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Telling stories is practically in our genetic code. It’s so inherent to our identity as humans that we’ve been doing since the Paleolithic Age, when the early Neanderthals used pigment to draw on walls.
We’ve come a long way since these crude finger paintings. Now, we can even tell stories with numbers and complex data.
Data storytelling is the process of conveying what’s happening behind all your numerical and non-numerical data.
It’s the method of presenting your analysis findings in a way that is easy for all parties to understand.
After all, visuals are the easiest and fastest medium for human comprehension.
Thanks to the continued prevalence and importance of big data in modern companies, data storytelling is a crucial skill.
Yet, when data is exceedingly complex (which it often is in PPC management), properly telling the narrative of your numbers is a challenge.
This discussion will look at data story examples and how you can use the same techniques to uncover compelling stories in your own PPC data.
There are many cases where you need to present PPC data to other parties. These parties include:
You need them to understand the insights behind the data, not the numbers themselves.
In other words, your client doesn’t care that their ads have generated 100 clicks this month. They care about why this matters and how it impacts their marketing goals and bottom line.
Data storytelling is the best way to communicate these insights, especially to parties that may not be as familiar with PPC metrics and analysis as you are.
If you can’t effectively communicate your insights, they are practically worthless.
With data stories, you can replace thousands of words in explanations with a single chart.
This saves time, improves communication in your organization and guarantees that everyone is on the same page.
Data storytelling is not a simple case of charting out the numbers and creating a report on the findings.
A great data story example visualizes the information so that even someone with no background knowledge can look at the chart and understand what’s being displayed.
You want the audience to reach the same conclusions that you do when they view your visualization.
You need the correct chart that expresses the data, the context of that data and what’s significant about it.
It’s a three-step process.
Before you can begin telling your data story, you must first perform a thorough and accurate analysis.
Data science is the field of expertise that deals with extracting knowledge and insight from raw data and making it accessible. Data scientists collect, clean and analyze data to find these insights.
In the business world, the need for business professionals to also be data scientists is crucial. This combination means you have the ability to extract insights and the experience and know-how to understand the opportunities hidden in the data.
Once you’ve uncovered opportunities or risks in the data, you need a means to depict those findings visually.
The problem is that tables and spreadsheets are not very engaging or easy to understand. You have to work line-by-line, comparing different values, to get what’s being shown.
It’s a tedious and challenging process that is far from efficient. Plus, it’s easy to make mistakes when only looking at a data table.
Visualization is the process of transforming your data rows and columns into easy-to-understand charts and other visuals.
This allows you to physically see the data and how it unfolds. This is the beginning of your data story!
Your typical data visualizations have limitations. They only provide an at-glance snapshot of the data, but fail to offer the crucial context needed for audiences to get the big picture.
This is where the narrative part of data storytelling comes into play.
The narrative uses language and other contextual clues to offer the necessary background that viewers need to understand the story.
You can achieve this narrative side in data visualization through titles, labels, colors and other formatting decisions. Even the chart type you choose can be the difference between a good and a bad data story example.
The ability to communicate data results effectively through data stories plays many critical roles in an organization.
Remember, your PPC marketing strategy is not on its own island. It’s part of a broader digital marketing strategy.
As you’re managing your campaigns, you may identify key changes to customer behaviors and attitudes. These findings can serve other areas of your marketing strategy.
That said, you need the ability to convey these insights to others properly. Otherwise, your best findings only improve a small part of the marketing strategy, instead of the entire company’s strategy.
When you can deliver these insights to audiences outside your team, they have verified marketing insights on how to serve customers best. This puts a stop to the practice of throwing ideas and strategies at the wall until something sticks.
The other vital role that PPC data stories play in digital marketing is in budgeting decisions.
If you want management to invest more money into your PPC marketing strategies, you need to show them the data. Without numbers and evidence, it’s hard to instill the confidence that these stakeholders need to make this budgeting decision.
However, raw data alone can be dull and lack the punch you need to get your point across. You don’t want to give a number-rich sales pitch.
You want to show the story of your campaigns and what impact they’ve had on the company.
As a PPC manager, your primary focus is managing your various campaigns. This means analyzing the data and looking for current risks and opportunities.
This is the data science part of crafting visual stories for your insights.
Once you identify these noteworthy changes, you can move on to visualization and narrative stages.
The problem is that monitoring and playing with your data to find these changes is incredibly time-consuming. This tedious process is why many advertisers rely on tools to help wrangle their data.
Google Ads Dashboard: Many PPC managers rely exclusively on the Google Ads dashboard to manage their data. There are multiple reports and other tools that you can use to monitor your campaigns.
Excel or Google Sheets: Collecting and organizing data into a spreadsheet via Microsoft Excel or Google Sheets is crucial in creating data stories. Data needs to be arranged in a spreadsheet before you can visualize it. You can export data from your Google Ads account directly into one of these spreadsheet programs.
PPC Signal: While the Google Ads dashboard has some basic features and tools, marketers often need more. PPC Signal is a management tool offered by PPCexpo. It uses AI and machine learning technologies to automatically monitor your Google Ads account for meaningful changes. With this automated system, you don’t have to spend countless hours uncovering the signs of data stories yourself. PPC Signal does it for you.
The next section will take an in depth look at how PPC Signal works and its benefits to advertisers.
As a PPC manager, you need to know what is happening in your campaigns and why these changes are occurring. Only then can you determine which changes are significant.
Once you’ve recognized a valuable insight, you have the beginnings of a data story. However, you still need to add context behind the numbers. This will allow audiences to grasp the information easily.
To accomplish this you need a few things:
The following steps will help you track, uncover and deliver data stories, while accomplishing all of these goals.
Anything unusual that happens in your campaign should be highlighted.
Yet, your campaigns produce a constant stream of data. Every time a prospective customer interacts with your ads, it generates meaningful data points.
This is why having an automated tool like PPC Signal is such a game-changer. You can’t always be there to monitor your campaigns. After all, you need to sleep, eat and take care of other marketing responsibilities.
PPC Signal is always on, which makes it perfect for finding the starts of your data stories.
Every change that PPC Signal identifies is shown on the tool’s dashboard. It’s like having a list of recent data stories ready to be told!
With PPC Signal automatically presenting you with data stories, you can jump right into the next step. At this stage, you need to highlight the essential parts of your tale.
When you’re writing a narrative story, you start by outlining the who, what, where, when, why and how. You can approach telling your data story example in a similar fashion. PPC Signal can help.
Let’s look at a single alert in PPC Signal. Immediately, the “who” and “what” questions are answered.
“Cost per Conversion is moving upwards…” is the foundation of the story. You know what’s being affected and the direction it’s traveling.
Cost per conversion is a crucial factor in budget utilization. If it is moving upwards, it presents a potential risk. You’re spending more for each conversion than usual. The text is highlighted red to signify the negative aspect of this change.
Next, you want to answer the “when” question. Again, the way that PPC Signal presents each change in your account comes in handy.
Why is knowing the beginning of your data story important? You need to know how many days your campaigns have been affected by this change, whether it is positive or negative.
Ideally, you want to detect changes as early as possible. If it is a negative change, this gives you plenty of time to adjust and mitigate the potential risk. On the other hand, catching a positive change early allows you to maximize the potential value of the opportunity.
You know what’s being affected and when it starts, but how significant is the change? PPC Signal also includes this part of your data story.
The “how” is a really crucial question to answer because it’s where a lot of the numerical data enters the story. You get to see the current status of the metric in question and where it was in the past.
In the above example, the current cost per conversion value is $798.30 – a whopping 1,285.9% increase from where it was in the past.
This is a massive and costly change that needs immediate attention. You’re currently paying almost $800 for every conversion, when you used to be paying only $57!
With the help of PPC Signal, you’ve answered the who, what, when and how. Now, you’ll locate where in your account this change is taking place.
At the bottom of each signal before trend line, you can see the campaign affected, as well as the device type. If the change involves a specific ad group, keyword, location, time or another dimension, it will be displayed in this space.
This makes it exceptionally easy to see the exact parts of your account that are impacted.
Now that you have all the basics covered, you can dig deeper into your story by clicking the Explore button.
As you explore each signal further, you’ll reveal more details about your data story. This is how you start to form the “why,” which is the hardest question to answer.
The Explore page shows you a zoomed-in view of the change with a more detailed chart.
This view allows you to see how the data has changed day-to-day and by how much. You can also add other metrics to the chart.
By adding different metrics, you can start to develop that crucial context.
In the example above, you can see that your number of conversions is lower than normal.
This could be a big clue as to why this change has occurred. Next, you could add clicks to the chart to see another angle.
Now you can see that clicks have stayed relatively the same, even increasing slightly. Yet, with conversions continuing to fall off, you’re paying for more clicks for each conversion. This is contributing to the high cost per conversion problem.
Thus, you can surmise that something is going wrong after audiences click. This could be a problem with your landing page, site speed or something else.
You can then turn to your Google Analytics data for further understanding.
If you’d rather see a tabular view of the data, you can click the icon in the upper left corner.
The data in question is red to make it easy to focus on the correct period of time.
You can easily export this data to your spreadsheet or another program for further analysis or visualization.
Now that you’ve used PPC Signal to uncover your data story, it’s time to visualize the information.
The trend that appears in PPC Signal is helpful, but there may be better ways to depict the data visually.
When you export your data into Google Sheets or Microsoft Excel, you have some additional charting options.
Yet, even these options are lacking, especially when it comes to visualizing PPC data.
Ideally, you want the most visualization options possible. The more charts you have in your arsenal, the easier it will be to find the perfect way to visualize your data story.
The ChartExpo tool for Google Sheets or Microsoft Excel adds around 90 additional charts to your library. These added options make it much easier to visualize your data story example in the best way possible.
How to install ChartExpo depends on whether you’re downloading it for Excel or Sheets.
Google Sheets: You can visit the Google Workspace Marketplace and enter “ChartExpo” into the search bar. After downloading the tool, you can access it in Google Sheets by clicking Add-ons in the top toolbar.
Microsoft Excel: To use ChartExpo with Microsoft Excel, visit their AppSource page and search for the tool. Once you’ve found it, download the add-in. The next time you access Excel, you can find the tool under the My Apps button.
Once you’ve successfully loaded the tool into your spreadsheet program, it is easy to use. Upon accessing ChartExpo, you’ll be given the option to create a new chart.
Then, you can select from a variety of different charting categories. Alternatively, you can use the search bar to look up the exact chart type you want.
With ChartExpo, you can try out a number of different visualizations and see which one best tells your data story.
Thanks to the expansive library of charts, you have lots of options to present your data. Here are some tips to help you narrow down your options and find that perfect visualization.
Know Your Audience: Who is the audience for your data story? This will impact how much contextual information you need to include.
For example, if you’re presenting insights to a fellow marketer, you don’t need to include basic knowledge about each metric because they already have this information.
Other audiences, on the other hand, may have zero understanding of PPC metrics. They need a lot more context. You may even have to present multiple visualizations to tell your data story effectively!
Predict And Answer Their Questions: Part of knowing your audience is predicting what their biggest concerns are.
For instance, if you’re managing a PPC account for a client, they probably don’t need to see data at the ad group or keyword level. However, a fellow marketer working on SEO would absolutely value keyword data.
One of the best ways to know what matters most to the audience is to ask. Every person is different. You may have a client that does want to see data at a very granular level.
If you don’t have the chance to ask, do your best to put yourself in their shoes. What questions would you want to know in their position?
Less Is More: When creating a visualization, you should have a specific narrative that you want to convey to audiences. Every detail and piece of your chart should be focused on explaining this narrative.
While there may be other exciting insights you want to share, adding too much in one chart will distract from this primary purpose.
You can always include additional charts in future reports!
Thanks to PPC Signal and ChartExpo, you quickly and easily arrive at the final stage of data storytelling: narrative.
The narrative is where you combine data science and visualization with creativity and storytelling. It requires you to know your audience and know what data is most crucial to present.
There is no tool or recipe to success at this stage. You have to rely on your expertise as a PPC manager to deliver the insights in the best possible way.
The good news is that with PPC Signal delivering fully-vetted data signals and ChartExpo offering a wide range of visualization options, you have two giant pieces to the puzzle.
When your data story gets off to the right beginning, the ending falls into place.
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