This module will cover:

• The importance of digital analytics
• Core analysis techniques
• Conversions and conversion attribution
• Creating a measurement plan

The importance of digital analytics

https://analyticsacademy.withgoogle.com/unit?unit=2&lesson=1

Study guide

Digital analytics is the analysis of qualitative and quantitative data from your business and the competition to drive a continual improvement of the online experience that your customers and potential customers have which translates to your desired outcomes (both online and offline).

Trends driving change:

A few major trends that are driving change, for every business -- both big and small alike.
First, the internet has made the world's information and media available to nearly everyone at the click of a button.
Second, mobile devices have helped connect nearly everyone around the world, 24 hours a day, 7 days a week.
And finally, cloud computing has provided us with practically infinite computing power and for cheap.
 

Because of the first two trends, the consumer journey is forever changed.

The linear purchase funnel is no longer relevant:

For a long time, we've had the marketing concept of a purchase funnel with various stages of customer interaction.
This funnel consists of the following stages:

• building awareness
• acquiring interest
• engaging with potential customers
• driving them towards a conversion online or offline
• and retaining them as customers.

Qualitative and Quantitative data:

• First, for ecommerce sites, an obvious objective is selling products or services.
• Second, for lead generation sites, the goal is to collect user information for sales teams to connect with potential leads.
• Third, for content publishers, the goal is to encourage engagement and frequent visitation.
• Fourth, for online informational or support sites, helping users find the information they need at the right time is of primary importance.
• And finally for branding, the main objective is to drive awareness, engagement and loyalty.
   

Micro & Macro conversions

There are key actions on any website or mobile application that tie back to a business' objectives. The actions can indicate an objective, like a purchase on an ecommerce site, has been fully met.

We call these your "macro" conversions.

Some of the actions on a site might also be behavioral indicators that a customer hasn't fully reached your main objectives but is coming closer, like, in the ecommerce example, signing up to receive an email coupon or a new product notification.

We call these your "micro" conversions. 

It's important to measure both micro and macro conversions so that you are equipped with more behavioral data to understand what experiences help drive the right outcomes for your site.

Continual improvement.
 

Data can be the driver of a continual improvement process for your business.
Let's step through this process and talk about it in more detail.
 

The whole process starts with measurement. How many people are completing the customer journey? And where along that journey are you losing or retaining customers? In a nutshell, the measurement stage is all about collecting the data needed to answer your business questions.
 

Next, we need to do reporting to package the data in a readable format and then get information out to decision-makers so that they can be empowered with the information they need to make business decisions. This often happens by developing and distributing pre-made reports or dashboards.

Then analysis has to happen. Analysis can be as simple as identifying larger trends, but it can also be complex, including deep segmentation of your data or competitive analysis comparing your performance to an industry benchmark. Essentially, analysis is the process of developing a hypothesis that reflects your expectations, and then figuring out why the numbers do, or do not, match those expectations. When unexpected events happen in your data, analysis helps you figure out why.

Testing is the next phase of the process. This is where you try different solutions to the problems you identified during your analysis. Testing is critical because it takes opinions out of the decision making process for discovering improvement opportunities.

Finally, you repeat what you learn from this whole process and you improve. 

To summarize this chapter: 

First, we talked about how the rapid growth of the internet and increased accessibility to information and data has opened new opportunities for measurement, but also complicated how we measure a customer's journey and their engagement with your business online.

Core analysis techniques

Study guide

• Describe segmentation and why it is an important technique for good analysis
• Understand internal and external benchmarks to add context to your data

Transcript

There are many different ways to analyse data. In this lesson, we would like to cover two techniques -- segmentation and context -- that we believe are critical to good data analysis.

First, let's talk about segmentation. Looking at aggregated data helps you understand overall user behaviour trends, like how their purchase patterns change over time.

But in order to understand why purchase patterns changed, you need to segment your data.
Segmentation allows you to isolate and analyse subsets of your data.
For example, you might segment your data by marketing channel so that you can see which channel is responsible for an increase in purchases.

Drilling down to look at segments of your data helps you understand what caused a change to your aggregated data.
All reports in Google Analytics provide segmentation of your traffic.
For example, take a look at your Traffic Sources report.
Each row in the table shows how a specific traffic segment performed.

This lets you compare different segments to understand which sources are bringing in the highest value traffic. Let's talk through some common segments that you might want to consider when looking at your own data. You can segment your data by date and time to compare how users who visit your site on certain days of the week or hours of the day behave differently. 

You can segment you data by device to compare user performance on desktops, tablets or mobile phones. 

You can segment your data by marketing channels to compare the difference in performance for various marketing activities.

You can segment by geography to determine which countries, regions or cities perform the best.

And you can segment by customer characteristics, like repeat customers versus first-time customers, to help you understand what drives users to become loyal customers.

In addition to segmentation, another analysis technique that's really important is adding context your data.

Context helps you understand if your performance is good or bad.

There are two ways to set context – internally and externally. 

Externally, contexts can come from industry benchmark data. This can help you understand how you perform relative to other businesses similar to yours.

For example, external context makes it easy to see if an uptick in your business is due to general growth trend for your sector or is just specific to your business.

Internal context helps you set expectations based on your own historical performance.
For example, you can use historical data as a benchmark and then use that benchmark to set your key performance indicator targets.

Throughout this course, we will talk about how you can use segmentation and context when working with Google Analytics data or other digital analytics data, so keep these techniques in mind for future application.

Conversions and conversion attribution

Study guide

• Define the term "conversion"
• Explain how marketing attribution works in Google Analytics and why understanding attribution is important for good analysis
• Understand the “last-click” attribution model versus other models

Transcript

In this lesson we're going to discuss two important concepts used to measure the customer

journey -- conversions and conversion attribution.

One of the most important concepts in digital analytics is the idea of macro and micro conversions.

A macro conversion occurs when someone completes an action that's important to your business.

For example, if you're an ecommerce company, the most important macro conversion is usually a transaction.

A micro conversion is also an important action, but it does not immediately contribute to your bottom line.

It's usually an indicator that a user is moving towards a macro conversion.

It's important to measure micro conversions because it helps you better understand where people are in on the journey to conversion.

Many times, when we talk about macro and micro conversions we discuss the idea of attribution.

Simply put, attribution is assigning credit for a conversion.

We want to assign credit to our marketing channels in order to understand the return on our marketing investment for each channel.

If we spend $100 on a marketing activity our hope is that we will generate more than $100 in revenue.

The most common type of attribution is called last click attribution. Last click means that all of the value associated with the conversion is assigned to the last marketing activity that generated the revenue.

The last marketing activity gets all the credit.

We've used last-click attribution for many years because it's the best measurement we've had.

But we're now able to look at all of the marketing activities that helped generate each conversion. This is important, because the reality is your customer will likely interact with you many times before conversion occurs.

How do we understand the value of those other marketing channels prior to conversion?

We use the concept of an assist.

You see, attribution is a lot like scoring points in a basketball game. It takes more than one player to make it happen. One player scores the goal, but other players may help, or assist, in the process.

If you were coaching a basketball team, you'd want to understand which of your players score the goals and which players assisted in the scoring.

This helps you understand how your team works together to be more successful.

It's the same in online marketing. If you think of the marketing channels as your players, some make assists and some score goals.

To properly understand the value of each channel, you need to know which role it's played in your customer's journey to conversion. There are many different ways to assign value to channels.

Rather than assign all of the value to the last channel, you might want to assign all of the value to the first channel -- the one that started the user on the customer journey.

This is called first click attribution.

The reason you might do this is to understand that the channel is a good channel for initiating conversions.

Or, you might assign a little bit of value to each of the assisting channels in the customer journey.

In summary, the whole point of attribution is to better understand the value of each marketing channel

and how multiple channels work together to drive conversions.

You can then use this knowledge to better understand your customer's journey and allocate your online marketing budget accordingly.

Creating a measurement plan

Study Guide

• Define meaningful goals, targets and segments
• Understand how your business objectives will influence what you track in Google Analytics

Digital analytics is all about using data to drive change.

But the data needs to be relevant to your business. To get the most benefit from analytics you need to tailor the implementation to your needs.

In this lesson we'll talk about how to create an analytics measurement plan that is specific to your business.

Good data is the foundation for making smart decisions. Managing and implementing infrastructure for this data may require some time and effort, people, processes and technology.

The larger your business, the more involved this can be.

Let's talk about the skills you need on your analytics team.

• You need someone who understands what the business objectives are and the strategies used to support those objectives.
• You also need someone who understands what analytics can do.
• Finally, you need someone with technical skills who can implement an analytics tool.

If your organization is large, you may need an analytics team that can support different business units. If you have a small business, your measurement plan will be simpler, and you may able to fill all these needs on your own. Once you've organized the right people to be involved with the planning conversation, decide what you need to measure. 

Start with a measurement plan which identifies your business objectives.

The next step is to understand your technical environment by documenting your technical infrastructure. In this stage you will be asking your team questions like:

• "What are our server technologies?"
• "Are we active on mobile?"
• "Are we using responsive design?"
• "Do the technologies we're using make it possible to track everything we need to track?"

After defining your business needs and documenting the technical environment of your business. The next step is creating an implementation plan that is specific to the analytics tool that you're using. For Google Analytics, this means defining the code snippets and specific product features that you'll need in order to track the data defined in your measurement plan.

Once the implementation plan is designed, the next step is to have the web development team, or the mobile team, actually implement the tracking recommendations that you've made. This process isn't complete once the implementation stage is over! Because the digital world changes so fast, your measurement plan needs to be maintained and refined so that your data can evolve with your business. Therefore, the measurement planning process should be cyclical, if not continuous.

Let's dive a little deeper.

We're going to spend most of this lesson talking about the measurement plan, using a simple model developed by Avinash Kaushik. This model can be used to design a digital measurement plan for any size of business -- large or small. Avinash's model teaches us that the way to approach digital measurement is by leading the conversation with the business' objectives

Why do we start here? The whole point of measurement is to understand if you're making good business decisions or bad business decisions, and then figuring out how to make changes moving forward. You will go through a series of 5 steps in order to define your measurement plan.

We'll go over each of the 5 steps in this lesson, but here's an overview of what they are.

• Step1: document your business objectives.
• Step2: identify the  strategies and tactics to support the objectives.
• Step3: choose the metrics that will be the key performance indicators.
• Step4: decide how you'll need to segment your data.
• Step5: choose what your targets will be for your key performance indicators.

Remember, this process requires you to meet with the people who make the decisions in your business. This could be managers, executives or you, if you're a small business owner!

Let's use a fictional outdoor equipment company as an example of how we would actually apply this process to create a real measurement plan. For the sake of this example, let's say that we sell our outdoor products on our website and in stores. This outdoor company also maintains a blog to engage customers in conversations about how to enjoy the outdoors.

The first step to create our measurement plan is to define our business objective.

We need to ask ourselves -- why do we exist? Often you need to dig really deep to get the true answer. In our example let's say the business objective is

"Help people enjoy the outdoors through innovative products and cultivate their love of the outdoors."

To support our objective, our business will use specific strategies and tactics.

One strategy to support our mission would be to sell outdoor products.

A tactic to support that strategy would be to sell online via a website.

Another would be to sell items in store.

We could even develop a mobile shopping app.

But, in this scenario we also have a physical store, so one way we might drive sales is by giving people information on our website or in our mobile app that helps them locate one of our stores.

That can be another tactic of our website.

Finally, to support the second half of our mission -- cultivating our customers' love of the outdoors

-- our strategy would be to engage customers in conversations about outdoor topics, and we might do that through posts on our blog.

Remember, each business will have its own set of strategies, but most of them will closely relate to these 5 common types:

Let's continue breaking this down.

The next step is to choose the Key Performance Indicators, also referred to as KPIs.

These are the measurements of your strategies and tactics and are the numbers that you'll look at day-to-day to understand how your business is performing.

In our example business, for selling products, we're going to look at KPIs like how much revenue we're generating and the average order value for each transaction.

For the tactic of driving brick-and-mortar store visits, we can look at how many times the store locator on our site is used, or how many times users print a coupon for in-store use.

To measure user engagement on our blog, we might look at recency and frequency metrics and whether or not users share our brand content on social networks.

Once you have defined the KPIs you want to measure, you need to document which segments of data are important to measure.

For example, when we're thinking about our fictional store, we might want to see our KPIs segmented by marketing channel. As a business we're likely investing in different marketing channels, such as search, display, email, and social. We want to know how much value we're ultimately getting from those investments.

We might also look at our customer type -- our new customers versus our repeat customers -- to see how much of our business is being driven by each segment and whether there are opportunities for driving more customer loyalty.

Since we have physical stores, we might also be interested in looking at the geography

of our site visitors to see if certain geographies near stores are performing better than other locations.

The segments you choose can be the same or different across all of your website -- it all depends on what your business is doing and which strategies and tactics are being used to reach your objectives.

Finally, you need to add some context to your data so that you can better understand the performance of your business. You need to know, from your business leadership, the targets for each of your KPIs.

Adding targets to the measurement plan helps everyone who looks at the data understand if the business is doing well or doing poorly.

Once your business measurement plan is complete, you will have documented what you want to measure. But, can you measure everything in your plan? It depends on the website, mobile app, or other device you're trying to measure.

You need the help of your IT team to translate the business needs to an implementation plan.

The IT team can help you understand the website or app environment and ultimately determine what you can track.

There are a few website technologies that will require additional planning. For example,

• Query string parameters
• Server redirects
• Flash and AJAX events
• Multiple domains and subdomains
• Responsive web design

All of these scenarios require extra attention when designing your implementation plan for tools like Google Analytics.

It is absolutely critical to have a thorough conversation with your IT team to understand the environment you want to measure.

For guidance on how to adapt your implementation to these technologies, check out our developers resources. (developer.google.com/analytics)

Once you know both the business requirements and details about your technical environment,

the next step is to create a basic implementation plan.

In this plan, you will document the features of your analysis tool that you'll use to capture the data you need.

Let's review a few of the most common features used in a Google Analytics implementation plan for a website.

• First of all, to get any data, you need to implement the standard Google Analytics page tag. This gives you the bulk of the data you'll need.
• Next, looking back at your measurement plan, you need a way to track the KPIs. You can do this using Goal Tracking and the Ecommerce module if you are an ecommerce business.
• Another feature you may want to use is filters. These normalize your data so that your reports are more accurate and useful.
• To properly track marketing campaigns you should use campaign tracking and AdWords linking.
• Finally, you can use custom dashboards and customer reports to simplify the reporting process. This can help save a lot of time.

Usually you will combine the measurement plan, technical information and Google Analytics features into a document that details the implementation recommendations for your business.

The result of this process is reliable, accurate set of data that helps you understand the performance of your business day in and day out.

The final step of the measurement planning cycle is to maintain and refine your plan. This is a really important step of the process because your business requirements and your technical environment can change over time.

Without a team to maintain your measurement plan, your data won't keep pace with your reporting needs. Also, keep in mind that in your first iteration you may not be able to implement your entire plan due to time or resource constraints.

If you have a robust implementation plan, you may consider tackling it in phases by prioritizing the most important features first.

In summary, creating a good measurement plan requires you to organize people, processes, tools and technologies.

Planning has 5 main stages:

• First, define your measurement plan. Make sure you involve your business leaders and marketing team. They will identify which objectives, goals, KPIs, segments and targets should be measured.
• Next, document your technical environments. This is when you'll want to get your IT team involved.
• Then, translate your measurement plan into an implementation plan based on your technical environment.
• Only once the plan is ready, move on to implement analytics.
• Finally, refine your implementation over time to keep your data current and useful.