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- How to create a data-driven culture

How to build a data-driven culture in your company

Creating a data-driven culture within an organization is a monumental task; especially if the organization is well established. In this blog post, we hope to outline the benefits of creating a democratized data-driven culture and some steps that you can take to achieve it.

What is selective data culture?

Most companies have a selective data culture. In this culture most employees don’t deal with data. Data resides in the C-suite and with the data team (if one exists). General employees receive nuggets of information, but they never see the numbers behind it. This often leads to something called the “Atlas effect”.

The “Atlas effect” occurs when an organization relies on one individual to keep all of the data and insights in their head. A system like this results in the individual becoming invaluable to the organization and causes major disruption when they leave.

In order to create a true data-driven organization, you need to democratize your data. This means sharing as much information as you can with your team. This creates a culture of transparency as well as serving as inspiration for your teams.

Our client, Organifi, has created a culture around their data. They democratize their data by having their dashboards displayed on TVs in their office that anyone can look at. And they have daily huddles around their data to make sure that they meet their goals every day.

This has created what they call the “lift effect” for their business. The “lift effect” has resulted from everyone seeing each other’s metrics, causing them create friendly competitions between departments.

You can see more about the effect that this type of culture has had on Organifi here:

Data democratization allows you to engage your entire team in the business data. By doing this, you can leverage the collective strength of your organization. This protects you from relying on individuals, and the “Atlas effect”.

What are the benefits of a democratized data-driven culture?

Employee engagement

“You can’t manage what you don’t measure” -Peter Drucker

In a data-driven culture, employees with less technical skills still work with, and benefit from data. Data allows employees to track their performance and impact on the organization over time, keeping them more engaged in their work. Employee engagement massively helps organizational growth, as engaged employees measure 17% more productive than their peers. Additionally, engaged employees report 20% higher sales than disengaged employees on average.

When employees know the criteria that they are measured against, it helps them remain focused and engaged in their work. Allowing them to track their performance over time helps to remind them of their improvement over time, or serves as a motivator in times of stagnation.

Better ideas

In addition to allowing employees to track their own performance, data-driven organizations allow employees to contribute their specific understanding and knowledge to an analysis. This diversity of viewpoints allows organizations to benefit from a wide variety of ideas. These ideas help them experiment with a number of solutions, and discover new opportunities.

Having someone from marketing look over finance data may seem counter-intuitive, but they may provide critical context to a trend that the finance department didn’t have. Having an operations expert look over sales data can help them understand needs of the team and update or implement new processes to streamline their performance.

Consistent value

In data-driven cultures, employees can discover, reuse, and adapt data to their situation. For example, investing to know the lifetime value of your clients pays off massively over time, as this information provides contextual for your finance, marketing, and operations teams.

As employees gain exposure to data, their data literacy will naturally improve. As data literacy improves, the insights that they bring to the table will get better and better. This cycle increases the potential output of every employee, lifting the entire organization to new heights. This is known as the ‘lift effect’ and we’ll talk about that more later in this post.

Financial

As touched on in the previous benefits, data-driven cultures experience several major financial benefits. One study found that data-driven companies had a 20%-30% higher EBITDA than similar companies.

In 2006, only one of the top-10 companies by market capitalization was data-driven. By 2017, data-driven companies held 6 spots on the list.

Data recently surpassed oil as the most valuable commodity in the world. Is your business sitting on an untapped oil field?

How to start democratizing data

The easiest way to democratize data is to share it. Organifi decided to display their data so that any and all of their employees could see it. Other companies may choose to do weekly meetings where they announce important business KPIs to the entire team. No matter how you go about it, the goal here is to get everyone excited and involved with company data.

Next, it’s imperative that the data be connected to a goal. Data is like gasoline, the goal gives you a destination, and your actions are the vehicle used to reach the destination. Data should fuel the decisions that you make to get to your destination.

From there, the process simply repeats itself. Create new goals, gather new data, share with the team, gather their insights, and hit your goals again.

As you complete this process over and over, it will become the norm and part of your organizational culture.

If you find yourself struggling to create a data-driven culture in your organization, we can help you achieve your goals. Schedule a call with a data expert to see what’s possible for your organization.

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- Major data privacy changes- What you need to know

Major data privacy changes- What you need to know

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.

Legislation

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?

Praxis Metrics- GDPR

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.

Corporate regulation

Apple

Praxis Metrics- Safari Privacy Update

Apple has changed how it handles personal data, with it’s ITP (Intelligent Tracking Prevention) framework in Safari. Third-party JavaScript cookie lifespans are now capped at seven days on all Safari browsers. This new, limited lifespan breaks traditional remarketing efforts and attribution models.

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.

Praxis Metrics- Firefox Privacy Regulations

Mozilla

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”.

Praxis Metrics- Chrome Privacy Update

Google

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.

Pixels

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.

If you’re freaked out by all of the changes hitting the data landscape, we can help. We offer complimentary data strategy sessions with a data expert who can walk you through these changes, and what your organization can do to prepare for the future.

Praxis Metrics- How to monetize your data

How to monetize your data

The most valuable commodity on earth

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.

Praxis Metrics- Data Maturity Spectrum
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.

Praxis Metrics- Data Maturity Spectrum Example

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

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/

External Monetization

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.

Metrics Mapping

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.

Praxis Metrics- Metrics Mapping Process

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.

Dashboarding

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/

Next Steps

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/

Praxis Metrics- How to win in the attribution war

How to win in the attribution war

One plus one equals one and a half?

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.

#1: Tracking

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.

#2: Reporting

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.

Praxis Metrics- Biggest Dashboard Mistakes (And how to avoid them)

The biggest mistakes when it comes to dashboards and how to avoid them

Why does everyone seem to be pushing dashboards right now?

Dashboards seem like the new “it” thing right now in business. Everyone seems to want them if they don’t already have them. But what are the benefits to having dashboards, and what are the most common drawbacks?

We answer these questions, and more, in our guest appearance on the Less Doing Podcast with Ari Meisel, featured here:

What is the biggest mistake that people make with dashboards?

The biggest mistake that people make with dashboards is making the assumption that visualizing the data through a dashboard will magically give them insights. Dashboards help you visualize your data, which can help you to understand your data better, but it’s not going to help you track something new. Many people see beautiful dashboards and they assume that it must be a good dashboard, but the underlying data is much more important than how it’s displayed.

What most people are looking for is not just a data visualization tool, but a business intelligence tool. A business intelligence tool allows you to pull all of your data together in one place, and allows you to see the relationships between what may seem like disparate metrics and systems. By utilizing a business intelligence tool, you can gain new insights from your data and decide how to take action from those new insights.

A lot of businesses use their dashboards only to display what we call “vanity metrics”. They can easily find these metrics elsewhere, and they don’t necessarily deliver insights. Businesses need to use their dashboards to visualize the relationships between different data. Sometimes, it doesn’t even have to be visualized… We have lots of clients that just want to see their numbers all aggregated together in one place. The most important thing is that you can take action from the data that you see. These systems need to give you new, unique insights into your data, or they have wasted your money.

What is your plan?

Your dashboards need to give you insights. The question that people ask next is “What do I do with those insights?”. You need to have a plan in place so that you know exactly what will happen when something changes, or you realize something new. At Praxis, we don’t build a metric unless there is an action tied to that metric. The visual part of the dashboard doesn’t actually matter that much, what matters is that the person who is in charge of that metric can understand what is happening with that metric, and what needs to happen.

We have had clients come to us asking for metrics, and once we have built it out, the client then asked “What now?”. They had no idea why they needed to track that metric, or what actions they needed to take off it, they had just heard other people talking about it and wanted to be ‘in the know’.

Before you start tracking something, you need to have a plan in place as to what you hope to accomplish with that metric. You need to know exactly who takes responsibility for that metric, and what action steps you will take based off that metric. Once you have a plan in place, you will actually see value delivered from your dashboards and analytics.

What are the core metrics that almost every business should track?

LTV-

Every business NEEDS to know the lifetime value of their customers. But they need to know more than just the LTV, they need to know what impacts it as well. It’s important for every business to break out their LTV as much as possible and make it as granular as possible. Your LTV can vary based off the first product they purchased, what platform referred them to you, and even what ad they clicked on. The aggregate LTV isn’t enough, you need to know the granular specifics of the things that impact it.

By understanding the specifics of what impacts your LTV, you can fine-tune how you interact with your customers and drive that number higher. The goal of this metric is not to know it, but to drive it higher.

ROAS/ROI-

Most businesses know this number, but they also need to know their acquisition cost by channel. This will allow you to see how each channel performs individually and see which channel is worthy of your ad spend.

In order to unlock the full potential of this metric though, you need to overlay your acquisition costs with your cost of goods sold, and customer lifetime value. When you put these metrics side-by-side, that will give you the formula for your allowable acquisition cost. This formula becomes one of the most powerful assets that a business can have if utilized properly. We have had clients grow more than 3000% once they have these numbers figured out.

Month over month/ year over year revenues-

While most businesses track this, few businesses take the time to analyze the effects of seasonality on their customers. Even fewer businesses look at their revenue by source. One of the best things that you can do as a business is figure out which platforms perform the best during different seasonal shifts. Should you spend more on Instagram advertising during the summer, or the winter? These insights can help businesses rapidly scale, and can make the difference between breaking out into success and dying off.

At what point does a business have enough data to start tracking these things?

Everyone thinks that only enterprise-level companies can leverage ‘big data’, or that they haven’t reached a level of sophistication to need that type of granularity; but in today’s marketplace, everyone has ‘big data’. Our phones alone contain unbelievable amounts of data about us, every website tracks a multitude of variables on their visitors. The main difference between an enterprise level company and a start-up is that the enterprise level company recognizes that they need to capitalize on their data in order to succeed, while many start-ups fail to recognize it’s importance.

Small businesses use, on average, 8 different technology platforms. Each of those platforms has their own way of tracking data and keeps a small portion of your data hidden away within their platform. The trick is to get all of those disparate systems to talk to one another, or at very least pass all of that data in to your dashboard so that you can analyze the relationships between them and gain greater insights.

Honestly, the best time to start tracking is as soon as you begin operating as a business. The next best time is right now. Tracking your data properly can transform your business in ways that you would not believe.

No business suffers from a lack of data, generally they just don’t know what data to focus on, and what will actually make a difference for their business.

How can I maximize the net benefit from tracking and dashboards?

The most important lesson that you can gain here is that your output is only as good as your input. The first thing that you can do in order to maximize your results is make sure that you have standard operating procedures (SOPs) in place. Because of the tedious nature of this work, many businesses overlook it or neglect it; but the best businesses don’t.

Many employees drag their feet when it comes to SOPs, they think that it doesn’t add enough value to be worth their time. One of the best ways to help them get past this thinking is to show them what’s possible when they utilize them vs what they lose by not utilizing them properly.

Lots of businesses ask, whether they should start with their tracking and make sure that they have done a good job with their tracking, or if they should start with dashboards and visualization. Either one works. If you start with visualization, that can help you to see exactly where you need to improve your tracking. If you start with tracking, then when you move on to visualization, you can have confidence in your data, knowing that it’s accurate.

What can companies do to prepare themselves to work with dashboards or data analysis?

Every company should know what questions they want answered before they ever start working with dashboards and data analysis. Go beyond buzzwords and jargon and really figure out what questions you have that you need answers to in order to progress your business. So start with your company’s goals, and then ask yourself what you need to know in order to achieve those goals. From there, you can drill down and begin to look at the metrics and numbers that contain the answers to those questions.

Once you know the numbers that you need to be pulling, you need to validate your data and make sure that everything tracks properly. Most companies struggle with their Google Analytics reporting, and their use of UTMs. If you struggle with either of these, we can help. For Google Analytics issues, we have an Analytics audit that will run through your entire Google Analytics account and pinpoint issues for you. You can find more on that service here: https://praxismetrics.com/google-analytics-audit/

If you’re struggling with the use of UTMs, or have no idea what they even are, we can also help. We have a course that will take you from UTM zero to hero in less than a day. You can find more information on that here: https://praxismetrics.com/utm-foundations-course/

Once you have your tracking in order, and you know what questions you’re answering with that tracking, it’s time to organize your objectives by feasibility and value. We like to map the objectives across quadrants: high feasibility, high value; high feasibility, low value; low feasibility, high value; low feasibility, low value. Obviously, we want to work through these from highest feasibility and value to lowest feasibility and value.

How can we better track and prevent customer churn?

The first thing that you want to track with customer churn is by source. You need to know which of your traffic sources produces the lowest value customers (those with the highest churn), so that you can pinpoint the issue. Do you need to better explain your offerings on that platform, do you need better qualifications on clients that come from that source?

We also want to analyze retention rates over time, and by cohort. This allows us to see trends over time that increased or decreased churn rates. This helps tremendously in measuring the effectiveness of marketing campaigns and the actual impact that they have on your overall business.

For subscription based businesses, most of them already track the days to cancellation; but they primarily track the average. The problem is that averages are inherently evil. Averages tell us a line from a story, but we need to know the entire story in order to truly understand. In order to know truly when you need to act, you need to know a lot more than an average. You need to know the days that people are most likely to cancel, so that you can update your nurturing sequences in order to reach those people before they leave.

How can I be more effective?

Collaboration-

Too many people isolate departments, data, and communication in their organizations. By democratizing data and decision-making processes, you can take full advantage of the expertise of all of the unique people on your team. The more eyes that you can have on a problem, the more unique perspectives you can gain, and the more solutions you can come up with.

Tracking-

In order to progress your business, you need to be able to pinpoint what worked and didn’t work. If you’re not tracking everything you do, it’s infinitely harder to replicate success and eliminate waste.

Automation-

Too many people spend too much time doing menial tasks. We’ve seen executives spending all of their time pulling reports and data together, rather than analyzing it for insights. Automation may have a high up-front investment, but it pays massively over time. It saves companies thousands of dollars in man-hours, plus all of the human error that goes into the reporting.

If you find yourself struggling with any of those issues, we can help!

We have a myriad of resources here on the blog, but if you’d like more help with your tracking and getting that set up, visit us here: https://praxismetrics.com/google-analytics-audit/

If you need help with automation or visualization, please visit us here: https://praxismetrics.com/dashboards/ltv-dashboards/

And lastly, if you just want to talk to someone about your needs, drop us a line here: https://praxismetrics.com/talk-to-a-data-expert/

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- How to make sure your data is trustworthy

How can I make sure my data is trustworthy?

How much do you trust your data?

When you see information displayed, are you skeptical of it, or do you believe that it is telling you the truth?

Today we wanted to go over why most businesses don’t trust their data, and how to increase your confidence in your data.

Assume nothing

One of the top 5 mistakes that businesses make is assuming that everything is tracking properly. Your output is only as good as your input. If your tracking software isn’t set up properly, then all of the insights that you get from that data are tainted.

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.

If you take anything away from this, do not assume that everything is set up properly, or tracking properly. Make sure that you have an expert set up and validate as much as possible.

People also make the mistake of assuming that once they have Google Analytics set up properly that they can leave it and it will track everything perfectly. Your business is constantly evolving, and your website also is going through constant tweaks, updates, and changes. You need to make sure that everything that you do is tracked in Google Analytics properly, from your goals to your ecommerce, you need to make sure that any changes that you make are reflected in your tracking.

Set up a Data Dictionary

Another big thing that you can do to help increase your trust in your data is to set up a data dictionary for yourself. A data dictionary is a place where you have a source of truth for all of your systems. This will act as a reference point and a description for where that data is generated (Like a phone book for your data). Having a data dictionary helps you know exactly where all of your numbers come from, and it also helps you keep your naming conventions consistent across the board.

Data dictionaries are awesome, but in order to get the most out of them, you need to keep them constantly updated and make them accessible to everyone. Data works best when it is democratized across an organization, rather than in one person’s head or computer. By democratizing the data, you can gain insights and perspectives from everyone across the organization, helping propel your entire company to be more data driven.

Track your data over time

If you want to increase your trust in your data, you need to track it over time. Tracking your data over time lets you pinpoint what works and what doesn’t work with your measurements and reporting. Having a finger on the pulse of your data lets you know when something seems wrong or out of place. This can protect you from making decisions based off bad data.

Do you have a hard time trusting your data? Would you like to have someone check up on your Google Analytics? We perform a 64 point Google Analytics audit to make sure that everything is set up and tracking properly. Contact us here and we can help you trust in your data again.