Major data privacy changes- What you need to know

The data landscape rapidly changes and shifts, but a flurry of recent announcements will shaken the core of how we measure and track customers.

What is happening?

Basically, until now we’ve been living in the wild west of data, but after a wave of data scandals a new sheriff has come to town. And this sheriff is changing all of the rules. The new priority for data is privacy first, marketers second. These new rules are coming through legislation, and the gods of the internet. We’ll explore what’s happening in both groups, and what happens next.

Legislation

It all started with GDPR, but now consumer data legislation is popping up around the globe. In the US, the California Consumer Privacy Act just officially passed (and will go into effect in 2020); meanwhile, similar regulations are developing in Brazil and India as well.

What do these laws entail?

GDPR

General Data Protection Regulation (GDPR)-

GDPR is a law passed by the EU in 2016, and began enforcement in 2018. The stated goals of the law are to: harmonize data privacy laws across Europe, protect and empower all EU citizens data privacy, and reshape the way organizations across the region approach data privacy. It does this by levying heavy fines against any business that is found in violation of the regulations. This applies to all companies processing the personal data of data subjects residing in the Union, regardless of the company’s location.

California Consumer Privacy Act (CCPA)-

The CCPA will allow consumers to force companies to tell them what personal information they have collected. It also lets consumers force companies to delete that data or to forbid them from sharing it with third parties. This law aims to target larger businesses, and only applies to businesses that earn more than $25 million in gross revenue, businesses with data on more than 50,000 consumers, or firms that make more than 50% of their revenue selling consumer data (I.E. data brokers).

While this law only applies to customers who live in the state of California, 17 other states are currently exploring similar legislation. It’s likely that most companies will just adopt these practices across the board.

Corporate regulation

Apple

Safari Privacy Update

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

Both Google Analytics and Adobe Analytics use a default 30-day conversion window, allowing you to see the impact of every touch that impacted a conversion in that time frame. Those attribution models on Safari browsers will now only collect data on the last seven days prior to conversion, deleting any data collected before that point.

For remarketing, marketers now only have seven days to programmatically target Safari visitors. After that, their data will be deleted, along with the ability to retarget them.

Other effects from this change include: cross-device visitor tracking becoming unreliable, and a dramatic uptick in unique visitor counts. Visitors who span multiple devices and have a buying journey more than seven days will look like new visitors when they finally return, skewing the data. Additionally, since they now look like new visitors every seven days, new visitor counts will skyrocket.

Firefox Privacy Regulations

Mozilla

Mozilla rolled out similar features to its popular internet browser, Firefox, earlier this year. They recently rolled out an “Enhanced Tracking Protection” feature, which blocks all third-party cookies by default. They also began blocking over 2,500 tracking domains, many of which control multiple cookies, and plan to “update and improve this list over time”.

Chrome Privacy Update

Google

Chrome will add a browser extension that will showcase the names of the AdTech providers on each page and the personalization factors associated with each cookie. They also plan to provide user-level cookie control for third-party cookies.

What can we do?

First party cookies

Moving from third-party tracking cookies to first-party cookies will help protect against these updates and changes.

Most of the changes implemented by the tech companies target third-party cookies, but none of them target first-party cookies yet. This allows you to continue tracking your customer journey without interference.

This change also provides a number of fringe benefits, including: ownership of the data, reduced likelihood of blocking, and better storage and utilization opportunities.

Owning your data insulates you from changes or updates to any future terms and conditions. It also allows you to store the data indefinitely.

In order to implement this, you’ll need to develop the cookies and have a data-warehouse to store the information collected.

It should be noted with this solution that since you own the data, you assume 100% responsibility for it. This includes compliance with the privacy laws previously discussed, as well as the protection of the data.

Pixels

Tracking pixels have managed to avoid much scrutiny yet, and therefore they have escaped the proverbial regulatory hammer so far.

Pixels transmit their data directly to a server, rather than storing data in the browser. This makes the pixel extremely useful, as the user cannot delete the data by clearing their cache.

As regulation ramps up, we predict that most tracking will transition from cookies to pixels, and the data produced by these pixels will move to large data-warehouses for storage. Similar to a first-party cookie, the data gathered from pixels will become the responsibility of the pixel owner.

What comes next?

It is clear that the old way of collecting data is officially dead. Privacy and consumer protections are here to stay.

The solutions that we presented here only serve to fix the issues created by these updates to browsers, they will not help avoid any of the new legal regulations. The internet is entering a new age, and every company will have to grow and adapt to this new ecosystem.

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

How to win in the attribution war

How to win in the attribution war

One plus one equals one and a half?

One of the most frustrating aspects of marketing right now is over-attribution when comparing Facebook reports to Google reports.

This occurs when you log into Facebook and it tells you it earned you $100,000 in a period, then Google says it earned you $100,000 in that same period, but you only received $125,000 worth of orders during that same time period.

This, unfortunately, is the new norm in the attribution war. Both Facebook and Google want your advertising money to go to them, so when it comes to tracking and reporting, there are a few things you have to understand:

  • Even though the two platforms integrate with each other, each is entirely separate. They have different goals, definitions, standards, and abilities for tracking.
  • Each platform only owns their own data. That means, when you go into the reporting aspects of Google Ads or Facebook, you will have mathematically biased information. Each platform only sees one variable (their ads) as an impact on your sales. However, there are always multiple variables involved—multi-channel marketing, public relations, organic posts… even the weather and political climate can impact your sales.

So, when you log in and see varying information, they’re not trying to lie, they’re just presenting their side of the story.

Everyone knows that there are three sides to any story. Each person has their version, and then there’s the truth, which is somewhere in the middle. So, when it comes to Facebook and Google reporting, neither is lying, but also neither is showing you the entire picture because they both are inherently biased. Facebook, for example, counts any conversion that has seen an ad on their platform and then converts as a “view-through” conversion; and Google uses last-click attribution by default in their reporting because that favors them.

Then how do I get data that I can trust?

There are two steps to get accurate reporting on your marketing efforts in your systems.

#1: Tracking

Get as much information as possible. Information is simply multiple points of data brought together to allow you to see patterns and gain answers to questions, like:

  • How much overlap do we have in reporting?
  • Are there clients that have been exposed to multiple marketing efforts?
    • If so, are we tying together their customer journey with accurate tracking efforts?
  • What are all the possible impacts on our sales?
    • How have they impacted sales before?
  • Are there correlations?

How are you going to answer these questions to get the insights you desire? You must have the data in order to be able to analyze the data to get insight.

That means, tracking is the first and primary component of accuracy in your reporting:

Are you tracking your client’s journey?

As we discussed earlier, Google uses last-touch attribution to assign credit to conversions. This slants credit towards Google, as by the end of a customer’s journey they tend to be aware of your brand, and therefore more likely to search for your name and click on a search ad or organic search result.

Google Analytics has many attribution models that you can try out to see which one works best for you. From position based (Which assigns 40% of the conversion value to the first and last touch, and then distributes the remaining 20% across all other touch points) to time decay (which assigns credit based off how close to the conversion date it was), it’s important to make a conscious choice of which attribution model you want to use. Each attribution model has its pro’s and con’s, but by staying aware of how the model affects your reporting, you can reduce bias in your reports.

Are you using pixels?

Tracking pixels have exploded in popularity. Many popular advertising platforms now use tracking pixels in order to track conversions and user interactions with the ads. Pixels provide amazing reporting because you can install them almost anywhere, from emails to landing pages, and, as of now, they can’t be disabled by a browser.

Pixels can help you gain greater understanding over how users interact with your advertisements and your website. Providing granular data about user’s behavior based off the platforms that they visit your site from.

Do you have unique identifiers for your clients that allow you to see their customer journey?

Specifically, you need a way to assign a user-id to your clients so that you can track their behaviors across devices. If you don’t have this set up, then when a user changes devices, you will lose all of the data from their initial visit. This can lead to incomplete customer journey’s and skew your attribution data.

Do you have organized UTMs setup?

The very best solution for the attribution problem is to utilize UTMs in all of your marketing efforts. UTMs allow you to tell Google Analytics exactly how you would like to categorize your traffic. Every external link that directs to your site should have UTM parameters appended to them in order to help assign credit to the proper source.  You can even add in campaign data in order to track which of your campaigns drives the best traffic to your site.

UTMs can be one of the most powerful tools available to marketers, or they can be their downfall. UTMs need to be standardized and utilized consistently, or they will make the data even more convoluted and confusing. You need to implement standardized rules for your UTM usage across the organization in order to make sure that your data remains as accurate and clean as possible.

If you don’t already have these things in place, that is your top priority.

By organizing your tracking efforts, you can start gathering the data you will need in the future. If you need help with your tracking, we have a variety of services that can help you get your tracking in order: https://bit.ly/2NtT9kt

#2: Reporting

Once you have tracking in place, you can typically manually create Excel reports that give you a much more accurate depiction of your marketing efforts (including lift effects and other variables). However, over time, that becomes tedious and time consuming and allows for too much human error.

The next logical step is to automate via ETL (extracting, transforming, and loading the information from these systems into a singular place) and then to visualize the combined, clean data with a dashboard.

This enables you to eliminate wasted time, effort, and give you insights in a quick and digestible manner. This process can be very intense and require the help of a data scientist.

Fortunately, we specialize in exactly this type of process and can help you revolutionize your data reporting. If you’d like to learn more about how we can help you with ETL and visualization, visit us here: https://bit.ly/2VYgKZq

Bonus #3: Democratize your data

This one may seem out of the blue, but it can change the way that your entire organization interacts with data.

Democratizing data means providing access to data to everyone in your company. Not just information that pertains to their specific corner of the business, but the business as a whole. We have clients who have walls of TVs dedicated to displaying their data for the entire company. Everyone from entry-level employees to C-suite officers has access to the same data.

You may be asking yourself, “How on earth would that help my business?” Everyone has different backgrounds and experience, so when one person looks at a metric they will see one thing and come up with an action item based off their experience; but if you bring in another set of eyes, that person may see something totally different and come to a different conclusion. Democratizing data and making it accessible to more people will lead to greater insights and more options for ways to proceed.

Accountants can be creative, and marketing people can help solve operational issues. Democratizing your data can help you gain a myriad of insights and give you an edge over your competition.

You have tons of data; but data alone will not grow your business. It’s the insights from the data that will inform your team on how to grow. Companies that focus on causation will scale. Those that don’t, will fail.

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/

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 here: https://bit.ly/2DpkdKd

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 one of our data experts! https://bit.ly/2Zpwx6o

How to scale in the modern business landscape

How to Scale in the Modern Business Landscape

All that it takes to scale your business is the proper data. In the following video and blog post, we’ll take you through how to take advantage of the information that you already have and use it to scale your business, no matter the industry.

 

Data, Information, Knowledge, Wisdom, and Praxis

Let’s simplify and redefine your views and definition of data. Data is simply the path to information. And information is your road map to knowledge, knowledge guides you to wisdom, which ultimately leads you PRAXIS, which is the ACTION you should take based on the knowledge and wisdom you have.

Data is simply events or outcomes, information is when you understand the relationships between those isolated events, knowledge is understanding the patterns- looking at trends over time and correlations in what is and is not working over time, wisdom is understanding the underlying principles and CAUSES, while PRAXIS is the action you take once you have that wisdom.

Data is an event or outcome without any context or true value by itself. Something like: IT IS RAINING. In and of itself, that would not be a revolutionary.

Information, however, is being able to connected multiple pieces of data together to see correlations and relationships: “the temperature dropped 15° and then it started raining”

Knowledge is then understanding the patterns between the variables: “Knowing that when humidity is high and temperature drops, the atmosphere is often not able to hold the pressure and so it rains”

Then wisdom is where we able to stop looking at the past, and we are now able to extrapolate and forecast what WILL happen rather than what HAS ALREADY happened:  “UNDERSTANDING ALL INTERACTIONS BETWEEN EVAPORATION, TEMPERATURE CHANGES, AIR CURRENTS, AND BEING ABLE TO PREDICT RAIN NEXT WEEK”

Lastly, Praxis is the practical application of all this wisdom in order to get positive results: It’s being able to predict that it will rain on your vacation next week, and that you need to pack boots and an umbrella to prepare for your trip.

The ultimate goal and outcome we are looking for is a result of the actions we take based on the wisdom we extrapolated from the raw data.

So here is a quick side note for you:
“Not taking action from data is like owning a race car and never putting fuel in it”
There is a ton of data available to you, but data itself will not grow your business.
Data itself will not give you the results that you want,
The knowledge you gain from data will help guide you and your team to make the best informed decisions on what actions they should and should not take throughout the day.

So let’s simplify this one last time before moving on to your action steps and road map to scaling.

Data is WHAT HAPPENED in your business, information is understanding the relationship between WHAT happened and WHERE and WHEN it happened, knowledge is understanding the patterns that tell you HOW that happened, wisdom is understanding the principles and mechanics of WHY that happened, which leads you to be able to predict when it might happen again in the future, and at each stage in this journey, Praxis is taking ACTION based on the data, information, knowledge and wisdom you’ve gathered.

Becoming Data Rich

By taking those actions, you are getting NEW valuable data. This is the path that the leaders in your industry are taking, this is what helps them grow and scale, it tells them exactly what is and isn’t working, and how to increase their revenues and profits… this is THE PATH ….. To becoming DATA RICH

Now you understand the road map on how to use data to scale. Up to this point in history, BIG DATA was only accessible to enterprise mega giants because collecting data and hiring data scientists for extracting and analyzing data could cost millions in Technology and Human Resources.

However, nowadays millions of rows of DATA can be found in our cell phones, in the back end of our email systems, and tracking on our websites, so raw data is now accessible to any small business owner.

So the question is, how can you take the raw data that is already available to you and use it gain knowledge and insight to scale your revenues and increase your profits?

That’s what we will be covering in the next part of this blog, what ACTIONS TO TAKE, no matter WHERE YOU ARE on the spectrum, to move to the next stage of data maturity.

Becoming Data Mature

So let’s start at the beginning: your outputs are only as good as your inputs. The foundation for growth is first HAVING data.
When small companies come to us and ask us how to scale, they typically do not have a foundation for success.

Data Foundation Stage

Here are some quick questions to ask yourself to see if your company is in the data foundation stage:

Do you have tracking in place at all stages of your customer’s journey? Including a basic Google Analytics set up?
Are you not using advanced tracking like UTMs, Custom Conversions, event tracking or pixels?

Do you know what KPIs your team should be monitoring?
Do you have standard operating procedures that everyone follows for naming conventions in your systems?

Are you or your team members MANUALLY creating excel or google sheets for your reporting because it’s all stored in a bunch of different technologies and is disparate?
Or are you simply logging into each of your systems to look at the native reports?

If you answered YES to most of these questions, then you are in the FOUNDATION stage.

Data maturity stage one

Your main action step in order to become more mature is to focus on TRACKING and MONITORING.

Remember, your outputs are only as good as your inputs, so we need you to HAVE data first. That’s the foundation for you to be able to scale.
In order to progress, you need to:

  • Implement tracking procedures in GA and UTMs
  • Define what metrics are important for you and your team to know
  • Implement SOPs to make sure the data is clean and consistent

Even if you don’t have the resources right now to do anything with this data, you need to start GATHERING it so that later, when you can afford to look back for patterns and hidden areas of opportunity, you have something to review… you can’t RETROACTIVELY pull data if the data wasn’t being tracked… so PLEASE, make sure you do this now… you will thank yourself later.

Automation Stage

Once that foundation of data collection exists, you can move on to the next phase: Automation

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

Let’s chat about this for a second:

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

It’s exponential leverage to scale
It’s reduction in overhead, it’s focus on what’s important – the ANALYSIS of the information, rather than the collection of data.

Data maturity stage two

To advance higher and to scale, the focus is on integrating your systems together so that they automatically transform the raw data into the insights you need to take action. This allows your team to focus on valuable actions rather than mundane data entry. In technical terms, this is called ETL (automatically extracting, transforming and loading your data into one place).

In addition, setting up this automation lays the foundation for visualized reports or DASHBOARDS. Dashboards allow you to quickly see the highs and lows of your business, and let you quickly see patterns and anomalies of success, as well as those areas of wasted time, money and valuable resources.

Finally, it also allows you to share this information with all the people on your team. You wouldn’t believe the value that democratizing your data can have on your organization… sharing this data allows your team to bring valuable insights to the table and different perspectives that you might not have seen. We call this the LIFT EFFECT.

Optimization Stage

So once you have the foundation of all your data tracking, and after that data has been gathered to one place, and you have automated reporting in dashboards,

THEN you can focus on optimization and analyzing really fun CAUSATIONS between your internal data and EXTERNAL factors…

For those of you who aren’t TOTAL nerds like I am, let’s define this because there is an extremely important principle in statistics that states: CORRELATION does not imply CAUSATION.

As a simple example: Polio rates and Ice Cream sales from 1949. Although they are CORRELATED, that does NOT mean that Ice Cream is the CAUSE of polio. It is very simple to see here, but how many of you make these assumptions in your business when you see trends or relationships like this?

The more data you have, the more accurate picture you can paint among it’s relationships. The more data points you have, the better you can tell which one is most accurate.

You have a ton of INTERNAL data, but there is ALSO a ton of incredible PUBLIC data that you can integrate with in order to gain a more robust understanding of your business, your ideal customers, and their purchasing behaviors.

 

Imagine knowing that when temperatures rise above 75º, your return on ad spend for your Sunscreen company increases by 15%…
or imagine KNOWING that your customers with the highest lifetime values have certain demographics or political affiliations?
Or that you have the best sales when certain economic factors align?

Data maturity stage three

Here at Praxis, we have found:

COMPANIES THAT CAPITALIZE ON CAUSATION
WILL SCALE:

THOSE THAT DON’T
WILL FAIL

Here is a real life example of this in use: Walmart sees a 7x increase in strawberry pop-tart sales when hurricanes are reported off the coast of Florida or Texas. Imagine being a competitive grocery store and not having enough pop-tarts in stock. You would suffer an incredible opportunity cost of potentially millions of dollars.

Can you imagine how many small to mid sized companies are put out of business because they don’t see these patterns? Because they don’t capitalize on these hidden insights that their competitors DO.

What causations are you missing out on in your business?

Mastery Stage

The final stage of data Mastery is for companies that are innovating and modernizing.

At Praxis, we help clients with the most cutting edge resources to help them understand their business better, including natural language processing, machine learning and Artificial Intelligence in order to innovate.

Data maturity stage five

To summarize, here are the recommended steps you can take to advance through each stage on your road to data mastery:

  • Data foundation- Tracking
  • Automation- Integrating
  • Optimization- Analyzing
  • Mastery- Innovating

No matter where your company is currently on this spectrum, these are action steps you should take to move you closer towards information optimization.

That is the definition of PRAXIS – the application of the knowledge you gain from your data.

Taking action from data, is the new competitive advantage. Here is your list of action steps for progressing:

  • Share this with your team
  • Collaborate to see where your business is right now
  • Follow the checklist for how to advance from each stage to the next
  • Assign appropriate team members each action step with a due date
  • Reach out to Praxismetrics.com if you need more information or help.

So, to recap the big rules of scaling:

  • Not taking action from data is like owning a race car and never putting fuel in it.
  • Your outputs are only as good as your inputs.
  • What compound interest is to your money, automation is to your time.
  • Companies that capitalize on causation will scale, those that don’t will fail.
  • Taking action from data, is the new competitive advantage

I’m Meaghan at Praxis Metrics, thank you for investing your time here with me today. Please connect with Praxis on Linkedin and Facebook for more resources to help you scale. We love to help companies like yours grow and achieve their goals faster, so please reach out to me if you have any specific questions about your unique business.

Good luck on your journey, We are looking forward to helping you scale!

Encompass Health Data

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: https://bit.ly/2VYgKZq

Becoming Data-driven

4 vital steps to becoming a data-driven company

Step 1- Remove emotion from the equation.

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

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

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

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

Step 2- Get your tracking in order.

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

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

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

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

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

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

We’ll go through each of these goals individually:

Organized UTM’s:

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

Advanced Pixels:

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

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

Custom Conversions/ Event Tracking:

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

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

Step 3- Automate your reporting

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

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

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

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

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

Step 4- Democratize the data

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

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

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

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

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.

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?