Meaghan was recently interviewed on Lena Elkin’s podcast, Unfiltered.
Check out the full episode below along with our insights on the most important points.
How did Meaghan get her start?
Meaghan grew up in a home that was not entrepreneurial at all. No one in her family had ever gone to college, so she was taught that management was the goal. If you could reach management, you had arrived.
She had her first taste of entrepreneurship in college selling encyclopedias door to door. This experience allowed her to become her own boss and manager her own “company”. This opened her eyes to how her own individual contributions affected her income. Through this experience, she learned the value of being 100% responsible for herself and her outcomes.
After that, she became a sales consultant, but still under an organization. During this time, she met AJ. AJ is an entrepreneur through and through. He started creating companies at age 10, so he opened her eyes to the possibilities of entrepreneurship.
One of the biggest transitions that she had to make was to shift her mindset from individual contributor to growing a company.
Luckily, her journey with data started much earlier.
Meaghan was the math nerd from an early age. She jokes that she had more math books than friends. Meaghan loved math and numbers because everything had a correct response. Everything was either right or wrong, and it was clear why.
She had planned to become a math teacher, but upon discovering her gift for sales, she decided to focus on hustling while she could and teach later in life.
The sales bottleneck
In all of Meaghan’s sales experience, she relied on her inputs to create outputs. She either knocked doors to get sales, or she cold-called businesses to get sales. Enter AJ.
AJ worked in marketing, and Meaghan wanted to learn more about what that meant. So she shadowed him working on a client. The client had set up a course that he wanted to sell, so AJ set up a sales funnel and landing pages, and then sent out an email to his list. They had 500,000 on that list, so they sat back and waited to see the responses. Within 8 hours, the campaign had cleared $1.2 million.
Upon seeing this, Meaghan knew that she needed to make the jump from sales to marketing. Because of her background in sales, she helped with copy and closing clients. Upon spending some time in the agency, she began to notice patterns in the data.
In her time working in sales, she would split test approaches and different scripts. Over time, she perfected her sales pitch. Upon making the switch to marketing, she realized that they did the exact same thing, just on a larger scale, and with more automation.
The marketing bottleneck
While running the agency with AJ, they had to report back to their clients on the progress of their campaigns. So they had a marketer who had to run reports for clients all day, every day. He wasn’t able to do anything else because they had to get this data to their clients.
So Meaghan started researching ways to automate their reporting. She found the solution in the world of data analytics and business intelligence. She found that many of these programs could automatically do what they had someone doing by hand. The programs could extract the data from all of the different sources, aggregate it, and even display it in an easy to interpret format.
Once they rolled out these reporting solutions to their clients, they naturally wanted more. They wanted more information on their business and wanted that same powerful reporting for everything. Ultimately, everything that Meaghan worked on led her down the path to Praxis.
AJ and Meaghan pivoted their marketing agency into a data analytics agency, and now help business owners and marketers understand their businesses better through data.
How to take advantage of your data
The first thing that you need to do to truly take advantage of your data is set your ego and emotions aside. As Meaghan talked about earlier, numbers allow you to see in black and white. Rather than focusing on how they make you feel, you can use that information to help you grow forward and progress.
The next thing that you need to do in order to truly take advantage of your data is a process called “ETL”. ETL stands for Extract, Transform, and Load. Essentially, you need to extract raw data from the back ends of your systems, then transform it to make sure that it accurately reflects what you want to measure, and then load it into a business intelligence or visualization tool.
Lots of solopreneurs and early stage entrepreneurs end up needing to learn sales and marketing in order to get their company off the ground. Learning data as well would likely push anyone over the edge.
That’s a big reason why Praxis shifted down-market. We used to work with larger companies, but we found that they needed answers to the same questions that the little guys did. Everyone wanted to know what worked, what didn’t work, where to spend more money, and where to cut spending in order to better optimize.
The best time to start thinking about integrating a BI or dashboarding tool is after you’ve already hit $250,000 in revenue. For businesses pre-$250,000 it’s best to focus on tracking. Too many businesses wait until they get big in order to worry about their data; but you can’t leverage data that you don’t have. Every business needs to set up tracking, and the earlier you set it up, the better.
Most businesses spend all of their time worrying about their copy and their look and feel, but they neglect their tracking. Google Analytics is one of the most underutilized and error-prone tools on the market.
We see lots of big companies that come to us with very little or no data available to them, looking for answers to their business questions, but they don’t have any data. We have to take them back to the beginning and help them set up their tracking, and then we can help them analyze the data as it comes in.
Data is sexy.
Lots of people view data as something that happened in the past, and therefore not something that can help them in their current situation; however, the true power of data is that it can help you see the patterns in the past, and then predict and shape the future.
As we covered earlier, it’s very important to get started as early as possible with this process. So now we want to cover how you can get started:
UTMs are a free tool that every business can and should use for all of their marketing. UTMs allow you to pass information through URLs in order to better track where your traffic comes from. Adding UTMs to your external links allows you to understand how your customers found you and what content they interacted with.
UTMs allow you to see much cleaner, more granular data about the performance of your marketing efforts. This allows you to get better insights, allowing you to decrease waste and double down on what works.
If you want to learn more about UTMs, we have a course that walks through how to build them and gives you tools to help you automate the creation of your UTMs. Here is the link to that course.
AJ and Meaghan recently had the opportunity to have a chat with Bernard Kelvin Clive of the BKC podcast.
It was a great opportunity to get a multi-cultural perspective on business growth and development. Check out the full interview below:
Data is the fuel for business success
In today’s marketplace, every business works in the data business. No matter what business or industry you fall into, data is vital to your success. While many people still think about data in terms of “big data”, every business can capitalize on the data they have.
While almost everyone understands that data has value, few businesses know what data they need to leverage to scale.
When we talk about data, the key point to remember is that data doesn’t involve crazy math or calculations. Data is just information. Eventually, once you have enough information, you can begin to recognize patterns in the data, and predict the future.
Every business has the power to access “big data” at this point. Most programs that businesses use to run their operations contain data on the back end. This includes things like: when your clients buy, how much they buy, what they buy, and so much more. Just having that small amount of information can help you understand your customer journey’s better. Once you understand their journey, you can better market your products and services.
No matter the stage of your business, you can be doing things with data
At Praxis, we often talk about the data maturity spectrum. No matter where your business falls on that spectrum, there are things that you can and should be doing to make sure that you can get the most out of your data.
If you’re at the beginning of your business, this could be pre-revenue or just starting out, the best thing that you can do is start collecting data. Lots of businesses in the start up realm still have CRMs, POS systems, websites, etc. Each of these systems can be a treasure trove of data if you set it up to track data. Most small businesses though don’t take the time to make sure that they have everything set up to track properly.
You can’t create data from scratch
The reason that it’s so important to set these things up early on in your business is because you can’t go back in time and create historical data. So if you find yourself ready to start analyzing data three years from now, and you haven’t set your systems up to track your customers properly, then you have to start completely from scratch.
You can’t make data-driven decisions without data, and you can’t get data without taking the time to set up your tracking.
More is better when it comes to tracking
Even if you don’t have the time to analyze your data, it’s very important that you start tracking it now. The more that you can track, the better. While you may not use all of it in the future, it’s much better to have too much data than too little data.
Whoever has the greatest understanding of their customers will win in the end.
Several of the biggest companies in the world are strictly data companies, and part of the reason that they got so big is because they collected data to better understand their customers.
Data helps you better understand your customers needs and wants; this allows you to better target and attract the right customers, as well as retain your current customers.
As a business owner, data analysis isn’t your responsibility
Your job as the business owner is to make sure that you have properly invested the time and resources into gathering the data. If you’ve done that, you can have specialists analyze the data for what they need. Your marketing team can scour the data for better customer insights, your project management team can find bottlenecks in your processes, etc.
In order to make sure that you track the right things, you need to know what metrics matter. Too many businesses track everything and then get caught in paralysis by analysis. They end up spending time worrying about metrics and numbers that will only make a small difference, if any.
The key to analyzing your data is making sure that you look at the metrics that will yield results for your business.
The best way to find these “needle moving” metrics is to figure out what business questions you need answers to. Generally, you can narrow down the metrics that you need to keep an eye on down to 5-10 metrics. We recommend “leading with revenue”, which means that you should focus on marketing and sales first.
Wrapping up the foundation level
To summarize the foundation level of data maturity, track everything, but don’t feel like you need to analyze everything that you collect. That is reserved for stage 2.
Stage 2: Analysis
Once your business has matured to the point where you want to start leveraging your data, you’ve reached stage 2.
You don’t necessarily need to analyze the data yourself. You can have your team analyze it, agencies that you work with, or you can do it yourself if you’re data inclined.
One way to start analyzing your data is to figure out the business questions that you want to answer.
The number one question we recommend that every business owner ask is “where do my best customers come from?”. Every business should have a clear answer to this question. You should know what marketing efforts create customers that come into your business and stay with your business.
Another way to analyze your data is to just start looking, and then see what questions arise as you look at the data.
Sometimes, by digging into the data, you can spot anomalies or outliers that spark your curiosity.
Many business owners think that they don’t have the time to analyze their data, and that’s why it’s important to set aside time to do it. Make data analysis a priority and chunk out time to at least poke around in the data. You can spend that time looking for answers to questions, or looking for anomalies. Either way, it’s important to keep your finger on the pulse of your business.
Most businesses are just one data-driven decision away from exponential growth
As we said in the last section, it’s very important to at least wade into your data once a week. Additionally though, it’s important that you schedule time to deep dive into your data, at least once a year.
AJ and Meaghan realized during one of these deep-dive sessions the key to exponentially growing their business. They realized that they wrote off hours like crazy in order to keep their clients happy. They over-delivered on their promises to make sure that they had raving fans.
This yielded them happy clients, but when they looked at their numbers, they realized that it had cost them $500,000 across the course of a year. This one thing was preventing them from scaling their business properly.
They decided to start scaling back the amount that they would write off with each client. They decreased how much they would write off each month by just 25%. This caused them to increase their revenues by 350% year-over-year, and their profit margin skyrocketed up by 1,000%! This allowed them to scale their team up to 10X the size that it was.
The definition of insanity is doing the same thing over and over and expecting different results. Until you analyze your data though, it’s hard to know what you need to change.
A positive data-driven decision
We had a client who came to Praxis looking to get better information on the lifetime value of their customers (LTV). They thought that they had an accurate idea of what it was, but wanted to double check to make sure that it was accurate. Together, we discovered that the lifetime value of their customers was much higher than they initially thought. Upon realizing this, they decided to increase their allowable cost per acquisition by just $5. This decision caused the funnel to go from about 12 sales per day to 350 sales per day in just 2 weeks.
From there, the funnel kept expanding, and within a month, they started to average 600 sales per day on this funnel… All from one data-driven decision.
A negative data-driven decision
We had another client who thought that they knew their LTV, but once we got into their data, we discovered that they had overestimated their LTV. Because of this, the company found out that they were actually losing about $3 per customer that they brought in. And they were doing a lot of sales…
Because they sought Praxis help though, they managed to stop the bleed and update their spend to reflect their reality.
The data will tell you what to cut and what to double-down on.
What is the next step, where should businesses go from here?
The answer to that question depends on where you fall on the data maturity spectrum. If you are stuck in phase one, you need to get your tracking set up. If you’re stuck in phase two, you need to determine if you need help understanding the data and taking action from it.
The best thing that everyone can do right now is run an audit of your systems and see where you stand in your business. Diagnose where you fall on the data maturity spectrum, and from there you can see what next steps you need to take.
Another huge thing that helps all companies regardless of size, is to aggregate your data in one place. Some people call this phase “spreadsheet hell”, because it generally requires a lot of spreadsheets. If you want to avoid spreadsheet hell, we recommend leveraging a business intelligence (BI) tool. BI tools are much more expensive than just using spreadsheets, but they also allow you to perform much more complex analysis and leverage the data in new ways.
Tools won’t solve your problems
It’s important to remember that even if you buy a BI tool, it’s not going to solve your data problems. You still need to have your tracking in place, and you still need someone to analyze the data. Additionally, you need to have plans in place to take action on the data. If you see a dip in your data, you should have a plan in place as to how you want to deal with it.
Every company needs to start thinking about their data as one of their most valuable resources.
Data just surpassed oil as the most valuable commodity on the planet. Information is king. If you know more than your competitor does, then you have an opportunity to outmaneuver and outperform them at every turn.
Caesar’s Palace recently went bankrupt. On their balance sheet, they listed out their data as the most valuable asset that they had.
Every interaction with your clients is an opportunity to learn something new. If you’re properly tracking everything, then you can gain insights and scale your business infinitely faster than by going off gut instinct.
The fastest way to scale your business is to figure out what is already working, and double down on it.
What can people do to better use data in the world of branding?
Start tracking creatively. Tracking doesn’t have to just be about how many people came to the website, or how many people clicked a button. You can track anything that you can imagine. We had a client come through who used Instagram as their primary lead source. They went through all of their posts and tracked what colors they used in the post, how they framed the image, the location, everything. They then overlaid this data with their like, share, and comment data to find optimal posts.
Because they had this data, they knew exactly what their customers wanted to see from them and when. This allowed them to double down on the things that worked for them and cut out the waste.
In this podcast episode, we decided to cover some less common topics.
We cover deep dives into entrepreneurship, how to manage a business and a relationship, and much more.
How did AJ and Meaghan get here?
AJ started out as an entrepreneur early in life. He started a “company” called “AJ’s odd jobs” as a child, offering to do household chores for his neighbors. From there, he graduated to selling his family’s agricultural produce door-to-door. Finally, he moved into the technology sphere, building and selling computers; from there, he started a magazine, and then moved on to selling supplements online. While selling supplements, he found that he loved doing data-driven marketing, so he decided to create his own marketing agency.
Meaghan took a different path. Growing up in a large household with a single mom, the focus was always on finding a job and making it to management. As a way of paying for college, Meaghan sold encyclopedias door-to-door. This exposed her to the idea of being her own boss and “running her own business” while still having the support of an organization behind her. Because of her success in sales, she pivoted into a sales-coaching and consulting role.
Upon meeting AJ, she decided that she wanted to learn more about marketing. At the time, AJ’s business focused on building out funnels for clients. She decided to shadow them to understand what they did for one client from start to finish. She watched them build the landing pages and sales pages, and then watched AJ send out the email campaign.
Once she saw the success that they generated with little effort, she realized that she needed to jump from sales to marketing.
They started working together in the marketing agency together, and found that one of their biggest frustrations was getting data for and to their clients. This frustration eventually led them to the creation of Praxis Metrics. In finding a solution for their reporting, they found that all of their clients wanted to implement that solution for themselves. Eventually, that grew into Praxis Metrics.
How did Meaghan and AJ meet?
They met through a series of mutual friends who thought that they would be perfect together. They say that the universe was trying to get them together for a long time, but they had a hard time with the timing.
Once the timing was right though, they moved quickly, dating for only a few months before moving in together. Then they started running a business together a few months after that.
How do Meaghan and AJ get along so well?
Because they own a data-driven business, they of course are data-driven in their lives. They take personality tests to understand what roles and responsibilities each of them fit into well; they study each other’s love languages to know how to help the other person. And then finally, they took brain scans to understand how their minds work.
They primarily used the brain scans to better understand how their brains handle stress and stressful situations. They hook you up to the machine, with nodes across your entire head, and then put you through stages of stress and then recovery. By repeating this exercise, they gained a greater understanding of how each of them deals with stress psychologically.
Through these tests, they grew to better understand one another’s needs and why they behave the way that they do.
What advice would Meaghan and AJ give to other “power couples” or business partners?
Clearly delineate roles and responsibilities. This allows you “divide and conquer”. The best way to do this would be to map out each other’s strengths and then assign tasks that align with those strengths. This allows each of you to focus on your “superpower” and achieve individually as well as together.
The other piece of advice would be to communicate. Communication needs to be clear, and concise; and then you need to allow vulnerability in that communication. AJ and Meaghan like to do “check-ins” with one another to really check to see how they’re progressing in their roles as business and relationship partners.
How do AJ and Meaghan break up their professional and personal lives?
At the moment, they don’t really. Since the business is going through a phase of rapid expansion, they are on call all of the time. But they also recognize the importance of decompressing. They recognize when they approach their breaking points, and make sure that they don’t cross that line.
They make sure that when they do take time for themselves, they put away all things related to work and focus on being truly present in the moment.
Even in their professional lives, they work together to make sure that they align and don’t get too wrapped up in one thing or another. Because they have such open communication, they can tell one another when they need to take a break or realign.
They also use travel to force themselves to realign and get more into the moment. AJ and Meaghan built Praxis Metrics to allow all of the employees to travel and escape from the routines of office work. They encourage all of their employees to take trips and take advantage of the opportunities that come with working remotely.
Meaghan specifically uses travel to help her remember why they built this business and what their long-term goals are, as she can often get lost in the details. But by traveling, she can create opportunity costs for herself, which forces her to choose what she finds truly important.
Because they have this opportunity cost, it forces them to delegate more, and utilize their time as profitably as possible.
How Meaghan and AJ use NLP to help them focus
By learning NLP (neuro-linguistic programming), AJ and Meaghan worked to understand how their communication styles would differ based off their brain types. Since Meaghan is naturally “chunked down” or in the weeds, it becomes difficult for her to communicate with someone like AJ who naturally “chunks up”. Because they both know about these issues, they developed keywords and phrases to help them better communicate and relate to one another.
What “Bio-hacking” secrets would they recommend?
Meaghan and AJ use biohacking to better understand their bodies, and therefore increase their effectiveness. Because our DNA and our genes are the building blocks of who we are, it’s important to start there. They went to genetic coaches who read their genetic profiles and gave them actionable information on how to maximize the effectiveness of their bodies.
After understanding your genetic code, the next thing that they recommend is to get blood-work done. Generic doctors most likely won’t look at your blood-work to the depth that you need if you truly want to “biohack”.
The point of all of this is to increase the amount of data that you have on your body. The more data that you have, the more of a complete picture you can put together of how to optimize your body. Once you have this data, you can begin to change your lifestyle to better fit your needs.
How to truly get ahead in business and health:
Data will never solve problems; it’s just individualized facts. Data becomes valuable when you get enough of it to create information. Once the information forms a pattern, it can lead to knowledge. By leveraging knowledge, you can predict outcomes, which is wisdom. From there, you can take action on your predictions, which is the definition of Praxis.
What is Praxis Metrics, and what do they do?
Praxis helps businesses transform their data into actionable insights.
Just like the process that we just outlined, Praxis helps businesses take disparate data points, merge them into information, transform that information into recognizable patterns, and then make predictive models based off that.
By gathering all of your data and information together, you can see patterns across seemingly disconnected pieces of data and information, and then leverage that into action, or Praxis.
Big data used to be reserved for the enterprise-level companies, but now almost all businesses have an overload of information available to them. The problem now is deciphering the data and finding the valuable insights.
Praxis Metrics extracts the raw data from the back end of each of the systems in order to guarantee accuracy, and then they merge the data together to help our customers understand how to best take advantage of that information.
The goal of the entire process is to help business owners easily discover hidden areas of opportunities; as well as areas of waste.
Finding these things helps businesses achieve explosive growth. By eliminating the waste, and reallocating it to areas of opportunity, businesses can scale much faster than they thought possible.
Praxis Metrics primarily deals with waste. Praxis’ goal is to help eliminate wasted time, energy, and money. Once you eliminate the waste, your optimization efforts are exponentially more effective.
Praxis Metrics success stories
Praxis had one client that was spending an incredible amount on cold media. They thought came to Praxis asking for the lifetime value of their customers (LTV). Upon drilling into their data though, we helped them realize that they hadn’t taken into account all of their costs, and this meant that they were losing money on every customer that purchased.
Another client thought that they could only afford to spend $15 to acquire their customers. They came to Praxis and we helped them realize that the lifetime value of their customers was much higher than they thought. Based off that information, they increased their CPA by just $5 and saw explosive growth. That funnel ended up increasing in sales by more than 2,000 in a month. Because of this success, they hired a full-time data scientist to their team, and build their own dashboards. One data-driven decision revolutionized their company.
What does working with Praxis look like?
Every project with Praxis starts with assessing the data maturity of the clients. For those in the early stages of data maturity, they most likely need help gathering data. Unfortunately, all of the pretty and cool dashboards in the world do nothing without data.
If the client already has data, generally they have a ton of spreadsheets that they’re working from, and need help with automation. In this stage, we focus on data validation, extraction, and loading it into dashboards. Most of our clients fall into this stage.
The way that Praxis Metrics helps these companies generally is through our pre-built dashboards. As Praxis Metrics grew and worked with several large clients, we found that most businesses have similar needs. The questions that our enterprise clients asked us were the same that SMBs did. What’s working, what’s not, how can I improve, etc. Once we realized this, we began to pre-package dashboards that were built to answer these questions specifically.
This pre-packaging allowed Praxis to greatly reduce the costs of building these dashboards. This opened the doors to smaller clients who previously couldn’t afford these type of insights.
What makes Praxis different from other dashboard companies?
Most dashboard companies only offer the dashboarding software. They have built powerful tools, but once you purchase them, you’re on your own. Praxis Metrics doesn’t have software tools, we act as an outsourced data agency that will help you harness the power of your BI dashboards. We have a team of on-demand data scientists and dashboard engineers available to help you complete your projects; but once they’re built, you don’t have to worry about them anymore.
Most companies can’t afford to keep a data scientist on staff, so we make it so that they can rent one as they need them.
What are the most important metrics that most businesses overlook?
There are a handful of metrics that most companies overlook, and they all interact.
Number one is the customer acquisition cost (CAC), specifically broken down by source.
Number two is the lifetime value of customers (LTV), also broken down by source. This one is particularly difficult for most ecommerce companies, as most are omni-channel, and that makes the reporting more difficult.
Number three is days to cancellation, viewed as a cohort analysis, not an average. Averages are inherently evil because they smash together all of the highs and the lows in order to give you one number. The cohort analysis allows you to see a bell-curve of the data, allowing you to better understand the spikes and valleys of your subscriptions, rather than one static number.
Number four would be the cost of goods sold (COGS). Many businesses struggle to get the true costs of each of their products because of bulk shipping or bulk ordering systems. Excel has a hard time breaking things down to that granular of a level, but a robust business intelligence tool can perform those complex calculations and give you the true cost of each of your products on a daily basis.
What are weird things that AJ and Meaghan eat and drink?
Pickle juice. Because she never drinks enough water, she uses pickle juice to boost the cellular water absorption so that the little water that she drinks actually gets where it needs to go.
How do Meaghan and AJ enter a state of flow?
Hypnosis. They have an app that they use that helps them to focus in and reach their subconscious and tap into the state of flow.
Wake surfing. Meaghan uses the outdoors and solo sports to help her reach her state of flow.
What habit or opinion do they have that other people disagree with?
AJ believes that people are the most important resource on the planet. Many people believe that money or time are the most important things, but AJ believes that people are the most important.
Meaghan believes that she is the most important resource on the planet…
If AJ and Meaghan ran a school, but could only teach one, non-traditional lesson, what would it be?
AJ would teach people the basics of understanding their bodies and how to think about things rather than what to think.
Meaghan would teach about the theory of how to make time travel possible.
What books had the greatest impact on them?
“I dare you”, by William Danforth when he was younger.
And now, it would be “The one thing”, by Jay Papasan and Gary Keller.
Meaghan also chose “The one thing”, by Jay Papasan and Gary Keller. That helped her to realize how much of a procrastinator she was as well as how unproductive she was. And then it helped her break out of those habits.
Meaghan’s second choice was “The power of now”, by Eckhart Tolle. This helped her to become much more present in the moment.
“Letting go”, by David Hawkins. This helped them understand the different vibrational frequencies that we resonate at, and helped them to find better motivation and emotional stability.
What do the first 30 minutes of their days look like?
Gratitude, showering (cold), and then mediation.
Just jumps right into work. She starts looking at emails in bed, and then looks at her calendar to see when she can squeeze those things in.
Since her mornings are the most productive time for her, she wants to get the most important things done quickly, and then deal with tedious, less important work later in the day.
What advice would they give to their previous bosses?
AJ never really had a boss, but he would recommend understanding and learning their employees very well. Not just personalities, but what gets them excited and motivated.
Meaghan would start by saying that she was sorry, because she never truly lived up to her potential working for someone else. And then thank them for the opportunities that they gave her. Finally, she would recommend that they invest in the tools necessary to help their employees and people reach their fullest potential.
Where do they go and what do they do to get inspired?
Meaghan is his daily inspiration. Then comes nature, and their trips. Those all get him inspired and excited.
Numbers inspire Meaghan and get her excited. Nature also inspires her.
If they had 24 hours to make an extra $5,000 how would they do it?
Meaghan said that if this were a little while ago, she would have invested it in Crypto-currency.
AJ would borrow their friend, Mike’s boat and take people out on the lake and teach them to wake-surf. Meaghan is an excellent wake-surfing instructor and AJ is a skilled driver. They have a 100% success rate in getting people up between the two of them.
They would combine the fun of the boat with NLP coaching, and business coaching; and that would allow them to quickly raise that money.
What’s the best advice ever given to them?
The best “advice” that Meaghan ever got was from a mentor who told her that she had no integrity. They pointed out that integrity means doing what you say you will do, even if nobody holds you accountable.
He told her to examine her checkbook and her calendar to see what she actually valued, as what you spend your time and money on truly shows your values. Upon examining hers, she realized that she wasn’t being honest with herself about what her priorities were, and worked to bring what she said her priorities were into alignment with her true priorities.
The advice that he actually gave her was that at any point, your time and your money need to be in alignment with what you claim your goals are.
AJ’s grandfather taught and showed by his example that you should always leave people better than when you met them. No matter who they are, they should always be better because they met you.
What silly thing should people do more of?
Laugh at themselves, and dance however you want. AJ apparently makes good practice of this every day, gyrating in a “bizarre” way at Meaghan.
Definitely dance, and allow yourself to release and just let the music flow through you.
Would they rather fight one horse-sized duck, or 100 duck sized horses?
One large duck. Because he wants to conquer it and then befriend and ride it.
Thought AJ was completely wrong. She wants to be able to lord over the tiny horses and crush them as their god.
How would they go about convincing someone to do something good that they didn’t want to do?
Chunk up! Tie the thing that they don’t want to do to something higher and help them to see that this really is the best thing for them.
If you can find a higher purpose that you both agree on and then help them to see how this task ties into that higher purpose, then they will most likely perform the task.
Apart from eachother, what makes Meaghan and AJ happiest?
New adventures. There are chemical changes that occur in the brain when you experience something new, and Meaghan has trained her brain to crave those chemicals, so that makes her very happy.
Having new experiences with people. AJ derives a lot of value from people, so it’s important for him to be around others and experience new things with them.
What can people do?
Reach out to Praxis Metrics! Our primary vision and purpose is to help other businesses grow and realize their potential through data; so if you have data questions or concerns, reach out and we’ll do our best to help.
Make sure that you have your tracking set up. Once you have the tracking in order, everything else can fall into place later, but you can’t make up data that doesn’t exist.
In this guest appearance on the Perpetual Traffic podcast, AJ and Meaghan talk about how to use your data to optimize your ad spend, and rapidly scale your business.
They cover everything from getting your tracking in order, all the way up to creating customized dashboards and leveraging complex machine learning and AI.
Enjoy the episode and our insights below.
The struggle today-
Many marketers feel that they aren’t getting the most accurate data inside of the ad platforms. Unfortunately, they are completely correct. Some marketers go so far as to purchase a cheap dashboarding tool in order to help them bring all of their metrics together into one platform in order to help them with this issue. Unfortunately, this will not solve the problem for them at all.
Why do we suddenly have this struggle with data? What drove us to this point?
In our opinion, the problem stems from an overabundance of data. Never in the history of the world has so much data been available to us. Even in the last 20-30 years, large-scale data projects were reserved exclusively for enterprise-level companies. But now, every company has access to “big data”; despite this, many still have the mentality that their business doesn’t have the same access to data, and therefore the same opportunities and responsibilities, as the larger organizations.
Because these smaller businesses fail to leverage the data available to them, they often find themselves utilizing incomplete or dirty data. If they utilized all of the tools and tracking options available to them, they would have a much more complete and accurate picture of what’s happening.
The opportunity today-
Similar to the dot-com boom of the late 90’s, we’re seeing a “data boom” today. Those that have embraced data and created strategic initiatives around data are already separating themselves from their competition. Taking action from data is the new competitive advantage.
Those who capitalize on data have the opportunity to outpace and out-scale their competitors. John Wanamaker said: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”. Those who eliminate waste in their budget open themselves to amazing opportunities. By doubling or quadrupling down on the things that work, they can drive exponential growth.
How you can capitalize on this opportunity-
Ask the right questions-
We firmly believe in the Socratic method. Asking questions helps you find deeper truths. The trick is finding the right questions to ask that will propel your business forward.
We found that the best way to find these questions is through a process called “metrics mapping”. The diagram below walks through an example:
Metrics Mapping starts with the big goals of your organization. This could include doubling your revenue year over year, increasing sales of a certain product by 30%, etc. From there, we want to drill down to the questions that you need to answer in order to meet that goal. If you want to double your revenue, then why don’t you? What questions do you need to answer in order to hit your goal?
Once you have the questions that you need to answer, it’s time to figure out what numbers can help you answer that question. In the example above, we need to know how to increase conversions and revenue from the website. In order to figure out how to do that, we need to figure out conversion rates, LTV, CPA, and profitability.
Once we have asked the right questions and gathered the necessary data, we need to:
Get granular with it-
Averages are inherently evil. Averages by definition mash together your highs and your lows and give you one number to work with. In order to properly scale your business, you need to know what creates the highs and what creates the lows. Once you know that, you can scrap the things that bring in the lows and double down on the highs.
Going back to the previous example; once we’ve gathered the numbers, we can strategize our next move. Perhaps we need to update our nurture sequence to increase return purchases. We may have a funnel step that causes dramatic drop-off that we can eliminate.
By getting granular in our analysis, we can discover a myriad of opportunities.
What metrics should every business look at?
Every business suffers from “terminal uniqueness”. While every business has certain things that they specifically need to track, there are a host of metrics that every business should know.
The obvious metrics that fall into this category are ad spend, return on ad spend, etc. In addition to these, businesses should also look at cost of goods sold (COGS), shipping expenses, and overhead. Many businesses forget to factor these costs when they look at what their allowable cost per acquisition can be.
This allows you to look at your return on ad spend through the lens of profitability, rather than just revenue generated.
What is the biggest problem businesses have with reporting?
Over-attribution. We see this issue with almost every client that we work with. Facebook, Google, and every other ad platform utilizes different attribution models. Generally, the platform will leverage an attribution model that favors them, and makes them look the best.
So Facebook utilizes an attribution window, meaning that if someone clicks on your ad, and then returns to your site within 28 days, they will claim that they produced 100% of the revenue from that client. Google defaults to last-touch attribution modeling, meaning that wherever that user came from when they made the purchase receives 100% credit for the revenue of that client. Other platforms count view-through conversions combined with an attribution window, meaning that if they saw your ad and then purchased within a certain time frame, that platform claims credit for that sale.
This scenario can lead to multiple ad platforms claiming that they are responsible for the exact same sale.
How do we combat this issue?
If you’re interested in learning more on this subject, we have a separate blog post on ways that every business can work through the over-attribution problem here.
In addition to those tips, our biggest suggestion for fixing this issue is getting a multi-source business intelligence tool. By extracting data from the back end of each of the ad systems, you can piece together a client’s journey and create your own attribution models. This allows you to see your true customer journey, rather than just a simple metric provided to you by a biased platform.
Unfortunately, even that solution relies heavily on the tracking that you have in place. If your tracking hasn’t been set up properly, then you have to rely on the data reported by these platforms, rather than leveraging and creating your own.
Your output is only as good as your inputs-
It doesn’t matter how much you spend on your powerful tools, they still rely on the data that you give to them. If your tracking isn’t set up properly, it’s impossible for a dashboard to correct that for you.
Powerful insights require great data. And unfortunately, good data requires great tracking.
Good news though, if you can get your tracking nailed down properly, then everything else glides into place. The old adage of “measure twice, cut once” applies to data as much as carpentry.
Going back to the metrics mapping process, we want to help you find the “source of truth” for every metric that you measure.
The “source of truth”-
Every metric should have a place where the definitive answer lives. If you want to know how much revenue you’ve brought in over the last month, you can check your bank account, or Stripe, or Paypal. If you want to know how long visitors from Instagram stay on your website, Google Analytics could help you find that answer.
Each data platform specializes in different data points, and we want to get the best data from the best sources.
Where to begin?
We recommend that every business start with the projects that will move the needle for the business. This generally means starting with sales and marketing initiatives, as they generate revenue for the rest of the business.
We have been shocked at how many issues businesses solve by getting their data set up properly for sales and marketing. Also, by leading with these departments, we can generally start to uncover holes in other parts of the business. If we see a spike in cancellations that coincides with customer survey emails, we know that we clearly have something to fix there.
It’s important to remember with every data initiative that it’s a journey. As much as we wish that we could fix every data problem overnight, it takes time to solve these issues and answer these questions. From there, we need to take action from the insights that we gained, and then we can see the results.
Leverage your uniqueness into growth-
As we stated earlier, every business suffers from terminal uniqueness. While this can complicate projects, that is also the place where you can see the greatest results.
By leveraging your uniqueness in the things that you track, you can get extremely granular, and explode your business in ways that others can’t.
One of our clients, Fancy Sprinkles, found amazing insights by tracking what no one else bothered to track.
Fancy Sprinkles, which does exactly what their name sounds like, gets most of their leads from Instagram. They decided to go back through every post that they had ever done and manually put into a spreadsheet the variables of the post. They tracked whether the product was shot indoors or outdoors, close or at a distance, color palettes, everything.
When they overlaid this data with their social media engagement rates over time, they found amazing insights. During October, they assumed that they should post something orange and black to capitalize on the holiday. But after consulting their data, they quickly realized that those colors got the worst engagement in October. The data told them that they should use purple and green, outdoors, and close-up. Their engagement skyrocketed because of these insights.
Tracking may require an up-front investment. Fancy Sprinkles needed interns to work for hours to catalog all of that data, but once they had the historical data, it became much easier to simply input those data points on every post that they made.
When should people seek help with their data?
As soon as it gets annoying or frustrating.
This may seem simplistic, but it doesn’t make sense for you to abandon your superpowers only to beat your head against a wall.
Your company hired you because of your skillset, and if data doesn’t fall into that skillset, it’s better to outsource that than to take away time and energy from the things that you do best.
What should businesses have in place before consulting with Praxis?
We built Praxis to meet companies wherever they are on the data maturity spectrum.
If you already have your tracking in order and want to move on to scaling your business and gleaning better insights, then we offer pre-built dashboards that can help you start leveraging your data into growth.
In this guest appearance on Mike Dillard’s Self Made Man podcast, AJ and Meaghan talk about how to rapidly scale your business using data and dashboards.
They cover everything from the data maturity spectrum to metrics mapping, tracking, UTMs, and how to combine these things for rapid growth in your business.
Check out the full episode below along with our summary of key takeaways.
How did Praxis get started?
Prior to starting Praxis, AJ and Meaghan created a data-driven digital marketing agency. They quickly found though that reporting on their marketing efforts was taking more time that actually implementing their strategies. Because of this, they began researching automated solutions to the reporting problem. Once they finally created a solution, they found that more people needed that solution than needed marketing help.
They decided to pivot and become an outsourced data agency, and Praxis Metrics was born.
Initially they courted enterprise-level clients because those clients were they only ones seeking out “big data” at the time. However, as time passed, they realized that they gained more satisfaction from helping SMBs achieve their potential through data. So they began to provide the same powerful insights and dashboards that they had built for the enterprise clients to smaller businesses.
What are the biggest takeaways from working with such a diverse group of clients?
SMB business owners need the same questions answered as the enterprise companies. While they may look at them through different lenses and different granularity, the questions remain the same.
The number one question that every client asks is, “how much can I spend to acquire my customers?”. Generally, the next questions asked are: “how much are those customers worth over time?” and “where and what do they purchase from me?”.
These questions all stem from the same desire: understanding your core customers, and how to best serve them.
It all boils down to what is and isn’t working in your business right now.
What are some of the biggest differences in SMBs and enterprise companies?
Enterprise companies recognize how much data they have, and the value of that data. SMBs often downplay the amount and value of the data that they already have.
Most SMBs don’t realize that even just having timestamps of when your customers purchase provides valuable insights to the business. This lets you know the times when your purchasers will be most receptive to your messages and most likely to purchase your products.
What difficulties do businesses face with their data?
Trusting your data is the key to gaining good insights. If you don’t trust your data, then the prettiest dashboard in the world will not help you.
You need to have the confidence to take action from your data; otherwise it’s like having gasoline but no car. You won’t get anywhere with that.
We’ve seen a multitude of dashboard companies that sell businesses on the visuals of their dashboards alone, but without fixing the underlying data issues, they end up providing very little value to their customers.
Many SMBs say that they simply don’t have the time to get their data in order; but we preach the opposite. The best time to set up your tracking and make sure that you gather clean, accurate data is before you have too much of it. As your organization scales and grows, the amount of clean-up required in order to get your data in order scales as well. If you make a concerted effort in the beginning to get clean, accurate data that you can trust, your business will scale faster. And when the time comes to transition into dashboards and advanced analytics, your data will be ready and actionable, saving you valuable time and money.
Every business has the time to sit down and set up standard operating procedures (SOPs) for their business. Setting down SOPs is especially important when it comes to UTMs. If you can lay down the groundwork early on for standardized tracking, you can gain amazing insights on how to communicate effectively with your clients.
UTMs will tell you what types of content your customers like to engage with, it will tell you the specific mediums that they like to engage with your business on, and it will help you eliminate the issue of over-attribution in your tracking. If you want to learn more about over-attribution, and how that affects businesses, we have a blog post on that here.
How do we lay the foundation for the future?
Even if you don’t have the time to analyze the data yet, it’s imperative that you begin tracking your customers and their behavior. You can’t retroactively gather data from your customers. When it gets to the point that you want to begin retargeting campaigns, or analyzing your customer behaviors, if you didn’t set up your tracking you won’t have any information to go off.
When they begin advertising, many businesses start with a shotgun approach. They distribute their spend equally across the most popular platforms without knowing which one will drive the best results for their business. If you track your customer behaviors over time, they will show you where they like to engage with you. You can know whether you get the highest traffic from Facebook or Instagram or Linkedin.
What are some of the data success stories that Praxis has seen?
Danette May wanted to see the true lifetime value of their customers to see if they could scale a funnel. They knew that the funnel converted well with retargeting, but they had a hard time getting the same response from cold traffic. They had an idea of the LTV of their customers, but they wanted to verify.
We found that their customers actually had a much higher LTV than they thought. This allowed them to increase their allowable cost per acquisition (CPA) by $5. This change caused them to take an initial loss on the first product sold, but they also knew that within 30 days, these clients would return and spend much more on other products.
This change drove them from 15 sales per day on this product to more than 350 sales per day in less than two weeks. Within a month, they were selling more than 600 units per day.
If you’d like to learn more about Danette May’s journey and how this information helped them transform their business, we have an entire case study on them here.
We built a social media dashboard for Fancy Sprinkles that allowed them to drill down to see what kinds of posts received the most engagements over time. By tagging all of their posts with series of metadata: I.E. indoor vs outdoor shot, colors used, theme, etc.
Because of this metadata, they found that during Halloween the top performing posts contained purple or green, were shot outdoors, and had close-ups of the products. Naturally, this ran completely counter to everyone’s instincts, but it allowed them to provide their audience with content that they actually wanted to engage with. Because they had this data, they outpaced their competitors in engagement and attention.
What are some of the data failure stories that Praxis has seen?
We’ve had clients who utilized free shipping discounts in order to better compete with Amazon. These clients assumed that this would inspire higher customer loyalty, and create repeat customers. Unfortunately, when we cleaned and examined their data, we found that this wasn’t the case at all.
This assumption was costing them dearly over time, preventing them from properly scaling, and could have driven them out of business if it had gone on for too long.
The key to success is listening to your data.
The most viewed person on Facebook was a magician who simply did magic tricks in front of his webcam in a coffee shop. He managed to scale his brand and following by tracking the videos that performed best and then replicating the factors in those posts over time.
Data doesn’t have to include machine learning, or advanced AI algorithms. A simple excel sheet that analyzes data points can drive more success than multi-million dollar solutions.
If you don’t analyze your data to see what works and what doesn’t; your competitors will analyze that data, and eventually overtake you because of your failure to capitalize. Data has the power to topple huge organizations like Barnes and Nobles or Blockbuster, and the pace of change is only accelerating.
Who does Praxis work with, and how can they prepare?
We have historically worked with enterprise companies; so we can work with larger organizations, but our passion is working with SMBs and helping them rapidly scale their businesses.
We have brought the “big data” insights to the SMB market by finding the common threads between every implementation that we have done for these enterprise companies. By finding the common questions that everyone has, we have built out plug-and-play dashboards that can help answer those questions. Because these dashboards require very little ramp-up or custom coding, we can offer them for a much lower price than normal, and roll them out much faster.
These dashboards answer some of the fundamental business questions that every business needs to know: what is the LTV of my customers, how are my subscription services trending over time, what products drive the most revenue and value, etc. We extract this data from multiple sources, ensuring that you get the most accurate and valuable data.
Our pricing ranges from $500-$1500 per month for platform costs, and then we just charge hourly for any work to build out the dashboards and connect to data sources.
We meet our clients wherever they are on the data maturity spectrum. A lot of our clients come to us and they need help getting their tracking in order before they move onto dashboards. We offer services to help with that. No matter what your data needs are, we can help you get from where you currently are to where you want to be.
Your data may be the most valuable asset in your organization. The question that you need to answer is, “Are you getting the value out of it?”
In our guest appearance on the JetRails podcast, we cover everything from what metrics are actually important to growing ecommerce businesses, to how to make sure that you’re prepared against the upcoming data privacy changes. Check out the episode and our insights below:
What does Praxis Metrics do?
Praxis is an outsourced data team. We specialize in helping businesses gather, store, validate, and visualize their data. As data becomes more and more valuable, we help remove the strain of having to extract that value. Our goal is to help you understand your data in a way that makes it actionable, scalable, and valuable.
Many businesses think that they can’t compete with the big businesses with their “big data”, but as with all things, data intelligence has funneled down to the SMB market. This shift allows any business to take control of their data from inception and use it to rapidly scale.
Why did Praxis start?
Prior to starting Praxis, AJ and Meaghan created a digital marketing agency. They quickly found though that reporting on their marketing efforts was taking more time that actually implementing their strategies. Because of this, they began researching automated solutions to the reporting problem. Once they finally created a solution, they found that more people needed that solution than needed marketing help.
They decided to pivot and become an outsourced data agency, and Praxis Metrics was born.
What is the solution they created?
In creating their automated reporting system, Meaghan and AJ found ways to pull in data from all of the platforms and data silos of a business, allowing businesses to see all of their data gathered and aggregated in one place. A “command center” of sorts. This “command center” helps solve many common issues that ecommerce companies regularly face.
Where does the name “Praxis Metrics” come from?
The term “Praxis” comes from Aristotle’s foundational truths. He believed that there were three main constructs of man: Theory- which is thinking about things, Theoria- which takes the information that you thought about in theory and combining them together to create knowledge, and then there is Praxis- which is the practical application of the knowledge and wisdom that you gained by combining your theories and knowledge together.
The process of Praxis is simple: data leads to information. Information can be turned into knowledge. Knowledge then transitions into wisdom. And taking action from that wisdom is praxis.
Data never solves a company’s problems. Data simply points out facts. You need to interpret those facts and find the driving force. Once you understand the driving forces, you can take action to impact those forces. Your actions are the only thing that will change your business. The practical application (praxis) of your wisdom will help you scale your business; not your data.
The goal of Praxis Metrics is to give businesses data that they can take action from. We want for everyone to leverage their data into action that helps them grow their business.
Every metric should have an action tied to it. Metrics without action tied to them are just vanity metrics.
How can I take strategic action from my data?
We start every client journey with a process called “metrics mapping”. Metrics mapping allows us to figure out what data you actually need to gather in order to reach praxis.
Pictured below is an example of the process of metrics mapping:
Metrics mapping starts with the goals that your business wants to achieve. In this example, this company wanted to double their revenue year over year. Once you have your goals in mind, you need to start asking the questions that will lead you to that goal. In this case, they need to increase conversions on their website in order to reach their goal. The question that they need to answer is, “how?”.
Once we know the questions that we need answers to, we know the metrics that we need to pull. We’ll begin pulling the metrics that help us answer the question: conversion rates, customer LTV, acquisition costs, and profitability.
From there, we need to find the “source of truth” for each of these metrics. The source of truth is the place where we can find the most accurate data. For financial data, this can be your bank account, Stripe, or Paypal. For traffic data, it could be Google Analytics, or the back end of your website. The point of this stage is to find the most accurate data source to pull from.
The rest of the steps would be carried out with the help of the Praxis team as we help you build out your dashboards.
How do I justify spending money on data?
It’s important to remember that data is an investment, not a cost center. Data recently surpassed oil as the most valuable resource on the planet, so any investment that you make into harvesting, leveraging, and improving your data should return massive dividends if implemented properly.
There’s a reason that data is now recognized as “king”. It has the power to create and destroy massive corporations, swing elections, and generate untold wealth for those who leverage it properly. If you know why something happened and your competitor doesn’t, you can pivot and adjust in order to take advantage of their ignorance.
Taking action from data is the new competitive advantage.
Companies that capitalize on data will scale, those who do not will fail. Speaking about the hurricanes, they mentioned that Walmart and Target were receiving huge shipments of Pop-Tarts, as they know that they are a staple during hurricanes.
Many businesses think that big data is reserved for enterprise-level companies; but tools have gotten cheaper, talent has gotten more affordable, and data has become more plentiful. One of the goals of Praxis is to bring those big, enterprise-level insights down to the SMB market and help them see hockey-stick growth.
Before you begin investing in your data though, it’s important that you know where you should invest your money. That is where the data maturity spectrum comes into play.
What is the data maturity spectrum?
The data maturity spectrum helps you identify where you are, and what your current data priorities should be.
The Foundation Stage-
In the foundation stage, everything revolves around tracking. You can’t analyze data if you don’t have data; so you need to make sure that you gather the data that you need in this stage.
Many companies ignore this step until they’re looking to move to the next stage. Unfortunately, by that time they’ve lost out on all of their historical data. We see many businesses come to us that want to build out amazing dashboards, but we discover that they haven’t tracked the data until this point. That means that they have lost out on years of data that could provide crucial context to the data that they gather from here forward.
Too many businesses want to get started, and push to start selling before they set up their tracking; but they need to realize that you cannot retroactively track. Any changes that you make to your tracking only adds data moving forward, and any data that you missed out on previously is lost.
Revenues do not determine your place on the data maturity scale, the only thing that matters on this scale is how well you handle your data.
What are the questions that you will have in the future?
You need to think on what things you may want to know in the future, and start tracking those things today. It may seem tedious right now, but in the future, it may drive your success.
Typically, the cost of marketing far outweighs the cost of taking the time to track these things. Tracking can inform and optimize your marketing budget, allowing greater success than previously imaginable.
What are the metrics and behaviors that allow for rapid scaling?
Phase two of the data maturity spectrum is automation. What compound interest is to your money, automation is to your time.
Automation increases efficiency, accuracy, and profitability of organizations. Automation is one of the primary drivers of rapid scaling and growth.
Customer Lifetime Value-
Understanding the lifetime value of your customers is one of the keys to rapidly scaling. The business that can afford to spend more on their customers will win every time. Understanding the value of your customers over time allows you to predict break-even points and therefore allows you to determine higher acceptable acquisition costs than those who base their spend exclusively off initial order value.
Why do averages suck?
By definition, averages pull in all of your data, the highs and the lows, and gives you one number. You don’t want to base your decisions off just one number though. The 80/20 rule applies to almost everything in life, and business is no exception. An average will hide the 80% of things that do nothing for your business behind the 20% of things that actually drive your results. We want to know what falls into the 20% category so that we can eliminate the 80% scale the 20% that works! Averages keep you growing at a steady pace; we want to deliver explosive, hockey-stick growth.
Too many businesses treat all of their customers the same way; whether they came in and spent a dollar, or a thousand. In order to scale though, you need to invest time and effort into your customers in proportion to the value that they bring to your organization.
Once you know where your most valuable customers come from, and how to properly target them, you can essentially print money for your business.
What should ecommerce companies know about their business?
Ecommerce companies should know what technology stacks they use in their business, and how those technologies handle data.
Amazon is a wonderful example of this. In the last couple of months, they have completely changed their terms of service (ToS) to restrict the data that merchants can access. Amazon collects a vast amount of data on the customers that come to your store and purchase, but they will now only allow you to see certain parts of that data. The worst part is that this is not unique to Amazon. Platforms across the web and world are cracking down on the data that they share with third parties. Because of this, you NEED to know how the companies that you work with handle data.
What should you do to protect against data loss?
You need to make sure that you either own the data completely, or that you have a backup of the data stored off of these platforms. In the podcast, we discuss how these platforms are your “frenemy”. They may seem nice, but the relationship can turn on a dime; so you need a backup plan.
As data becomes more and more scarce and consolidated within platforms, the value of that data will increase dramatically. For that reason, it’s imperative that you take ownership over your data and protect it from outside sources that would limit your access to it.
What sort of subscription metrics should ecommerce companies look at?
We see so many companies come to us and ask what their average subscription length is. As we already discussed, averages are evil.
Instead, we build a chart that shows how many cancellations they have per day. If you have an average, it will tell you that your average subscription length is 60 days; this chart will show you that 30% of your cancellations occurred between day 3 and 7, so you can take action during that time period to reduce that churn.
Everyone wants to increase the average, but the average in and of itself doesn’t help with that. You need granular detail in order to actually make an impact.
What are the next steps?
The first step is to start investing in your data. No matter where you fall on the data maturity spectrum, it’s important to start investing time, energy, or money into advancing your data.
If you need help diagnosing where you fall on the data maturity spectrum, or how to get to the next level, we can help you discover where you fall on the data maturity spectrum, and build a custom data roadmap for your business. Click here to schedule your free appointment.
For this blog post, we wanted to revisit a guest episode that we did with the Vision Tech Team. This episode was filmed at the end of 2018, and focused on the changes that we saw in the data landscape in 2018, as well as predictions for 2019.
We found this episode particularly relevant given the changes in the data landscape that we detailed in last week’s post (which you can find here).
Enjoy this short podcast episode, and our insights below.
Insights from 2018:
The data landscape changed rapidly, making it very difficult to predict what different platforms would do.
Infusionsoft became much more open with their data in 2018, while Facebook began to clamp down on what data they would allow access to.
Businesses began to understand the value of data, and started to understand it’s importance.
Similar to the dot-com boom, businesses that fail to take advantage of their data started falling behind in the market.
Data overload started coming to a head. Businesses started needing to figure out what data actually drives results.
Trust in data became an issue. Data validation became a necessary part of data projects.
Data visualization became the new buzzword.
Everyone became obsessed with visualizing their data.
This often came at the expense of actually driving new insights, as they would simply slap graphs on the same data.
Automation started to spread
In the beginning, nobody tracked anything.
Then, businesses started tracking, but the data was stuck in silos.
From there, data nerds started creating complex pivot tables and Excel sheets to bring the data together.
Now, automation became feasible, and started taking over. This removed the need for manual reporting, and made the visualizations better.
Going back to data overload, tracking exploded in 2018.
You started being able to track anything that you wanted, and this lead many companies to overload on data.
For those that actually leveraged this data, it caused explosive growth.
Chatbots exploded onto the scene.
Chatbots began to expand their footprint, with very promising results.
Businesses began realizing the value of data democratization.
Rather than having just one data nerd knowing everything about your data, businesses began to share data with all employees.
By opening up data to the entire organization, you can gain insights that you previously would have missed out on.
This allows organizations to leverage the combined brain-power of their entire team, rather than just the select few.
Predictions for 2019:
Increased competition for data.
As more companies realize the value of data, more and more companies will start competing for it.
As data becomes more ubiquitous, companies will get better and better at targeting and marketing. This will drive inefficient organizations into the ground, leaving only the best to survive.
Data overload to the max.
As more data becomes available, businesses will need to start deciding what metrics actually matter to them.
Most businesses will need to hone in on the handful of metrics that actually drive results (80/20).
Those that capitalize on this principle will thrive in 2019
Increased transparency and accountability.
As more companies move towards data democratization, we will see a shift towards increased accountability across organizations. This will create cultures that thrive on extreme accountability.
Since everyone has access to the data, it will become much more difficult for low performers to hide behind the work of others.
Looking back on 2018, things seem so much simpler. They only worried about compliance with GDPR. In 2019, we have a host of regulations on the horizon to worry about, decreased access to data and information, and platforms throttling data.
Looking forward to 2020, we’re likely to see an acceleration of the changes from 2019. We expect more data regulations to come into effect, and as a result of this, we expect a decrease in marketing efficiency.
One of the things that every business should start doing is gathering data into a data warehouse. This protects you from the whims of the larger platforms, and gives you complete ownership over your data. By gathering your knowledge and wisdom into your own database, you insulate yourself from the storm that is brewing on the horizon.
Praxis specializes in data, so we can help you take ownership over your data, create back-ups, and help you understand your data better than ever before. You can learn more about our products and offerings here. If you have immediate questions, you can contact a data expert directly here.
The data landscape rapidly changes and shifts, but a flurry of recent announcements will shaken the core of how we measure and track customers.
What is happening?
Basically, until now we’ve been living in the wild west of data, but after a wave of data scandals a new sheriff has come to town. And this sheriff is changing all of the rules. The new priority for data is privacy first, marketers second. These new rules are coming through legislation, and the gods of the internet. We’ll explore what’s happening in both groups, and what happens next.
It all started with GDPR, but now consumer data legislation is popping up around the globe. In the US, the California Consumer Privacy Act just officially passed (and will go into effect in 2020); meanwhile, similar regulations are developing in Brazil and India as well.
What do these laws entail?
General Data Protection Regulation (GDPR)-
GDPR is a law passed by the EU in 2016, and began enforcement in 2018. The stated goals of the law are to: harmonize data privacy laws across Europe, protect and empower all EU citizens data privacy, and reshape the way organizations across the region approach data privacy. It does this by levying heavy fines against any business that is found in violation of the regulations. This applies to all companies processing the personal data of data subjects residing in the Union, regardless of the company’s location.
California Consumer Privacy Act (CCPA)-
The CCPA will allow consumers to force companies to tell them what personal information they have collected. It also lets consumers force companies to delete that data or to forbid them from sharing it with third parties. This law aims to target larger businesses, and only applies to businesses that earn more than $25 million in gross revenue, businesses with data on more than 50,000 consumers, or firms that make more than 50% of their revenue selling consumer data (I.E. data brokers).
While this law only applies to customers who live in the state of California, 17 other states are currently exploring similar legislation. It’s likely that most companies will just adopt these practices across the board.
Both Google Analytics and Adobe Analytics use a default 30-day conversion window, allowing you to see the impact of every touch that impacted a conversion in that time frame. Those attribution models on Safari browsers will now only collect data on the last seven days prior to conversion, deleting any data collected before that point.
For remarketing, marketers now only have seven days to programmatically target Safari visitors. After that, their data will be deleted, along with the ability to retarget them.
Other effects from this change include: cross-device visitor tracking becoming unreliable, and a dramatic uptick in unique visitor counts. Visitors who span multiple devices and have a buying journey more than seven days will look like new visitors when they finally return, skewing the data. Additionally, since they now look like new visitors every seven days, new visitor counts will skyrocket.
Mozilla rolled out similar features to its popular internet browser, Firefox, earlier this year. They recently rolled out an “Enhanced Tracking Protection” feature, which blocks all third-party cookies by default. They also began blocking over 2,500 tracking domains, many of which control multiple cookies, and plan to “update and improve this list over time”.
Chrome will add a browser extension that will showcase the names of the AdTech providers on each page and the personalization factors associated with each cookie. They also plan to provide user-level cookie control for third-party cookies.
What can we do?
First party cookies
Moving from third-party tracking cookies to first-party cookies will help protect against these updates and changes.
Most of the changes implemented by the tech companies target third-party cookies, but none of them target first-party cookies yet. This allows you to continue tracking your customer journey without interference.
This change also provides a number of fringe benefits, including: ownership of the data, reduced likelihood of blocking, and better storage and utilization opportunities.
Owning your data insulates you from changes or updates to any future terms and conditions. It also allows you to store the data indefinitely.
In order to implement this, you’ll need to develop the cookies and have a data-warehouse to store the information collected.
It should be noted with this solution that since you own the data, you assume 100% responsibility for it. This includes compliance with the privacy laws previously discussed, as well as the protection of the data.
Tracking pixels have managed to avoid much scrutiny yet, and therefore they have escaped the proverbial regulatory hammer so far.
Pixels transmit their data directly to a server, rather than storing data in the browser. This makes the pixel extremely useful, as the user cannot delete the data by clearing their cache.
As regulation ramps up, we predict that most tracking will transition from cookies to pixels, and the data produced by these pixels will move to large data-warehouses for storage. Similar to a first-party cookie, the data gathered from pixels will become the responsibility of the pixel owner.
What comes next?
It is clear that the old way of collecting data is officially dead. Privacy and consumer protections are here to stay.
The solutions that we presented here only serve to fix the issues created by these updates to browsers, they will not help avoid any of the new legal regulations. The internet is entering a new age, and every company will have to grow and adapt to this new ecosystem.
Data recently surpassed oil as the most valuable commodity in the world. The question that we need to ask ourselves is “Why?”; why is data so valuable, and are we making sure that we are getting the maximum value out of our data.
Why is data so valuable?
Data in itself is not particularly valuable. Data is simply a single point of information. The value of data is the actions that you are able to take a a result of the data.
As an example of this, knowing that it is raining does nothing for you in itself. It is simply a point of data. When you begin to merge related points of data together, you get information. By extrapolating your information into patterns, you get knowledge.
Data, information, and knowledge are all powerful tools, but they only help you understand things in hindsight. Taking that knowledge of patterns and using it as a model for the future allows you to gain wisdom. But that wisdom in itself does nothing for you without taking action from it, which is Praxis, or the practical application of wisdom.
Data is like a race car. It has limitless potential, but it requires you to put fuel into it before it realizes it’s value. Data requires analysis and action in order to create any value for your company. This brings us to the question of:
How do I make sure that I’m maximizing the value of my data?
There are two ways to make sure that you are getting value out of your data, internal monetization and external monetization.
Internal monetization refers to utilizing your data to glean insights to help your company. This can be things like improving your marketing efforts, managing customer experience, or management of your supply chain and equipment maintenance.
Most companies use the internal monetization of data to identify areas of inefficiency. Our client, Digital Marketer, was one of these. We helped them discover a structural issue with their site that was causing a huge SEO issue for them. Upon discovering the issue, they implemented a fix and saw a 50% increase in their traffic. You can read more about that story here: https://praxismetrics.com/success-stories/digitalmarketer/
Another way to monetize internally is to leverage data to expand your product and service offerings. Our client, Danette May, found themselves in a similar position to this. They had been trying to expand a funnel that they had built to offer it to more clients, but they found that they couldn’t increase their ad spend to reach this new market and maintain profitability on the product. They were about to abandon this idea when they came to Praxis to try to figure out what their lifetime customer value was; we helped them discover that their LTV for that funnel was much higher than they initially thought. This allowed them to increase their allowable cost per acquisition by $5, which caused them to experience explosive growth, and now that funnel brings in millions in revenue per year. You can read more about their story here: https://praxismetrics.com/success-stories/danette-may/
Another way to take advantage of your data is to monetize it externally. This can include selling the data that you have on your customers, creating mutually beneficial partnerships with other data-driven firms, and creating new subsidiaries or divisions within your company to take advantage of insights that you have gained. Selling and trading data with other companies is growing more challenging, as data rules and regulations are becoming much stricter across the globe, but these type of partnerships can be extremely lucrative for both parties if done properly.
How can I start monetizing my data?
The most important thing that you need to do before trying to monetize your data is to make sure that your data is accurate and “clean”. Attempting to make decisions off of bad data is like trying to drive that race car, but with a filthy windshield that you can’t see through.
Once you have confidence in your data, the next thing you need to do is start to figure out what numbers are actually important to you an your business. We recommend a process called “Metrics Mapping”. Metrics Mapping helps you to understand exactly what you should be tracking, and what actions you should be taking based off of your numbers.
Metrics Mapping starts with determining your business goals and objectives. So if your goal is to double your revenue by 2021, then what questions do you need answered in order to get there? An example question would be “How do we increase the revenue from our website?”. From there, you can determine the metrics that would help answer that question. “How many conversions are we getting per day/month?” “What is our average order value?” “What are our repurchase rates?” “Where do we get our highest converting traffic?” would all be good questions that can help lead you to the metrics that you need to be tracking.
Once you know what you want to track, the next step is to figure out where your “source of truth” is for each of these metrics. Revenue per day/month should be tracked by your accounts (Paypal, Stripe, bank), average order value should be tracked through your sales system, highest converting traffic can be found in Google Analytics, etc. Once you have your “source of truth” selected for each of the metrics that you need to track, you know where you need to check in to see your progress.
Once you know your metrics and where they live, you need to assign someone to manage them. Even if it’s yourself, it’s critical that someone be specifically responsible for these metrics. This person needs to keep an eye on the metrics and know exactly what’s going on with them at any given time. Whether improving or worsening, this person should be aware of why they’re changing.
Once you have your metrics mapped out, the next thing that you should do is start aggregating and visualizing your data in business intelligence dashboards. These dashboards will help you track your important metrics over time, and at a glance.
At Praxis, we prefer dashboards that go beyond just simple visualizations. We build dashboards that merge multiple sources of data in order to create new, reliable data sets. Our dashboards perform complex analysis and calculations to help you not only understand what has happened in your business, but also help you shape the future of your company.
We’ve built everything from “command centers” where executives and investors can log in to see all of the key metrics that they need, to drill-downs that allow you to see the performance of each of your ads. Through our experience creating these dashboards for our many clients, we have perfected their creation and roll-out. We have more information about these dashboards and what they can do for your business here: https://praxismetrics.com/dashboards/ltv-dashboards/
This article contains a roadmap for data monetization. This may seem overwhelming, but we can help you wherever you are in your journey. We offer services for tracking, dashboarding, and even metrics mapping. All you need to do is follow this link to schedule a call to get a personalized data roadmap for your company from a data expert: https://praxismetrics.com/strategy/schedule/
One of the most frustrating aspects of marketing right now is over-attribution when comparing Facebook reports to Google reports.
This occurs when you log into Facebook and it tells you it earned you $100,000 in a period, then Google says it earned you $100,000 in that same period, but you only received $125,000 worth of orders during that same time period.
This, unfortunately, is the new norm in the attribution war. Both Facebook and Google want your advertising money to go to them, so when it comes to tracking and reporting, there are a few things you have to understand:
Even though the two platforms integrate with each other, each is entirely separate. They have different goals, definitions, standards, and abilities for tracking.
Each platform only owns their own data. That means, when you go into the reporting aspects of Google Ads or Facebook, you will have mathematically biased information. Each platform only sees one variable (their ads) as an impact on your sales. However, there are always multiple variables involved—multi-channel marketing, public relations, organic posts… even the weather and political climate can impact your sales.
So, when you log in and see varying information, they’re not trying to lie, they’re just presenting their side of the story.
Everyone knows that there are three sides to any story. Each person has their version, and then there’s the truth, which is somewhere in the middle. So, when it comes to Facebook and Google reporting, neither is lying, but also neither is showing you the entire picture because they both are inherently biased. Facebook, for example, counts any conversion that has seen an ad on their platform and then converts as a “view-through” conversion; and Google uses last-click attribution by default in their reporting because that favors them.
Then how do I get data that I can trust?
There are two steps to get accurate reporting on your marketing efforts in your systems.
Get as much information as possible. Information is simply multiple points of data brought together to allow you to see patterns and gain answers to questions, like:
How much overlap do we have in reporting?
Are there clients that have been exposed to multiple marketing efforts?
If so, are we tying together their customer journey with accurate tracking efforts?
What are all the possible impacts on our sales?
How have they impacted sales before?
Are there correlations?
How are you going to answer these questions to get the insights you desire? You must have the data in order to be able to analyze the data to get insight.
That means, tracking is the first and primary component of accuracy in your reporting:
Are you tracking your client’s journey?
As we discussed earlier, Google uses last-touch attribution to assign credit to conversions. This slants credit towards Google, as by the end of a customer’s journey they tend to be aware of your brand, and therefore more likely to search for your name and click on a search ad or organic search result.
Google Analytics has many attribution models that you can try out to see which one works best for you. From position based (Which assigns 40% of the conversion value to the first and last touch, and then distributes the remaining 20% across all other touch points) to time decay (which assigns credit based off how close to the conversion date it was), it’s important to make a conscious choice of which attribution model you want to use. Each attribution model has its pro’s and con’s, but by staying aware of how the model affects your reporting, you can reduce bias in your reports.
Are you using pixels?
Tracking pixels have exploded in popularity. Many popular advertising platforms now use tracking pixels in order to track conversions and user interactions with the ads. Pixels provide amazing reporting because you can install them almost anywhere, from emails to landing pages, and, as of now, they can’t be disabled by a browser.
Pixels can help you gain greater understanding over how users interact with your advertisements and your website. Providing granular data about user’s behavior based off the platforms that they visit your site from.
Do you have unique identifiers for your clients that allow you to see their customer journey?
Specifically, you need a way to assign a user-id to your clients so that you can track their behaviors across devices. If you don’t have this set up, then when a user changes devices, you will lose all of the data from their initial visit. This can lead to incomplete customer journey’s and skew your attribution data.
Do you have organized UTMs setup?
The very best solution for the attribution problem is to utilize UTMs in all of your marketing efforts. UTMs allow you to tell Google Analytics exactly how you would like to categorize your traffic. Every external link that directs to your site should have UTM parameters appended to them in order to help assign credit to the proper source. You can even add in campaign data in order to track which of your campaigns drives the best traffic to your site.
UTMs can be one of the most powerful tools available to marketers, or they can be their downfall. UTMs need to be standardized and utilized consistently, or they will make the data even more convoluted and confusing. You need to implement standardized rules for your UTM usage across the organization in order to make sure that your data remains as accurate and clean as possible.
If you don’t already have these things in place, that is your top priority.
By organizing your tracking efforts, you can start gathering the data you will need in the future. If you need help with your tracking, we have a variety of services that can help you get your tracking in order.
Once you have tracking in place, you can typically manually create Excel reports that give you a much more accurate depiction of your marketing efforts (including lift effects and other variables). However, over time, that becomes tedious and time consuming and allows for too much human error.
The next logical step is to automate via ETL (extracting, transforming, and loading the information from these systems into a singular place) and then to visualize the combined, clean data with a dashboard.
This enables you to eliminate wasted time, effort, and give you insights in a quick and digestible manner. This process can be very intense and require the help of a data scientist.
Fortunately, we specialize in exactly this type of process and can help you revolutionize your data reporting. If you’d like to learn more about how we can help you with ETL and visualization, visit us here.
Bonus #3: Democratize your data
This one may seem out of the blue, but it can change the way that your entire organization interacts with data.
Democratizing data means providing access to data to everyone in your company. Not just information that pertains to their specific corner of the business, but the business as a whole. We have clients who have walls of TVs dedicated to displaying their data for the entire company. Everyone from entry-level employees to C-suite officers has access to the same data.
You may be asking yourself, “How on earth would that help my business?” Everyone has different backgrounds and experience, so when one person looks at a metric they will see one thing and come up with an action item based off their experience; but if you bring in another set of eyes, that person may see something totally different and come to a different conclusion. Democratizing data and making it accessible to more people will lead to greater insights and more options for ways to proceed.
Accountants can be creative, and marketing people can help solve operational issues. Democratizing your data can help you gain a myriad of insights and give you an edge over your competition.
You have tons of data; but data alone will not grow your business. It’s the insights from the data that will inform your team on how to grow. Companies that focus on causation will scale. Those that don’t, will fail.