Personalization at scale can have a very positive impact on your marketing campaigns. From reducing production and scaling time to increasing customer engagement and satisfaction, click-through rates, and average order value, marketing personalization strategies can increase your ROI and make your brand resonate with a larger audience.
So, you’ve decided to look into personalized advertising. But what do you need to know to determine if it’s right for your brand? How and where do you start? In this article you will get the 21 most frequently asked questions around personalized ads. We’ve made sure to keep our answers short and succinct, while still providing all the information you need to get a good grasp on personalized advertising.
Personalized advertising is the strategy of using customer behavior and preferences to create targeted ads. The audience is divided into segments and each segment gets a different, customized ad. This way, brands can target their entire audience more successfully, since they avoid generic ads and promote their product in the most efficient way per segment.
While they share some similar points, targeted advertising isn’t the same as personalized advertising. With targeted advertising, ads are shown to specific audience segments based on chosen criteria, which can be geographical, based on interests, etc., but the ad content isn’t necessarily tailored to the specific segments. Targeted advertising is created with rules that have been set beforehand. With personalized advertising, on the other hand, the content of the ad is tailored to each specific audience segment, ensuring a larger ad impact, and the ad can be adapted to the audience’s actions even after it has been deployed.
Personalized advertising leverages user data to see your audience’s behaviors and understand their problems, wants, and needs. Based on the context your strategy relies on, you divide the audience into segments. For example, a clothing company might opt to target their audience based on their style preferences, showing specific dresses to one segment, and jeans to another. A telecommunications company could create personalized ads based on the audience’s needs: offering a larger data package to university students, and better broadband to freelancers that work from home.
Personalized advertising strategies provide you with the best online advertising solution. Customers nowadays expect a certain level of personalized experiences. Your brand gains a more impactful exposure, since it reaches the right audience and talks to them in a way that helps them solve a personal problem or fulfill a personal need. Your advertising campaigns have a greater impact, increasing both your conversion rates and your ROI.
The effectiveness of your personalized advertising campaign will depend on many factors, but here are the basic things any brand needs to focus on to ensure their campaign is effective:
Every good strategy comes with its challenges. While deploying personalized advertising, brands might come up with some hurdles. Here are the most common ones:
Determining the right level of personalization: There’s a difference between a personalized ad and an awkward one, and the line can sometimes be fine. While customers appreciate and even demand a certain level of personalization, they certainly don’t want an ad that feels invasive. Striking the balance right can be tricky, but getting it right can yield impressive results for your brand.
Managing data: In order for your personalization campaign to work, you need to collect the right data, integrate it to your systems, and ensure you’re not creating duplicate entries or data silos. This can take time for a company to resolve, but it is an important aspect of a successful personalized campaign.
Technological constraints: Brands that deploy omnichannel personalization strategies often find that they have to adjust their technology. Personalized ads at scale can maximize your campaign’s ROI, but for the desired results, you need to invest in the right tools. A Creative Management System can greatly help you streamline your personalization process and reduce the production time needed to deploy your strategy.
Dynamic ads are a specific type of personalized ad. Their content automatically adjusts based on customer data (behaviors, preferences, etc.). Dynamic ads are widely used, since they adjust automatically, so they contribute to higher conversion rates and are connected to higher customer engagement.
The fundamental common elements of every successful personalized advertising strategy are collecting data in one place and avoiding data silos, making sure no duplicate data is collected, and remaining compliant with data collection and management.
Another significant aspect is creating personalized content that resonates with a brand’s audience segments. For that to be successful, the segmentation needs to be aligned to your personalization campaign’s objectives, and the content needs to be specifically tailored per audience segment.
Lastly, brands that run successful personalized ad campaigns measure the results regularly and adjust their campaign according to the data collected.
This is one of the most common pain points of brands that deploy personalization strategies: how do you strike the balance between personalized and intrusive?
Make sure you get explicit consent from your customers for any data you collect. Collect only the data you need, and be transparent about how you are going to be using the data. Comply with all relevant data privacy laws so that you keep your customer’s data secure. Lastly, make sure you don’t use any sensitive data or create messaging that sounds too intrusive.
Personalized advertising impacts many aspects of your brand’s customer journey. Personalized ads lead to higher purchase rates, while also increasing customer retention. Since customers expect and welcome personalized experience, personalized ads also drive higher customer satisfaction. All these lead to a significant increase in Customer Lifetime Value.
In simple terms, the difference among first, second, and third-party data is how the data is collected and by whom. Companies collect first-party data themselves, directly from their customers, using their website and other channels. Second-party data is collected by a company’s partners instead. Third-party data is acquired from external sources, usually purchased.
Every company chooses which kind of data to use in their personalized advertising strategies. While there are benefits with all three, companies need to carefully consider factors such as customer privacy and the quality of the data utilized.
Personalized advertising can do wonders for your marketing strategy, but as anything relying on customer data, there are some things you need to be careful about. Here are the main concerns to consider:
Data collection and usage: Companies need to be transparent about data collection and usage. Customers have the right to know what kind of data is collected and how it is going to be used. Data should only be used for the purpose it was collected. Not only does this protect your customers, it also helps you remain compliant with data privacy laws and regulations, and builds trust with your audience.
Data security: The data a company collects should, of course, be kept safe. Data breaches are a common phenomenon. You need to take precautions so that your company remains breach-free, and your customers’ data is kept safe.
As you probably guessed already, this heavily depends on your company’s data practices. It’s important to be transparent with customers on the type of data you collect and how you use them. Customer data must also be protected from potential leaks and breaches. Lastly, make sure your privacy policies are easily accessible to your audience.
Predictive advertising leverages customer data and predictive analysis to anticipate customer behavior. Instead of reacting to customer changes, predictive advertising helps marketers anticipate changes. This way they can optimize the campaign ads faster and more effectively.
In real-time bidding, ad impressions are bought and sold in the span of milliseconds through real-time auctions. The process is automated and it allows personalized advertising to become even more effective, since marketers can bid on ad impressions in real time, allowing brands to deliver the ads in the right place at the right time.
As in all marketing campaigns, businesses tie in their goals to specific metrics. The KPIs will vary depending on the marketing strategy goals, but some of the most popular key performance indicators are Conversion Rate, Click-Through Rate, Return On Investment, Customer Lifetime Value, and Average Order Value. It’s important that every company uses the KPIs that better reflect the strategy goals and measure its effectiveness in the most accurate way possible.
Incrementality testing is a form of testing used to understand the true impact of a marketing campaign. It measures the conversions that actually came from the campaign itself, excluding any conversions that would happen even without the campaign. By measuring the pure conversions that happened due to a campaign, incrementality testing helps marketers understand the effectiveness of an ad campaign. In personalized advertising, incrementality testing helps companies determine whether personalized ads are indeed more effective than other ad campaigns.
A/B testing can be utilized to show two different variations of a personalized ad and determine which one is more effective. You can test your copy, segmentation, or even determine whether a personalized ad works better than a conventional, generic ad. A/B testing is widely used in determining which ads are more successful and in optimizing personalized advertising campaigns.
Attribution modeling can enhance the impact of personalized advertising strategies. It helps marketers understand which touchpoints are the most important in a customer journey. Utilizing that information, brands can pay more attention to and configure the touchpoints that have the greatest impact for each of their customer segments, enhancing the ad’s impact on their audience.
With third-party cookies being slowly phased out of use, the shift is moving toward zero and first-party data. Marketers now rely on data collected by their own companies to base their personalized marketing strategies on.
Voice search and smart assistants provide new ways to potentially gather more data into user behavior. But there are some serious ethical considerations when it comes to that data, since users aren’t always aware of its collection and usage. While data like this could be used to further refine personalized ads and make them even more effective, companies will need to be extremely careful if they opt to use it in the future.
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