Praxis Metrics- Leveraging data to optimize ad spend

Leveraging data to optimize ad spend

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

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

Enjoy the episode and our insights below.

The struggle today-

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

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

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

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

The opportunity today-

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

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

How you can capitalize on this opportunity-

Ask the right questions-

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

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

Praxis Metrics- Metrics Mapping

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

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

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

Get granular with it-

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

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

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

What metrics should every business look at?

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

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

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

What is the biggest problem businesses have with reporting?

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

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

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

How do we combat this issue?

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

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

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

Your output is only as good as your inputs-

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

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

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

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

The “source of truth”-

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

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

Where to begin?

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

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

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

Leverage your uniqueness into growth-

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

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

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

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

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

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

When should people seek help with their data?

As soon as it gets annoying or frustrating.

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

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

What should businesses have in place before consulting with Praxis?

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

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

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

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

Praxis Metrics- How to create a data-driven culture

How to build a data-driven culture in your company

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

What is selective data culture?

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

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

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

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

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

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

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

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

Employee engagement

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

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

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

Better ideas

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

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

Consistent value

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

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

Financial

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

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

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

How to start democratizing data

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

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

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

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

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

Praxis Metrics- Data Predictions

Predicting data trends (2018-2020)

For this blog post, we wanted to revisit a guest episode that we did with the Vision Tech Team. This episode was filmed at the end of 2018, and focused on the changes that we saw in the data landscape in 2018, as well as predictions for 2019.

We found this episode particularly relevant given the changes in the data landscape that we detailed in last week’s post (which you can find here).

Enjoy this short podcast episode, and our insights below.

Insights from 2018:

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

Predictions for 2019:

  1. Increased competition for data.
    1. As more companies realize the value of data, more and more companies will start competing for it.
    2. As data becomes more ubiquitous, companies will get better and better at targeting and marketing. This will drive inefficient organizations into the ground, leaving only the best to survive.
  2. Data overload to the max.
    1. As more data becomes available, businesses will need to start deciding what metrics actually matter to them.
    2. Most businesses will need to hone in on the handful of metrics that actually drive results (80/20).
      1. Those that capitalize on this principle will thrive in 2019
  3. Increased transparency and accountability.
    1. As more companies move towards data democratization, we will see a shift towards increased accountability across organizations. This will create cultures that thrive on extreme accountability.
    2. Since everyone has access to the data, it will become much more difficult for low performers to hide behind the work of others.

Looking back on 2018, things seem so much simpler. They only worried about compliance with GDPR. In 2019, we have a host of regulations on the horizon to worry about, decreased access to data and information, and platforms throttling data.

Looking forward to 2020, we’re likely to see an acceleration of the changes from 2019. We expect more data regulations to come into effect, and as a result of this, we expect a decrease in marketing efficiency.

One of the things that every business should start doing is gathering data into a data warehouse. This protects you from the whims of the larger platforms, and gives you complete ownership over your data. By gathering your knowledge and wisdom into your own database, you insulate yourself from the storm that is brewing on the horizon.

Praxis specializes in data, so we can help you take ownership over your data, create back-ups, and help you understand your data better than ever before. You can learn more about our products and offerings here. If you have immediate questions, you can contact a data expert directly here.

Praxis Metrics- Major data privacy changes- What you need to know

Major data privacy changes- What you need to know

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

What is happening?

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

Legislation

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

What do these laws entail?

Praxis Metrics- GDPR

General Data Protection Regulation (GDPR)-

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

California Consumer Privacy Act (CCPA)-

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

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

Corporate regulation

Apple

Praxis Metrics- Safari Privacy Update

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

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

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

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

Praxis Metrics- Firefox Privacy Regulations

Mozilla

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

Praxis Metrics- Chrome Privacy Update

Google

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

What can we do?

First party cookies

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

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

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

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

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

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

Pixels

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

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

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

What comes next?

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

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

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

Praxis Metrics- How to win in the attribution war

How to win in the attribution war

One plus one equals one and a half?

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

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

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

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

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

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

Then how do I get data that I can trust?

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

#1: Tracking

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

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

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

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

Are you tracking your client’s journey?

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

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

Are you using pixels?

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

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

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

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

Do you have organized UTMs setup?

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

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

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

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

#2: Reporting

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

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

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

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

Bonus #3: Democratize your data

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

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

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

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

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

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

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

Why does everyone seem to be pushing dashboards right now?

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

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

What is the biggest mistake that people make with dashboards?

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

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

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

What is your plan?

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

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

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

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

LTV-

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

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

ROAS/ROI-

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

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

Month over month/ year over year revenues-

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

How can we better track and prevent customer churn?

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

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

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

How can I be more effective?

Collaboration-

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

Tracking-

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

Automation-

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

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

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

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

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

Praxis Metrics- 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

Praxis Metrics- 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.

Praxis Metrics- Data maturity scale 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.

Praxis Metrics- Data maturity scale 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?

Praxis Metrics- Data maturity scale 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.

Praxis Metrics- Data maturity scale stage four

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!

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: https://bit.ly/2VYgKZq

Praxis Metrics- Becoming Data-driven

4 vital steps to becoming a data-driven company

Step 1- Remove emotion from the equation.

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

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

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

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

Step 2- Get your tracking in order.

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

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

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

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

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

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

We’ll go through each of these goals individually:

Organized UTM’s:

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

Advanced Pixels:

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

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

Custom Conversions/ Event Tracking:

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

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

Step 3- Automate your reporting

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

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

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

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

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

Step 4- Democratize the data

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

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

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

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