In the Digital Age, advertising campaigns have become increasingly sophisticated. They produce mountains of data that advertisers can use to answer all of their most vital questions:
●
How do I spend my budget?
●
What’s the best way to maximize my
PPC ROI?
●
Which keywords are most valuable?
●
Who is the best audience to
target?
● When should I run ads?
The problem is that data is highly complex, which is why data science in advertising is becoming commonplace.
After all, having mountains of information may seem like a gold mine, but only if you have the skills to understand it.
Many businesses and marketing teams are looking to hire specialized data scientists to help wrangle the complex data that digital campaigns produce.
Acuity with data is quickly becoming a must-have trait for new advertisers.
However, it’s not all numbers, data, and science. For this skill set to be usable in marketing, you need equal parts science and art. Only then can data science empower your marketing and ad strategies.
This discussion will look at data science in advertising and how you can apply it to your strategies to produce optimal results.
Let’s get started.
Too Much Data Requires Data
Science In Advertising
SEM has always been a data-driven branch of marketing. Your PPC campaigns produce tons of metrics that marketers need to eat, sleep and breathe daily, from conversion rates and click costs to impression share and conversion values.
It all matters.
There may have been a time when you could manage these metrics manually, but that’s no longer the case. Over the years, Google Ads has introduced new settings and features to help advertisers.
While these additions are excellent for your ad targeting and campaign control, they are troublesome for your data analysis.
The more your PPC accounts scale in size, the less feasible it is to handle data on your own. More data leads to more problems and increased complexity.
Not to mention, PPC data changes rapidly and constantly. Every time your ad appears, data is created and your metrics change. The same is true when you adjust your campaigns or add new ones.
Competitor strategies, changes to user search behaviors, new updates to Google Ads are other factors that influence your data.
It’s a lot of moving parts. There is an unfathomable number of potential combinations in just one of your campaigns!
Data science in advertising can navigate this ocean of data to find the most relevant and valuable bits.
These actionable insights are what make your data valuable. They help you answer critical questions to optimize your ads and improve your results.
Data scientists are adept at asking the right questions and gathering related data to answer this query.
Tip: Data science enables you to understand your campaign metrics and the
stories they tell. These stories are where high-value, actionable insights
hide.
The 6 Stages Of Data Science In
Advertising
To understand the role of data science in your
PPC campaigns, it’s helpful to understand the process behind this discipline.
It is a 6-stage process.
Stage 1: Knowing What To Ask
Wrong questions lead to irrelevant answers.
This creates two problems.
- It wastes
time and other resources.
- Decisions based on irrelevant answers or incorrect data produce poor results.
Sometimes, when bad data guides decision-making, it has a devastating result. Businesses forget that data can be wrong. Thus, they make these decisions with full confidence, like going all-in at the poker table.
When it becomes apparent that it’s the wrong choice, it’s hard to recover.
To ask the right questions, you need to consider your overall marketing goals. This should be the theme behind any questions you ask. It should always come back to your goals.
Asking relevant, goal-related questions will
lead you to the most valuable insights for your business.
Stage 2: Collecting The Right
Data
Your strategies and ad campaigns produce tons of data every day. Unfortunately, not all of this data will be relevant to your needs. Realistically, the majority of data you collect is just noise.
To answer your questions, you need to filter out all of this miscellaneous and irrelevant data. This will help you find the insights that matter most.
Again, your goals will be the determining factor in what data is most and least relevant. You want to identify the metrics that are most vital to your success, also known as key performance indicators, or KPIs.
To make the most of your data, you want to
develop collection processes that focus on automatically filtering for these
crucial metrics. This ensures that you’re only bringing in quality data that is
useful to you.
Stage 3: Processing &
Normalizing Data
This is the point in the process where data science in advertising really shines. A seasoned marketer will be able to ask goal-related questions and know which metrics are relevant.
However, as you gather data, especially from various resources, it needs to be processed and normalized.
It is a tedious process that removes errors and inconsistencies from data sets. It also normalizes different data sets so you can merge them without issue.
There are very few shortcuts at this stage. The data set needs to be reviewed by hand to fix these errors and other issues.
Having data science skills makes this process
easier and less prone to errors.
Stage 4: Charting Data
Once your data is collected, cleaned, and processed, it’s ready for analysis. The problem is that raw numbers are challenging to work with and analyze.
Even a cleaned, processed spreadsheet is a wall of numbers. It’s not the most engaging way to interact with the information and find insights.
The best method for analyzing your spreadsheet data is to chart it. Charts visually depict your numbers and add structure to the raw data. You can see what’s happening in your spreadsheets directly.
Insights appear right before your eyes!
Data science skills will help you select the
right PPC charts for each analysis project.
Stage 5: Interpreting Results
With your charts and other data tools utilized, you can begin interpreting the results. The goal of this stage is to further your understanding of what’s happening behind all the data.
The different charts and tools you use during the analysis all additional information to the puzzle. It all contributes to answering your initial analysis question.
Again, being skilled at working with data is vital. You don’t want to reach this advanced stage in the process only to interpret the results incorrectly!
Hopefully, you should end this stage with
insight.
Stage 6: Taking Action!
With an insight successfully extracted, the only thing that is left to do is to take action.
You have the answer to your initial question. Now you need to know how to apply it through actions.
In other words, what’s the next step after finding the answer?
Sometimes, your next step is to start this process all over again with a follow-up question. This is common — one analysis leads to another — before you’re able to extract any insight.
No matter what action you take, you must track its impact on your campaigns. Not only do you want to test that it solved the initial problem, but you also want to monitor any other results, whether negative or positive, that may come as a result.
There can occasionally be unintended
consequences when you make changes to your campaigns!
How Does Data Science In
Advertising Benefit Your Campaigns?
If you can turn raw data into actionable insights, all of the data you’ve collected becomes a treasure trove of value.
Thus, there are several benefits of data
science in advertising. This section will explore these different advantages
and how data skills empower your entire marketing strategy.
Understanding Your Customers
Successful marketing and advertising rely on your ability to understand your target audience and customers intimately.
This is why many businesses implement a client/customer relationship management (CRM) solution. This tool pulls all of the details your organization has collected about each unique customer.
CRMs are useful, but only if you have data
science skills to make sense of the data they collect. You’ll be able to answer
valuable questions, such as:
●
What are your most and least
valuable audience segments?
●
What makes customers choose your
business over competitors?
● How did customers discover your brand? What are your best traffic sources?
●
What types of offers, discounts,
products, and other offerings do customers prefer?
● Why did customers defect? What are the biggest issues in your customer experience?
The more you understand your customers, the
easier it is to develop more relevant campaigns, content, and products for them.
In turn, this improves your client retention and creates more loyal customers.
Optimizing Your PPC Campaigns
Your PPC campaign data from previous months will help you improve your current efforts. It’s the classic adage that you have to know where you’ve been, to know where you’re going.
What’s worked in the past (and what hasn’t) will help you plan and execute better strategies in the present and future.
It creates the opportunity to use evidence and empirical evidence to guide your campaign optimization, rather than assumptions, gut feelings, and intuitions.
Your historical campaign data can uncover
several insights, including:
●
Which ad creatives sparked the
most engagement from customers? You can develop better ads following what’s
worked in the past.
●
What times have customers
historically been most active? You can use this schedule to target your current
strategies.
●
Which channels produce the best
conversion rates? Allocate your resources to the channels that have proven to
be effective over time.
● What keywords and campaigns produced the most clicks and results? Review these strategies to ensure each new campaign starts strong.
Data science makes it easy to compare past performance to the present. This comparison analysis will help you learn from your past successes and failures.
Applying these lessons to your campaigns makes
optimization easier.
Improving Your Ad Relevance
Ad relevance is a crucial factor for successful PPC marketing. If your ad content is not relevant to the user’s search, you won’t generate many clicks.
Any clicks you receive, won’t result in conversions because your site content won’t be relevant to their needs. Irrelevant content hurts your customer experience and can damage your brand reputation.
Google Ads uses ad relevance when formulating Quality Scores. This is a rating that Google uses to assess how good your ad experiences are.
Quality Scores allow the search engine to deliver the best ads possible to its users. The higher your scores, the better your ad ranks.
Google will even prioritize higher quality ads, even if their CPC bid is less than others. Thus, improving your ratings will help reduce ad costs.
You must apply data science to improve your ad
relevance, especially given the significance of this factor. It will help you
develop overall stronger ad experiences.
Optimizing Your Funnel For More
Conversions
The marketing funnel is a helpful device to explain the process that consumers undergo before becoming a customer. It starts with awareness and ends in conversions.
You can use PPC marketing to target users at every stage of the funnel. This allows you to optimize the process and encourage a smoother journey from awareness to conversion.
Often, marketers will deploy different campaigns for each funnel position. For instance, one campaign focuses on generating brand awareness through ad impressions. A second campaign works from the other end of the funnel to convert nurtured leads and drive revenue.
Data science makes this strategy more effective. It helps you understand the needs of prospective customers and the content, messages, and other tactics that work for each funnel position.
This maximizes your efforts at every stage!
Empowering Your Ad Budget
Budgeting your ads is a tricky process. Ideally, you want to generate the maximum returns, for the least amount of spending. To achieve this, you need to experiment with different strategies.
When you test the wrong things, it can be costly. Losing money in PPC can be difficult to explain to stakeholders, though it can sometimes be necessary to understand your budget and campaigns fully.
Data science reduces budgeting issues by developing spending models that analyze how marketers spend on ads. It compares this data to acquisition reports to decide how to allocate your Google Ads budget best.
It will also help identify the locations,
devices, channels, audience segments, and other factors that help or hurt your
spending optimization.
Increasing Your Marketing Agility
Marketing decisions need to happen swiftly. The moment you detect a potential opportunity or risk, you need to take action immediately.
The longer you wait, the less valuable the opportunity holds and the more damage the risk causes.
Data should drive these decisions and actions. You don’t want to jump to conclusions that are based solely on assumptions. However, without data science skills, utilizing your insights and metrics can slow you down dramatically.
Data science enables you to collect, analyze and process data faster, thereby transforming it into insights much more efficiently.
This allows you to plan, design, and execute new campaigns swiftly, while also adjusting current strategies at a moment’s notice.
Tip: With data science providing critical insights into user preferences,
business owners can create optimal campaigns at lower costs. This improves
their ability to influence consumers and achieve marketing goals.
How To Optimize Ad Spend With
Data Science In Advertising
Some digital marketing strategies are free in theory. It doesn’t directly cost you anything to post to social media, write a blog, improve SEO, etc.
PPC, however, has “pay” right in the name.
Due to the costs, optimizing your spending and budget is an essential concern of PPC marketers.
As mentioned above, data science can resolve this concern and ensure you’re optimizing how you spend your ad budget.
It’s worth taking a closer look at how you can use your data to make the most of your budget. This method will ensure you’re maximizing your profits and returns.
There are a few things to keep in mind during
budget optimization:
Benchmarking Your Ad Performance
The goal of budget optimization is to maximize the results you achieve with your ad dollars. Your marketing goals and KPIs determine these results.
To understand when your budget is producing poor, average, or excellent results, you need to set some benchmarks. The benchmark is the average or expected range that your metrics perform.
By setting these averages, you can quickly
identify campaigns, keywords, and ad groups that are under or overperforming.
Detecting Data Anomalies
When reviewing your performance and looking at your benchmarks, you’ll occasionally encounter unexpected outliers and anomalies.
These occurrences can be the most significant swings in performance, whether positive or negative. Thus, they can be the most damaging to your budget if you aren’t careful.
For instance, imagine a sudden 300% increase in your CPC. This is a massive anomaly that could result in devastating wasted spending. You’re paying triple the normal click cost!
It’s crucial to be able to detect these
unexpected occurrences before they dry up your budget.
Predicting Customer Values
Depending on your business, customers may have very different values.
For example, if you run an electronics store, a customer buying a new computer is vastly more valuable than one that’s going to buy a new cell phone case.
If you can predict a customer’s value, you can
allocate your budget to the most valuable advertising prospects.
Automation
Remember, budget optimization decisions must happen quickly.
The above steps are not simple tasks that you can perform quickly. They take significant blocks of time, especially if you’re handling these tasks manually.
Automation is now a necessity to manage data science in advertising. Even if you have a full-time data expert working on your campaigns, the volume, complexity, and data speed are too much for manual analysis.
These solutions use AI and machine learning to
monitor and analyze data in real-time. You’ll detect anomalies, uncover more
profound insights and manage your data more efficiently.
How PPC Signal Automates Data
Science In Advertising
To reiterate, automation is now a necessity for most Google Ads accounts.
When your account reaches the point where manual analysis and data management is no longer possible, the need for automation increases.
PPC Signal is one of the best automated PPC solutions available to marketers. Using machine learning algorithms, the system automatically detects shifts, trends, anomalies, and other interesting data occurrences.
No matter how much data your ad accounts produce, PPC Signal monitors it in real-time and provides immediate alerts for any performance changes.
This level of automation holds many benefits
for PPC marketers.
Optimize Your Time Spent
One of the most significant issues with managing your PPC campaigns is the time it takes. Many tasks and responsibilities fall under the umbrella of PPC marketing.
Finding time for all of these duties is a constant challenge and source of stress. Data is one of the major roadblocks in the workflow of a PPC manager. Even with a professional data scientist, the process is tedious and requires constant time and attention.
Thanks to automation through PPC Signal, you no longer have to dedicate these countless hours to monitoring and analyzing your data. The system handles these cumbersome tasks for you.
This frees up hours that you can spend on
other projects. Suddenly, you have free time for all of those ideas and tasks
you’ve been putting off!
Take Swift Action
Automation is necessary to handle the speed of advertising data. You must make decisions quickly to mitigate risks and capitalize on opportunities on time.
The sooner you can act on changing data, the better your results. You’ll clear up any account issues before they hurt your performance and capture emerging opportunities ahead of the competition.
If you don’t know how to act on a current
performance change, PPC Signal will recommend an action.
Constant Measurement Of KPIs
You need to stay on top of your KPIs at all times. Any shift in performance for these metrics will impact your goals directly.
PPC Signal offers the chance to always have your KPIs under surveillance. If something happens to your PPC strategies that alter these metrics in any way, you’ll receive an alert.
You can even filter the signals that the
system provides to only showcase ones that align with your KPIs.
Forecast Future Changes
Much of data science in advertising focuses on optimizing your present performance based on past results.
The algorithms behind PPC Signal’s automated system are sophisticated enough to forecast the possible results that changes to your campaigns will cause.
These predictive models will help you make smarter decisions about how to optimize your efforts. This will reduce possible slip-ups that hurt your efforts and cause drops in performance.
It’s like being able to see around corners at
what’s to come!
Easily Report Changes
PPC marketing doesn’t happen in a bubble. It is part of your overall business strategy. Thus, there are times when it’s pertinent to report PPC data to stakeholders, other marketing teams, clients, or others.
Many of these individuals do not interact with PPC data and metrics regularly. The concepts that are second nature to you may be entirely foreign to them.
PPC Signal makes it easier to report your analytics. You can see a high-level overview of your account and what’s been done to improve performance.
You can also quantify your work as a marketer by using your actioned signals. Each alert you resolve represents a positive action taken to improve performance. You can use this to justify your results to management.
Tip: Data scientists help businesses in many ways by extracting, processing, and analyzing marketing metrics to deliver valuable insights. You can use the information to learn about customers, optimize strategies and achieve better overall marketing results.
FAQs About Data Science In
Advertising
How Is Data Science Applied In
Marketing?
Marketers use data to learn how to optimize
their campaigns to attract customers best. The problem is that marketing data
is complex, varied, and constantly created. Data science is used to make sense
of this data and find the best ways to maximize marketing results.
Can A Marketer Become A Data
Scientist?
Yes! More and more businesses are looking for
specialized marketing data scientists. These are marketing professionals with
advanced knowledge of data science. The merger of these two skill sets makes
these individuals wizards at optimizing campaigns and uncovering meaningful
insights, trends, and patterns.
Is Data Science Useful In Digital
Marketing?
Absolutely! Data science helps you understand
all of the various metrics and information generated by your marketing
campaigns. Campaign data is crucial if you want to capitalize on consumer
trends, develop stronger ad experiences, maximize your ROI and so much more.
What Is The Difference Between
Data Science And Marketing Analyst?
A marketing analyst analyzes marketing metrics
and looks for changes and trends that lead to valuable insights. The data
scientist role has a wider range of skills. They can do everything that a
marketing analyst does, but they also build charts, develop predictive models,
convert data into business stories, and much more.
Conclusions
Data science in advertising is a must-have skill. This expertise helps unlock the potential of your raw data and transform it into actionable, valuable insights.
As your accounts grow larger and data complexity and size scale, data science will give you the ability to continue utilizing it as a resource.
That said, no matter how skilled you are at handling and manipulating data, there comes a time when it becomes too overwhelming and time-consuming to analyze manually.
Automation is a valuable asset for data science in advertising.
It enables you to match the complexity of your data with sophisticated algorithms and AI technology to automate the monitoring and analysis stages.
PPC Signal is an exceptional Google Ads tool that allows you to tap into your insights with almost no extra effort.
With PPC Signal automation, you streamline your workflow as a PPC marketer and supercharge your campaigns.
It’s your personalized marketing data
specialist!
