Understanding your audience is crucial to your brand storytelling process. Certain stories resonate with particular types of people differently. When crafting a message, whether it be in the form of advertising or a marketing campaign, it’s important to keep in mind who your intended viewer is in order to make it as engaging for that group as possible.
Your target audience is an overarching term representing everyone who might be interested in your message. It’s important to note that the population that makes up your target audience is not all alike. People are attracted to messages for different reasons. Your target audience is made up of all your audience data, which means it’s made up of different kinds of people with very different motivations and needs.
It’s unrealistic to think that a company should cater different messages to every single data point that makes up their target audience. This is why audience segmentation is important. If you take a look at the different segments that make up your target audience and what resonates with those different groups, you can A) cater marketing messages to the most profitable segments and B) make sure no important groups are being left out of your marketing efforts.
The best way to approach this is to look for patterns within your target audience in order to help you reach the largest and most profitable segments of people. The patterns that come about from your audience data reveal sub-audiences. Each audience segment is a different “type” of person, called a customer persona. Each persona represents a group of people within your target audience that share similar wants, needs, and motivations regarding your product or message. Comparing digital storytelling tools can be a
From a marketing perspective identifying these different segments is crucial because certain segments of your audience are more profitable than others. When creating marketing campaigns or other targeted content it is important that you are creating things that are most engaging with those segments.
Once marketers understand the different segments of their audience they can use it to make optimal decisions regarding advertising, marketing, and content creation.
Data Management Platforms
Data management platforms (DMPs) are at the forefront of data-driven marketing. DMP platforms are meant to ease the process of analyzing all of the information surrounding customers, potential audiences, and other marketing data in order to inform advertising and content decisions. DMPs pull in a variety of customer data ranging from first-party information like a company’s websites, socials, and marketing information to second and third-party data to fill in any data gaps. DMPs can use machine learning algorithms and data analytics to detect patterns within the information. They traditionally then export this information to an advertising tool. While alone, DMPs aren't of much use, when paired with other software, they can help streamline the ad-buying/selling process as well as assist in marketing strategy.
Adobe Audience Manager is one application that is part of the larger Adobe Marketing Cloud. Adobe Marketing Cloud is a collection of marketing applications that span everything from data analytics, advertising, audience targeting, web management and content management. The collection of applications is catered to the advertising and marketing field.
The application Adobe Audience manager is a data management platform that focuses on client data and behavioral data to create audience segments. By analyzing audience data, it breaks down a target audience into personalized segments, which you can use to create customer personas. The Audience Manager helps the user build unique audience and buyer personas, so they can use them as part of marketing and content strategy.
There is a tremendous amount of data that surrounds your audience. Typically, this data rests in a variety of different systems and is separated by media type. Meaning data surrounding your email audience is separate from your website visits etc.
Adobe Audience Manager collects all of the audience data from different sites, performs audience analysis, and then compiles it in an easy to understand way. This process translates data points into a target audience based on all of your data. Audience manager can then be used to break down this large target audience into smaller persona segments.Adobe Audience Manager also keeps track of segment populations in real time. This means that as a campaign is going on it can monitor which segments are the most valuable.
Limitations of DMPs
Data management platforms are extremely helpful in understanding data. However, they have their limitations. Like any data-driven platform, they are only as good as the data they are presented with. The more data they have the better they can work. The best DMP platforms collect data from multiple sources in order to make up for any discrepancies in the first-party data.
While a software doesn't necessarily need to utilize AI in order for it to be a DMP, the best ones utilize machine learning to look for patterns and continually learn from its data in real time.
Additionally, DMPs only present patterns in the data, not what to do with that data. Because of this, they have little value on their own without other platforms to plug in to. Traditionally, a characteristic of a DMP is that they can plug into an advertisement technology to optimize
buying or selling ad spots. They can also be useful in putting together a marketing strategy but again, only if the information from the DMP is utilized properly in the decision-making process after.