Praxis Metrics- Leveraging data to optimize ad spend

Leveraging data to optimize ad spend

In this guest appearance on the Perpetual Traffic podcast, AJ and Meaghan talk about how to use your data to optimize your ad spend, and rapidly scale your business.

They cover everything from getting your tracking in order, all the way up to creating customized dashboards and leveraging complex machine learning and AI.

Enjoy the episode and our insights below.

The struggle today-

Many marketers feel that they aren’t getting the most accurate data inside of the ad platforms. Unfortunately, they are completely correct. Some marketers go so far as to purchase a cheap dashboarding tool in order to help them bring all of their metrics together into one platform in order to help them with this issue. Unfortunately, this will not solve the problem for them at all.

Why do we suddenly have this struggle with data? What drove us to this point?

In our opinion, the problem stems from an overabundance of data. Never in the history of the world has so much data been available to us. Even in the last 20-30 years, large-scale data projects were reserved exclusively for enterprise-level companies. But now, every company has access to “big data”; despite this, many still have the mentality that their business doesn’t have the same access to data, and therefore the same opportunities and responsibilities, as the larger organizations.

Because these smaller businesses fail to leverage the data available to them, they often find themselves utilizing incomplete or dirty data. If they utilized all of the tools and tracking options available to them, they would have a much more complete and accurate picture of what’s happening.

The opportunity today-

Similar to the dot-com boom of the late 90’s, we’re seeing a “data boom” today. Those that have embraced data and created strategic initiatives around data are already separating themselves from their competition. Taking action from data is the new competitive advantage.

Those who capitalize on data have the opportunity to outpace and out-scale their competitors. John Wanamaker said: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”. Those who eliminate waste in their budget open themselves to amazing opportunities. By doubling or quadrupling down on the things that work, they can drive exponential growth.

How you can capitalize on this opportunity-

Ask the right questions-

We firmly believe in the Socratic method. Asking questions helps you find deeper truths. The trick is finding the right questions to ask that will propel your business forward.

We found that the best way to find these questions is through a process called “metrics mapping”. The diagram below walks through an example:

Praxis Metrics- Metrics Mapping

Metrics Mapping starts with the big goals of your organization. This could include doubling your revenue year over year, increasing sales of a certain product by 30%, etc. From there, we want to drill down to the questions that you need to answer in order to meet that goal. If you want to double your revenue, then why don’t you? What questions do you need to answer in order to hit your goal?

Once you have the questions that you need to answer, it’s time to figure out what numbers can help you answer that question. In the example above, we need to know how to increase conversions and revenue from the website. In order to figure out how to do that, we need to figure out conversion rates, LTV, CPA, and profitability.

Once we have asked the right questions and gathered the necessary data, we need to:

Get granular with it-

Averages are inherently evil. Averages by definition mash together your highs and your lows and give you one number to work with. In order to properly scale your business, you need to know what creates the highs and what creates the lows. Once you know that, you can scrap the things that bring in the lows and double down on the highs.

Going back to the previous example; once we’ve gathered the numbers, we can strategize our next move. Perhaps we need to update our nurture sequence to increase return purchases. We may have a funnel step that causes dramatic drop-off that we can eliminate.

By getting granular in our analysis, we can discover a myriad of opportunities.

What metrics should every business look at?

Every business suffers from “terminal uniqueness”. While every business has certain things that they specifically need to track, there are a host of metrics that every business should know.

The obvious metrics that fall into this category are ad spend, return on ad spend, etc. In addition to these, businesses should also look at cost of goods sold (COGS), shipping expenses, and overhead. Many businesses forget to factor these costs when they look at what their allowable cost per acquisition can be.

This allows you to look at your return on ad spend through the lens of profitability, rather than just revenue generated.

What is the biggest problem businesses have with reporting?

Over-attribution. We see this issue with almost every client that we work with. Facebook, Google, and every other ad platform utilizes different attribution models. Generally, the platform will leverage an attribution model that favors them, and makes them look the best.

So Facebook utilizes an attribution window, meaning that if someone clicks on your ad, and then returns to your site within 28 days, they will claim that they produced 100% of the revenue from that client. Google defaults to last-touch attribution modeling, meaning that wherever that user came from when they made the purchase receives 100% credit for the revenue of that client. Other platforms count view-through conversions combined with an attribution window, meaning that if they saw your ad and then purchased within a certain time frame, that platform claims credit for that sale.

This scenario can lead to multiple ad platforms claiming that they are responsible for the exact same sale.

How do we combat this issue?

If you’re interested in learning more on this subject, we have a separate blog post on ways that every business can work through the over-attribution problem here.

In addition to those tips, our biggest suggestion for fixing this issue is getting a multi-source business intelligence tool. By extracting data from the back end of each of the ad systems, you can piece together a client’s journey and create your own attribution models. This allows you to see your true customer journey, rather than just a simple metric provided to you by a biased platform.

Unfortunately, even that solution relies heavily on the tracking that you have in place. If your tracking hasn’t been set up properly, then you have to rely on the data reported by these platforms, rather than leveraging and creating your own.

Your output is only as good as your inputs-

It doesn’t matter how much you spend on your powerful tools, they still rely on the data that you give to them. If your tracking isn’t set up properly, it’s impossible for a dashboard to correct that for you.

Powerful insights require great data. And unfortunately, good data requires great tracking.

Good news though, if you can get your tracking nailed down properly, then everything else glides into place. The old adage of “measure twice, cut once” applies to data as much as carpentry.

Going back to the metrics mapping process, we want to help you find the “source of truth” for every metric that you measure.

The “source of truth”-

Every metric should have a place where the definitive answer lives. If you want to know how much revenue you’ve brought in over the last month, you can check your bank account, or Stripe, or Paypal. If you want to know how long visitors from Instagram stay on your website, Google Analytics could help you find that answer.

Each data platform specializes in different data points, and we want to get the best data from the best sources.

Where to begin?

We recommend that every business start with the projects that will move the needle for the business. This generally means starting with sales and marketing initiatives, as they generate revenue for the rest of the business.

We have been shocked at how many issues businesses solve by getting their data set up properly for sales and marketing. Also, by leading with these departments, we can generally start to uncover holes in other parts of the business. If we see a spike in cancellations that coincides with customer survey emails, we know that we clearly have something to fix there.

It’s important to remember with every data initiative that it’s a journey. As much as we wish that we could fix every data problem overnight, it takes time to solve these issues and answer these questions. From there, we need to take action from the insights that we gained, and then we can see the results.

Leverage your uniqueness into growth-

As we stated earlier, every business suffers from terminal uniqueness. While this can complicate projects, that is also the place where you can see the greatest results.

By leveraging your uniqueness in the things that you track, you can get extremely granular, and explode your business in ways that others can’t.

One of our clients, Fancy Sprinkles, found amazing insights by tracking what no one else bothered to track.

Fancy Sprinkles, which does exactly what their name sounds like, gets most of their leads from Instagram. They decided to go back through every post that they had ever done and manually put into a spreadsheet the variables of the post. They tracked whether the product was shot indoors or outdoors, close or at a distance, color palettes, everything.

When they overlaid this data with their social media engagement rates over time, they found amazing insights. During October, they assumed that they should post something orange and black to capitalize on the holiday. But after consulting their data, they quickly realized that those colors got the worst engagement in October. The data told them that they should use purple and green, outdoors, and close-up. Their engagement skyrocketed because of these insights.

Tracking may require an up-front investment. Fancy Sprinkles needed interns to work for hours to catalog all of that data, but once they had the historical data, it became much easier to simply input those data points on every post that they made.

When should people seek help with their data?

As soon as it gets annoying or frustrating.

This may seem simplistic, but it doesn’t make sense for you to abandon your superpowers only to beat your head against a wall.

Your company hired you because of your skillset, and if data doesn’t fall into that skillset, it’s better to outsource that than to take away time and energy from the things that you do best.

What should businesses have in place before consulting with Praxis?

We built Praxis to meet companies wherever they are on the data maturity spectrum.

If you need help with your tracking, we offer Google Analytics audits and implementations. We even have courses that can walk you through setting up your tracking at your own pace.

If you already have your tracking in order and want to move on to scaling your business and gleaning better insights, then we offer pre-built dashboards that can help you start leveraging your data into growth.

If you have issues unique to your market or business that you need specific help on, we offer custom dashboards and implementations that we can build from scratch to better suit your needs.

Praxis Metrics- How to 10X your company using data and dashboards

How to 10X your business with data and dashboards

In this guest appearance on Mike Dillard’s Self Made Man podcast, AJ and Meaghan talk about how to rapidly scale your business using data and dashboards.

They cover everything from the data maturity spectrum to metrics mapping, tracking, UTMs, and how to combine these things for rapid growth in your business.

Check out the full episode below along with our summary of key takeaways.

How did Praxis get started?

Prior to starting Praxis, AJ and Meaghan created a data-driven digital marketing agency. They quickly found though that reporting on their marketing efforts was taking more time that actually implementing their strategies. Because of this, they began researching automated solutions to the reporting problem. Once they finally created a solution, they found that more people needed that solution than needed marketing help.

They decided to pivot and become an outsourced data agency, and Praxis Metrics was born.

Initially they courted enterprise-level clients because those clients were they only ones seeking out “big data” at the time. However, as time passed, they realized that they gained more satisfaction from helping SMBs achieve their potential through data. So they began to provide the same powerful insights and dashboards that they had built for the enterprise clients to smaller businesses.

What are the biggest takeaways from working with such a diverse group of clients?

SMB business owners need the same questions answered as the enterprise companies. While they may look at them through different lenses and different granularity, the questions remain the same.

The number one question that every client asks is, “how much can I spend to acquire my customers?”. Generally, the next questions asked are: “how much are those customers worth over time?” and “where and what do they purchase from me?”.

These questions all stem from the same desire: understanding your core customers, and how to best serve them.

It all boils down to what is and isn’t working in your business right now.

What are some of the biggest differences in SMBs and enterprise companies?

Enterprise companies recognize how much data they have, and the value of that data. SMBs often downplay the amount and value of the data that they already have.

Most SMBs don’t realize that even just having timestamps of when your customers purchase provides valuable insights to the business. This lets you know the times when your purchasers will be most receptive to your messages and most likely to purchase your products.

What difficulties do businesses face with their data?

Trusting your data is the key to gaining good insights. If you don’t trust your data, then the prettiest dashboard in the world will not help you.

You need to have the confidence to take action from your data; otherwise it’s like having gasoline but no car. You won’t get anywhere with that.

We’ve seen a multitude of dashboard companies that sell businesses on the visuals of their dashboards alone, but without fixing the underlying data issues, they end up providing very little value to their customers.

Time constraints

Many SMBs say that they simply don’t have the time to get their data in order; but we preach the opposite. The best time to set up your tracking and make sure that you gather clean, accurate data is before you have too much of it. As your organization scales and grows, the amount of clean-up required in order to get your data in order scales as well. If you make a concerted effort in the beginning to get clean, accurate data that you can trust, your business will scale faster. And when the time comes to transition into dashboards and advanced analytics, your data will be ready and actionable, saving you valuable time and money.

Every business has the time to sit down and set up standard operating procedures (SOPs) for their business. Setting down SOPs is especially important when it comes to UTMs. If you can lay down the groundwork early on for standardized tracking, you can gain amazing insights on how to communicate effectively with your clients.

UTMs will tell you what types of content your customers like to engage with, it will tell you the specific mediums that they like to engage with your business on, and it will help you eliminate the issue of over-attribution in your tracking. If you want to learn more about over-attribution, and how that affects businesses, we have a blog post on that here.

How do we lay the foundation for the future?

Even if you don’t have the time to analyze the data yet, it’s imperative that you begin tracking your customers and their behavior. You can’t retroactively gather data from your customers. When it gets to the point that you want to begin retargeting campaigns, or analyzing your customer behaviors, if you didn’t set up your tracking you won’t have any information to go off.

When they begin advertising, many businesses start with a shotgun approach. They distribute their spend equally across the most popular platforms without knowing which one will drive the best results for their business. If you track your customer behaviors over time, they will show you where they like to engage with you. You can know whether you get the highest traffic from Facebook or Instagram or Linkedin.

What are some of the data success stories that Praxis has seen?

Danette May-

Danette May wanted to see the true lifetime value of their customers to see if they could scale a funnel. They knew that the funnel converted well with retargeting, but they had a hard time getting the same response from cold traffic. They had an idea of the LTV of their customers, but they wanted to verify.

We found that their customers actually had a much higher LTV than they thought. This allowed them to increase their allowable cost per acquisition (CPA) by $5. This change caused them to take an initial loss on the first product sold, but they also knew that within 30 days, these clients would return and spend much more on other products.

This change drove them from 15 sales per day on this product to more than 350 sales per day in less than two weeks. Within a month, they were selling more than 600 units per day.

If you’d like to learn more about Danette May’s journey and how this information helped them transform their business, we have an entire case study on them here.

Fancy Sprinkles-

We built a social media dashboard for Fancy Sprinkles that allowed them to drill down to see what kinds of posts received the most engagements over time. By tagging all of their posts with series of metadata: I.E. indoor vs outdoor shot, colors used, theme, etc.

Because of this metadata, they found that during Halloween the top performing posts contained purple or green, were shot outdoors, and had close-ups of the products. Naturally, this ran completely counter to everyone’s instincts, but it allowed them to provide their audience with content that they actually wanted to engage with. Because they had this data, they outpaced their competitors in engagement and attention.

What are some of the data failure stories that Praxis has seen?

We’ve had clients who utilized free shipping discounts in order to better compete with Amazon. These clients assumed that this would inspire higher customer loyalty, and create repeat customers. Unfortunately, when we cleaned and examined their data, we found that this wasn’t the case at all.

This assumption was costing them dearly over time, preventing them from properly scaling, and could have driven them out of business if it had gone on for too long.

The key to success is listening to your data.

The most viewed person on Facebook was a magician who simply did magic tricks in front of his webcam in a coffee shop. He managed to scale his brand and following by tracking the videos that performed best and then replicating the factors in those posts over time.

Data doesn’t have to include machine learning, or advanced AI algorithms. A simple excel sheet that analyzes data points can drive more success than multi-million dollar solutions.

If you don’t analyze your data to see what works and what doesn’t; your competitors will analyze that data, and eventually overtake you because of your failure to capitalize. Data has the power to topple huge organizations like Barnes and Nobles or Blockbuster, and the pace of change is only accelerating.

Who does Praxis work with, and how can they prepare?

We have historically worked with enterprise companies; so we can work with larger organizations, but our passion is working with SMBs and helping them rapidly scale their businesses.

We have brought the “big data” insights to the SMB market by finding the common threads between every implementation that we have done for these enterprise companies. By finding the common questions that everyone has, we have built out plug-and-play dashboards that can help answer those questions. Because these dashboards require very little ramp-up or custom coding, we can offer them for a much lower price than normal, and roll them out much faster.

These dashboards answer some of the fundamental business questions that every business needs to know: what is the LTV of my customers, how are my subscription services trending over time, what products drive the most revenue and value, etc. We extract this data from multiple sources, ensuring that you get the most accurate and valuable data.

Our pricing ranges from $500-$1500 per month for platform costs, and then we just charge hourly for any work to build out the dashboards and connect to data sources.

Preparation-

We meet our clients wherever they are on the data maturity spectrum. A lot of our clients come to us and they need help getting their tracking in order before they move onto dashboards. We offer services to help with that. No matter what your data needs are, we can help you get from where you currently are to where you want to be.

If you need help diagnosing your data needs, we offer free, personalized data roadmaps to clarify the next steps for your business.

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- 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- The importance of knowing the lifetime value of your customers

Data-Driven Conversations: The Importance of Knowing The Lifetime Value of Your Customers

What is the lifetime value of a customer? How does that affect the way that you market your products and scale your business?

These are some of the questions that we had in mind when we went into our conversation with Jeremy Reeves on the Data Rich Podcast. Below is the video of the entire conversation, as well as a transcript of the highlights:

What does it mean to be data driven as it relates to customer LTV?

Being data driven boils down to being aware of the choices that you are making, and making the right choices by utilizing data.

An example of this would be if you are looking to roll out a new product, you need to know exactly how much you can spend to acquire a new customer. If you don’t have data to tell you that information, you are essentially guessing, and that can cause you to be limiting yourself in terms of growth if you’re not paying enough for new customers, or it can be driving you out of business if you’re spending too much to acquire those customers.

If you don’t know the metrics, you don’t know what decisions to make.

How soon in a business should you worry about LTV?

This varies from business to business, but comes down to how quickly you want to scale your business. If you are looking for explosive growth, then LTV is THE metric that you need to worry about. This will help you determine the cost per acquisition that you are willing to pay. In the example above, they realized that if they set their break-even point per customer at 3 months rather than immediate, they were able to pay 30% more per acquisition, which allowed them to jump from making 15 sales per day to making 300-400 sales per day.

By drilling into the numbers and truly understanding the value of their customers over time, their sales were able to increase by 2500%! When you view the true value of a customer over time, you can make decisions like this that help you to experience explosive growth as a company.

How do you maximize returns based off customer LTV?

The best way to maximize your returns is to get extremely granular with your data. Go beyond just looking at the generic LTV of all customers, and see the LTV of customers based off of their referral source, or check to see what other products they purchase after the initial purchase. The more that you can break down the data and individualize your targeting, the more you can glean insights into your consumers, and in turn maximize your returns.

What is the best way to track LTV?

This is the question that you really need to answer for your business. You need to determine how you want to define and track the value of your customers over time. This will be contingent on the systems that you are using, the types of products that you sell, and how you want to think about your products.

Going back to the previous point about getting as granular as possible, you can break down the LTV of your clients based off what their initial purchase was, by referrer,

When should you make changes to your budget based off the LTV calculation?

Unfortunately, just like the last question, this depends on your business. If your company has a long buying cycle, you should probably wait to increase your budget until you see the results from your efforts. If you are able to make back your budget based off the initial purchase, you can increase your budget immediately. By understanding when people are able to hit that break-even point in your business, you can know exactly when you should increase your spend.

How can I set up tracking to make sure that I am getting good data?

You need to make sure that your attributions are set up properly in Google Analytics, so that you can break out customer behavior by traffic source in order to see exactly what your spend should be for each source. Past that, it is highly recommended that you break them out into funnels or campaigns that you are using so that you can properly attribute the LTV to each of the campaigns that you run, as well as the sources.

This requires a great deal of work up front, but once you lay the foundation of good data it is much easier to continue down that path, and you know that you can trust your data.

What is the number one thing that all marketers should know about the LTV of their customers?

The obvious first thing that you need is to know the number. If you are not conscious of the LTV of your customers, you need to find out what that is. After you are aware of the average LTV across the company, you need to get more granular with it, and drill down into the LTV per product.

Once you have those numbers, you need to determine your business goals. If you are in a growth stage of your business, where you are trying to scale, don’t be afraid to break even up front. Be aware of how long it will take for you to start profiting, and make sure that you are comfortable with waiting for that; but once you have determined that, you need to move forward. The business that can afford to spend the most to acquire the customer wins every time.

If you have any questions about dashboards, tracking, analytics, or if you want custom dashboards built for your business then talk to one of our data experts.

Praxis Metrics The 5 Devastating Data-Driven Mistakes You May Be Making Right Now

The 5 Devastating Data-Driven Mistakes You May Be Making Right Now

Let me ask you a question. How important is data and reporting to your company? It’s interesting when I ask people this question, which I do almost every day. It varies from “not using data that much” to “we’re data driven masters who implement data discovery into almost every decision we make.”