What is marketing analytics?! | Unlock growth by understanding data and analytics

Summary

This video from Funnel's YouTube channel delves into marketing analytics, explaining its significance for marketers. It outlines the process of harnessing data from various marketing channels to enhance strategy and ROI. The video introduces a marketing analytics maturity framework, guiding viewers from understanding past performance to predicting future outcomes. Practical examples, such as budget estimation, illustrate the application of analytics. The host also touches on data transformation, emphasizing the importance of data organization for insightful analysis. The video concludes with advice on starting with marketing analytics, suggesting tools like Google Data Studio for visualization.

Takeaways

• 📊 Marketing analytics is the process of managing and analyzing data to enhance marketing efforts and improve ROI.
• 🔍 It involves identifying patterns and trends in marketing data to draw actionable insights and make data-driven decisions.
• 📈 The importance of marketing analytics lies in its ability to leverage data from various marketing channels to create a comprehensive view of the marketing funnel.
• 📝 The process includes collecting and managing data, extracting insights, and reporting findings to guide marketing strategy.
• 📈 A marketing analytics maturity framework consists of understanding what happened, why it happened, predicting future outcomes, and making prescriptive decisions based on these insights.
• 💡 Predictive analytics within the framework aims to forecast future marketing outcomes based on historical data and current trends.
• 📉 Prescriptive analytics enables marketers to not only predict but also to act on those predictions to optimize marketing strategies.
• 💼 Marketers often use marketing analytics to determine budget allocations and measure the effectiveness of their spending across different platforms.
• 🛠 Data transformation is a critical step in marketing analytics, involving cleaning, grouping, and mapping data to ensure it's organized and reliable for analysis.
• 📊 Marketing analytics dashboards and visualization tools like Google Data Studio are essential for visualizing data and identifying areas for deeper analysis.

Q & A

What is marketing analytics?

Marketing analytics is the management and analysis of data to improve the performance of marketing efforts. It involves looking for patterns and trends in marketing data to draw insights that help in better marketing of a product or service, ultimately increasing return on investment and decreasing time spent to achieve improved output.

Why is marketing analytics important for marketers?

Marketing analytics is important as it leverages data from various parts of the marketing and sales funnel to create a holistic picture, helping marketers to optimize their strategies, understand the effectiveness of different marketing channels, and make data-driven decisions.

What does the marketing analytics process involve?

The process of marketing analytics includes collecting and managing data, extracting insights and learnings from past activities, and reporting on analysis findings and planning strategies. It also involves understanding what happened, why it happened, predicting what will happen, and making decisions based on those predictions.

Can you explain the marketing analytics maturity framework?

The marketing analytics maturity framework is a way to think about the progression of marketing analytics. It starts with understanding what happened, then moves to understanding why it happened, predicting what will happen, and finally, making decisions based on those predictions, which is prescriptive analytics.

How can marketers use marketing analytics to determine budget allocations?

Marketers can use marketing analytics to determine budget allocations by looking at past spending across platforms, mapping that with web and conversion data to understand returns, and using this analysis to plan budgets accordingly.

What is the role of data transformation in marketing analytics?

Data transformation in marketing analytics involves organizing or preparing data by cleaning it, grouping it, and mapping it together. This ensures the data is of high integrity, organized for easy segmentation, and can be reliably used for future decisions.

How can marketers visualize and analyze their marketing data?

Marketers can visualize and analyze their marketing data using tools like data warehouses, marketing data hubs, dashboards, and Google Data Studio. These tools help in aggregating data from various sources and presenting it in a way that facilitates easy analysis.

What are the challenges in marketing analytics that marketers often face?

Marketers often face challenges such as the need for self-sufficiency in analytics, the complexity of using data warehouses, and the reliance on busy data engineers or analysts, which can cause bottlenecks in the process.

How can marketers get started with marketing analytics?

Marketers can get started with marketing analytics by preparing their data for analysis, using tools to aggregate and organize data, and then analyzing it to find trends and patterns that provide actionable insights.

What is the difference between marketing analytics and attribution?

While marketing analytics involves tracking and analyzing the performance of marketing campaigns, attribution is the process of assigning credit to specific touchpoints in the customer journey that influenced a conversion, trying to determine the impact of each marketing channel.

Outlines

00:00

📊 Introduction to Marketing Analytics

The paragraph introduces the concept of marketing analytics, emphasizing its importance for marketers to improve the performance of marketing efforts. It explains that marketing analytics involves the management and analysis of data to identify patterns and trends, which can enhance marketing strategies and increase return on investment. The paragraph also touches on the significance of marketing analytics in leveraging data from various parts of the marketing and sales funnel to create a comprehensive view. The process of marketing analytics is outlined, including data collection, analysis, and reporting, which aids in making informed decisions for marketing strategies.

05:03

📈 Deep Dive into Marketing Analytics Process and Tools

This paragraph delves deeper into the process of marketing analytics, starting with the collection and management of data to measure marketing performance. It discusses the importance of extracting insights from past activities to guide future marketing strategies. The concept of a marketing analytics maturity framework is introduced, outlining the stages from understanding what happened to predicting and prescribing actions based on data analysis. The paragraph also provides a practical example of how marketers can use analytics to determine budget allocations and measure the effectiveness of different marketing channels. It highlights the need for data transformation, including cleaning, grouping, and mapping data, to prepare it for analysis. The paragraph concludes with a discussion on the use of marketing analytics dashboards, reports, and visualization tools to facilitate data analysis and decision-making.

10:04

🔗 Conclusion and Call to Action

The final paragraph serves as a conclusion, summarizing the importance of marketing analytics for tracking campaign progress and feeding insights back into marketing strategies. It encourages viewers who are new to marketing analytics or looking to improve their current practices to prepare their data for easy analysis. The paragraph ends with a call to action, inviting viewers to subscribe for more content on digital marketing best practices, marketing data, analytics, and data visualization, positioning the channel as a valuable resource for marketers seeking to enhance their skills.

Keywords

💡Marketing Analytics

Marketing analytics is the process of managing and analyzing data to enhance the effectiveness of marketing campaigns. It involves identifying patterns and trends in marketing data to draw actionable insights, which can improve marketing strategies and increase return on investment. In the video, marketing analytics is emphasized as crucial for understanding the performance of marketing efforts and making data-driven decisions, such as optimizing marketing spend across various platforms.

💡Data Visualization

Data visualization refers to the graphical representation of data to make it easier to understand and analyze. It plays a key role in marketing analytics by providing a clear and concise view of complex data, helping marketers to quickly grasp the performance of their campaigns and make informed decisions. The video mentions data visualization in the context of creating a marketing analytics dashboard, which helps in presenting data in an easily digestible format.

💡Marketing Funnel

The marketing funnel is a concept that illustrates the customer journey from initial awareness to purchase. It is a multi-stage process that includes awareness, interest, consideration, intent, evaluation, and purchase. In the video, the marketing funnel is mentioned as a part of the holistic picture that marketing analytics helps to create, allowing marketers to understand the customer journey and optimize their marketing efforts at each stage.

💡Data Transformation

Data transformation is the process of organizing, cleaning, and mapping data to make it suitable for analysis. It is a critical step in marketing analytics as it ensures that data is accurate, reliable, and organized in a way that facilitates meaningful insights. The video script discusses data transformation in the context of preparing data for budget planning and analysis, highlighting its importance in connecting different data sets and creating new segments for a comprehensive view of marketing performance.

💡Return on Investment (ROI)

Return on Investment (ROI) is a financial metric used to evaluate the efficiency of an investment or to compare the efficiency of different investments. In marketing, ROI measures the profit gained from a marketing campaign relative to its cost. The video emphasizes the importance of marketing analytics in increasing ROI by optimizing marketing efforts and reducing the time spent to achieve improved results.

💡Attribution

Attribution in marketing refers to the process of determining which touchpoints, channels, or sources contributed to a conversion or sale. It helps marketers understand the effectiveness of their marketing channels and allocate resources accordingly. The video script briefly touches on attribution, cautioning against it as a complex issue and suggesting that marketing analytics focuses more on overall campaign performance rather than individual touchpoint effectiveness.

💡Data Warehouse

A data warehouse is a system used for reporting and data analysis. It stores data from one or more sources and serves the purpose of data analysis and reporting. In the video, data warehouses like Google BigQuery and Snowflake are mentioned as tools that can aggregate data from various marketing platforms, allowing for comprehensive analysis and insights into marketing performance.

💡Google Data Studio

Google Data Studio is a data visualization tool that allows users to create interactive reports and dashboards. It is mentioned in the video as a starting point for marketers who may not have coding capabilities, enabling them to visualize their data and identify areas for deeper analysis. It plays a role in simplifying the process of creating marketing analytics dashboards.

💡Predictive Analytics

Predictive analytics is the use of statistical algorithms to analyze current and historical facts to make predictions about future events. In the context of the video, predictive analytics is part of the marketing analytics maturity framework, where it helps marketers to forecast outcomes based on past data, such as predicting the impact of different marketing spend levels on campaign performance.

💡Prescriptive Analytics

Prescriptive analytics is an advanced form of analytics that provides guidance on the best course of action based on data analysis. It goes beyond descriptive and predictive analytics by offering specific recommendations for action. The video describes prescriptive analytics as the stage where marketers have a deep understanding of their marketing data, allowing them to make informed decisions and optimize their strategies, such as tailoring creatives for different platforms based on their performance.

Highlights

Marketing analytics is the management and analysis of data to improve the performance of marketing efforts.

It involves looking for patterns and trends in marketing data to draw insights and conclusions.

Marketing analytics helps increase return on investment and decrease time spent to achieve improved output.

It leverages data from various parts of the marketing and sales funnel, including paid advertising, email, content, web, sales, and customer success.

Advanced marketing analytics can include data on products, services, or even back-end financial data.

The process of marketing analytics includes collecting and managing data, extracting insights, and reporting findings.

A marketing analytics maturity framework helps in understanding what happened, why it happened, predicting what will happen, and making decisions based on those predictions.

Marketers often need to determine annual or quarterly budgets using marketing analytics for reasonable estimations.

Data transformation is a key concept in marketing analytics, involving cleaning, grouping, and mapping data together.

Data warehouses and marketing data hubs facilitate the aggregation and analysis of data from various marketing platforms.

Modern marketers should be self-sufficient in marketing analytics to be agile and make quick decisions.

Marketing analytics dashboards, reports, and visualization tools are essential for analyzing and presenting data.

Google Data Studio is a good starting point for marketers to visualize and analyze data without coding capabilities.

Marketing analytics allows tracking the progress of campaigns and analyzing their performance to improve marketing strategies.

For beginners in marketing analytics, getting all data prepped and ready in one place is crucial for easy analysis.

Transcripts

Marketing data is being created all around us.

But what good is it if we don't know what it's trying to tell us?

Hi and

welcome to Funnel’s YouTube channel where I talk all things digital marketing,

data visualization and analytics. All the great content

you need to shortcut your way to being a better marketer.

In this video, I'm going to give you a quick lesson

on what marketing analytics is, why it's important for marketers

to understand, what you need to include in a marketing analytics dashboard.

And also give you the knowledge you need to get started with it right away.

Marketing analytics definition

Marketing analytics is the management and analysis of data

to improve the performance of your marketing efforts.

But what does that mean?

It’s the process of looking for patterns and trends in your marketing data.

To draw insights and conclusions that can help you be better at marketing

your product or service.

This ultimately increases your return on investment,

but also decreases your time spent to achieve an improved output.

It helps you learn quickly so you can optimize even quicker.

Why is marketing analytics important for marketers?

Marketing analytics leverages data from various parts of the marketing

and sales funnel, including paid advertising, email, content, web, sales

and customer success.

To create a more holistic picture of the marketing funnel. The more advanced

marketing analytics becomes, the more data that's in play, which could include data

on your product or service or even back-end financial data.

What is the process of marketing analytics?

Marketing analytics requires collecting and managing data. For marketing data

this means measuring the performance of your marketing efforts,

then collecting and preparing the data that’s produced.

The next step is extracting insights and learnings from past activity,

trying to understand what happened and why it happened.

This helps decide what direction to take your marketing strategy,

which, let's face it, is your way of telling the right story

to the right potential customers at the right time.

So they buy a product or service now or at some point down the road.

Finally, you need to report on your analysis, findings

and plan strategy to your managers, board or clients.

A marketing analytics maturity framework.

Another way of thinking about the process of marketing analytics

is through a maturity framework.

As you can see, the first stage here is to understand what happened.

You need to somehow produce data to see what happened

with your marketing activity.

This would be something like showing you how much you spent on a channel

like TikTok or Facebook, what it resulted in,

and how many clicks or how many video views.

The next stage is to understand why that happened.

This is when we dive more into the analysis side of things

following the same example this will be understanding why a lot of

people viewed your videos on TikTok and why you got more clicks on Facebook

looking for correlations and trends then trying to prove causation.

Predictive analytics then tries to look ahead and predict what will happen.

Following this same example, we might want to ascertain

what will happen when we spend $1,000 a month on TikTok or $100,000 a month.

Will spending more affect the return on investment?

Will the customer journey work in the same way?

Will the quality of the traffic be effected?

It is having enough data to map out what could happen

based on what has happened and what is currently happening.

Finally, there's prescriptive analytics.

This is to have such a strong understanding of your marketing

that you can make predictions, then take actions as a result.

Again, following our TikTok example, this would be knowing

TikTok will drive more video views, but Facebook will drive more clicks.

So you should optimize

TikTok creatives for views and Facebook creatives for clicks.

It might sound simple, but understanding what happened, why it happened, then

predicting what will happen and then being sure

enough to make decisions on those predictions is pretty hardcore

marketing analytics.

That was a whistle stop tour of a marketing analytics maturity framework.

But maybe I need to do another video going into a little bit more detail.

Let's look at a common example of marketing

analytics for in-house marketers and agencies.

Marketers are usually asked

to submit some kind of annual or quarterly budget, right?

But how do you go about determining what you need to spend to reach your targets?

Is it gut feeling? Is it an opinion?

What you probably need to do

Is some sort of marketing analytics to arrive at a reasonable budget estimation.

So where do you start?

First, you need to look at what you spend across each platform.

Then map that together with web data from Google Analytics and conversion

data from your CRM to understand what you've got in return for that spend.

The deeper

you're able to follow the thread, the closer to the bottom line you can go.

And I visualized this in a simple way to help you understand.

You can see here that I spent $20 on YouTube ads

last quarter, and 10 people who made a purchase have “first page seen”

as a landing page I sent people to from YouTube ads.

That's already really good to know.

But depending how good my marketing analytics is, I might be able to go

further.

If I've connected my various data and systems, I may also be able to see

how much each one of those people spent when they made a purchase.

From that,

I can determine an average order value for YouTube.

Super helpful to know. But I can go even more granular.

Maybe I can see which items those people bought

and if I know the margins for each of those products, I can see

what the average margin is for people who came from YouTube.

Ads. What this means is that you can start to analyze

how various channels work for you and plan a budget accordingly.

Based on that analysis. To be clear, this is not attribution.

Attribution would be trying to decide if the person with “first page seen” in my CRM

actually did decide to click my YouTube Ad and purchase something

because they saw my YouTube Ad

or if it's because they saw other ads on other platforms

or have brand recognition from somewhere else, etc., etc.

Attribution isn’t a rabbit hole

I want to go down here so let's move on.

How do you get started with marketing analytics?

So if the goal of marketing analytics is to measure the progress

of your marketing efforts and to draw insights from it to get more

of your marketing dollars, the question is how does it work?

As you're looking for trends and patterns that give you actionable insight,

you need a way of seeing your data in a way that makes that possible.

If you simply looked at all

the data from all the different platforms you use to execute your marketing

it would likely be very difficult to scroll through thousands of rows of data.

Data warehouses like Google, Big Query and Snowflake or marketing

data hubs like Funnel make it possible to automatically download data

from all the different marketing platforms,

aggregate it, and put it in one place to be analyzed.

However, before you're able to analyze the data, you need to organize it.

This is the step of marketing analytics that can be challenging for marketers,

which is why they often rely on the assistance of data engineers

or data analysts.

But anyone who has collaborated with those teams before

know that they are always extremely busy and can cause bottlenecks.

Modern marketers

need to be relatively self-sufficient when it comes to marketing analytics

so they can be agile, analyze in real time,

and make quick decisions to affect the outcome of their activity.

What is data transformation in marketing analytics?

A key concept for understanding

how marketing analytics is achieved is data transformation. Also referred

to as organising or preparing data.

To prepare data is to clean it, group it, and map it together

like I mentioned earlier, when you’re planning budgets.

Cleaning data is making sure that the identifiers

you need in your data to slice and dice it are in there

or not in there, as it's very difficult to easily segment data if it isn't organized.

Think of it like organizing a library without sections or labels.

How would you even go about organizing it or finding a book?

It's also about making sure that the data is of high integrity

and can be relied on for future decisions.

Grouping data is creating new segments of that data,

basically like creating new dimensions and metrics that combine

other metrics and dimensions or take subsets of them.

Mapping data is

to connect the dots between different sets of data.

Given that you need to aspire to seeing the full picture

to get the most informative and accurate analysis of your data,

you need a way of ensuring that data can be analyzed together.

Marketing analytics dashboards, reports and visualization.

Once you have prepared

your data for analysis, you need to decide where you want to view that data.

If you’re comfortable with it, or you have the resources to help you,

maybe a data warehouse

is the destination for you as they do offer ultimate flexibility.

With that said, they are difficult to use and require coding

capabilities. For those who don’t have coding capabilities,

a good place to start is with a dashboard and Google Data Studio. That allows you

to identify areas that you should try and do deeper analysis on.

That deeper analysis can be done in a few different places,

but a common destination for ad hoc analysis is Google Sheets.

Marketing analytics is a broad topic, but ultimately

it means being able to track the progress of your campaigns and analyze

the performance of those campaigns to feed insights into your strategy

and improve the outcome of your marketing efforts.

If you're just getting started with marketing analytics

or you want to improve how you are already doing it,

looking for trends and patterns to act on requires

getting all your data prepped and ready in one place for easy analysis

so that you can find the answers to any questions.

If you found this video useful,

subscribe where you get more videos about digital marketing best practices,

marketing data and analytics, and data visualization. All the great content

you need to shortcut your way to being a better marketer.