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Home > Blog > Digital Marketing > PPC >

Big Data Marketing Definition: Why Automation is the Future of Managing Marketing Data?

When you know your marketing’s big data, you can answer virtually any marketing question!

Big data marketing definition

Need to set marketing goals? Data tells you what to do.

Want to improve your marketing strategy? Data.

Are you under or over performing versus competitors? Data, again.

Want to know what audiences to target? You guessed it — Data.

Defining your big data comes back to everything you do. It’s a prerequisite to managing your campaigns.

However, there are challenges to applying big data to your marketing decisions. Big data is large in volume (hence the name), it needs to be analyzed and it’s complex in nature.

You cannot overcome these challenges with hard work and perseverance alone. Even a team of marketers can’t compete with the overwhelming nature of big data.

This is why automation is the future of managing marketing data. With the help of AI and machine learning, you can overcome these challenges. You’ll reap the rewards of data-informed decisions that optimize your marketing strategies for peak performance!

Let’s discuss the big data marketing definition and how automation impacts the future of the analysis process.

Big data marketing definition

What Is Marketing Data?

Marketing data shows you the big picture of your campaigns and strategies. You get an overhead view of what’s happening and what new changes have occurred, whether good or bad.

You can also use marketing data to zoom in and explore individual campaigns, keywords or other components.

Modern marketing strategies require data analysis to know every detail of your campaigns, such as:

  • Where are customers coming from?
  • What are customers’ pain points, habits, preferences, etc.?
  • How effective are your strategies at generating leads?
  • What information or content resonates most with audiences?
  • Which campaigns are producing the best returns? What about the worst?

By using your marketing big data to answer these questions (and many more), you can take immediate actions to improve your efforts.

That said, using your big data to define your marketing strategies is a process.

Managing your marketing big data means collecting, organizing, filtering and analyzing the massive amounts of information created by your strategies.

What Marketing Data Should You Collect?

The types of data you collect will depend on your marketing goals and the nature of your business. Remember, not all data is valuable! You only want to focus on the metrics that align with your current objectives.

Typically, you want to focus on four types of metrics, which mostly depend on the target customer’s position in your funnel. Here are some examples:

  • Awareness metrics (top of funnel): Impressions, views, followers, etc.
  • Engagement metrics (middle of funnel): Clicks, likes, shares, CTR, bounce rate, etc.
  • Conversion metrics (bottom of funnel): conversions, conversion rate, conversion value, ROAS, etc.
  • ROI and cost-related metrics: cost per lead, cost per conversion, total conversion value, etc.

Ideally, you want to collect data at each phase of the funnel because this will help you understand your customer journey. You’ll be able to identify pain points in your funnel that are causing customers or leads to lose interest.

For instance, let’s say you have an ad campaign with above-average impressions and clicks. Unfortunately, it’s struggling to convert those clicks into customers.

With this data, you know that customers are interested because they are clicking. Now, you need to identify what’s holding them back from converting. Is it a problem with your landing page? Are your products priced too high? Etc.

This is why it is crucial to gather data at all stages of the customer journey.

The more familiar you are with your data and campaigns, the better you’ll be at determining what data needs collecting. That said, it’s better to gather too much information than too little.

It’s much easier to remove irrelevant information later than incorporate new data at the later stages of your analysis.

How Data Helps You Connect Your Goals To KPIs

The connection between your data and your goals helps you identify your key performance indicators (KPIs). These are the metrics that you’ll use to measure how well your strategies are performing.

You should think clearly about your goals and which types of metrics are most valuable to track and analyze. For example, a PPC manager may want to look at cost per click and return on ad spend, as these are two metrics that reflect costs and ROI.

However, several factors will influence these metrics, which means you have to dig deeper into your data to understand the big picture.

These more detailed metrics will help you understand when and how to tweak your strategies to meet your goals.

KPIs may change depending on what marketing strategy you’re optimizing. The metrics and KPIs that impact customer satisfaction are different from the ones that influence content marketing performance.

Here are some examples of what your PPC marketing KPIs might be:

  • Impressions/ Impression Share
  • Clicks
  • Clickthrough rate (CTR)
  • Quality Score
  • Cost Per Click (CPC)
  • Cost Per Conversion / Acquisition (CPA)
  • Conversion Rate
  • ROAS

KPIs are the linchpins of your strategies. If these metrics are low, your campaigns are suffering.

You may have to take some time to understand the best KPIs for your strategies. Many metrics are closely related to one another. It may be challenging to know whether clicks are a better

performance indicator over CTR or vice versa.

Tips

Why Is Data Important To Digital Marketers?

No matter what type of marketing data you’re working with, there are three fundamental reasons why this information is vital to your success.

1. Better Understanding Your Customers

Big data marketing can define who your customer is (demographics, interests, etc.), and how they think, feel and act.

If you explore this data enough, you can get a complete picture of their age, location, likes, dislikes, how much they are willing to spend, what product features they want and so much more.

Once you have this information, you can align your marketing messages and even your products to match what the customer wants. When you can achieve this alignment, success and conversions are practically a guarantee!

Personalization is also a valuable result that comes from better understanding your customers. If you can get your customer data down to the individual level, you can deliver strategies that are customized to each person.

Today’s customers not only want personalized offers and messages, they expect it. Data is the only way to accurately determine how to create a unique experience for each user based on their preferences.

2. Improving Your Campaigns

Marketing strategies are never set in stone. They are fluid and require consistent change and improvement.

Primarily, this is because of two factors:

  1. Your customers are constantly changing. They grow up and their interests and attitudes change. You need to recognize and adapt to these changes if you want to keep their business.
  2. Your competitors are also always changing. Not only are they constantly changing up their strategies as well, but competitors will also come and go. New ones will enter the space and challenge you, while old ones will fizzle out and leave the market.

As mentioned previously, the challenge is knowing when and how to adjust your strategies.

Data holds the answer.

By examining your strategies’ historic and current data, you can pinpoint areas that have increased or decreased in performance.

These are avenues towards potentially improving your campaigns. An increase in performance could be an exciting opportunity ready to be seized.

Meanwhile, dips in performance could pose risks to your account that need to be mitigated.

Whenever you’re able to adjust strategies to respond to these changes, you improve your performance.

3. Predicting What’s To Come

Predictive analytics is a type of analysis that uses past data to determine the likelihood of certain outcomes occurring in the future.

It’s not quite a magic crystal ball, but with the right level of data, it’s close!

This type of analysis can help your business predict trends, shifts and other changes that are just around the corner.

For instance, you could study consumer shopping habits and predict when specific products will be in high demand. This allows you to act preemptively and adjust your strategies before changes occur.

When you’re the first to take advantage of an emerging trend, you’re able to maximize the value. The first people through the gate have more time to capitalize. You may be the first to catch on to that “next big thing” that customers care about.

Similarly, you can detect when customers are losing interest in certain products or topics. This allows you to back out before these strategies become obsolete and waste your time and budget.

Big data marketing definition

PPC Data Has Its Unique Challenges

So far, we’ve primarily defined big data marketing. For PPC marketers, data plays an even more crucial role for two reasons.

  1. PPC campaigns produce more data than the majority of your marketing campaigns. Plus, there’s a broader range of metrics at play here.
  2. As a paid strategy, there is a direct cost involved with PPC. Thus, you have to pay even closer attention to the data. If it isn’t scrutinized closely, you may end up wasting more money than you earn!

This section will examine the pitfalls and challenges tied to utilizing PPC data.

Finding The Right Data

Again, PPC campaigns produce a lot more data than other strategies. It also involves many different metrics that have to be understood and adequately tracked.

The real challenge is not all of these metrics are useful or carry the same value. Much of this depends on your unique PPC goals.

Some PPC experts argue that most of the data generated by campaigns create more problems than good. The more data you have, the more noise to distract from the metrics and KPIs that matter most.

It can be an absolute mess figuring out which parts of your PPC data lead to actionable insights.

Actionable insights are the end product that data yields, which marketers use to make informed decisions about their campaigns.

It allows you to make changes and adjustments based on factual evidence, instead of educated guesses or interpretations.

On its own, raw data is not all that valuable, unless you can transform it into actionable information. Yet, this is a challenging process.

Knowing What To Ask

Finding the right data starts with asking the right questions.

Wrong questions lead to less valuable answers. They may still provide some help to your campaigns, but not as much as questions pertaining to your KPIs.

This is known as the useful many versus the vital few. It’s the idea that the majority of your results only come from a handful of your efforts (the vital few).

For instance, if consider the Pareto Principle, 80% of your conversions may come from only 20% of your keyword targets. Meanwhile, there are the remaining 80% of keywords that only produce 20% of your results.

You could argue that there are no wrong answers. However, there are less important ones. You want to pay attention to your overall PPC marketing goals and align your questions accordingly.

Eventually, you may reach a point where you’ve answered all your vital questions. Then, you can focus on resolving the useful many.

Normalizing Your Data

When it comes to performing PPC marketing analysis, you’re pulling in data from at least two sources. Your Google Ads account and your Google Analytics will be the two main sources. You may also be incorporating data from third-party tools.

As you merge these data sets, you need to normalize each one to make sure that they “talk” to one another.

For example, you may have multiple sources tracking the same metrics. When you unify these data sets, you need to make sure you’re not double-counting the metric.

Alternatively, various data sources may have different labels for the same metric. You need to normalize these labels to ensure that the data is counted correctly.

Interpreting Data

Collecting and normalizing your data lays the groundwork for the crucial part of the process — knowing what it all means.

Interpreting your data is the most challenging stage. First, you have to contend with the sheer volume of data at play. Next, you have to overcome the complexity of the different PPC metrics.

Finally, there’s the timing aspect. To make the most of your actionable insights, you need to react quickly. You have to be able to gather, organize, normalize and interpret your PPC data in real-time.

Otherwise, the insights you extract may be dated. It’s old news.

This is where automated data tools shine. They handle the bulk of the interpretation and analysis through artificial intelligence and machine learning algorithms.

AI enables marketers to focus on making decisions and taking action on their insights, instead of interpreting the constant changes to their data.

Big data marketing definition

How Automation Helps Digital Marketers Manage Data

Automation and AI are popular buzzwords in today’s marketing world. PPC managers are increasingly turning to AI technology for greater productivity with their data.

“Productivity” means taking the right action at the right time. A productive PPC manager can continuously find ways to improve their campaigns in intelligent and relevant ways.

With every decision requiring data evidence, aligning your PPC management with automation technology can be a big win. It may be the best way to maximize the returns from your ad strategy.

The truth is — and this is no knock to any marketer — AI is smarter and faster at analyzing and interpreting PPC data.

There are several paybacks to working with automated tools.

Cleaner Data

AI is adept at detecting and correcting unclean data. This means removing duplicate data, correcting errors and other tasks.

If you’re working with exceedingly large amounts of campaign data, manually cleaning your data could be exhausting your time and other valuable and limited resources.

To make matters worse, improper cleaning can lead to poor results and other problems. Unclean data creates inaccuracies that may lead you down the wrong roads or towards false opportunities.

However, when your data is properly clean, it leads to more decisive campaigns and better results. Leading PPC marketers have been leveraging AI to ensure their data is always accurate.

More Revenue

Marketers quickly see a positive spike in revenue after implementing AI tools. Clean, accurate data produces better insights, which translates to higher conversion rates and consistent performance.

In other words, AI discovers more valuable opportunities for positive change in your accounts.

Moreover, when you automate the tedious sides of big data marketing, it frees up copious amounts of time (and energy) that you can spend on more vital tasks.

You may be spending twice as much time on these low-priority tasks than needed, if not more!

Better time management allows you to get more done in the time that you have. By focusing on tasks with the highest potential impact, you can accelerate your revenue generation.

Less Fatigue And Confusion

Manual PPC campaign management is clunky and tiresome. If you’re handling a huge account, the size of your data can be downright overwhelming!

It can also be a challenge to know where to start with your PPC data. Even with well-established goals, you may feel lost knowing where to begin.

Thanks to AI, this is never a problem. You always know what’s going right and wrong in your campaigns. This provides easy recommendations for what steps need to be taken to improve your account.

Automation effortlessly detects existing and emerging trends, shifts and other patterns. All you need to do is decide what course corrections are necessary.

For many PPC marketers, this is an absolute blessing.

Tips

How Does PPC Signal Help Managers To Get The Most Of Their Data?

We’ve defined the importance of big data marketing, especially for PPC managers, and the impact of automation on campaign analysis.

Now, let’s take a look at PPC Signal — an AI tool that automatically detects and analyzes significant fluctuations in your PPC account data.

With this level of PPC automation, you can overcome the challenges presented by analyzing your campaigns.

If you’re working with large or multiple accounts, PPC Signal’s automated system will be a much-needed relief.

Using both your real-time and historical campaign data, PPC Signal shows you actionable ways to improve your campaigns and increase your overall ROI.

Big data marketing definition

Why PPC Marketers Need PPC Signal

There are many benefits of automating the management of your PPC marketing big data. Here are some of the reasons why PPC Signal is the best AI system for your Google Ads account.

Better PPC Strategy

PPC Signal’s AI returns better insights from your campaign data. These insights lead to actionable ways to improve your campaigns and be more productive as a manager.

Each signal that the system provides is thoroughly analyzed and vetted. You’re only shown the highest quality and most accurate insights.

Thus, each alert that you resolve has a direct, positive impact on your campaigns. The more signals you act on, the better your PPC strategy becomes.

You can stack an unbeatable advantage through these continuous improvements!

Tips

Better Decision-Making

If you manage several PPC accounts or campaigns, which one needs the most attention? Which tasks are most important and take priority?

PPC Signal removes the risk of making poor management decisions that waste time. The system only shows you the most relevant and noteworthy changes to your account.

This allows you to prioritize your time and efforts on the areas with the most potential value. It’s a streamlined workflow that removes the distracting noise and enables you to focus on the signal exclusively.

Find Opportunities & Risks

Each data signal that this AI-driven automation tool provides is classified as either a risk or an opportunity.

  • An opportunity is a signal where action would create a positive increase in campaign performance.
  • A risk is a signal where action would prevent a negative decrease in campaign performance.

This is the holy grail of PPC management — capitalizing on each emerging opportunity, while simultaneously mitigating issues and risks.

PPC Signal enables you to refine your strategies for better or worse. You always have ways to improve your ROI directly.

Big data marketing definition

PPC Signal In Action

The best way to demonstrate the power and value of PPC Signal is to look at an example of the system in action.

Let’s suppose you are managing a PPC account for a retail business. You want to explore your cost per conversion values across all of your campaigns. You may have over a hundred campaigns in this single account. That’s far too much data to analyze manually.

Big data marketing definition

When you access PPC Signal, you see each automatically generated alert that is currently active.

Since you’re focusing on cost per conversion, you’ll want to filter these 33 active signals to only show ones that involve this metric. The filtering options are along the left side. The menu expands when you click on one of these settings.

Big data marketing definition

By filtering by the bottom-funnel metric Cost per Conversion, you can get right to the automated signals you want.

You’re now left with just two alerts. By clicking on either one, you have the option to Explore the data deeper.

Big data marketing definition

This opens a new page that shows all of the relevant details for that specific signal.

Big data marketing definition

With this zoomed-in view, it’s easier to see exactly how the data has changed, when the change started and how significant the shift, trend or outlier is compared to the usual activity.

You can also add data to the visualization to see how other metrics affected, or are impacted by, this spike in cost per conversion. For instance, you can add cost data to see how the spike in conversion costs has influenced your overall ad expenses.

Big data marketing definition

When you’re finished extracting valuable insights from the visualization, you can choose to view the data as a table that can then be exported and saved to your spreadsheets.

Thanks to PPC Signal, you always have actionable insights available. This hastens your decision-making processes and ensures that every adjustment you make to your campaigns is founded on verified data.

Actions you can make include:

  • Pausing non-converting keywords.
  • Reviewing keywords to determine best and worst performers.
  • Checking each ad message’s performance to determine your top headlines and descriptions.
  • Reviewing landing page performance and relevance.
  • Reducing or increasing keyword bids.
  • Reviewing keyword targets for new opportunities and exclusions.
  • Adjusting your targeting for better results.
  • And much, much more.

Wrap Up

The big marketing definition is constantly evolving. New sources of data, technologies and challenges arise and shift the ways we analyze information.

What always remains unchanged, however, is the incredible value of actionable insights. If you can’t turn raw data into these actionable insights productively, then the value of all the data you’ve generated is significantly less.

This is why automation is the future of managing marketing data. By conquering the many challenges of wrangling big data, AI solutions can transform your real-time analytics into actionable insights instantly.

PPC Signal is the perfect example of how AI and automation can positively impact your digital marketing performance.

The tool automatically generates actionable alerts on how your PPC campaigns are changing. This enables you to quickly respond to every opportunity or risk currently affecting your strategies.

You never have to wonder what to do next or what’s happening in your account. PPC Signal does it for you.

Start taking control of your data!

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