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4 Types of Data Analytics to Improve Your Business (With Examples)
The 4 Types of Data Analytics:
* Business Intelligence Reporting (B.I) – The most common type of analytics, also known as data mining, and it is really all about understanding your environment. A few examples are: “I blasted this e-mail and this campaign is going well.” “I have a very small bounce rate, or delivery rate, open rate, click-through rate, conversion rate.” These metrics are normally displayed on dashboards not to dis-similar from your car. These metrics give you an idea of your marketing’s performance.
* Descriptive Analytics – Descriptive analytics are about describing who your customers are with real data. For example, “What is the median income? What kind of neighborhood is this? Or, what is their income level? What kind of car do they drive?” With descriptive analytics businesses understand who they are dealing with in their database. A perfect example of descriptive analytics are clusters, a “cluster” is a group of people who have similar attributes (they look-alike).
* Predictive Analytics – Predictive analytics, the word itself, is about the future: who are more likely to do something? But in the age of big data, it’s not just about future prediction. It also fills in the gap of incomplete data.
* Optimization Analytics – Optimization Analytics are about finding what combination of marketing efforts will yield the most revenue or profit. This is a multi-channel, omni-channel world. You have a limited marketing budget. How should you spend your money? That’s optimization.
Below is a lightly edited transcript of Episode 19 of the Inevitable Success Podcast.
Transcript:
Damian: We touched on this a little bit in our previous episode, but we felt: hey, let’s go deeper. And today we’re going to talk about the four main types of analytics and high level. They are: BI reporting, descriptive analytics, predictive analytics, optimization analytics. And by the end of this episode, you’ll have an understanding of what each is; an example, so you kind of relate to it; and then we’ll talk a little bit about solution-ing, as you call it, what to do.
Stephen: Exactly. Solution-ing is nothing but understanding what situation you are in and deciding what to do. But to do that, you have to know what each of these types of analytics do for you and what this is for, and…it’s like doctors knowing what treatment does to a patient. You’ve got to know what it is, actually. Even as a patient, you have to know what those treatments are. I’m not asking you to treat yourself. You’ve got to know what those things are.
Damian: So the first one: BI reporting—business intelligence reporting.
Stephen: So that’s the most common type, by the way. A lot of folks who say, “Oh, I’m in the world of analytics.” Data mining is really all about understanding your environment, what is going on in the world. And the easiest example that I can give you is that when you drive a car, you have to look at your dashboard. How much gas do I have left? How fast am I going? If I drive at this rate, how far can I go? And will I reach the next gas station? So ‘how long was I in the car?’ and all that kind of stuff. So that’s like what’s going on. So, in the marketing world, if you translate all this to the term that we always use, it’s like: Yeah, I blasted this e-mail and this campaign is going well. I have a very small bounce rate, or delivery rate, open rate, click-through rate, conversion rate. Or: how much money did I make on each click?
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By The Inevitable Success PodcastThe 4 Types of Data Analytics:
* Business Intelligence Reporting (B.I) – The most common type of analytics, also known as data mining, and it is really all about understanding your environment. A few examples are: “I blasted this e-mail and this campaign is going well.” “I have a very small bounce rate, or delivery rate, open rate, click-through rate, conversion rate.” These metrics are normally displayed on dashboards not to dis-similar from your car. These metrics give you an idea of your marketing’s performance.
* Descriptive Analytics – Descriptive analytics are about describing who your customers are with real data. For example, “What is the median income? What kind of neighborhood is this? Or, what is their income level? What kind of car do they drive?” With descriptive analytics businesses understand who they are dealing with in their database. A perfect example of descriptive analytics are clusters, a “cluster” is a group of people who have similar attributes (they look-alike).
* Predictive Analytics – Predictive analytics, the word itself, is about the future: who are more likely to do something? But in the age of big data, it’s not just about future prediction. It also fills in the gap of incomplete data.
* Optimization Analytics – Optimization Analytics are about finding what combination of marketing efforts will yield the most revenue or profit. This is a multi-channel, omni-channel world. You have a limited marketing budget. How should you spend your money? That’s optimization.
Below is a lightly edited transcript of Episode 19 of the Inevitable Success Podcast.
Transcript:
Damian: We touched on this a little bit in our previous episode, but we felt: hey, let’s go deeper. And today we’re going to talk about the four main types of analytics and high level. They are: BI reporting, descriptive analytics, predictive analytics, optimization analytics. And by the end of this episode, you’ll have an understanding of what each is; an example, so you kind of relate to it; and then we’ll talk a little bit about solution-ing, as you call it, what to do.
Stephen: Exactly. Solution-ing is nothing but understanding what situation you are in and deciding what to do. But to do that, you have to know what each of these types of analytics do for you and what this is for, and…it’s like doctors knowing what treatment does to a patient. You’ve got to know what it is, actually. Even as a patient, you have to know what those treatments are. I’m not asking you to treat yourself. You’ve got to know what those things are.
Damian: So the first one: BI reporting—business intelligence reporting.
Stephen: So that’s the most common type, by the way. A lot of folks who say, “Oh, I’m in the world of analytics.” Data mining is really all about understanding your environment, what is going on in the world. And the easiest example that I can give you is that when you drive a car, you have to look at your dashboard. How much gas do I have left? How fast am I going? If I drive at this rate, how far can I go? And will I reach the next gas station? So ‘how long was I in the car?’ and all that kind of stuff. So that’s like what’s going on. So, in the marketing world, if you translate all this to the term that we always use, it’s like: Yeah, I blasted this e-mail and this campaign is going well. I have a very small bounce rate, or delivery rate, open rate, click-through rate, conversion rate. Or: how much money did I make on each click?