Praxis Metrics- Are you getting the most out of your ecommerce data?

Are you getting the most out of your ecommerce analytics?

What can your data do for you?

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.

Praxis Metrics- Data Maturity Scale

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:

Praxis Metrics- 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.

Praxis Metrics- Data maturity stage one

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?

Automation-

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.

Praxis Metrics- Data Predictions

Predicting data trends (2018-2020)

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:

  1. The data landscape changed rapidly, making it very difficult to predict what different platforms would do.
    1. Infusionsoft became much more open with their data in 2018, while Facebook began to clamp down on what data they would allow access to.
  2. Businesses began to understand the value of data, and started to understand it’s importance.
    1. Similar to the dot-com boom, businesses that fail to take advantage of their data started falling behind in the market.
  3. Data overload started coming to a head. Businesses started needing to figure out what data actually drives results.
    1. Trust in data became an issue. Data validation became a necessary part of data projects.
  4. Data visualization became the new buzzword.
    1. Everyone became obsessed with visualizing their data.
    2. This often came at the expense of actually driving new insights, as they would simply slap graphs on the same data.
  5. Automation started to spread
    1. In the beginning, nobody tracked anything.
    2. Then, businesses started tracking, but the data was stuck in silos.
    3. From there, data nerds started creating complex pivot tables and Excel sheets to bring the data together.
    4. Now, automation became feasible, and started taking over. This removed the need for manual reporting, and made the visualizations better.
  6. Going back to data overload, tracking exploded in 2018.
    1. You started being able to track anything that you wanted, and this lead many companies to overload on data.
    2. For those that actually leveraged this data, it caused explosive growth.
  7. Chatbots exploded onto the scene.
    1. Chatbots began to expand their footprint, with very promising results.
  8. Businesses began realizing the value of data democratization.
    1. Rather than having just one data nerd knowing everything about your data, businesses began to share data with all employees.
    2. By opening up data to the entire organization, you can gain insights that you previously would have missed out on.
    3. This allows organizations to leverage the combined brain-power of their entire team, rather than just the select few.

Predictions for 2019:

  1. Increased competition for data.
    1. As more companies realize the value of data, more and more companies will start competing for it.
    2. 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.
  2. Data overload to the max.
    1. As more data becomes available, businesses will need to start deciding what metrics actually matter to them.
    2. Most businesses will need to hone in on the handful of metrics that actually drive results (80/20).
      1. Those that capitalize on this principle will thrive in 2019
  3. Increased transparency and accountability.
    1. 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.
    2. 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.

Praxis Metrics- LTV business scaling

What is customer lifetime value, and how does it impact my business?

What does LTV mean, and how does it impact my business?

LTV stands for customer lifetime value, and measuring it can revolutionize your business.

Most businesses determine their ad spend based off their return on investment from said ad spend. Unfortunately though, many people calculate the return on ad spend (ROAS) exclusively based off the initial order value. If you calculate your ROAS exclusively based off initial purchase value, you are most likely missing out on explosive growth, just like our client Danette May. See the video below to hear more about their story:

As you can see from that video, knowing the true lifetime value of their customers made all of the difference for them. They couldn’t scale that funnel reliably without increasing their budget; but they thought that they couldn’t increase the budget on the funnel and still have an allowable ROAS. They had made all of these calculations based off the initial order value though. By widening their scope and tracking the lifetime value of those customers, they realized that they could still get an allowable ROAS even if they increased their budget.

Upon increasing their ad spend, they were able to scale up that funnel tremendously and they went from 15 sales per day to over 200 sales per day in less than a month. Since this video was recorded, they went as high as 600 sales per day and are now averaging about 300 sales per day. That is the power of knowing your true customer lifetime value.

How does LTV impact finance?

While LTV in and of itself can completely change the way that you view customer journey’s and their acquisition costs, the true power of customer LTV comes when you combine it with a few other metrics. Once you know the true value of your customers, the next thing that you need to know is the true cost of goods sold on what you sell. To get the true cost of goods sold for your products, you need to roll in everything, legitimately everything. You need to break down the cost of every employee, all of your overhead, every cost that your business has needs to be tied into this metric.

Once you know the true LTV of your clients, and your true cost of goods sold (COGS), you can now start to look at how much money you make off each client and each product that you sell. You may find that on some funnels you’re not profitable off the initial purchase, but that the clients come back and repurchase multiple times over several months, making that customer profitable overall. From there, the finance team can determine acceptable timetables for profitability. Some businesses have funnels that they know will not turn a profit for several months, but they know that it will be profitable within a certain acceptable time frame for them as well.

Once you know the acceptable profitability time frame, you can begin to work out an acceptable cost per acquisition, which leads us into our next section:

How does LTV impact marketing?

Now that you know the path to profitability and the timeline for it; you can begin to look at how much you can acceptably spend on advertising costs. By studying your cost per acquisition (CPA), you can understand how much ad spend you will need in order to get one person to convert. From there, you can rework this into your established cost of goods sold, and look at your timeline for profitability. We recommend that you find the absolute maximum allowable CPA, and then make sure that you stay underneath that threshold.

The next step in your journey is to get even more granular in how you measure your customer lifetime value. Since your allowable acquisition cost is based off the lifetime value of your clients, it makes sense to break out the lifetime value based off where they came from as well.

In this next video, we show you exactly what that looks like.

As shown in the video, clients who come from different referral sources behave differently. They may be interested in different things based off the type of content that drove them to your site. This will affect the items that they buy, and in turn, their lifetime value as your customer. You can also take this analysis even further by segmenting your customer LTV based off the initial item that they purchased.

How can I start tracking the LTV of my customers?

The hardest part of finding the true LTV of your customers is extracting all of the data from all of the disparate systems. The average small business uses at least nine different systems to track different things, though many have more than that. In order to get a clear picture on the true LTV of all of your customers, you need to gather all of that data. This is a tedious, difficult process known as ETL (Extract, Transform, Load).

The first step of ETL is data extraction. It takes a lot of time to extract data from all of the disparate systems, but it’s rather simple to do. From there, you need to make sure that all of the data meshes together properly. This leads us into the transformation stage.

Transforming data requires a lot of time and mental energy to complete. Each system tracks things differently, so you have to go through and realign the data to make sure that it matches properly between the different tracking systems.

The last stage is the simplest stage and, generally speaking, the one that everyone jumps to. The load stage consists of taking your new, clean data and loading it into a visualization tool so that you can see all of the information that you have gathered in one place.

Many people jump straight to the load phase and get a data visualization tool without having the previous two steps, and that leaves them with a pretty dashboard that doesn’t tell them anything new. The process of ETL is VITAL for you to find your true LTV and of paramount importance for you to propel your business forward.

If you need help with this, we have helped countless businesses go through this process. Simply fill out this form, and we can talk about the unique needs of your business and how we can help you turn your data into growth: https://praxismetrics.com/talk-to-a-data-expert/

Praxis Metrics- Financial Marketing Summit

Financial Marketing Summit Keynote Speech

Data is a lot like teenage sex-

Everyone talks about it, but nobody really knows how to do it. Everyone thinks that everybody else is doing it though, so they pretend that they are doing it too.

– Dan Ariely

Now that we have your attention, we can get into the meat of the content. This lecture was initially presented to a group of financial marketers, but it’s applicable to businesses in any sector.

Why do I need to know the lifetime value of my customers?

Lifetime Value (LTV) may be one of the most important metrics that a business can measure. Everything from cash-flow to ad spend relies almost exclusively on this number. If you know the lifetime value of your customers by source, and you know the amount of margin that you need to make off that customer, then finding the maximum acceptable Cost per Acquisition (CPA) is a simple equation. Likewise, with cash-flow calculations. If you know when customers who purchase item A will likely return to purchase item B, then you can forecast your revenues pretty accurately.

Our client Danette May has the perfect example of these pieces coming together. They had a funnel that wasn’t converting to the level that they needed it to, and they were about to cut it. They came to Praxis Metrics to find out what their average LTV was for customers who came through the funnel. We supplied them with that data, and armed with that new information, they found that they could afford to spend more on acquiring those customers than they previously thought.

By increasing their acceptable CPA by just $5, they increased from 15 sales per day to 350 sales per day within two weeks. The trend continued upward to hit 615 units per day off this single funnel. With an average value per order of roughly $97, they now make more than $30,000 per day in sales. Across the year this funnel alone accounts for more than $10,000,000. If you would like to hear more about their story, you can see more of what they have to say here: https://praxismetrics.com/success-stories/danette-may/

How can you get a leg up in your business?

There is more noise and competition for clients than ever before. Anyone with a laptop and an internet connection can now start a business and possibly disrupt entire industries. How do you compete in a landscape like this? Information.

Information is at the heart of most of the problems faced by businesses today. Either you wander around blindly because you have too little information; or you have too much information stored in information silos. These silos may contain valuable insights, but since they don’t communicate with the other systems, you have to rely on humans to extract the valuable information and make it usable.

Taking action from data is the new competitive advantage.

The only difference between a successful online marketer and a failure is that the successful marketer knows why they were successful and can replicate that success.

Data does not solve problems.

Data is never the solution to a problem, data merely guides you to information. Information leads to knowledge. Knowledge transforms into wisdom, and wisdom when applied to your actions, creates Praxis.

The major dividing line in this system is the transition from knowledge to wisdom. Everything that comes before wisdom is based off past observations, and makes no statements on the future. Wisdom allows you to make predictions about things to come. Praxis requires taking those predictions and then doing something about it to better your life.

Not taking action from data is like owning a race car, but then never putting fuel into it.

Data contains the what. Information tells you the when or the where. Knowledge teaches you how. Wisdom guides you to why. Praxis is the actions that you take based off the data, information, knowledge, and wisdom that you gain.

Where do I begin?

Your outputs are only as good as your inputs.

Therefore, you need to begin by tracking your data. This forms the base of everything that you build later, so you need to make sure that your tracking is in order.

Meaghan and AJ provide a personal example of taking data all the way through Praxis beginning at 19:10 if you are interested in hearing more about that.

The initial phase of your journey is all about getting clean, accurate data. The number one mistake that small to medium businesses make is that they are not using UTM’s in all of their marketing efforts, and they don’t have their Google Analytics set up properly.

What the devil is a UTM, and why does it matter?

You can track your marketing campaigns uniformly across most analytics tools utilizing UTM parameters. UTMs work with Google Analytics and many other tracking tools.

UTM is an abbreviation for “Urchin Tracking Module”. “Urchin” came from one of the very best website analytics tools that used on-page scripts to collect visitor data.

Like a lot of great web software, Google eventually acquired Urchin.

A UTM has five variants of URL parameters used by marketers to track the effectiveness of online marketing campaigns across traffic sources and publishing media. UTMs contain an encoded suffix that you append to a URL (A URL being a website link). The suffix is generally quite long and is made up of various ‘parameters.’

Each parameter provides specific information about the link in question. And by stringing parameters together, you can track your online marketing campaigns with a tremendous amount of detail and granularity.

UTM’s are one of the most powerful tools that you have in your analytics arsenal, but they can also be very daunting to get started with. We have written several blog posts on the subject matter, which can help you understand them much better. You can read more of those here: How to increase revenue with one simple tweak, and here: Why UTM’s are so important, and we even set up a course that will teach you from start to finish how to create UTM’s and even has a spreadsheet that will automatically create them for you here: https://datarich.thinkific.com/

After UTM’s, what’s next?

Once you have control of your UTM parameters, you need to start a process called Metrics Mapping. Metrics Mapping allows you to gain clarity on what metrics you should track, and what those metrics do for your business.

Metrics Mapping starts with your business goals. You need to know where you want to go before you can create a map to get there.

From there, you need to figure out what questions you have to answer in order to accomplish that goal. You could ask questions like, “Where do my sales come from?”, or “How many sales have I averaged over the last 30 days?”.

Once you have the questions that you need to answer, you need to find the metrics that answer those questions for you. You need to hunt down where the most accurate information on the topic lives, and then work to connect all of the most accurate data sources together.

Once we have pulled all of the data together, you have to validate the data to make sure that it is accurate.

After you have all of your accurate data in one place, you can apply formulas and filters to make sure that it’s showing you just what you’re looking for, and then it’s time to plug that data into a data-visualization tool.

OK, I am done with tracking, everything looks good. What now?

Congratulations on making it through the tracking stage! You’re now ready to move into the fun stage: automation.

What compound interest is to your money, automation is to your time.

Automation takes your business to the next level, it allows you to scale your business in ways that most people don’t even imagine. By removing manual reporting and human errors, you not only save your company money, but time. Automation allows you to free up some of the smartest people in your organization to do what they do best rather than fetching data and compiling reports.

The automation stage allows your team to no longer have to look at raw data, but now they can look at actionable KPI’s that they can easily glean insights from. The automation stage rapidly progresses people out of the information and knowledge stages and allows you to begin to focus on the wisdom and Praxis stages exclusively. That is one of the primary reasons that companies who get to this point are able to rapidly scale and expand their business.

Businesses that reach automation can focus on what they do best and let machines do the rest.

That covers the first two steps of data maturity.

The action steps that you need to take in order to get past these stages are:

  1. Start tracking now
  2. Organize your tracking
  3. Map out your most valuable KPI’s
  4. Begin to track those KPI’s
  5. Automate as much as possible.

If you would like to see more of the path of data maturity, be sure to check out our presentation of the entire process of data maturity here: https://praxismetrics.com/blog/data-rich/how-to-scale-in-the-modern-business-landscape/

Praxis Metrics- Chatbot KPI's

4 Fantastic KPI’s that you should be using in your chatbot marketing

How do I measure the effectiveness of my chatbot marketing?

We decided to have a “chat” with the king of Facebook marketing, Curt Maly, to get his thoughts.

Curt is a social marketing expert, owner of multiple online marketing businesses, consultant and national speaker joins us today with his vast knowledge of all things marketing data related.

What are the benefits of chatbots?

People generally react faster to the notifications from a Facebook message than to notifications about an email. Not every customer responds positively though, most people tend to the extremes in their feelings towards these messages: they either love them or they hate them.

Another benefit of using chatbots in marketing is that they help to automate out customer service. Chatbots essentially create auto-responders within an AI platform, allowing you to dedicate your time and resources elsewhere.

Chatbots also help decrease the necessity of traditional funnels. You can utilize chatbots to move your clients from one point of the traditional funnel to the next without needing to set up traditional stages. Rather than segmenting people into phases like a traditional funnel, chatbots allow you to just have a conversation with the client and naturally progress them through their journey.

How hard is it to set up chatbots?

Just like funnels, you can make chatbots as simple or as complex as you would like. Creating a basic chatbot requires minimal knowledge, and only needs a few options for auto-response. Essentially you just need to think through a standard conversation that happens on a sales call or customer service call, and input the different variables into the chatbot.

KPI #1- Cost per Acquisition

This is the amount of money that it takes for someone to engage with your message. You can find this information by dividing your ad spend across the total number of new messages that you get. Facebook will try to conflate this data with Cost per Reply, but that will give you an inaccurate picture of your actual cost per acquisition.

KPI #2- Cost per Reply

Facebook will track this metric automatically for you. It’s a very important metric to keep top of mind, because it can help you understand the cost of re-engaging a lead that you fell out of contact with.

KPI #3- Cost per Open

This metric matches up nicely to open rates on email, with one difference: most people see at least an 80% “open rate” on Facebook messages. This happens because if someone browses Facebook on their browser, the message will automatically open, inflating the open rate.

KPI #4- Click Through Rate

Click through rates on Facebook messenger generally align very closely with email click through rates. Most people will see between 6-10% click through rates on Facebook messages. Many people mistakenly claim that they get better click through rates through Facebook messenger. In reality, they are generally getting more leads than from email, due to the increased open rate of Facebook messages.

Praxis Metrics- Becoming Data-driven

4 vital steps to becoming a data-driven company

Step 1- Remove emotion from the equation.

Your data will always tell you a story; it just sometimes tells a story that you don’t want to hear. Often we find that people stop listening to their data when it gets hard, or right when the details are becoming the most important; but those are the times when you need to listen to the story that it’s telling you even more.

You need to take emotion out of your decision making process if you really want to become a data-driven company. Often the climate of the business has a huge impact on our lives, so it’s often difficult to separate your emotions from the decisions that you make, especially during the hard times. When the times are the toughest are generally when you need to be the most data-driven, and those are the hardest times to take emotion out of the equation; but if you do, it will help you to trust your decision-making process much more.

How do you remove emotion from the equation? The simplest way to remove emotion from the equation is to just let the numbers speak for themselves. No matter how hard things get, they will always get harder if you make the wrong decision.

It’s one thing to make the wrong decision because you went with a knee-jerk reaction; it’s a whole other beast to make the wrong decision because you had bad data. That’s why our next step is:

Step 2- Get your tracking in order.

You can’t make good decisions off of bad data. If your tracking is off, all of the insights that you get from that data are tainted.

One of the top 5 mistakes that businesses make is assuming that everything is tracking properly. Google Analytics is a very powerful, robust tool that helps businesses gain insights into their customers and their behaviors. It is also the number one most underutilized and error-prone tool used by small and medium businesses.

Analytics tools are notoriously difficult to set up properly, and unless you have an expert come in to set it up for you, or you invest the time to truly understand how to set it up properly, it can quickly turn from a bucket full of data to a bucket full of holes.

Many businesses know that their tracking is not correct, but they don’t know how to fix it; so they take the incomplete or inaccurate data that they have and they do their best with what they have.

The end goal of this step is to get you to the point where you have:

  • Organized UTM’s
  • Advanced Pixels
  • Custom Conversions
  • Event Tracking

We’ll go through each of these goals individually:

Organized UTM’s:

UTM’s are one of the most powerful tools that you have in your analytics arsenal, but they can also be very daunting to get started with. That is why we have written several blog posts on the subject matter, which you can find here: How to increase revenue with one simple tweak, Why UTM’s are so important, and we even set up a course that will teach you from start to finish how to create UTM’s and even has a spreadsheet that will automatically create them for you here: https://datarich.thinkific.com/

Advanced Pixels:

Tracking pixels generally have a similar functionalities to cookies. However, as more and more users are blocking cookies using browser functions, cookies provide incomplete data, and are often blocked completely.

Tracking pixels area good alternative to cookies as they cannot be blocked by a normal browser currently. Pixels gather a vast array of user data and pass it along to analytics tools. Some of the most popular advertising platforms use pixels to track user behavior and conversions. In addition to the basic tracking functions, pixels can also track custom events, such as video plays, button clicks, or time spent on a page.

Custom Conversions/ Event Tracking:

As we discussed in advanced pixel tracking, you can track so much more than simply page views and conversions. There is no end to the number of behaviors that you can track on a page. We recommend setting up custom goals, conversions and events within your analytics properties and assigning values to each of these items. While someone may not have purchased through your site, they may have filled out a contact form, or given their email address. If you know the average conversion rate for clients on your email list, and the average order value for them, you can assign a value to each email signup.

It’s just like we always say, your output is only as good as your input. If you can get your tracking in order, you are more than halfway through the journey to become a data driven company.

Step 3- Automate your reporting

Once you have your tracking in order, and you know that you have accurate data; you can move on to the next step: automation

You’ll know you’re ready for this step if you have all the complex tracking in place, but you or your team spends a ton of time gathering valuable insights from different systems and compiling them together into google sheets or into excel and pivot tables.

What compound interest is to your money, automation is to your time.

Businesses that we work with get most excited by this step, because it’s where we begin to focus on scaling the business. Automation leads to a reduction in overhead, increase in productivity, and allows you and your team to focus on the analysis of the information, rather than the collection of data. Automation eliminates the human error component of reporting, further allowing you to have complete confidence in the data that you receive.

To scale your business and progress even more, the focus shifts to integrating your systems together so that they automatically transform the raw data into the insights you need to take action. This allows your team to focus on valuable actions rather than mundane data entry. In technical terms, this is called ETL (automatically extracting, transforming and loading your data into one place). For more information on this process, and how we use it with the companies that we work with, be sure to check out our post on data-driven mistakes even good ecommerce business owners make (and how to avoid them).

Step 4- Democratize the data

The final step that you need to take is to share this information with all the people on your team. You wouldn’t believe the value that democratizing your data can have on your organization. Sharing data allows people to bring their diverse backgrounds and viewpoints to the data to help interpret it.

By allowing your team to access the data, they can bring valuable insights to the table and different perspectives that you might not have seen. We call this the lift effect, and we have seen it happen many times across multiple companies and industries. We recently talked to one of our clients about the value that democratizing data has had for them. Be sure to check out our full interview with Organifi here.

Everyone has their own ideas about what it means to have a data-driven culture. We don’t believe that this list is exhaustive by any stretch of the imagination; but we do believe that if you follow these steps, your business will transform into a data-driven organization. If you follow the steps that we outlined here, we guarantee that you will see a change in your business.

If you have questions on any of these steps, or need help with implementation; we are here to help. We provide comprehensive analytics audits to help see where you may have issues with your data. If you struggle with automation, we have a series of pre-built dashboards that can automate your data for you. If none of those interest you, we can also build out custom dashboards to measure unique metrics for your business.