How ecommerce companies can turn data into growth

How ecommerce companies can turn data into growth

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

Data shouldn’t be scary

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

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

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

The roadmap to data mastery

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

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

The data infancy stage

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

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

The data foundation stage

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

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

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

The data optimization stage

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

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

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

The end goal

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

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

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

Metrics Mapping

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

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

Metrics Mapping

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

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

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

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

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

Lead with revenue

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

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

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

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

Praxis Metrics Feasibility Quadrant

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

The big data secret

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

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

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

Every company is a data company

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

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

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

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

You don’t have to reinvent the wheel

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

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

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

How to use data to rapidly grow your ecommerce business

How to use data to rapidly grow your ecommerce business

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

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

Data for entrepreneurs

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

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

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

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

The importance of LTV

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

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

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

Reduce waste to increase results

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

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

Avoid wasting time and effort with a dashboard

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

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

Metrics Mapping

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

Metrics Mapping

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

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

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

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

Focus on the needle-movers

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

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

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

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

Leverage attribution to your advantage

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

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

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

The un-sexy part of data

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

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

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

Choosing a data platform

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

Getting started

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

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

Get creative with your data

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

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

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

Lessons from AJ and Meaghan's entrepreneurial journey

Lessons from AJ and Meaghan’s entrepreneurial journey

In this week’s blog post, we wanted to showcase our appearance on the First $100K podcast with Joseph Warren. In this episode, they cover everything from lessons learned to current fears about business. Make sure to check it out with our insights below:

What do I really want?

Too often in our lives, we get caught up in the flow of things. We allow ourselves to just progress in our lives without taking the time to ask what it is that we’re truly looking for. By becoming intentional and taking the time to ask ourselves what we actually want, we can start being proactive about our decisions rather than just reactive.

AJ and Meaghan realized that the path that they started on no longer suited the lifestyle that they wanted. They ran a successful marketing agency, but they found that the business could not function without them. This made it impossible for them to live the lifestyle that they wanted, and didn’t fit with their long-term vision for the business.

They decided to ask themselves what had brought themselves to this point in their lives, and what things kept them from reaching their goals. In order to run this analysis though, they first had to define what they really wanted. After they defined what they wanted, they reverse engineered that into what they needed to do to achieve success.

What is stopping me from achieving my goals?

Meaghan and AJ found that they wanted time freedom. But when they looked at their situation, they found that their business was blocking them from that. Because the business was built around AJ and his expertise, he needed to be on every call and project. This made it impossible for them to properly scale the business properly, and cost them their time freedom. They started to analyze the business, and quickly realized that they had a problem with hiring. None of their hires could replace AJ, so he was stuck. In order to gain the freedom that they craved, they needed to start hiring smarter.

Creating a multiplier-

At this point, Meaghan and AJ realized that even though they owned their business, they were still stuck trading their time for money. Inevitably, you reach a plateau or a breaking point in that deal. They realized that they needed to break out of that cycle to live the lifestyle that they wanted. The only way to improve that exchange is to find a multiplier.

Multipliers come in a myriad of forms: employees, automation systems, processes, etc. A multiplier includes anything that can increase your output without requiring more input from you.

Tips and strategies for creating your first $100K-

Hire the right people

Getting the right people on your team will drive your first $100K, almost more than anything else. You can do almost anything with the right team around you. You have to remember though, the people who helped you get to $100K may not be the right people to help you get to your next $100K. For AJ and Meaghan, they hired whoever they could until they reached their first $100K. Once they broke through that initial barrier though, they decided that they could afford to select better employees. They went back and started replacing their mediocre team members with better team members, and this helped them rapidly scale the business.

Target your market

The next tip that they would suggest is focusing on the right customers. For Meaghan and AJ, they luckily already had some clients built in to this new business that they launched. They had some marketing clients that needed tracking and analytics services. This allowed them to hit the ground running, and then expand their offerings to suit the needs of their target market.

During this phase of finding their ideal clients, AJ and Meaghan established a mantra: easy and effortless. They wanted to target clients that would be easy to capture, easy to educate, and easy to serve. By following this focus, they quickly expanded their client base, allowing them to scale in other ways, as we previously discussed.

Over-deliver for them

By properly targeting their clients, they knew that Praxis could over-deliver to their clients, and that is their third tip. During the start-up phase, it’s imperative that you create raving fans for your product. In the early days, most of Praxis’ growth came from word of mouth referrals from business owners. Because Praxis delivered such value to their clients, they told everyone that they knew about their amazing work. This over-delivery keept their clients coming back for more work, and the referrals created a steady stream of new business for Praxis.

What was the biggest mistake?

The biggest mistake that Praxis made was also one of the keys to their growth early on. Unfortunately, Praxis just continued the practice for too long. After years of business, Praxis still struggled with scaling. They brought in great top line revenue, but very little of it made it to the bottom line. AJ and Meaghan decided to run a deep-dive on their expenses to figure out where this money went. They discovered that over-delivering to the clients made it impossible for them to scale.

Basically, when they drilled down into the numbers, they discovered that they wrote off tons of hours in order to provide better products for their customers. This meant that the client didn’t pay for those hours worked on their project, but Praxis did. This one thing ate up almost all of the profit from the business, and cost them more than half a million dollars annually.

Meaghan and AJ feared that if they stopped writing off the hours, that their clients would revolt against them and leave. However, they found that no one had a problem paying the extra money, because the finished product was worth it. They got stuck in the mindset of the entrepreneur, and thought that they still needed to prove themselves. But they discovered that they had already passed that phase of the business, and people trusted and valued them enough to pay the true price.

The unfortunate truth-

Too many businesses get trapped in this same mindset. While it is important to over-deliver to the client, you also need to make sure that you charge what you are worth. At the end of the day, you need to make sure that the relationship works for both parties, not just the client. Most of the time, your clients will understand. If you have priced your products properly, you shouldn’t need to discount them in order to maintain the relationship.

Why do so many entrepreneurs struggle to cross $100k?

Over 90% of entrepreneurs struggle to break through the $100K mark. AJ and Meaghan never felt like the business struggled to cross that threshold, but they found it difficult to reach $100K personally. Meaghan specifically wanted to pour all of the money back into the business, as she felt that she could make more by forgoing her pay and instead bringing on a new employee or expanding the business offerings. She learned over time though that if she didn’t take a paycheck herself, then she would hold that against her employees. If they made more than her, then she felt that they needed to work harder than her.

Once she started paying herself though, she discovered that she valued her time more. She no longer took on menial tasks within the business because her time now had a cost attached to it. This caused her to shift focus towards bringing in people that could do those tasks in her place.

At this point, the podcast shifted to a lightning round of questioning, so we included the questions and responses below:

What is the best thing about being an entrepreneur?

AJ-

AJ loves the creative process. He loves the process of coming up with an idea, and then turning it into a plan and executing on it.

Meaghan-

Meaghan loves working from anywhere, and not having a standard dress code for work.

What is the worst thing about being an entrepreneur?

Meaghan-

Meaghan doesn’t like working 18 hour days. Especially when no one appreciates it.

What do AJ and Meaghan fear the most?

AJ-

AJ fears not having Meaghan around.

Meaghan-

Meaghan fears insecurity. This includes emotional and financial insecurity.

What did Meaghan and AJ spend too much time doing in the first year of business?

AJ-

AJ feels like he spent too much time managing expectations, also doing things outside of his wheelhouse.

Meaghan-

Meaghan also felt like they spent too much time outside of their strengths. They spent too much time putting the entire business on their shoulders and not bringing in specialists to help them out.

What secret fear do they have about people?

AJ-

AJ loves people too much to be afraid of them. He loves to figure people out and help them to maximize their potential, so no fears from him.

Meaghan-

Meaghan fears that people will let her down. She has high expectations of everyone, and has had a lot of people let her down.

What do they struggle with personally?

AJ-

AJ is currently struggling with imposter syndrome. As the business grows and scales, he feels less and less involved in the company. This has caused a bit of an identity struggle within him about who he is to the company and where his role is.

Meaghan-

Meaghan is struggling with her outlook. As a natural pessimist, she tends towards the negative very quickly. AJ always sees the potential for good, and she tends towards seeing the potential downside.

What do they wish they had learned sooner in business?

AJ-

Better hiring skills. If they had mastered hiring earlier on, it would have saved them a lot of time and money.

Meaghan-

To piggyback off of AJ’s answer, training as well. Training and coaching employees rather than being a taskmaster.

What 3 words would they choose to describe themselves?

AJ-

Radiant, inspiring, and clear.

Meaghan-

Disciplined, realistic, and prideful.

What 3 words would you use to describe yourself in the first year of business

AJ-

Scattered, frustrated, and hopeful.

Meaghan-

Naive, non-committed, and unfocused.

What is one bad habit that you want to break?

AJ-

Sticking to the morning routine more consistently.

If you could come back to life after death and offer one piece of advice to your family, what would it be?

AJ-

Love more. Every day try to love more.

Meaghan-

Focus on the things that matter.

Praxis Metrics- Improve sales using data

How can I use data to improve my sales?

Do you have more data than you know what to do with?

Most businesses do. In today’s world, everything is tracked, and it produces an overwhelming amount of information. Today, most professionals have a harder time sifting through irrelevant data than they do collecting data.

That’s a problem that we wanted to address in this podcast. We wanted to tackle the question: “Now that I have the data that I want, what do I do with it?”.

It’s not about how much data you have, it’s about asking the right questions and then letting the data tell it’s story.

Time is the most valuable asset that we have, yet we don’t keep very good track of it. Most people go through their days not really thinking about how they spend their time, and not realizing all of the time that they waste in a day. You should spend as much time monitoring your time budget as you do your fiscal budget.

If you want to maximize your effectiveness and happiness, you need to find ways to maximize your time. We all want to increase our productivity and optimize the effectiveness of our time, but eventually we all reach our “optimal level”. At that point, if we want to keep progressing, the only thing left to do is to eliminate waste.

Whether or not we want to admit it to ourselves, wasting time is a huge part of our lives. By decreasing the time that we spend on non-income producing tasks, we can further optimize our time, increasing our time spent on actually valuable tasks. By refusing to track your time as carefully as you track your money, you often lie to yourself. You convince yourself that you spent your time wisely, when in reality, you could have done so much more.

Track your time for 24 hours a day across 2 weeks, and see the story it tells.

Break down your day into 15 minute increments and see exactly how you spent your time across those 2 weeks. Often times it paints a picture that you don’t want to see; but that’s the picture you need to see. By seeing exactly how much time you spend doing things that aren’t worth it, you can see how much more you are capable of.

One client found that they spent only 2.5 hours per day producing actual income for themselves. They spent the rest of the day doing tasks that they considered productive, but on further examination, they found that they had much more pressing things to deal with.

We can automate, delegate, or eliminate so many of the tasks that fill our days; making us more productive, or allowing us the freedom to follow a new passion.

We have data in our CRM’s, data coming from social media, data from our website; how do we sift through it and find the things that actually make a difference?

We found that most small to medium businesses have 15-18 different sources of data. We also found that those sources of data rarely talk to one another. This turns into a huge drain on your effectiveness and time, having to go between all the sources of data to find the information that you need.

The first thing that you need to do in order to get out of the rut of going through all of those disparate pieces of data is a process called metrics mapping. Metrics mapping requires you to start with a high level view of your business and ask the questions that you want answers to. Most people want to know things like, “How much money am I making?” “Which products are driving the most revenue?” “Where am I losing money?”. After asking the questions, it’s time to figure out what metrics, or KPI’s (Key Performance Indicators) answer that question.

After you know what metrics you want to measure, it’s time to find what system tracks that data, and which one you trust the most. If you want to know how much money your business has, your Paypal, Stripe, or bank account is probably a good place to use as where you pull that metric from. If you want to know how many visitors came to your site yesterday, you would probably turn to Google Analytics. Once you have picked out that “source of truth” for each metric, you can begin to track that information and start answering your business questions.

Almost every company has holes in their data, generally because people don’t recognize the value of that data.

Many organizations have problems with incomplete or inaccurate data. There are several potential solutions to this, but the best ones generally are to either automate out the data collection or to train everyone in the organization in the value of the data. Automation represents a long-term and scalable solution to the problem, but it also generally requires a large up-front investment in the technology. For that reason, many businesses would rather just train everyone in their organization on the importance of the data, and how it can actually make a difference for both the individual and the organization over time.

The sales team is the most important team to communicate this to. As one of the first groups that has contact with the clients, they have access to massive amounts of data that often falls by the wayside because they don’t view it as important. Allowing them access to the data and the insights that come from that data is one of the easiest ways to show them the true value of the data that is being collected. If they can see the direct correlation between their data collection efforts and the insights that allow them to make more money, they will never again willingly let data slip through the cracks.

Reward the habits and not the results.

In sales we have lead indicators and lag indicators. The lead indicators are the things that you have complete control over, i.e. contacting x number of leads per day, making x number of cold calls, making at least x number of sales pitches. Lag indicators are the results that follow the lead indicators, i.e. number of sales, amount of revenue, etc. What’s truly powerful about harnessing the power of data is that once you know your lead indicators well enough, you can shift the focus from rewarding lag indicators to rewarding the lead indicators. A system like this allows you to reward the behaviors that drive results, rather than just the results themselves.