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Personalized Advertising Using Data-Driven Dynamic Advertising

In today’s rapidly evolving landscape of digital marketing, technological and marketing innovations have changed the way marketers engage with their potential customers. Innovations such as using artificial intelligence to effectively deliver and manage multichannel ad campaigns through probabilistic matching, and the use of native advertising to exponentially increase the CTR of digital banner ads have great potential to not only increase the ROI of ad spend, but also to enrich customer experience.

These, however, are just really effective means to deliver the message that marketers want to convey to their customers. As Bill Gates rightly predicted, content is king and without being able to deliver the right message to the right person at the right time, ad campaigns will fail. This personalized approach to digital advertising is called data-driven dynamic advertising, and it is completely reshaping the way global brands, media agencies and publishers are communicating with consumers.

“Data-driven dynamic advertising refers to ads where the design elements — the images, the message, and the format — are dynamically generated based on data captured on a particular audience.” The data captured from customers vary from previous ad exposure, previous online purchases, device used, past internet searches, location, etc.

Collecting customer data is the first step in delivering personalized experiences. Taking that data and using it to deliver dynamic advertising helps bridge the gap between the data itself and the person. Based on the data that’s captured, ad creative components are assembled, and the ad is served to the user. The most basic example of dynamic advertising involves customizing an ad creative based on a user’s browsing history. An ad creative is automatically generated based on the products and categories a customer has shown interest in.

With demand for personalized advertising increasing, marketers are readily implementing automated real-time, personalized, omnichannel marketing strategies across inbound touch points. When done right, these more meaningful interactions can truly transform the customer experience.

Best practices to achieve such truly personalized content is to make sure that real time ad directing – offering appropriate products and services at the right time – is done for a set of extremely targeted customers. This should be supported by proven data-driven marketing techniques, where relevant information can be identified, analyzed over time, and used to drill down to specific marketing touch points (i.e., number of website hits that come in when a specific direct-response show airs).   

Data-driven dynamic advertising is a necessity for all marketers. It represents the first step in developing a more comprehensive, personalized approach to communicating with customers and embarking on a continued relationship.

The heavy use of data and the corresponding use of data analyzing tools to target and customize content has changed the entire landscape of marketing. Companies like Jivox, Merkle and Epsilon lead in providing data-driven dynamic advertising services. Major social media companies like Facebook and Google are also leaders in providing personalized data-driven ads. Recently, technology-based companies like IBM and Accenture have also entered the data-driven advertising landscape.

For marketing procurement, this means a change in agency structuring. Digital agencies have an upper hand when it comes to creating digital content which can be dynamically customized. However, with the heavy use of data analytics, major technology companies such as IBM (with its Watson offering) can dominate. Going forward, procurement managers will have to wait and watch how the data-driven dynamic advertising landscape will change.

Marketing
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