with your purchase and you still get the emails and ads. Sound familiar? Before diving into creatives, social media platforms, ad copy, or any other details to run a successful marketing campaign, you need to understand the behavior of your target audience at different stages of the funnel. This will guide the structure of your campaign to effectively reach your audience. In the awareness stage (ToFu), think about how you want to introduce your brand to someone who’s never heard of it. In the middle stage (MoFu), focus on content that keeps your audience engaged—whether it’s a blog, an informative short form video, or a comparison of your product to competitors. The goal is to keep your audience informed as they consume content and weigh their options. Finally, there’s the conversion stage (BoFu), where you want to encourage people to buy your product and potentially come back for more. You might also need to follow up with those who abandoned their cart and just need a gentle reminder to complete their purchase. Plan your Campaign Timing Understanding how your audience behaves at different stages of the funnel is key, but it’s equally important to consider when they will need your product or service. This concept, known as seasonality, refers to how demand for your product fluctuates based on the time of year, month, or even day. For example, as fall and winter approach, more people start buying Pumpkin Spice Lattes and playing Mariah Carey right after Halloween. It's crucial to recognize how sensitive your product is to these shifts in behavior over various periods of time. Keep in mind that seasonality can last anywhere from a few hours to several decades, so it’s essential to analyze your data—or work with someone who knows how to do that effectively. One of the tools I use to track seasonality for a product or promotion is Google Search Trends. Take back-to-school season, there’s a clear cut connection between the end of summer, the winter holidays, and students heading back to school. Many bookstores, online stationery shops, and other businesses see sales fluctuate during these times. To better understand this, I looked up the popular “Back to School” promotion as a search term on Google Search Trends and found this graph based on 5 years of data. I’ll share my insights below. Let’s say I have a client interested in running a back-to-school promotion and they want to know when to launch their marketing campaigns globally. I tend to visualize data, like the graph above, to get a sense of when seasonality tends to occur. The graph shows 5 tall peaks and 5 shorter ones, with some smaller bumps in between. If you hover over the tall peaks, you’ll notice that August consistently shows up across all 5, though the exact dates vary. Similarly, the shorter peaks consistently point to January. This gives us a clear idea that August and January are the two key months when my client can expect the highest sales. Although this is a fictional example, it’s always important to cross-reference this kind of data with internal sales, conversion, and other relevant information to ensure that the fluctuations you observe align with what your business actually experiences. So, we’ve identified January and August as the best months to maximize sales, but we still need to determine when my client should launch their campaign. Launching in January or August wouldn’t be ideal since that's when interest among the target audience peaks—we want to make a strong first impression long before they start finalizing their purchasing decisions. To pinpoint the best dates, I like to analyze data from the last 12 months to identify more specific timing. Based on the graph below, we can see that interest in "Back to School" began to pick up as early as the week of May 19th-25th in 2024. For the smaller January peak, interest starts rising around Christmas time. Choosing the Right Digital Channels Before choosing, setting up, and using all sorts of audience targeting settings on advertising platforms, it’s wise to do an audit. Whether you have me, an agency, or someone working in house doing this, audits are an opportunity to learn what went right, but more importantly what went wrong with campaigns from the past. It’s the one opportunity to set up the best possible conditions for your team and your business to reach the conversions and sales goals that you have set out for yourself.  Since my fictional client has never run a digital marketing campaign before, we’ll assume they have a strong organic presence among students and parents. Based on our understanding of the marketing funnel and the seasonal trends we’ve just analyzed, I’d recommend an omni-channel approach with Google Ads and social media as the primary drivers to maximize sales. Below is a general guide to the channels I would suggest at different stages of the funnel. It’s also important to note that funnel structures can be dynamic—there’s no one-size-fits-all solution for every business. Always take the time to research the unique composition of your target audience and how they engage with your business. Funnel Stage Objective What Channels to use? Budget Allocation ToFu First Impression and awareness Youtube, TikTok, Meta, Demand Gen, etc 10-20% MoFu Engage with users Channels where your target audience interacts with you 20-30% BoFu Maximize Sales and/or conversions Retargeting audiences, search engines, and market- places 50% or More For the top of the funnel (ToFu), I’d suggest my client focus on making a strong first impression with as many new people as possible, especially students and parents for a "Back to School" promotion. Whether they want to advertise specific products or just the overall promotion, the first step is letting the target audience know that my client has a promotion that just launched. I usually recommend launching the campaign and promotion simultaneously to keep the user experience seamless. Pre Order campaigns can work too, but it’s important to clearly share the Pre Order details in the ad copy and creatives to avoid any confusion about what the user is getting. After factoring all of this in, I’d typically allocate 10-20% of the total ad spend to top-of-funnel channels that generate a lot of impressions, like TikTok, Social Display, Display,  YouTube, YouTube Shorts, and Demand Gen. For the middle of the funnel (MoFu), I focus on channels that encourage strong engagement between the business and users. At this stage, the goal is to engage users who have recently learned about my client’s “Back to School” promotion and direct them to the landing page. Typically, you’d allocate 20-30% of your ad spend to platforms like Meta, Pinterest, Reddit, or any other channel that fosters meaningful interactions between your business and target audience. Be sure to advertise on platforms that encourage interactions like comments, likes, and follows. These meaningful interactions can then be used to create custom audiences, helping to further optimize campaign results. At the bottom of the funnel (BoFu), you’ll likely allocate 50% or more of your budget to ensure you’re converting as many users as possible. The results here will show how well your initial impressions and consistent interactions have worked throughout the funnel. At this stage, you’ll want a mix of retargeting audiences from the social media channels you’ve used earlier in the funnel and Search Engine channels like Google, Bing, Amazon, and any other high-converting platforms for the business. This helps reach the users most likely to make a purchase during the “Back to School” promotion. Final Thoughts If you take the time to truly understand your target audience and what they expect from your business, you’ll be able to maximize the results of any digital marketing campaign. Focus on making a strong first impression, maintaining consistent engagement, and staying active on platforms where your audience makes purchasing decisions. Plan your campaign to align with the seasonality of your market, like summer and winter holidays for a “Back to School” promotion. By understanding your audience’s decision-making process and the seasonality of your market, you’ll be in a great position to choose the right platforms to sue for your marketing campaign. With a strong marketing funnel you won’t find yourself in a position where cutting back on advertising to save money feels like the only option.

“He who does not risk, will never drink champagne” - Proverb Sometimes, we take a chance on something without knowing if it’ll pay off—that’s exactly how I felt when I first strapped on my Whoop. I even sent a photo to a friend, thrilled to use his promo code (and hey, I’ll shamelessly link mine here  too!). I checked my metrics the next morning, thrilled to start tracking my sleep, and within the week, I was convinced: monitoring my health was the key to achieving my fitness goals, running that half marathon I’d been talking about, and—most importantly—finally sleeping well. It felt like the start of my own Rocky-style transformation montage. Over the past three years, I’ve felt the rewards of using Whoop, but recently, I had the urge to dig deeper with a data project to analyze my journey, especially around fixing my sleep schedule. I wrote this piece to show why monitoring and prioritizing your sleep is one of the best investments you can make—if not today, then definitely by tomorrow. Most of my life, I only slept when absolutely necessary—I’d rather stay up partying, have a few late-night brews with my friends, play video games until dawn, and prioritize anything but sleep. Eventually, all those late nights caught up with me, and I started having trouble falling asleep. I wondered if it was just a lack of hours in the day or if there was something wrong with me. So, I checked Google Search Trends to see how “sleep” had trended over the past 20 years. Turns out, the top search query was “can’t sleep” or some variation of that, and seeing it wasn’t just me struggling was a relief, so I went back to business as usual. Top Search Queries Related to Sleep Even after I had Whoop tracking my every move and telling me that I wasn’t getting enough sleep, I still didn’t feel the incentive to change anything. I was fully committed to my lifestyle, which didn’t seem all that unhealthy to me. I was working out, building up a career, and having a great time—just like everyone else, or so I thought. But when I realized that simply monitoring my health wasn’t enough to make a real difference, I decided to try something revolutionary: going to bed early. Metrics and Hypothesis A nalyzing my sleep & HRV W as it all a coincidence? Final Thoughts Metrics and Hypothesis from Whoop Of all the metrics Whoop tracks, I chose my total sleep duration and Heart Rate Variability (HRV) as my focus for this analysis, I chose HRV to measure against my sleep duration because it’s often regarded as a solid indicator of overall health, reflecting stress levels, autonomic nervous system balance, cardiovascular health, and sleep quality. Put simply, the higher your HRV on a given day, the better the state of your health. Going into my analysis, I hypothesized that the more I slept, the higher my HRV would be. Quick Note : I’m not a health professional, and HRV alone shouldn’t be taken as a health diagnosis. This analysis is a personal project to explore how sleeping earlier might have positively impacted my health.  Analyzing my sleep & HRV I thought wearing the Whoop would be the hard part, but I was way off. I assumed that tracking my sleep would somehow make me sleep better, with no extra effort needed. Reality hit when, in my first month, I discovered I was averaging a daily sleep deficit of 3 hours and 27 minutes. After a year, it worsened to 3 hours and 42 minutes. I wasn’t getting any healthier and clearly missed something important. I always thought 6 to 8 hours of sleep was ideal, and with so much to do in the day, I usually settled for 6 hours. In the graph below, you’ll see I didn’t reach a 7-hour sleep average (Y-axis on the left) until May 2022—9 months into my Whoop journey. Interestingly, that’s also when my HRV made its biggest improvement. Motivated, I aimed to sleep earlier, but life got in the way (I moved), and I delayed my plan.  By July 2022, I was back on track, only to relapse by September. Over the following months,I kept going through a similar cycle. It wasn’t until May 2023, where I finally began to consistently sleep close to 7 hours or more—and I’ve maintained it since. My HRV is far beyond the 140 mark it started at in August 2021, and I feel more energized and better overall. Was it all a coincidence? Looking back, it’s great to see that making the adjustment to sleep earlier was paying off in terms of getting more sleep. Later on I also made some other lifestyle adjustments beyond going to bed earlier like: drinking less alcohol, avoiding blue light before bed, and, believe it or not, not checking my phone for 30 to 60 minutes after waking up. Even though the metrics I chose to focus on showed that sleeping earlier and other sleep hygiene habits were paying off, I still needed to answer the following question: Did going to bed earlier significantly increase my sleep, and did that impact my HRV? Or was it all a coincidence? Since HRV and sleep duration used different units of measurements, I had to standardize them for a comparison to understand whether their peaks and troughs were related. I used Z-scores as a way to achieve this and plotted the results in Graph 2.0. Essentially a Z-score let me know how my HRV was impacted as a result of sleeping more or less hours. For example you can see that after May 2023 both the bar chart and line graph stay above zero more often than they go below it. This means that both my sleep duration and HRV were above my all time averages for each respective metric. In other words, since starting to consistently sleep earlier in May 2023 I started seeing a statistically significant improvement in the amount of sleep I was getting and my HRV scores. Final Thoughts While I may not be sipping champagne to toast my improved sleep, changing a lifestyle I was so accustomed to felt like a genuine risk. As I explained in my analysis of sleep duration and HRV, there were several setbacks along the way, with plenty of times where I slipped back into old habits. But this data analysis revealed that going to bed earlier and some additional lifestyle changes had a big payoff, both in the amount of sleep I’m getting and in my overall health. Interestingly enough, remember how I said the top related search queries to sleep are “can’t sleep” or some variation? Remember how it gave me some relief for my troubles when I first started this journey? Well I recently looked at the same search trends I first searched up in August 2021 and turns out that this trend has been on the rise since. So if you are someone who relates to anything that I said in the opening paragraphs, then give going to bed earlier a shot. Who knows you might feel better the next morning and at the latest, you can give it a shot tomorrow.