A.C.I.D. (Atomicity, Consistency, Isolation, Durability) is a set of properties of database transactions intended to guarantee validity even in the event of programming errors or power failures. A.C.I.D. allows users to solely focus on their programming logic, without having to worry about additional failures a system might encounter. This database property ensures that the user does not have to write additional code to correctly implement detection and resolution of failures.
- Advocacy Marketing
Advocacy Marketing is a form of marketing that emphasizes getting existing customers to talk about the company and its products.
- Amazon Athena
Amazon Athena is an interactive query service that allows you to conveniently analyze data stored in Amazon Simple Storage Service (S3) by using basic SQL.
- Amazon Redshift
Amazon Redshift is a fully managed data warehouse that exists in the cloud and is designed to deliver fast query and I/O performance for any size dataset.
- Annual Contract Value
Annual Contract Value (ACV) is the average annualized value per customer contract. If the subscription includes one time fees, the first year ACV may be higher.
- Annual Recurring Revenue
Annual Recurring Revenue (ARR) is the value of recurring revenue of a business’s term subscriptions normalized to a single calendar year.
Attribution is a means of assigning credit from a sale to the touchpoints that a customer was exposed to prior to their purchase.
- Bar Line Chart
A bar line chart is a visualization that combines the features of the bar chart and the line chart by displaying data using a number of bars and/or lines, each of which represent a particular category.
- Bubble Map Chart
A bubble map chart is a visualization tool that combines bubbles and a map chart. It displays the bubbles on a geographical map to represent the geographical data.
- Business To Business
Business To Business refers to a situation where one business makes a commercial transaction with another. This typically occurs when a business is sourcing materials for their production process.
- Customer Acquisition Cost
Customer Acquisition Cost (CAC) is the total cost needed to acquire a new customer for a product or service. It is a process of gaining new customers for your business. The goal is to convert the initial brand awareness campaigns into new customers. Along this journey, you need to help the potential customers identify what’s successful for them, solve their problems, and build trust with them.
How to Calculate Customer Acquisition Cost
For more information on how to track customer acquisition, take a look here.
- Customer Churn Rate
Customer Churn Rate (CCR) is the percentage of subscribers to a service who discontinue their subscription within a certain time period. In order for a company to expand its client base, the customer churn rate must be lower than its growth rate. Therefore, it is important to know what the CCR is as well as how to minimize it.
How To Measure Customer Churn Rate
Customer churn calculation is pretty straightforward. You have to take the number of customers you have lost during a specific time period and divide it by the number of customers you had in the beginning of the same time period.
For example, say you have 1000 customers at the beginning of the month, and 950 at the end of the month. This means that 50 customers were lost during that month. That means the CCR is 50 / 1000, or 0.05. That means that the customer churn rate is 5%. A good annual customer churn rate should stay between 5-7%. Anything higher may potentially be harmful for the company and should be worked at to be reduced.
For a more in depth explanation about how to measure CCR, take a look at this tutorial.
Why Measuring CCR is Important
It is important to keep a low CCR. If the churn rate is higher than the growth rate, that means the company is losing customers. When this happens, it is helpful to find out which customers are a churn risk. Knowing this allows actions to be taken that can minimize that risk. Measuring the churn rate of a company can help catch higher rates before they get too bad. For more information on identifying who is a churn risk, check out this tutorial here.
Customer churn rate is not to be confused with revenue churn rate. Revenue churn rate has to do with how much profit a company has lost during a given time rather than the number of customers. This is a better indicator to the health of the organization. While they are related, different insights can be drawn from both, meaning both should be tracked.
- Customer Lifetime Value
Customer Lifetime Value (CLV or CLTV) is the predicted revenue a customer will bring in over their contract lifetime. Also known as Lifetime Customer Value (LCV) or simply Lifetime Value (LTV). The prediction model can be anywhere on a range of accuracy.
The Purpose of Customer Lifetime Value
The main purpose of the CLV is to assess the financial value of each customer. Each customer is unique and will therefore give a different lifetime value. This means that the predicted CLV is important in the decision making of whether or not to spend the money to acquire the customer.
While the actual predicted CLV can be complicated to calculate, below is a depiction of a simplified version. It is the combination of the average transaction cost the customer has, how frequently they purchase from the company, and the expected length of the relationship. While this may be oversimplified, the concept is the same when trying to predict CLV. In it's simplest form, it is how much revenue that customer will bring in.
CLV as it Relates to Acquisition
Customer Lifetime Value is directly related to customer acquisition cost. This is because you want the maximum payback from the customers you are acquiring. If the predicted CLV is less than the acquisition cost, it is not smart to spend the money on acquiring that customer. The CLV for a customer is the upper limit of what the company should be willing to pay to acquire that said customer.
More About CLV
CLV is an important part of customer acquisition. To learn more about this process, this tutorial about tracking acquisition can be useful. CLV is also useful when measuring customer engagement levels, which is discussed more here. Knowing how much money a customer can bring in is a good indicator of how engaged they will be in the company.
- Customer Satisfaction Score
Customer Satisfaction Score (CSAT) is a widely used method to measure a customer’s satisfaction level with a business's service. It is the most straightforward of the customer satisfaction metrics. It is a rating on a scale that answers the question "How satisfied are you with your experience?".
Customer Satisfaction Score is Simple
The simplicity of the CSAT is part of the reason that it can be so useful. It can be looped into the product quite easily. This allows you to easily pinpoint the reasons behind a good or bad experience. The customer is providing constant feedback so it becomes easy to track where the score increases or decreases at a higher rate. Finding out which parts of the product are causing this jump or dive in customer satisfaction is an easy way to find issues and fix them or find good parts of the product and expand them. Either way, improving overall customer satisfaction.
How CSAT is Useful
Since it is so simple, the question can be asked over multiple experiences that the customers have and a big picture view can be gotten of the whole process. While The customer satisfaction score is very similar to the NPS, they both answer different questions. This means they tell your company different things about the customers, if ever so slightly.
Customer Satisfaction Score helps to tie key moments in a customer experience. This way you are able to tie the customer insights with business questions and measure the effectiveness of those key moments.
How to Track CSAT
Due to the simplicity, CSAT is fairly easy to track. It is an important part of many dashboards though. To look into why the customer satisfaction score is useful for a CMO dashboard as well as many other metrics that are important to track, take a look at this tutorial.
- Data Warehouse
A data warehouse is a large store of data that is collected from multiple different sources so that it can be compared and analyzed for greater business intelligence.
- Database Record
A database record is a group of fields in a table that form a single implicitly structured entry; also known as a row or a tuple.
Here is a tutorial on how to select records using PostgreSQL.
- Funnel Chart
A funnel chart is a visualization chart that represents data in multiple stages that is progressively reducing. It is often used to show the stages of the sales process. Starting at the top, a funnel starts at 100% of some form of data. As you track down the chart, the funnel chart narrows to lower percentages. Each step should lower in percentage by a certain rate that can give information about the efficiency (or lack thereof) of a certain transition between steps.
Purpose of a Funnel Chart
Generally, a funnel chart is used to depict a process. This process ideally starts at 100% and ends at a lower percentage. As the chart shrinks going down the funnel, certain realizations can be made. One of which is finding where the most noticeable decrease happens, or the fall out. Then it is easy to identify the bottlenecks of a process. Funnel charts are extremely useful to figure out the efficiency of certain steps in a given process.
Examples of Funnels
Funnel charts can be useful for a wide variety of data, but is most often used to depict the efficiency of processes. As seen in the first chart, the funnel narrows very quickly, showing a process where data is getting narrowed quickly. The amount that makes it to the end is quite small compared to the start, but you can see that from the first step to the second step is where most of the data is lost.
In this example, the funnel is more efficient. The two parts of the funnel that have the highest rates are Leads to MQLs and MQLs to SQLs. This means that on these two transitions in the funnel is when most of the leads are lost, speaking to the efficiency of those steps. This leads to wins funnel is one of the most common uses of the funnel chart. It is referred to as the marketing funnel, or sales funnel.
How to Make a Funnel Chart
As they can be used in many ways, there are also many different ways to create a funnel chart, one of which is with Chartio. A tutorial on how to do this can be found here. There is also a great tutorial for how to create specifically a marketing funnel chart.
- Google BigQuery
Google BigQuery is a serverless data warehouse that supports super-fast SQL queries using the processing power of Google's infrastructure.
To see how it compares to Amazon Athena, check out this comparison article.
- Line Chart
A line chart is represented by a series of data point connected by a line on an x,y plane. They are most often utilized to show data over time. In this case it can also be called a run chart. The series of data points in line charts can be referred to as markers. These markers are connected by straight line segments.
Purpose of a Line Chart
The main purpose of the line chart is to show how a variable reacts (y-axis) to another ordered variable (x-axis). Since the x-axis is often over time, it will usually be separated by some time interval.
Finding out how a variable is changing over time can be helpful for many different reasons. For example, the line chart depicted below is showing a change of revenue over time. Knowing that the revenue is increasing over time, it is then possible to make other line charts over time to see which variables are most likely to be causing the increase in revenue.
Another piece of information that can be gleaned is that from April to March, revenue decreases. Again, after looking into what happened over that span of time (possibly using other line charts) it is conceivable to find out the reason that revenue dropped over that month. Once knowing why, adjustments can be made to make sure that revenue increase can be as efficient as possible.
How to Make A Line Chart
While the most common purpose of line charts is to show how data is changing over time, they can be used in many other ways as well. As they can be used in many ways, there are also many different ways to create a line chart, one of which is through Chartio. There is a tutorial on how to do this here.
- Marketing Qualified Leads
Marketing Qualified Leads (MQLs) are leads that are more likely to become a customer compared to other leads based on lead intelligence and lead behavior. To be a MQL, the visitor has to have demonstrated some form of interest in the website. Whether this is through filling out a form, placing an item in their cart, signing up for a newsletter, downloading content, signing up for a trial, or a number of other actions, in order to show that their interest is legitimate. A marketing qualified lead should not be confused with a Sales Qualified Lead (SQL), which is a later step in the marketing funnel. A marketing qualified lead is simply more likely to be a customer than other leads.
Not all visitors to a website are actually leads. While most leads can be an MQL, it is the marketing team's job to only pass on the most viable leads to the sales team. This is the role of the MQL; to make the sales teams job more efficient by narrowing down the number of leads they must vet. It’s important to look at the lead to MQL conversion rate to check on effectiveness of your marketing efforts. The better that the marketing qualified leads at the top are, the more efficient the funnel will be. This will ensure the sales team is delivered high-quality leads. Then they can improve their productivity, while Sales and Marketing remain aligned in their goals.
Marketing Qualified Leads as Metrics
Sales qualified leads are also an important metric to be tracked by CMO's. They show leads can be followed up on efficiently by the marketing team. While there are many possible ways to track this metric, Chartio is one such way. For more information about this and how to track MQLs, take a look at this tutorial.
- Massively Parallel Processing
Massively Parallel Processing (MPP) is the coordinated processing of a program by multiple processors that work on different parts of the program, with each processor using its own operating system and memory.
- Net Promoter Score
Net Promoter Score (NPS) is a way to measure how likely a customer is to recommend your service to someone else, and can be used to gauge customer loyalty. While the scale can take many forms, a common one is a score from 0 to 10.
The scale answers a key question: “How likely would you be to recommend the product/service/brand to a friend or colleague?” The answer that customers give puts then them in one of three categories.
Net Promoter Score Groups
The respondents are divided into 3 different groups:
Promoters (score 9-10): most likely to recommend you. Loyal enthusiasts who will keep buying your product or service.
Passives (score 7-8): satisfied customers, but not enthusiastic buyers. These customers are vulnerable to competitive offerings.
Detractors (score 0-6): unhappy customers who can easily damage your brand by bad recommendations.
Calculating Net Promotor Score is straight-forward once respondents are grouped. As seen in the graphic above, it is the percentage of detractors subtracted from the percentage of promoters (passives are not taken into account).
% Promoters - % Detractors = NPS
The Net Promoter Score represents the customer satisfaction and company growth in a straightforward way. It allows you to benchmark your companies performance and to improve your customers’ overall satisfaction. Being able to visualize the score is important so that it is possible to see when and why it is increasing or decreasing. An increasing NPS shows that customers’ experience is improving while a decrease shows the opposite. There are many tools that can be used to visualize the data, one of which is Chartio which can help you to monitor the development of your customers satisfaction.
For more information on how to track and monitor your Net Promoter Score, take a look at this tutorial.
There are many reasons why it is important to keep track of Net Promoter Score. One of which is for Business to Business transactions. Since the score is a part of the Advocacy of a company, it can be important for other companies to know before doing business. This is because NPS is a useful proxy for customer satisfaction and retention.
Here is a more in depth explanation of important NPS and other important Business to Business metrics.
- Objectives and Key Results
Objectives and Key Results (OKRs) are a performance management framework that brings company core values and objectives together. OKRs can be tracked on company, team, and individual level.
What are Objectives?
The goal of an OKR is to connect goals and objectives in a measurable way. This is to ensure that all members of a company are working towards that company's goals in a unified direction. OKRs help teams spend less time being distracted by trivial tasks, and more time achieving team and company goals successfully. It is easier to achieve the objectives through measurable and specific factors when they are broken down into OKRs.
Every company, team, and even individual has different objectives, so it it important to set OKRs at every level. Every company is also unique so finding the right objectives that are best for your company or team can be hard. To find out some of the best ways to find the right ones, take a look at this tutorial.
What are Key Results?
The Key Results (KRs) are the measurements that help you know you’re on track. You can help find them easier by asking your team “How will we know we’re getting there?”. KRs have to make the objective clearly achievable. They are quantifiable and lead to the objective grading.
Any metric defined in KRs should follow the S.M.A.R.T model – Specific, Measurable, Attainable, Relevant and Time-bound. KRs are most likely very different from team to team within a company and for each functional position.
It is important to track the OKRs once they are set. Knowing how much progress is happening and where more focus should be put into is always helpful. One easy and visually appealing way to keep track of your company's OKRs is with Chartio. There is a great tutorial on how to make an OKR dashboard with Chartio.
When tracking, it is important to think about what information should be communicated as well as how to visualize it. Everyone's OKRs are different so the visualization will depend on what information is being displayed. It can also depend on why it is being displayed and who it is being shown to.
An example of a simple Annual Contract Revenue OKR is shown below.
A query is a request from a database to extract information in a readable format. While usually in the form of a SQL statement, it can be graphical.
- Sales Conversion Rate
Sales conversion rate (SCR) is the rate of conversion from leads into new customers. Tracking conversion rates is an important part of finding out how the sales funnel is performing.
Leads and Conversions
A lead is any person or business that is possibly interested in buying your product. Some leads are better than others though. This is why the sales funnel is so important; so that conversions can be more efficient. To learn more about different forms of leads and the funnel that they create, you can read about Marketing Qualified Leads and Sales Qualified Leads.
Conversions can be defined in many different ways: a purchase, download, video watch, sign up, or a plethora of other goals. The type of conversion being used is unique based on company needs and goals. The most common conversion is the number of sales, which is the conversion type used in calculating the sales conversion rate.
How to Calculate Sales Conversion Rate
Calculating this form of conversion rate is quite simple. First and foremost, you need a way to track the number of lead and total sales. Once this information is obtained, it becomes as simple as plugging into the following formula:
Conversion Rate = (Total Number of Sales / Number of Leads) * 100
For example, say there are 1,000 unique visitors on a site in a given week. If in the same week you know that 30 sales took place, you can easily calculate the SCR. The 1,000 visitors is the number of leads in this instance and the 30 sales is the number of conversions. Plugging this information in the formula then, we get: (30/1000) * 100 = 3%.
Knowing conversion rate is important in a lot of cases. It is important to try and optimize your conversion rate in order to make the most of leads. Sales conversion rates can frequently be found on OKRs as it it is an important metric to track and always improve upon.
- Sales Qualified Leads
Sales qualified leads (SQLs - not to be confused with SQL, a database programming language) are leads that has been qualified by the sales team and are directed towards the logistics of making a purchase. The lead has displayed some form of intent to buy the product and have also met the requirements of being a right fit. A sales qualified lead should not be confused with a Marketing Qualified Lead (MQL), which is an earlier step in the marketing funnel. A sales qualified lead must be properly vetted first.
SQL is the step right before a lead becomes a customer in the Marketing and Sales funnel. It is an important part of the lead lifecycle as it helps narrow down realistic customers even further. This funneling is depicted below. Once a lead has passed the requirements, they can be followed up on to close the deal. For more information on marketing funnel and how it works, check this out.
Sales and Marketing teams generally will set up the requirements of a sales qualified lead. In order to save the sales team time, the requirements can be set up as scores so that leads can be ranked. While all companies have different requirements for what qualifies a sales qualified lead, there are general characteristics that are desirable.
For instance, repeat visitors and visitors who download forms are deemed better candidates for SQLs than other visitors. Demographics of the company that is the potential lead can also be important. This can include company size, budget of the company, timeframe, and need.
Sales Qualified Leads as a Metric
Sales qualified leads are also an important metric to be tracked by CMO's. They show leads can be followed up on efficiently by the sales team. For more information about this, take a look at this tutorial.
- Scatter Plots
Scatter plots are a useful data visualization that is useful to compare two different quantitative variables. Scatter plots are basic depictions of data, but also convey a great amount of information. These plots also have a number of extensions that produce even further analysis of your data.
A scatter plot is depicted on a cartesian plane. One variable has values which lie on the x-axis, and the other on the y-axis. In some cases, variables on the x-axis are referred to as explanatory variables, and variables on the y-axis as response variables. Here is an example of a scatter plot chart.
Scatter Plot Uses
Scatter Plot Charts compare two quantitative variables. When using a scatter plot we want to see how two variables relate. Known as correlation, variables can have high, low, or no correlation. For example, flower petal length and petal width have high correlation. The longer a flower petal is, the wider it will be in general.
Another thing that scatter plots are able to show you is clumping or groupings. Again looking at the example, you can see that the different colors are more clumped together. Gleaning information from this, we can tell that, in general, the Iris-setosa is the smallest species followed by the Iris-versicolor and then the largest being the Iris-virginica. Within each of these species, longer petal length still correlates to larger petal width as well.
You can use scatter plots in many different ways, but can be quite useful when attempting to gain information about how two quantitative variables relate to each other. Finding a correlation between them is always useful, as is finding groupings.
Resources on How to Make Scatter Plots
As they can be used in many ways, there are also many different ways to create a scatter plot, one of which is through Chartio. There is a tutorial on how to do this here.
- Symmetric Multiprocessing
Symmetric Multiprocessing (SMP) is the coordinated processing of a program by multiple processors that work on different parts of the program, where two or more identical processors are connected to a single, shared main memory.