Meaghan and AJ were invited to speak with Alex Brown, founder of Ecommerce Rockstars. They cover everything from data foundations to predictive analytics, so don’t miss out! Check out the full interview and our insights below:
Data shouldn’t be scary
When businesses think about data, most of them think of massive data warehouses with AI and machine learning algorithms. While that may be something to strive for, that’s not data. Data is simply information. Every business has information; now more than ever.
Praxis wants to help businesses find ways to leverage the data that they already have to make better decisions. We always say that we’re in the waste business. We help eliminate wasted time, effort, and money.
The goal of any data project should be to answer your business questions. We want to help businesses answer the questions that will help them scale. Whether your ecommerce business is just getting started, or if you’ve been in business for a few years; this can help you figure out what next steps to take and how to grow your company.
The roadmap to data mastery
While the end goal may be to run massive data projects and collect granular data on every customer’s spending habits; we need to start at the beginning. The more information you have, the better decisions you can make; that means that the less data you have, the worse decisions you make.
That’s why Praxis built out the data maturity spectrum, to help businesses figure out where they stand, and then what to do next.
The data infancy stage
Most companies start in data infancy. They don’t have time or means to dedicate to data and analytics projects; so they put it off. We characterize this stage with a general “spray and pray” type of attitude. Businesses in this stage generally are just throwing ideas at the wall in order to see what sticks.
As they start to see what sticks, and what works and doesn’t work; they begin to lay the foundation for their data strategy. This moves them into the data foundation stage.
The data foundation stage
As businesses start to gather reports and notice patterns, they start to grow their data maturity. In the foundation phase, businesses start to track the cause and effects of their actions. Generally this involves manual reporting, pulling data from disparate sources into spreadsheets, and using complicated pivot tables to analyze the data.
We call this stage “spreadsheet hell”. Businesses in this stage generally have some automations when it comes to their reporting; but they often rely heavily on human input and data aggregation.
The data foundation stage is generally the phase in which businesses start to see explosive growth. Because they track what works and doesn’t work, they’re able to start replicating efforts and successes. In order to continue growing at the same rate, they’ll need to move up the scale of data maturity to the data optimization stage.
The data optimization stage
In the data optimization stage, businesses focus on automation. During this stage, businesses move away from manual reporting and begin to create automatic ETL processes. ETL stands for Extract, Transform, and Load. The idea behind this process is to extract the data from the different “sources of truth”. The source of truth is the place where the most accurate data on whatever you want to measure lives. For example, in the case of financial data, the source of truth would be your payment processor or bank account. For Source/Medium data, the best place to get that data would be Google Analytics.
Next, we need to transform the data as needed. Transformation of the data entails taking all of the data from your disparate sources, joining it and then cleaning it to make sure that it’s all tracking uniformly and the data is formatted properly.
From there, we load the data into a data visualization tool so that you can easily analyze and leverage your data into growth.
The end goal
The end goal of this entire process is getting you data that you can take action on. Data for the sake of data won’t do anything for your business; you need to take action from it. Having data and not taking action from it is like having an expensive race car and then never putting gas in it.
Going with the race car analogy, if you want the car to perform optimally, you need to put only the highest quality gasoline in the car. Your output is only as good as your inputs. The same is true with data; in order to get amazing insights from your data, you need to have clean data coming into your systems.
If you don’t know how to make sure that everything tracks properly, we recommend using a process called “Metrics Mapping”.
The process of metrics mapping is actually pretty simple, and helps you gain clarity in what you need to track and how to use the data once you have it.
You start metrics mapping by defining your goals. As you can see in the example below, this company wanted to double their revenue year over year.
From there, you need to figure out what questions you need answered in order to attain that goal. In this case, they need to know how to increase the conversions on their website.
Once you know the questions that you need to answer, it’s time to figure out what metrics can help you answer those questions. In this case, they decided that the metrics that would help them the most would be the conversion rates for each of their funnel stages, customer LTV, allowable CPAs, and channel profitability.
From there, you need to decide on a source of truth for each of those metrics. You can find funnel stage conversion rates through Google Analytics goals, enhanced ecommerce tracking, or event tracking. Lifetime values would be through your ecommerce platform. You would need to calculate allowable CPAs for your business based off your margins, COGS, and LTV. And finally, you can find channel profitability by tracking your CPAs, LTV, and COGS.
From there, you want to validate the data across as many sources as possible and make sure that your sources of truth align. Then you can begin the process of applying your calculations and loading it into a data visualization tool.
If you’re not able to track any of these metrics, then you can know exactly where you need to focus your tracking and figure out a platform that will help you track those metrics.
Lead with revenue
Every data project should help you make more money. If you’re running a data project to get a metric that is “nice to have” or “nice to know” then you’re likely wasting your time, energy, and money.
As we talked about before, you need an action tied to your data. If something changes, you need to know what you’ll do, and who will do it. Once you have action tied to metrics, it becomes much easier to determine the value of that metric. For example, if you can get a 10% increase in the lifetime value of your customers, you can easily calculate out the value of that kind of change for your business.
The key when determining KPIs is figuring out which ones are the most feasible and deliver the maximum impact. As shown in the chart below, we want to focus on the things that drive the highest business value and are the easiest things to implement for your business.
The key is to make sure that you don’t work on data projects just because you can. Those belong in the bottom right quadrant and should be treated as the second to lowest priority for the organization.
The beauty of this chart and this process is that as you implement your data projects and improve your data processes, you can increase the feasibility of future projects.
The big data secret
The biggest secret when it comes to data projects is that no matter the size of the company, everyone wants the same information. They want to know how to decrease their waste and increase their bottom line. The easiest way to do that is to ask the right questions, you can just run down the rest of the metrics mapping process.
Too many SMBs think that they don’t have enough data to compete at scale with large companies, but today everyone’s cell phones have big data. We had a client that had 4 million rows of data stored in the back end of his payment processor; and that was just a couple months worth of data.
Almost every tool the businesses use store data, and every data point can help deliver valuable insights. We have found that most small businesses have a treasure trove of data available to them, but they don’t realize it.
Every company is a data company
If you’re not looking at your data and finding ways to better optimize your company, your competitors likely are. We have seen massive giants fall by the wayside because they failed to take appropriate action off their data.
The time to start taking action off your data is now. At very least, start setting up your tracking, or aggregating data. Even if you’re not ready to use it yet, you’ll be grateful to have it when you are ready to tackle big data projects.
Another great place to get started is with your North Star Metrics. These are metrics that all other metrics rely on. For Airbnb, their North Star metric is nights booked on the site. The more nights they have booked, the better their overall business does. For Facebook, they look at active daily users; this allows them to keep their finger on the pulse of usage of the site and retention over time.
You may not have time to run down and figure out all of the KPIs that impact your business; but you can figure out the one. Take the time to figure out your North Star Metric, and start tracking that. You can start to map out the trends, look for causation, figure out what drives it up and down. This is an easy way to get started with a data project, and helps establish value for future data projects.
You don’t have to reinvent the wheel
Dashboards and data visualization tools have been a hot topic as of late. Lots of businesses jump in to the world of data visualization and end up getting an expensive platform that ends up just displaying data that was readily available on other platforms, or they get a powerful business intelligence tools that they can’t fully utilize.
Praxis helps businesses incubate their dashboards under our umbrella. We offer several pre-built dashboards that can answer some of the most important business questions. Once you have gleaned value from those dashboards, we want to help you graduate into custom dashboards that answer questions specific to your business.