Data Science is an interdisciplinary field that provides numerous ways to modern businesses. It comprises both statistical and programmatic models that enable industries and businesses to process raw data and extract insights that can be used to make informed decisions and improve their products or services.
One of the biggest challenges that businesses faced was getting the right marketing strategy. Previously, people made marketing decisions based on their experience and their gut feelings. But, it’s not viable in today’s cut-throat competition where the slightest mistake in your strategy or master plan could devastate the entire product or pose a threat to your business.
Nowadays, companies use Data Science applications and methodologies to gather data about their customers and market, analyze it and then use it to make informed data decisions that give them maximum ROI(return on investment) on every dollar they spend on advertisements. If you’re a marketer or one who wants to learn the technology, you can take the Data Science Course and learn the core concepts that drive our modern marketing strategies.
Now, let’s discuss how data science helps businesses to optimize a business and the ways in which they optimize their business strategy.
How Data Science and Machine Learning Help Your Business?
When you hear about using data science or machine learning in advertising, it’s usually related to the way ads are designed and how to automate the marketing process. Data Science is mainly used to study the effectiveness of your advertising and see how the customers might react to them. Data science is also used for finding the best timing to place your ads through traffic analyses, finding the lowest cost-per-lead(CPL), and channels with high-quality leads.
ML helps us to analyze the data in order to group the users based on their location, search history, or behavior so that we can place targeted ads and make them a success. Some of the algorithms used to perform such operations are classification modeling, regression, clustering, and decision trees. You can learn more about the role of each algorithm and ML model in different fields from this Machine Learning Tutorial.
Top 5 Ways to Optimize your Ad budgets through Data Science
Following are the ways in which you can use Data Science to optimize your advertising budget and get the best results out of campaigns or ad-spend:
1. Benchmarking the Ad Performance
Simply put, benchmarking your ad performance means setting a point of reference or on which the performance of other ad campaigns will be judged. There are different types of ad campaigns like Email marking, push campaigns, rebranding, brand awareness, Cost-per-click(CPC), etc. let’s take CPC as an example, here you’ll pay for the ad only if the user clicks on it. However, there are many factors that play behind the curtains which you need to consider.
Here, data science helps you to analyze different campaigns and find the variables like bounce rate that affect your ad performance.
2. Marketing Automation
One of the emerging trends of data science is its usability to automate various processes. You can automate several processes that either take more time and effort or are repetitive in nature. For example, demand-side platforms can be optimized for real-time bidding and adjust your ad spend accordingly. Calculating and tracking the value metrics while considering the different platforms where the user might see your ads before he becomes your customer.
3. Identifying the right time and channel to place your ads
An average human being spends around 2-3 hours on the internet surfing through various websites and special media apps, Therefore, finding a sweet spot where the chances of your ads getting the most attention and international presence are often complicated. You have to do a lot of slicing and dicing to find out the best timings to place your ads. Data science projects can be used to consider various parameters like platforms, locations, timezone, and more.
4. Customer value Prediction
Some data science models are heavily used by companies to predict their customer value. This means calculating the worthiness of a customer to you and saving yourself from overspending and creating a negative ROI. Revenue and spent cost are the two variables used for calculating the customer value.
5. Knowing you Data
Perhaps the most important and challenging thing where the majority of businesses lag is not having enough knowledge about their data. They don’t know the true potential or the amount of valuable information they can extract from seemingly useless data. A business can deliver outstanding performance if it’s able to make the right decisions at the right time. And, data science is the only way you can make sense out of your data.
Data Science plays at the forefront of many industries and helps them create better products and marketing campaigns. Companies spent around 30% percent of their total revenue on advertisements and promotions. Therefore, it’s imperative for them to be careful and not to waste those resources. With the right talent and strategic analysis, they can make better decisions and optimize their spending on different marketing strategies.