How ecommerce companies can turn data into growth

How ecommerce companies can turn data into growth

Meaghan and AJ were invited to speak with Alex Brown, founder of Ecommerce Rockstars. They cover everything from data foundations to predictive analytics, so don’t miss out! Check out the full interview and our insights below:

Data shouldn’t be scary

When businesses think about data, most of them think of massive data warehouses with AI and machine learning algorithms. While that may be something to strive for, that’s not data. Data is simply information. Every business has information; now more than ever.

Praxis wants to help businesses find ways to leverage the data that they already have to make better decisions. We always say that we’re in the waste business. We help eliminate wasted time, effort, and money.

The goal of any data project should be to answer your business questions. We want to help businesses answer the questions that will help them scale. Whether your ecommerce business is just getting started, or if you’ve been in business for a few years; this can help you figure out what next steps to take and how to grow your company.

The roadmap to data mastery

While the end goal may be to run massive data projects and collect granular data on every customer’s spending habits; we need to start at the beginning. The more information you have, the better decisions you can make; that means that the less data you have, the worse decisions you make.

That’s why Praxis built out the data maturity spectrum, to help businesses figure out where they stand, and then what to do next.

The data infancy stage

Most companies start in data infancy. They don’t have time or means to dedicate to data and analytics projects; so they put it off. We characterize this stage with a general “spray and pray” type of attitude. Businesses in this stage generally are just throwing ideas at the wall in order to see what sticks.

As they start to see what sticks, and what works and doesn’t work; they begin to lay the foundation for their data strategy. This moves them into the data foundation stage.

The data foundation stage

As businesses start to gather reports and notice patterns, they start to grow their data maturity. In the foundation phase, businesses start to track the cause and effects of their actions. Generally this involves manual reporting, pulling data from disparate sources into spreadsheets, and using complicated pivot tables to analyze the data.

We call this stage “spreadsheet hell”. Businesses in this stage generally have some automations when it comes to their reporting; but they often rely heavily on human input and data aggregation.

The data foundation stage is generally the phase in which businesses start to see explosive growth. Because they track what works and doesn’t work, they’re able to start replicating efforts and successes. In order to continue growing at the same rate, they’ll need to move up the scale of data maturity to the data optimization stage.

The data optimization stage

In the data optimization stage, businesses focus on automation. During this stage, businesses move away from manual reporting and begin to create automatic ETL processes. ETL stands for Extract, Transform, and Load. The idea behind this process is to extract the data from the different “sources of truth”. The source of truth is the place where the most accurate data on whatever you want to measure lives. For example, in the case of financial data, the source of truth would be your payment processor or bank account. For Source/Medium data, the best place to get that data would be Google Analytics.

Next, we need to transform the data as needed. Transformation of the data entails taking all of the data from your disparate sources, joining it and then cleaning it to make sure that it’s all tracking uniformly and the data is formatted properly.

From there, we load the data into a data visualization tool so that you can easily analyze and leverage your data into growth.

The end goal

The end goal of this entire process is getting you data that you can take action on. Data for the sake of data won’t do anything for your business; you need to take action from it. Having data and not taking action from it is like having an expensive race car and then never putting gas in it.

Going with the race car analogy, if you want the car to perform optimally, you need to put only the highest quality gasoline in the car. Your output is only as good as your inputs. The same is true with data; in order to get amazing insights from your data, you need to have clean data coming into your systems.

If you don’t know how to make sure that everything tracks properly, we recommend using a process called “Metrics Mapping”.

Metrics Mapping

The process of metrics mapping is actually pretty simple, and helps you gain clarity in what you need to track and how to use the data once you have it.

You start metrics mapping by defining your goals. As you can see in the example below, this company wanted to double their revenue year over year.

Metrics Mapping

From there, you need to figure out what questions you need answered in order to attain that goal. In this case, they need to know how to increase the conversions on their website.

Once you know the questions that you need to answer, it’s time to figure out what metrics can help you answer those questions. In this case, they decided that the metrics that would help them the most would be the conversion rates for each of their funnel stages, customer LTV, allowable CPAs, and channel profitability.

From there, you need to decide on a source of truth for each of those metrics. You can find funnel stage conversion rates through Google Analytics goals, enhanced ecommerce tracking, or event tracking. Lifetime values would be through your ecommerce platform. You would need to calculate allowable CPAs for your business based off your margins, COGS, and LTV. And finally, you can find channel profitability by tracking your CPAs, LTV, and COGS.

From there, you want to validate the data across as many sources as possible and make sure that your sources of truth align. Then you can begin the process of applying your calculations and loading it into a data visualization tool.

If you’re not able to track any of these metrics, then you can know exactly where you need to focus your tracking and figure out a platform that will help you track those metrics.

Lead with revenue

Every data project should help you make more money. If you’re running a data project to get a metric that is “nice to have” or “nice to know” then you’re likely wasting your time, energy, and money.

As we talked about before, you need an action tied to your data. If something changes, you need to know what you’ll do, and who will do it. Once you have action tied to metrics, it becomes much easier to determine the value of that metric. For example, if you can get a 10% increase in the lifetime value of your customers, you can easily calculate out the value of that kind of change for your business.

The key when determining KPIs is figuring out which ones are the most feasible and deliver the maximum impact. As shown in the chart below, we want to focus on the things that drive the highest business value and are the easiest things to implement for your business.

The key is to make sure that you don’t work on data projects just because you can. Those belong in the bottom right quadrant and should be treated as the second to lowest priority for the organization.

Praxis Metrics Feasibility Quadrant

The beauty of this chart and this process is that as you implement your data projects and improve your data processes, you can increase the feasibility of future projects.

The big data secret

The biggest secret when it comes to data projects is that no matter the size of the company, everyone wants the same information. They want to know how to decrease their waste and increase their bottom line. The easiest way to do that is to ask the right questions, you can just run down the rest of the metrics mapping process.

Too many SMBs think that they don’t have enough data to compete at scale with large companies, but today everyone’s cell phones have big data. We had a client that had 4 million rows of data stored in the back end of his payment processor; and that was just a couple months worth of data.

Almost every tool the businesses use store data, and every data point can help deliver valuable insights. We have found that most small businesses have a treasure trove of data available to them, but they don’t realize it.

Every company is a data company

If you’re not looking at your data and finding ways to better optimize your company, your competitors likely are. We have seen massive giants fall by the wayside because they failed to take appropriate action off their data.

The time to start taking action off your data is now. At very least, start setting up your tracking, or aggregating data. Even if you’re not ready to use it yet, you’ll be grateful to have it when you are ready to tackle big data projects.

Another great place to get started is with your North Star Metrics. These are metrics that all other metrics rely on. For Airbnb, their North Star metric is nights booked on the site. The more nights they have booked, the better their overall business does. For Facebook, they look at active daily users; this allows them to keep their finger on the pulse of usage of the site and retention over time.

You may not have time to run down and figure out all of the KPIs that impact your business; but you can figure out the one. Take the time to figure out your North Star Metric, and start tracking that. You can start to map out the trends, look for causation, figure out what drives it up and down. This is an easy way to get started with a data project, and helps establish value for future data projects.

You don’t have to reinvent the wheel

Dashboards and data visualization tools have been a hot topic as of late. Lots of businesses jump in to the world of data visualization and end up getting an expensive platform that ends up just displaying data that was readily available on other platforms, or they get a powerful business intelligence tools that they can’t fully utilize.

Praxis helps businesses incubate their dashboards under our umbrella. We offer several pre-built dashboards that can answer some of the most important business questions. Once you have gleaned value from those dashboards, we want to help you graduate into custom dashboards that answer questions specific to your business.

If you’re not sure where to start, we offer free data strategy calls where we can walk through and help you diagnose where you are now, and help you figure out how to get to where you want.

How to use data to rapidly grow your ecommerce business

How to use data to rapidly grow your ecommerce business

If you are looking to grow your business, get more leads, simplify, or create more freedom, then you’re going to want to continue. AJ and Meaghan recently went on the Growth to Freedom podcast with Dan Kuschell to talk about data, automation, health, and relationships.

Check out the full podcast here, and out insights below.

Data for entrepreneurs

Most entrepreneurs think of themselves as left-brain individuals. They rely on intuition and instinct to help them make their decisions. Meaghan and AJ used to think this way as well, but someone helped redefine that for them. While talking to a mentor, Meaghan mentioned that she was the down-in-the-weeds person and AJ was intuitive and head-in-the-clouds. As an illustration, she talked about how she relied on data and AJ went with his gut.

This mentor quickly pointed out to Meaghan that intuition didn’t work the way that she described it. Intuition occurs when the brain processes data and recognizes patterns faster than we can perceive. That means that even those that think that they aren’t in tune with data really are.

Often these intuitive people think that they just get lucky, or they’ve just got good gut instincts; but in reality, they just connected data points in the back of their mind without recognizing it.

Data is just individual points of information, but it’s not useful like that. The value of data comes when you connect those data points together and find a pattern or correlation. When people say that they’re naturally intuitive, they have an ability to create those connections in their mind without even noticing.

The importance of LTV

We’ve talked a lot about customer lifetime value and how it important it is for organizations to track. What we want to make clear is the importance of not just using an average as your measurement for LTV. We always say that averages are truly evil because they don’t give you an actionable insight. Knowing a single, static number doesn’t do much for a business; the point is to take action from it. Businesses don’t just want to know what the number is, they want to impact it, to change it, and to increase it.

You need to examine LTV over time. Your business is constantly in flux, and so the value of your customers naturally will vary as well. What was the LTV of your customers last month, or one year ago, or even two years ago? You need to have multiple data points in order to create a trend or pattern. Once you have that trend or pattern, you can find the causes for the fluctuations, and then you can capitalize on the things that caused the upswings and eliminate the things that caused the decreases.

In order to do that, you have to get granular with your LTV. You need to know where your highest LTV clients come from, what they purchase, when they repurchase, etc. And on the other side of the coin, you want to know where the lowest value clients come from, what they purchase, etc. If you can double down on getting the high end clients and stop spending money on lower-value clients then you can dramatically increase the overall LTV of your clients.

Reduce waste to increase results

If you’re using an average and taking action off of that, you’re creating a massive amount of waste. Because averages mush together the highs and lows, if you just double down on everything, then you end up doubling down on some things that don’t work. That creates massive amounts of waste.

The best way to reduce and avoid waste is to get granular with your data. Rather than taking a shotgun approach, you need to take a precision, surgical approach. By taking the precision approach to your data, you can hyper-focus your efforts on the things that work, and eliminate the things that don’t.

Avoid wasting time and effort with a dashboard

Most businesses start looking at dashboards, and they don’t even know where to start; so they start with what they know, or what they’ve read. They look at dashboards for specific KPIs or specific metrics. They forget to look deeper into the why of the dashboard.

At Praxis, we don’t build out a metric without both us and the client understanding the “why” of the metric. That’s why we start all of our data projects with a process called metrics mapping. Metrics mapping is a process that helps you make sure that you’re only tracking things that are actually valuable to your organization.

Metrics Mapping

The process of metrics mapping starts with establishing your high-level goals. What does your business want to accomplish? As you can see in the example below, this business wanted to double their overall YoY revenue.

Metrics Mapping

The next step in the process is to determine what questions you have that you need to answer in order to reach your goal. Do you need to know how to increase customer retention by 30%? Do you need to figure out how to double your average order value? In this example, we’ll stick with how to increase conversion rates on the site.

From there, you need to figure out what metrics you can use to answer that question. In this example, the client needed to know the conversion rates for the different stages of their funnel. Additionally, they needed to know their customer LTV, allowable CPA, and finally their profitability by channel.

Once you know the metrics that you need to measure to answer your questions, it’s time to determine the “source of truth” for each of those metrics. The source of truth is the place where you can find the most accurate information. So, for financial metrics, we would recommend using a payment processor, or bank account. For source data, Google Analytics works best.

From there, you want to validate your data across sources and then plug it into a dashboard.

Focus on the needle-movers

Before you can understand how to scale your business, you need to understand lead indicators and lag indicators. Lag indicators are the easiest and most common things that people measure. They measure what happened after the fact. Examples of lag indicators are revenue, total sales, etc. Leading indicators are the actions taken that drive the results. These could be things like emails sent, phone calls made, ad spend, etc. These are the efforts that drove the lag indicators for the company.

When it comes to metrics, we divide them into 3 classes. Descriptive, prescriptive, and predictive. Descriptive analytics tell you what happened in the past, prescriptive analytics help tell you what you should and shouldn’t do, and predictive analytics tell you outcomes to expect when you implement the prescriptive analytics.

Each of those classes of data can be thought of as a phase of data maturity. In order to get to machine learning and AI, you need to have descriptive analytics that tell you what happened. From there, you can start to merge your data together and combine metrics in complex calculations to help you understand what to do next. Finally, you can move on to allowing computers to extrapolate models and forecasts based off the information that you have already gathered and tracked.

The most advanced AI can’t create models without data to rely on. That’s why it’s important to make sure that at every phase you have everything set up and tracking properly before you move on.

Leverage attribution to your advantage

Unfortunately, attribution will always be a war-zone. Every platform will leverage the model that makes them look the best, and there isn’t one attribution model that works best.

The easiest attribution model for the most businesses is last-touch. Since Google Analytics defaults to that as well, it’s generally the baseline for most companies. The ideal attribution model is one that can tell you what the best first-touch campaigns are (the ones that generate the most interest and awareness for your business), then the ones that tell you what the ideal middle-touch points are, and finally the best last-touch campaigns. That would allow you to optimize your ad spend across those campaigns and create a fully optimized customer journey.

Unfortunately, at the moment, such a model doesn’t exist. The best way to create such a model for yourself would be to use attribution comparison tools to compare each model and find the ideal journey yourself. This relies heavily on accurate tracking though; every podcast appearance needs to have a UTM link in the show notes, every email campaign needs to be tagged, and your website needs to have all of the tracking installed properly. If any of those fail to work properly, then the entire model can fall apart.

The un-sexy part of data

We’ve covered the best parts of data, turning your data into insights, and insights into revenue; but all of that requires the un-sexy, foundation. In order to get 6-pack abs, you have to sweat and look janky at the gym.

Tracking is the gym section of data. We have to pump some serious data iron in the back-end before your data is beach-ready. You need to make sure that you have UTMs attached to every single customer touch-point; additionally, those UTMs should ideally be standardized. You need to have every page and every funnel on your website tagged and tracked. You need to have event, goal, and ecommerce tracking in place to make sure that you’re tracking funnel steps properly.

Once you have all of that set up, you have to validate the data to make sure that everything fires correctly, with no duplicates or missing pieces of data.

Choosing a data platform

There are hundreds of data visualization tools on the market. The problem is that most of them are just visualization tools; and not business intelligence tools. Business intelligence tools can connect multiple sources of data together, whereas most of the platforms today are just single-source dashboards. While it may be helpful to see your data visualized, the best insights come when you can combine multiple sources of data together.

Getting started

As we talked about with the foundation stages earlier, the first thing that you need to do is make sure that your tracking is set up correctly. Once you get your tracking set up, the next thing that you want to do is standardize your tracking. Make sure that all of the parameters are aligned so that you can get clean, standardized data across your platforms. Once you have that taken care of, the next step to take is automation.

Most of our clients come to us in between standardization and automation stages, in what we call “spreadsheet hell”. In that stage, you have tracking and data set up, and you’re trying to get all of the data together in one place; that lends itself to spreadsheets, and generally that turns into lots of spreadsheets. Once you hit that point, it’s generally time to start migrating to a dashboard solution.

Get creative with your data

As we’ve stated a few times, data can and should be sexy. One of the ways to make it sexy is to leverage it in creative ways. Meaghan and AJ decided that they wanted to quantify love and figure out how to optimize their love life. Once they started tracking the data on their relationship, they found gaps that were causing fights between them. Upon realizing this, they quickly made adjustments and now get more out of their relationship.

One of our clients, Fancy Sprinkles, had another example of how you can get creative with your tracking and data to make it sexy. They wanted to figure out what types of content they should post on social media. In order to figure that out, they went back through all of their social posts and tagged each one with meta-data. They tagged each post with information on whether the photo was inside or outside, a close-up or wide shot, and what colors they used.

When they mapped that data out across time with the engagement rates, they quickly found actionable insights that allowed them to skyrocket their social engagement.

Praxis Metrics- Leveraging data to optimize ad spend

Praxis Metrics – 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, visit Praxis Metrics – How to win the attribution war to read more.

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- 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: Praxis Metrics Case Study – Digital Marketer

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: Praxis Metrics Case Study – 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 free Praxis Metrics strategy call to get a personalized data roadmap for your company from a Praxis Metrics data expert.

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 Praxis Metrics – Google Analytics Setup to read more.

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 the Praxis Metrics free data strategy session form, and we can talk about the unique needs of your business and how we can help you turn your data into growth.

Praxis Metrics- How dashboards can double your revenue

Could you be one smart data-driven decision away from doubling or tripling revenue?

How can data visualization help my business?

Most companies have tried out some sort of data visualization or dashboarding solution. And lots of those companies feel like they have not gotten their money’s worth.

In this video, we sat down with Alex Brown to talk about how to: grow your eCommerce revenue now, increase lifetime customer value, and have accurate data you can trust.

As we discussed in the video, we came up with a refined list of KPIs that every eCommerce company SHOULD have insights into, but most don’t.

We built this “command center” that combines your top of funnel marketing efforts with your entire customer purchasing journey, so that you can see patterns and anomalies otherwise unknown to you, like:

Which marketing efforts are yielding the highest 30, 60 or 90 day LTV?
Which affiliates are bringing you customers who come back and purchase again and again?
What funnels are yielding the highest or lowest customer retention rates?

Knowing the accurate LTV of your customers is crucial for exponentially growing your eCommerce business.

Once you know how much you make per customer and how long it takes you to collect that money from each customer, you can adjust your budget to acquire them.

We had a client that grew from 15 leads per day to 350 leads per day using just this one metric. Check out their story: Praxis Metrics Case Study – Danette May

Knowing the LTV of your customers allows you to answer a litany of business questions.

This dashboard gives you the EXACT insights into what your customer is worth at 30, 60, and 90-days. In addition to this, it also answers several other business questions you are probably already asking; but aren’t getting instant answers to, such as:

What variables in my business and my marketing efforts yield higher LTVs?
Does customer LTV change when customers based off their traffic source? Does it change based off what product they purchased first?
Are my marketing efforts increasing my LTVs, or making them worse?
What products are people coming back to purchase after their initial sale?
How many customers are repurchasing from us, and when can I expect that revenue?
Am I speeding up my customer’s journey to purchase? Is it somehow slowing down over time?

Who are my best customers? Where did they come from and what are their purchasing behaviors?
How much revenue am I getting from different products?
How’s this month’s revenue compare to the same month last year, or last month?

This is just one of several pre-built dashboards that we have ready for your business. Our platform integrates with thousands of analytics tools to help you get the most out of your data.

Do you want to learn more about this pre-built LTV revenue and subscription dashboard?
Be sure to watch our more in-depth video and apply to see if you qualify for this awesome dashboard then schedule a call with a Praxis Metrics data expert.

Praxis Metrics- Encompass Health Data-Rich

How Encompass Health became data rich

What does data have to do with medicine?

Obviously a lot. Just in practicing medicine, doctors need to examine a multitude of data points; but then they also have to run a business on top of that. Every business has their own set of metrics and KPI’s that they have to track, but compounding that with the difficulty of running a medical practice can be too much. That’s where Encompass Health steps in. They help the doctor’s offload some of the office work so that they can focus on practicing medicine, and we help them in that quest.

How did Encompass Health get involved with Praxis Metrics?

Encompass Health was initially just using Domo for their data visualization, but they wanted to get more training on how to best utilize the program. Seeing as Encompass Health is still a small company, they couldn’t afford to dedicate an employee to learning the platform. Contracting with Praxis allowed them to have an outsourced data team available whenever they need, but at a fraction of the cost of an employee. This also allows them to take control of the platform and learn at their own pace, and then whenever they need help, Praxis can step in to help.

How did Praxis Metrics help?

Praxis helped them with the visualization of their data as well as the ETL (Extract, Transform, Load). The process of ETL is to take data that is formatted, reported, and measured differently in disparate systems and standardizing it so that it can be visualized together.

The team at Encompass knew what they wanted their data to look like, and then the team at Praxis was able to execute on that vision. We set up their data as an executive view, with the option to drill down into specifics. In the healthcare industry, most people focus on the executive level summary. From there, individuals may want to drill down into the details; so we set up their dashboards with that option. The Encompass team could set up the executive view, but the Praxis team also created a drill down path for them as well.

What benefits has Encompass Health seen?

Encompass Health knew that they wanted customization first and foremost. The dashboards that we built allowed them to do just that.

Another benefit was the outsourced data team; as they stated, Austin is a powerhouse of an employee. Austin knows data extremely well, and can create almost anything that the mind can conjure.

Being able to take their data on the go, and view it wherever they need to has also helped them tremendously.

What’s next?

Encompass Health has become data-rich, and now they will help their doctor’s become data rich as well. They plan to start rolling out more advanced features for their clinicians, helping them to make even smarter business decisions.

If you’d like to learn more about the dashboards discussed in this video, visit us here.

Praxis Metrics Organifi dashboard data team

How Organifi became data rich

Want to see what’s possible when you turn your data into growth?

We sat down with one of our long-time clients, Organifi, to talk about how their business has changed and grown since they became data rich. Below is the full video of our conversation, as well as some of the highlights:

Your output is only as good as your input.

There is a reason that we say this all of the time; as Louie described, Organifi was using dashboards before they became our client, but their dashboards were just linked to spreadsheets. People updated the spreadsheets on a daily basis (or at least they were supposed to), but their dashboard data relied on human input. We automated out their dashboards, eliminating the possibility of human error, and also guaranteeing the most up-to-date information.

This data has helped them to rapidly scale their business.

How has this data changed the way that they do business?

Organifi can now see the lifetime value of their customers broken out by the channel that they come from, or what they purchased when they became customers of Organifi. This allows the team to determine and adjust their ad spends across different platforms, and better determine which products to push. The best part of all of this? They know that their data is accurate. Since we removed the human element of their tracking, they now have complete confidence in their reporting.

The team at Organifi has daily huddles where they can review the key performance indicators for each of their departments. This reporting in front of the whole company allows for greater transparency across the company. This also increases the accountability of each individual department. As Louie describes in the video, this increased accountability has also led to an increase in friendly competition between the departments, creating a “lift-effect” for the company.

Louie also talked about how the democratization of data allows everyone in the company to feel like their efforts make a difference. Everyone from the C-suite to the entry-level employees sees the same data, and can see how every department contributes.

What data is fun to look at?

Louie’s favorite metric to look at is E-commerce spend vs revenue. This is his favorite because it allows him to see their ROAS in a visual way (as he puts it, the big spike with the little one beneath it).

Everyone has a metric that they love to look at, and a reason that they love it. For most, it generally has to do with revenue, since that impacts everyone in the company; but we want to know, do you have a favorite metric, and why?