Week 4: Measure performance success

Welcome back. Earlier
in the course, you learned about
the relationship between digital
marketing and branding. You also explored the
different parts of a digital marketing and
e-commerce strategy, including research,
goal-setting, and selecting the right
channels and tactics. Lastly, you found out
a little about some of the channels and
tactics like SEO, SEM, social media,
and email marketing. This part of the course
is all about data, how you measure it, how you interpret it, and how it can make
your strategy better. We’ll explore the concept of performance marketing and
examine some ways you might be working with data in an entry-level digital
marketing or e-commerce role. We’ll discuss how data can
help you find out what’s working well and how to
adapt to necessary change. We’ll also go over some
ways to demonstrate those findings through
data storytelling. Measuring the success of your
marketing efforts may be the most important
thing you’ll learn in your digital marketing
or e-commerce career. No matter how carefully
you plan your strategy, measuring your results can always help you make it better, from building your brand, to engaging customers,
and maximizing sales. The first time I
really worked with data and digital marketing was when I began running paid advertising for my
own e-commerce store. I wanted to understand
if the effort I was making was worth the extra cost. This made me realize that
there was a whole world of measurement beyond the paid
campaigns I was running. I can measure the health
of my whole store through different dashboards and
analytics resources. This is where e-commerce and digital marketing
really gets fun because you can
actually prove that your tactics are helping
you reach your goals. You’re almost to the
end of the course, and I’m so excited for you
to cross the finish line. Let’s get back into it.

Tutorial on Measuring Progress with Performance Marketing

Performance marketing is the process of using data and analytics to measure the effectiveness of marketing campaigns. By tracking key performance indicators (KPIs), performance marketers can gain insights into how their campaigns are performing and make necessary adjustments to improve results.

Steps to Measure Progress with Performance Marketing

1. Define your goals. What do you want to achieve with your marketing campaign? Are you looking to increase website traffic, generate leads, or boost sales? Once you know your goals, you can choose the right KPIs to track your progress.
2. Choose the right KPIs. There are a variety of KPIs that can be used to measure the success of a performance marketing campaign. Some common KPIs include:

• Website traffic
• Lead generation
• Sales
• Conversion rate
• Cost per acquisition (CPA)
• Return on investment (ROI)

3. Collect data. Once you have chosen your KPIs, you need to collect data to track your progress. This data can be collected from a variety of sources, such as website analytics, CRM software, and social media platforms.
4. Analyze your data. Once you have collected data, you need to analyze it to see how your campaign is performing. This involves looking at trends and patterns in the data to identify areas where you are meeting or exceeding your goals, as well as areas where you need to make improvements.
5. Make adjustments. Based on your analysis of the data, you may need to make adjustments to your marketing campaign. This could involve changing your targeting, your messaging, or your budget.

Tips for Measuring Progress with Performance Marketing

• Set realistic goals. When setting goals for your marketing campaign, it is important to be realistic. If you set goals that are too ambitious, you may be discouraged if you do not meet them.
• Track your progress regularly. It is important to track your progress on a regular basis so that you can identify any problems early on. If you wait until the end of your campaign to review your results, it may be too late to make changes.
• Use a variety of data sources. Don’t rely on just one data source to measure the success of your campaign. By using a variety of data sources, you can get a more complete picture of how your campaign is performing.
• Be prepared to make changes. No marketing campaign is perfect. As you collect data and analyze your results, you may need to make changes to your campaign. Be prepared to make these changes so that you can improve your results.

By following these steps, you can effectively measure the progress of your performance marketing campaigns and make necessary adjustments to improve results.

What is performance marketing?

The process of using concrete information about customer behaviors to plan and refine marketing and sales strategies

Performance marketing is the process of using concrete information about customer behaviors to plan and refine marketing and sales strategies.

Throughout this course, we’ve emphasized how important
it is to measure the results of digital
marketing tactics, campaigns, and strategies. In fact, these activities are
so important that there is a special term to describe
them: performance marketing. In this video, we’ll explore what’s involved in
performance marketing, and how it allows
businesses to set goals, track results, and
improve on their work. Let’s get started. Imagine this: It’s 1985, and you work for a
marketing agency that’s promoting a
new breakfast cereal. You run some focus
groups to learn about your target audience
and what they like. You use those interviews and your past experiences
as a marketer to create memorable ads for newspapers, billboards,
and televisions. And then you wait. Your sales
go up. The campaign works! But what you don’t know is
which ads were most effective and how many of
the new customers found the product
through your campaign. That doesn’t mean your ad
strategy is all guesswork— just that there’s limited
information you can gather. You can keep going with that
same successful strategy. Now imagine you’re running that same campaign
today, only online. With digital marketing, there are dozens
of ways to measure the success of your
tactics and campaigns. So if you place an ad
for cereal online, you can track the
things that just aren’t possible with billboards, like how many people encounter and engage with
your ad each week. Collecting and evaluating all of that information can help you rethink a weak strategy or
make a good one even stronger. That’s performance marketing. It’s the process of using
concrete information about customer behaviors to plan and refine marketing and
sales strategies. It focuses on measurable results like clicks and conversions. Performance marketers
set specific goals and use metrics to find out
if they’ve reached them. You’re already familiar with some performance metrics like the number of impressions or
cost per click on paid ads. Another performance metric
is customer lifetime value, which refers to the
average revenue generated by customers over a
certain period of time. There’s also ROAS, or
return on ad spend. ROAS is how much revenue is gained versus
how much was spent. So if you spend $100 on an ad, but made $150 as a
result of that ad, the ROAS would be 150%. So for the cereal example, if you were to set a goal of
increasing overall revenue, ROAS might be one of the metrics
used to measure success. There are so many
ways to measure performance at every stage
of the marketing funnel, and those measurements
are critical because the average customer journey
takes about six touchpoints. That number has
doubled more than twice over a 15-year period. Performance marketing
lets us gauge how each of those touchpoints
contributes to our goals, which helps us reach and engage with customers more effectively. Time to review. Measuring results with
performance marketing is one of the most important things you
can do to ensure success. By tracking metrics like ROAS and customer lifetime value, digital marketers can
reach their goals and refine their
strategies over time. Up next, you’ll learn more about performance metrics and working with the data they produce.

Tutorial on Working with Data in Digital Marketing

Data is essential for success in digital marketing. By collecting, analyzing, and interpreting data, marketers can gain insights into customer behavior, measure the effectiveness of their campaigns, and make informed decisions about how to improve their marketing efforts.

Steps for Working with Data in Digital Marketing

1. Collect data. The first step in working with data is to collect it from a variety of sources. This could include website analytics, social media platforms, CRM software, and surveys.
2. Clean and organize data. Once you have collected data, you need to clean it and organize it so that it can be easily analyzed. This involves removing errors, inconsistencies, and duplicates from the data.
3. Analyze data. Once your data is clean and organized, you can begin to analyze it. This involves using statistical methods to identify trends and patterns in the data.
4. Interpret data. Once you have analyzed the data, you need to interpret it. This involves drawing conclusions from the data and identifying insights that can be used to improve marketing efforts.
5. Communicate findings. Once you have interpreted the data, you need to communicate your findings to others. This could involve creating reports, presentations, or dashboards.

Tips for Working with Data in Digital Marketing

• Use the right tools. There are a variety of tools available to help marketers work with data. Some common tools include Google Analytics, Microsoft Excel, and Tableau.
• Be aware of limitations. No data set is perfect. There will always be limitations to the data you collect. Be aware of these limitations when interpreting the data.
• Focus on the story. Data can be used to tell a story. When communicating your findings, focus on the story that the data tells.
• Be prepared to answer questions. When you present your findings, be prepared to answer questions from others. This will help ensure that your findings are understood and that they can be used to make informed decisions.

By following these steps, you can effectively work with data to improve your digital marketing efforts.

Examples of Data Analysis in Digital Marketing

• Identifying trends in website traffic. By analyzing website traffic data, marketers can identify trends in how visitors are finding their website. This information can be used to improve the website’s search engine optimization (SEO) and to create more targeted marketing campaigns.
• Measuring the effectiveness of social media campaigns. By analyzing social media data, marketers can measure the effectiveness of their social media campaigns. This information can be used to determine which types of content are resonating with audiences and to identify areas for improvement.
• Segmenting customers. By analyzing customer data, marketers can segment customers into different groups. This information can be used to create more targeted marketing campaigns.
• Predicting customer behavior. By analyzing customer data, marketers can predict customer behavior. This information can be used to personalize the customer experience.

Conclusion

Data is a valuable asset for digital marketers. By working with data, marketers can gain insights into customer behavior, measure the effectiveness of their campaigns, and make informed decisions about how to improve their marketing efforts.

What is data analytics?

Monitoring and evaluating data to gain actionable insights

Data analytics is the process of monitoring and evaluating data to gain actionable insights.

Performance marketing
generates a lot of data, from impressions and
clicks at the top of the funnel to conversion and
sales numbers at the bottom. Data is critical throughout the whole marketing
and sale cycle. Data is a collection of
facts or information. Your company’s total number
of social media followers, how many hours a team
spends on a project, or total year in revenue, all of those numbers are data. Marketing data can help
you answer questions in a concrete way by drawing on real customer behaviors
and interactions. The insights are useful
for planning campaigns, predicting future behaviors, and finding out whether
your activities are helping you reach your KPIs. You’ll recall that a KPI, or Key Performance Indicator, is a measurement used
to gauge how successful a business is in its effort to reach a business
or marketing goal. Your KPIs could be certain
metrics, like ROAS. But if you find that you
aren’t reaching your goals, you might need to prioritize
different KPIs instead. To know if you’re
meeting your KPIs, you’ll need to collect and
interpret the relevant data. The process of monitoring
and evaluating data to gain actionable insights,
is called data analytics. It’s one of the most important
skill sets you can develop for a career in digital
marketing or e-commerce. That doesn’t mean you need to be a statistics expert to
work in these fields. What it does mean is that
most entry level roles you’ll encounter involve
working with data in some way. Let’s go over a few
of the main data analytics responsibilities
you might have. Pulling, reporting,
and analyzing data. Data pulling is the process
of collecting data from analytics tools and putting it into a spreadsheet or database, making it easy to
access and work with. For example, you might have campaigns with similar
goals running on different platforms like
Facebook, Bing, and Google. To make it easier to compare
and analyze your data, you’ll need to bring
it all together. One way to do that is by pulling the data
from each source, and organizing it into
a spreadsheet. Data reporting, also called
performance reporting, involves organizing and
summarizing data to track performance across
marketing and sales efforts. This process makes it
easier to identify trends and spot unexpected
results more quickly. For example, if you’ve pulled
data from multiple sources, reporting makes it
easier to tell if one has a higher ROAS than another. Quality reporting
provides a clear picture of the raw numbers. It should help you
shape questions that can be answered
through analysis. Data analysis is the process of examining data in order
to draw conclusions, make predictions, and drive
informed decision-making. If reporting is the what, then analysis is the why. It helps you develop
insights that explain the reported results and make suggestions for next steps, like shifting your budget or
prioritizing different KPIs. You’ll learn lots more
about working with the data later in the program. But I hope you feel
like you’ve got a better understanding
of what data is and why it’s so important for marketing and sales success. Now, let’s recap. The data produced by
performance marketing is an incredibly
valuable resource for understanding how
well your strategy is meeting its goals. In an entry level role, you may find yourself pulling, reporting or analyzing
performance data. Through data analytics, you can find out if you’re
meeting your goals, anticipate customer behavior, and make plans for the future. Coming up, we’ll get
into some ways to interpret data and
present it to others.

Tutorial on Attribution Models for Digital Marketing

Attribution modeling is the process of assigning credit to different marketing channels and touchpoints for their role in a conversion. This can be a complex task, as there are often many different channels and touchpoints involved in the customer journey. However, attribution modeling is essential for understanding which marketing efforts are most effective and for allocating resources accordingly.

There are a number of different attribution models that can be used, each with its own strengths and weaknesses. Some of the most common attribution models include:

• Last-click attribution: This model assigns all the credit for a conversion to the last touchpoint that the customer interacted with before making a purchase. This is the simplest attribution model to implement, but it can be inaccurate, as it does not take into account the role of other touchpoints in the customer journey.
• First-click attribution: This model assigns all the credit for a conversion to the first touchpoint that the customer interacted with. This model is more accurate than last-click attribution, but it can overstate the importance of early touchpoints and understate the importance of later touchpoints.
• Linear attribution: This model assigns equal credit to all touchpoints in the customer journey. This model is more accurate than last-click or first-click attribution, but it can be difficult to implement.
• Time-decay attribution: This model assigns more credit to touchpoints that are closer to the conversion and less credit to touchpoints that are further away. This model is more accurate than linear attribution, but it can be even more difficult to implement.
• Data-driven attribution: This model uses machine learning to assign credit to different touchpoints based on their relative importance. This model is the most accurate attribution model, but it requires a large amount of data to be effective.

The best attribution model to use will depend on the specific needs of the business. For example, businesses that are just starting out may want to use a simple attribution model like last-click or first-click attribution. As businesses grow and have more data available, they can switch to more complex attribution models like time-decay attribution or data-driven attribution.

Here are some tips for implementing attribution modeling in your digital marketing campaigns:

1. Choose the right attribution model for your business. Consider your business goals and the amount of data you have available when choosing an attribution model.
2. Set up tracking in your analytics platform. This will allow you to track the different touchpoints that customers interact with before making a purchase.
3. Analyze your attribution data. Once you have tracking in place, you can start to analyze your attribution data to see which marketing efforts are most effective.
4. Use your attribution data to optimize your campaigns. Once you know which marketing efforts are most effective, you can allocate your resources accordingly.

Attribution modeling can be a complex topic, but it is an essential part of digital marketing. By understanding and using attribution modeling, businesses can improve the performance of their marketing campaigns and maximize their ROI.

All right. You’ve set your strategy,
picked your channels, planned your content, and
measured your results. Now what? You know all that data should
tell you which channels and content are performing well. But what does good
performance actually mean? Is it when an ad gets a lot of clicks? When a Tweet goes viral? What about increased website traffic? With so many different touchpoints and
channels shaping customer brand interactions, how do you
know where to start? In this video, we’ll explore how
businesses use reporting data to find out which of their marketing and
sales efforts are the most successful. Success can mean different things
depending on your particular marketing and business goals. But every digital marketer wants to know
which touchpoints are getting customers to take action. Say you’re running a campaign for
a company that sells art supplies. If tons of people are clicking on
an ad for a new line of paints but only a few of them
eventually make a purchase, that ad might not be so
successful after all. In order to optimize a strategy, you need to know which touchpoints are
influencing customer decisions the most. Of course you can’t know exactly
what your customers are thinking. All you have to go on is what they do. But those customer behaviors can tell
you a lot about where your efforts are succeeding and
where they’re falling short. The process of determining which content
and channels are responsible for generating leads, conversions, or
sign-ups is called attribution. This isn’t something you need
to determine on your own. Most analytics tools include features
that can use your data to find out which touchpoints and keywords customers
interact with before taking action. You’ll get some practice with
these tools later in the program. By accurately attributing success to
specific marketing and sales efforts, businesses can make informed decisions
about where to invest their time, budget, and resources. Now, some people assume that the last
touchpoint should get all the credit, and it makes sense, right? People often think that the touchpoint
right before a purchase must be the one that convinces a customer to take action. But that isn’t always the case. You know that the average customer
encounters six touchpoints on their purchase journey, and that the path
isn’t always straightforward. Say someone is shopping for a new computer,
and they decide which model to buy after the second touchpoint but then they
put off actually making the purchase. Maybe they’re waiting for a holiday or
for the computer to go on sale. Maybe they just get distracted. It might take another touchpoint to remind
them of the purchase they already planned to make. Both of those touchpoints deserve some
credit, and attribution is how they get it. Businesses have some choices when
it comes to attribution models. We won’t go over all of them here— just a few to give you a sense
of how they attribute success: data-driven, first click,
last click, and linear. Data-driven attribution measures customer
engagement with marketing content across channels to understand what’s
motivating them to take action. It assigns credit to each touchpoint
based on statistics like which ads or keywords most often lead to conversions. Data-driven attribution draws on real
customer behaviors to assign credit. But if you don’t have enough
meaningful data for this model, they have other options. Here are a few examples: First click attribution assigns all
the credit to the first touchpoint that eventually leads to a conversion. Let’s go back to our art supply store. If a customer’s first interaction with
the brand is a social media ad for oil paints, all the credit for their
purchase will go to that ad, even if it takes a few more touchpoints for
them to buy something. Last click attribution
assigns all the credit to the last known touchpoint
before conversion. If our art store customer makes a purchase
after the fourth or fifth touchpoint—maybe a promotional email—last click attribution
would give full credit to that email. Linear attribution assigns equal credit
to each touchpoint along the customer journey. So for our art store customer’s journey,
the social ad, promotional email, and all the touchpoints in between share
credit for the eventual conversion. Attribution isn’t an exact science, but
it can give you a better idea of how customers are interacting
with your content and what’s leading them to take action. Using models like data-driven, first click, last click, and linear attribution,
businesses can put their resources in places that will maximize
customer conversions. Up next, you’ll learn about communicating the
insights you get from your data insights to other people.

Data storytelling basics in Digital marketing

Data storytelling is the practice of using data to tell a story that is both informative and engaging. It is a powerful tool for digital marketers, as it can be used to communicate insights, persuade stakeholders, and drive results.

Why is data storytelling important in digital marketing?

Data storytelling is important in digital marketing because it allows marketers to communicate their findings in a way that is both clear and compelling. By using data to tell a story, marketers can make their insights more memorable and actionable.

How to create effective data stories

There are a few key things to keep in mind when creating effective data stories:

1. Start with a clear question. What do you want your audience to learn from your story? Once you know your question, you can start to gather the data you need to answer it.
2. Choose the right data. Not all data is created equal. When choosing data for your story, make sure it is relevant to your question and that it will be easy for your audience to understand.
3. Create a compelling narrative. Your story should have a clear beginning, middle, and end. It should also be engaging and easy to follow. Use data to support your narrative, but don’t let the data overwhelm your audience.
4. Use visuals. Visuals can help to make your story more engaging and easier to understand. Use charts, graphs, and other visuals to communicate your findings in a clear and concise way.

Here is an example of a data story in digital marketing:

Question: What is the most effective way to reach our target audience on social media?

Data: We analyzed our social media data and found that our target audience is most active on Facebook and Instagram. We also found that they are more likely to engage with content that is visually appealing and informative.

Narrative: Our target audience is most active on Facebook and Instagram, so we should focus our social media efforts on these platforms. We should also create content that is visually appealing and informative.

Visual: A bar chart showing the number of active users on each social media platform.

This data story is effective because it is clear, concise, and actionable. It also uses visuals to help communicate the findings in a way that is easy to understand.

Tips for using data storytelling in digital marketing

Here are a few tips for using data storytelling in digital marketing:

• Use data storytelling to communicate your findings to stakeholders. This can help to get buy-in for new initiatives and improve your chances of success.
• Use data storytelling to persuade potential customers. By telling a story about your data, you can make your brand more relatable and trustworthy.
• Use data storytelling to drive results. For example, you can use data storytelling to create more effective marketing campaigns or to improve your customer service.

Data storytelling is a powerful tool that can be used to achieve a variety of goals in digital marketing. By following the tips above, you can create effective data stories that will help you to communicate your findings, persuade your audience, and drive results.

What are the three main components of a data story? Select three.

Data, A compelling narrative, Clear visualizations

The three main components of a data story are: the data itself, a compelling narrative, and clear visualizations.

Working with data isn’t
just about the numbers. You know that the process of data pulling,
reporting, analysis, and attribution, produces valuable insights that can change
the course of a project or strategy. But how do you turn those
insights into action? How do you persuade key people
that something needs to be done, by using your data to tell a story. Without a story, data is just numbers. Those numbers can tell you what happened,
but they can’t tell you why it happened, why it’s important, and
what you can do about it. That’s where data storytelling comes in. Data storytelling is the practice of
conveying data insights to a specific audience using a clear and
compelling narrative. Data has a lot of stories to tell, and no
two people will tell exactly the same one. Everyone brings their own perspectives,
experiences, and biases to data storytelling. And you’ll find out about navigating
some of those challenges in a bit. For now, let’s think about how
to create stories with data. A data story has three main components,
the data itself, a compelling narrative, and clear visualizations. Together, these pieces should engage your
audience by explaining what you learned, and how you can use that
information to take action. Let’s take them one at a time. First, data. Think of your data
points like the characters in a play. If they’re all on stage at once, it can be hard to know where
to focus your attention. So you need to be selective about
which numbers you highlight. The most important data points are your
lead characters, while others could play supporting roles, and some may
not need to be in the scene at all. To decide which data points are important, it’s crucial to understand
the questions you’re trying to answer. For example, maybe you work for a toy company that’s measuring the results
of a new social media campaign. Your question could be as simple as
asking whether this new campaign is more efficient than the last one. For that question, your main data
point might be return on ad spend. But remember, you need to understand the question you
want to answer to know what data to use. Being clear about your questions and the
data you can use to answer them is also the first step in planning your next
piece of your data story, the narrative. The narrative is like the plot of a play,
it’s what happens in the story. A well-structured narrative is engaging,
memorable and persuasive. Once you’ve picked the data points and
insights that answer your questions, you can start building a narrative
that conveys them effectively. In the toy company example you’d explain
how the ROAS data you’ve gathered compares to the previous campaign and how those
results can impact your future efforts. In other words, your data story should
explain not just what your insights mean, but why they matter to your audience and
what they can do about them. That doesn’t mean you need
to have all the answers. In fact, some of the best stories
create space for discussion. But appealing to your audience with
a strong narrative can draw attention to your insights and
encourage others to take action. You’ll learn more about how to create
an effective narrative in just a bit. Now that we’ve explored
a simple narrative structure, let’s get into the last element of
data storytelling: visualizations. Data visualizations are graphic
representations of data that convey information. Data visualizations are like the costumes,
lightings, and stage set of a play. They focus attention and help the audience understand
what’s happening in the narrative. Visualizations can take the form of
charts, graphs, infographics, or other illustrations. A well-placed visualization
clarifies trends and expresses relationships
between data points. Returning to the toy
company example again, we could choose to represent the ROAS
data as a series of numbers. But if what we want to do is compare
the current campaign to the last one, it’s a lot clearer to convey that
relationship with a bar graph. It gets the point across quickly and
clearly. You’ll learn more about
visualizing data and making presentations accessible to
different audiences in a later course. Data storytelling is a powerful tool,
and one that’s in high demand for digital marketing and e-commerce roles. Using data, narrative, and
visualizations, we can engage audiences, communicate insights, and
influence big decisions. Up next, we’ll explore more about
how to structure data stories.

Hi again. Remember me? My name’s Erica and I’m a people consultant at Google, known
elsewhere as an HR business partner. The last time we were together,
you had just started this course and now here you are, almost at the end. Congrats on your progress so far and on taking meaningful
action to advance your career. Now that you’re wrapping
up the first course, I wanted to let you know about some of
the great career building activities and resources you’ll encounter
in the rest of this program. In the next course and those that come
after it, you’ll have the chance to complete a number of hands on activities
based on real world marketing and e-commerce scenarios. They’ll let you put what you’re
learning into practice and help you discuss your skills with
hiring managers in a concrete way. Be sure to save your work
from these activities. They’ll be useful to you as you near
the end of the program and start thinking about the next stage of your digital
marketing or e-commerce career. When you get to the last
course in the program, we’ll go in depth on preparing for
a job search. We’ll cover how to find and
apply for jobs that interest you. I’ll also share some tips to help you
prepare for the interview process, so you’ll know what to expect going in. You’ll learn how to put together an online
portfolio that will help you demonstrate your knowledge and experience. You’ll also complete a scenario based
project, from beginning to end, that you can put in your portfolio and use to present your thought
process to potential employers. Just like a customer journey,
your career journey will be unique to you. But whatever path you choose, the knowledge and resources you gain from
this program will give you a strong start. You’ve accomplished so much already and
there’s so much more to come. Good luck on the next
part of your journey. I’m excited to meet up
with you again soon.

[MUSIC]
Hi, my name is Elle, and I’m the Vice President of the Mastery Team. My role is to support Google’s
business organization with great learning experiences. One of my core values is curiosity, and my favorite part of my job is that I
get to support the curiosity of our entire business organization with great learning
experiences that help people learn, grow, and develop and bring their
whole selves to work every day. You have moments through this program and throughout your journey when
you don’t feel confident, and confidence is so important. I’m going to tell you a story about
a moment that I lacked confidence and what I did to pick myself up. It was about ten years into my career, and
I was sadly let go from my job. I was devastated. I completely lacked confidence, and I had no idea how I was going to
pick myself up and find my next job. And so I went to a quote that I often
think about in moments like this. And that quote is: “It’s
not about how you fall. It’s how you get back up that counts.” And I surrounded myself with a support
system to help me rebuild my confidence. And there are two types of people that
I highly recommend that you surround yourself with. The first is a cheerleader. This is a person that completely believes
in you because they’ve seen that you have capabilities and that you could do this. They hold up a mirror, and they describe
to you moments that they’ve seen evidence of you displaying these capabilities. If you’re not clear where you could
find your biggest cheerleader, that person can be anyone in your
life that has experience and exposure to you in all
aspects of your life. A quick example is my sister. For me, my sister was
reentering the workforce, and I had an opportunity to support her and
cheer her on as she looked for whether or not she had the skills to apply for a job. And I reminded her of all of the moments
that she displayed key skills that would set her up for success in that job. All right, the second person that you can surround
yourself with is a practice partner. So, find a practice partner—somebody
that can hold you accountable and support you as you practice. That can come from this program.That can
come from any aspect of your life, as well. All right, so as you think about embarking
on this program, two things: Find yourself your biggest cheerleader, and
find yourself your practice buddy. Because there will be times
where your confidence is shaken, and confidence will be so important. I didn’t enter the marketing or e-commerce
world until about midway through my career when I was
choosing to make a pivot. And this certificate program
didn’t exist back then, but I wish it did. I’ll give you a couple of tips about how I
started to learn more about the marketing and e-commerce space. The first thing I did was I
created a search campaign. A friend of mine was selling her condo, and so I created a campaign that
really helped promote her condo, and I learned a lot about search
marketing through that experience. The second thing I did was I decided
to learn more about websites and decided to create a blog. And something I’m really
passionate about is yoga. So I created a blog all
about my yoga journey, and then I applied analytics to the blog
and started to see who was accessing and reading my blog and saw people from India, all parts of Asia, that were accessing and
reading this, and it was so much fun to learn through
doing in both of those experiences. And so my tip for you: Engage with the hands-on practice
experiences through this program, and potentially, experiences that you might
have access to outside of this program. But the main point is that we
learn the most through doing, so find opportunities to practice. There will be people in your
life that may try to define for you who you are and
what your career should be. Some may even put doubt in your mind that
you could complete this certificate and potentially create and/or
pivot your own career. And I’m here to tell you,
step back, trust your gut, and believe that you can define who
you are and who you want to be.

You did it. You’re
almost done with this section in the whole
first course in the program. Before we wrap it up, let’s recap what you’ve learned in this part of the course. First, you found out about the importance of data and how performance marketing
can help businesses succeed at every stage
of the marketing funnel. You heard all about
collecting, organizing, and interpreting
data in order to reach marketing and sales goals. You discovered how
businesses use attribution models
to find out which touchpoints are most effective at getting customers
to take action. You also learned
about the power of storytelling and how
conveying insights through stories can
help businesses make informed,
data-driven decisions. Finally, you explored some skills that
can help you adapt to change when you really
need to adjust your course. You’re so close to the end now and I know you’ll
finish strong. Just a little bit further
and you’ll be on your way.

Congratulations on
completing the first course. You’ve come so far and
learned so much about what I personally think is
a really exciting industry. Before you move on,
let’s take a minute to celebrate and reflect on all you’ve learned
in this course. You started out with the basics: exploring what digital
marketing and e-commerce are in a few of the many
different roles and opportunities you might
find in these fields. Next, you learned about how customer journey maps
and marketing funnels can help a business reach their target audience and turn
them into loyal customers. Then you examined what goes into creating a digital
marketing strategy, how to use digital channels
for brand-building, building relationships,
and driving sales. Finally, you explored how
measuring and interpreting performance data can improve a campaign in progress and
help you plan for the future. I hope you’re proud of the
work you’ve done so far. No matter what you end up doing, whether you’re a digital
marketing coordinator or an e-commerce analyst, a social media manager
or something else. Everything you’ve
learned up till now will lay the foundation for the next phase of your career. And as you
move through this program, you’ll have the chance to hone
your skills even further. In the next course, you’ll learn from my
fellow Googler, AK, about how to attract and
engage customers using SEO, SEM, and display ads. You have some great
instructors coming up in this program and I can’t
wait for you to meet them. I’m so glad I got to be here for the beginning
of your journey. You’re off to a great start. I hope I’ve helped you
gain the knowledge and confidence you need
to move your career forward and recognize
the skills you already have that can make you a great marketing or
e-commerce specialist.