Data is important for many businesses. It helps them to understand their customers better, provide personalized content and improve marketing campaigns.
However, a business needs to process the data to access these benefits. This only works with data analytics tools.
We take a closer look at how advertisers use data analytics for their advertising campaigns.
Why Is Data Analytics Used For Advertising?
Before we find out more about how data analytics is used in advertising, it’s a good idea to understand why it is so important.
The processing of data is essential to a business because it helps to understand a company’s target audience better.
This allows a company to target their campaigns specifically towards certain users. Studies have proven that more targeted advertising campaigns have a greater return on investment.
This means that data analytics is a great business tool to get better advertising results with a lot less money waste.
How Advertisers Use Data Analytics
There is a variety of different ways in which data analytics is used by businesses that advertise online and offline.
Understand The Target Audience
Data analytics is especially important when a business or brand chooses to advertise directly to customers.
They need to understand the exact audience they want to speak to. If a brand doesn’t advertise to the right audience, then they waste marketing money and valuable time.
That’s why, it is essential to spend some time looking at audience data.
Data analytics allows marketers to spend their advertising money wisely and more effective.
But data analytics does not just provide basic demographics insights. It also helps advertisers to understand likes, dislikes and usage patterns.
Marketers can then use this data to create certain categories, also called segments, of customers who will be shown advertisements based on their interests.
Even before advertisers can create specific marketing campaigns, they need to understand first how consumers find any information online.
Data analytics can give an insight into what keywords users put into search engines to look for services and products.
These keywords are important because advertisers can use them to target consumers online and on social media to drive more traffic to their website.
Audience segmentation is a vital marketing tool, and advertisers need data analytics to segment their audience into marketing categories.
But not only markets use data analytics for audience segmentation. Also sales teams can use data analytics tools to understand what leads customers to make a purchase.
With this knowledge, sales and marketing teams can then segment their audience into certain groups and send out personalized messages.
Content which is relatable and relevant for a customer is always appealing. This helps to improve customer retention rates and it also increases conversion rates.
Improve Content Quality
The quality of content shown to potential customers makes a big difference to conversion rates.
When an advertiser can adapt the content to a specific target audience, then the ad presented to this audience will lead to more sales.
Another advantage of data-driven advertising is that higher quality content for one audience segment can also be adapted for other segments.
Data analytics can be used to design content for almost any content format, including videos, social media posts, email campaigns and paid advertisement.
Feature Personalized Content
Marketers used collected audience data to turn a potential customer into a regular customer.
Once customers buy on a website, advertisers can use specific website data to find out why customers are visiting the site and what they are looking for.
It’s important to point out here that this customer data is typically anonymized, so marketers are only able to see certain trends.
However, these trends are often enough for marketers to create personalized advertisement which targets a certain demographic or interest group.
Identify The Right Marketing Channel
There is a large range of different advertising channels, from videos to paid advertising. Each of these channels reaches certain types of audiences.
For example, younger audiences are often more likely to engagement with video ads.
Data analytics can help advertisers to identify what channels are suitable for their chosen target group.
Choosing the right channel means that marketers can make full use of their allocated advertising budget for a good ROI.
Predict Audience Behavior
When advertisers use data analytics insights from audience segmentation and channel identification, then they can create AI-powered predictive algorithms.
These AI algorithms can anticipate how and what customers will buy in future. This behavior data can then be used to optimize marketing campaigns.
Data analytics related to artificial intelligence is becoming increasingly popular with the rise of AI channels and tools.
An addition benefit of AI-driven analytics is that marketers can focus more on content than collecting customer data.
Engage Loyal Customers
Data analytics does not just help advertisers to engage with new customers but it can also be very useful when businesses want to improve customer retention rates.
A loyal customer buys products or services much more readily than new customers.
DCT advertisers can use optimized customer data for loyalty programs, email promotions and even subscription services.
Thanks to data analytics, advertisers can also create personas which can help to reach and engage certain customer groups.
New Customer Acquisition
Businesses cannot just target loyal customers but they also need to reach potential customer groups.
Once direct-to-consumers (DTC) advertisers have worked with a well-defined target, they can use a similar data set to attract new customers.
There are a number of different ways to use data analytics to reach new customer segments.
From upselling in your chat service to social media campaigns, all these advertising campaigns require a solid data analytics background to speak to new audiences.
Data is becoming ever more important for businesses, marketers and advertisers alike. But only when data is analyzed in the right way, it can be useful.
Advertisers use it in a variety of ways, from sending out more specific advertisements to certain audience segments to creating better quality content.