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Data is one of your company’s most valuable resources, but only if you know how to connect it to tangible business value.
To do this, you need to utilize analytics techniques that transform your raw data into actionable insights on improving your strategies.
What’s the difference between data and insight? We’ll answer that question and many more as we look at data analytics examples in business.
We’ll start by looking at some of the basics of data analytics. Then, we’ll move into the benefits of data analytics and how you can make the most of your PPC campaign metrics.
Let’s get started.
Before we start looking at specific data analytics examples, we need to first define a few terms. These definitions will help you understand the later parts of this discussion.
The terms include:
You should be familiar with all of these terms. However, they may have slightly different definitions in the marketing analytics space.
Data is the raw numbers, stats, metrics and other information that your business creates and collects. It can be quantitative or qualitative.
Quantitative data expresses a quantity. For example, if your ad receives 100 clicks, that’s an example of quantitative data.
Qualitative data is used to measure a quality or characteristic. If you’re analyzing customer feedback, you may look for qualitative words that describe the experience, such as great, good, bad or terrible.
In some cases, data can be both qualitative and quantitative. Quality Scores, for instance, can be measured on a scale of 1-10 or as below average, average or above-average.
Raw data on its own is useless. If you have 100 clicks, so what?
Is it more or fewer clicks than you’ve experienced in previous months?
What was the cost of those clicks?
How many conversions did those clicks generate?
What’s the business value of those conversions?
Which keywords created the majority of these clicks?
The questions go on and on.
What raw data lacks is insight. This is the context that helps you understand the role the data plays in understanding the bigger picture. In other words, context tells you what the point of the data is.
Insight and context are created by linking raw data together. The more information you can correctly link, the deeper the context and the more actionable the insight.
For instance, if you take that initial data of 100 clicks and then add clicks from past months, you can effectively determine if 100 clicks are normal, above average or below average.
Then, you can connect additional data, like CPC, conversions etc. to begin answering the above list of questions.
As you compile more and more insights, it becomes knowledge. Knowledge is the culmination of all of your information. It’s your collective understanding of the “big picture.”
The more you know about what’s happening behind your raw data, the easier it is to make accurate decisions and apply your knowledge to any situation. If you become able to understand the difference between data vs. information vs. knowledge then you will be become good decision maker.
Decisions and actions guided by data are far more accurate and impactful than ones made based on opinions or assumptions.
You don’t want to guess what the best route to take is. You want to know.
Before you can become knowledgeable, you need to follow this process of turning data into insight.
You also need the proper framework and company culture that knows how to translate data analytics examples in your business into action.
Not all data will lead to insight and knowledge. Businesses have to be strategic with what data they gather.
Mainly, you have to think about where that data is coming from. You don’t want to establish your knowledge or decisions on data from unverified sources.
This section will look at the various characteristics that good data possesses.
As you’re collecting data, you have to think about what information you need to move towards insight.
Context is typically created through comparison and benchmarking. For example, if your company created 1,500 leads this month, it’s a good performance if you normally produce around 1,350.
That said, you need to look at multiple angles when developing PPC campaign context. What’s the reason for this uptick in performance?
Without developing enough context, your insights will create more questions than action. So, focus on data that add helpful details and context to your analysis.
Every business has unique goals and objectives. This means that a valuable insight for another company may not be relevant or useful for yours.
This is one of the challenges of data analytics in business. You’re producing heaps of data all the time, but only some of it is actually relevant.
Some teams spend more time separating relevant from irrelevant data than actually analyzing the information to extract insights and obtain knowledge.
You have to think about your goals and what data and information relate to those objectives.
Time is money when it comes to data analytics examples. You want to detect and use insights as swiftly as possible.
If your insights aren’t timely, they may be too old and stale to still be actionable. You don’t want to make decisions based on outdated knowledge.
This is especially true in PPC marketing because your strategies are regularly influenced by user behaviors, competitor strategies, changes to the ad platform and more.
To grasp the current status of your strategies, you want to use the latest data.
Insights should be specific and detailed. When you have specific details, the information becomes more actionable.
Conversely, when your insights lack sufficient details, it’s harder to choose the appropriate reaction. You don’t have the full picture yet!
If you don’t have the knowledge to understand why something happened and how to respond appropriately, the data isn’t actionable. This also means the data isn’t specific enough.
You need to dig deeper in your analysis!
Insights aim to make your data more accessible and easier to understand. Thus, the advertising insight itself should be clear.
It needs to be immediately apparent why the insight is important and how you can use it to improve your business strategies.
Remember, you may have to present your data analytics results to others, like managers, clients or stakeholders. They may not be as familiar with the data as you are, which means you have to work extra hard to ensure that the insights are understood.
You don’t want poor communication or unclear data to prevent your business from taking the correct action!
Converting data to insight and knowledge is an arduous process. There are plenty of data analytics examples in business that ended in strife instead of success.
Is it worth to analyze your data in business? Absolutely!
When you can effectively transform raw metrics into actionable insights, it unlocks many significant benefits.
As we’ve established, data-born knowledge helps you make better decisions.
Through data analysis, you can develop indisputable evidence to choose the right path to take consistently.
You no longer have to rely on past experiences, assumptions or unverified observations. This improves the accuracy and agility of your decisions.
Again, timing is crucial in PPC marketing. It doesn’t help to have the latest data available if you can’t act on it right away.
In short, data analytics in business helps you make informed decisions in less time.
With data informing your decisions and consistently leading you down the right path, you effectively stop the guessing game prevalent in many businesses.
You’ll make decisions with greater accuracy and more confidence than relying only on intuitions and guesswork – no more stressing over making the right selection.
This makes it easy to overcome competitors that are still letting gut feelings and assumptions guide their decision-making processes.
Plus, you eliminate the unknowns. Whenever you make a decision based on guesswork, you don’t 100% know the outcome. On the other hand, data-driven strategies have ample evidence to predict the results of the decision.
The data-driven decision-making approach also makes it easier to rationalize your choices for clients and stakeholders. You have concrete evidence backing up every move you make!
Data analysis for marketing can help you detect early warning signs of problems, turning your data streams into a crisis warning system.
The sooner you spot potential issues, the easier it is to mitigate risks before molehills become mountains.
By consistently monitoring your data and swiftly detecting these issues, you transform into a proactive marketer rather than a reactive one.
This approach allows you to eliminate potential risks long before they cause significant damage.
It’s an excellent method for quality monitoring that helps you create better offerings, whether in marketing materials or products.
Data analytics examples in business don’t just detect problems. Analytics also informs you why the issues started and how to correct it.
By studying the relationships between different data sets, you can track how one change impacts your other strategies, departments, systems, etc.
This is particularly common in PPC marketing. You have multiple metrics that share close correlations. One minor change to a campaign may unexpectedly impact your entire account.
With proper data analysis techniques, you’ll gain a complete view of how each potential risk impacts your business.
You don’t have to wait to find the answer to your problems. It’s right there in your data!
Your business data is vast. As mentioned, not all of it is useful to you and your organization’s goals.
Thanks to data filtering, you can set irrelevant data aside and focus on the most critical information.
This enables you to achieve the results you want. If your business doesn’t find value in tracking impression share %, you don’t have to.
It’s your data!
Once you can remove the noise (i.e., irrelevant data sets) from the equation, you can focus entirely on the most vital insights.
As you engage with your data more and more, you begin to develop a deep understanding of what works and what doesn’t. You’ll identify what you’re doing well and what areas still need improvement.
This is at the core of why data analytics examples in business exist.
Once you know your biggest winners (and the worst losers), you can optimize your time, energy and other resources accordingly.
You’ll be able to pause strategies that are underperforming and wasting your ad budget, while simultaneously capitalizing on the tactics that net you the most returns.
The same is true of your products and services. Data analytics shows you what items, features, offers and other details that customers care about most. These insights will improve your overall marketing success.
While data analytics examples allow you to zoom in on the individual tactics that are working or not working, it also enables you to view a more complete “big picture.”
With this overhead view, you can measure the success of your advertising campaigns. You’ll set better goals, establish solid benchmarks, understand your performance standards and more.
Having a complete view of your business makes it easy to deliver a cohesive experience to customers, even when several different departments or teams are involved.
Data will show you the correlations between each team’s efforts and how they impact one another. This knowledge will help you produce an overall more efficient and efficacious company.
No matter what data analytics example you look at, the value and benefits of developing a data-driven approach are evident.
The problem is how do you make data analytics in PPC more efficient. Is there a way to steadily and swiftly turn raw data into insight?
Yes! The answer is PPC Signal.
PPC Signal is a tool that leverages the power of artificial intelligence and machine learning to simplify the data analysis process.
The PPC Signal system automatically monitors your PPC account data and finds substantial changes in performance. The tool presents each significant change as a signal.
Essentially, PPC Signal alerts you every time one of your PPC elements behaves abnormally, whether it’s performing better than average or worse.
Each active signal is a complete insight waiting to be explored and resolved.
It is one of the best PPC optimization tools at blending human action with machine automation. The AI collects and analyzes your data, leaving you to decide which signals to investigate and how to resolve each one.
The gap between raw data and insight has grown significantly in the big data era. Businesses now produce unfathomable amounts of information that needs to be analyzed promptly.
Again, time is a crucial factor. The longer you wait, the less actionable the data and insights become.
Thanks to PPC Signal, you can seize all of the data analytics benefits in only part of the time. The system takes care of the most time-consuming and headache-inducing tasks.
This leaves all of your time and attention for the analysis steps that actually matter: making meaningful changes to your strategies based on insights extracted from PPC data.
Relevance is one of the most troubling data challenges. There are examples of data analytics in business where substantial filtering is required to remove irrelevant data. Sometimes, this results in only a simple insight.
That’s a lot of work for very little reward.
PPC Signal alleviates this hassle by automatically delivering daily insights about your ad campaigns’ performance.
The system doesn’t discriminate which insights it presents. Any significant change in performance is analyzed and delivered to you.
However, filtering options ensure that you dive right into the insights that align with your objectives.
Say you want to improve the performance of a struggling campaign. You can apply a filter for the at-risk campaign. This will remove all of the other signals in your dashboard, so you’re only looking at ones affecting the designated campaign.
You can also filter by metric type, which makes finding changes to your KPIs a breeze. Other filters include device type, location, time of day, signal type and more.
Filters enable you to remove any excess noise, so only the most valuable insights remain.
PPC Signal is a competitive advantage in a box.
By automating the detection and analysis of insights, businesses achieve both efficacy and efficiency.
The truth is that AI is better at data analytics than you are, no matter how deep your statistical or data science background runs.
Machine learning algorithms can swiftly and effortlessly convert even an enormous spreadsheet into actionable insights that can help you begin improving your strategies immediately.
The speed of PPC Signal’s detection and analysis of insights becomes a significant competitive advantage for your business.
With instant insights, you’ll respond to emerging opportunities faster than competitors. You’ll be proactively adapting your strategies to the current environment, instead of reacting to changes a week later.
Your business is a data-creating monster. Every customer interaction, from the initial greeting to the eventual sale, produces useful data. Data analysis allows you to make sense of your big data and determine what’s going on in your business. You’ll identify problems, capitalize on successes and find meaningful ways to improve your company overall.
Data provides clarity and understanding about your target audiences, marketing efforts, products and everything in between. You’ll be able to predict changes before they happen, make accurate decisions more efficiently, sharpen your targeting and much more. Simply put, marketers use data to improve their marketing and achieve more substantial results.
The process to convert data into actionable insights consists of many steps. It starts with a question: what are you trying to find out? Then, you have to collect data from various sources that help solve this quandary. The collected data needs to be filtered to remove irrelevant or unhelpful information. Next, you need to review that data and remove errors or discrepancies. This leaves you with a cleaned, filtered data set that is ready for analysis. Using charts, algorithms and other tools, you engage with the data until you obtain insight, or a deeper understanding of your initial problem/question.
History has taught us that knowledge is power. Data analytics in business exemplifies this adage perfectly.
If you can effectively transform your raw business data into actionable insights, the benefits are outstanding.
For years, the complex and tedious nature of data analysis made it difficult to obtain insight and expand your knowledge.
PPC Signal fixes that with its automated monitoring and analysis system.
By receiving complete insights in real-time, you can respond faster than any of your competitors to PPC changes.
This is a significant advantage that enables you to make swift, accurate decisions to minimize risks and maximize opportunities.
The more you work with the PPC Signal, the greater your competitive advantage becomes!
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