The digital advertising landscape keeps evolving. With an ever-growing number of people moving into the digital realm, advertisers are being forced to find new ways of addressing omnichannel marketing challenges. A more extensive prospect and customer base indicate the need for a scaled-up advertising budget and improved ad targeting for greater cost efficiency. This becomes a tough ask when the advertiser is faced with different audience groups having diverse preferences. To add to the difficulty, most consumer categories are in the crosshairs of multiple brands with billions in ad spend budgets at their disposal.
Brands connect with customers over a variety of channels and touchpoints. On the plus side, they have at their disposal billions of data points collated across interactions with customers during transactions, usage behavior on their websites and apps, loyalty point redemptions, purchase history, responses to past campaigns, and much more. Advertising platforms can leverage this first-party data to build new campaigns with better ROI.
Very often, the more you know about your audiences, the better will you be able to create tailored advertising content to engage them.
In an increasingly digital world, the amount of data that the customers are willing to share with genuine service providers is immense. Such data collection practices and usage scenarios are often governed by regulatory and legal frameworks defined by governments worldwide. The data cannot be made publicly available for 3rd party data analysis and processing. Policies like GDPR ensure that data privacy standards are enforced across every digital channel where customer data is handled.
With the rapid proliferation of diversity and scale in the target consumer base and restrictions imposed on data collection due to privacy concerns and government regulations, it’s not always possible to know as much as you would like about your audience. This “unknown” category will soon include 3rd party data sources that collect audience data and information pertaining to ad events and content that different sets of audiences have consumed.
Advertisers have valid fears of the unknown elements about the audience, causing roadblocks in the journey of targeting.
But is this something advertisers need to worry about? Do they need to fear the unknown data about their customers? Should the fear of the unknown keep the intrepid advertiser up at night?
The answer may surprise you!
It’s a fact that marketers and advertisers will have to deal with incomplete knowledge about their target audience. They must devise strategies to win loyalty and interest through creative campaigns. However, the good news is that with the growth of technology, what you don’t know about your audience needn’t hurt you.
Data analytics tools driving powerful customer analytics are capable of tapping the information advertisers have at hand to create robust, highly functional, and capable models of what their audiences are likely to appreciate. On using the existing data points, these intelligent tools can help flesh out customer personas, define their potential needs, and possible responses to messages. Technology capabilities like Machine Learning allow these systems to get better as they go and constantly refine their results. Futuristic capabilities like AI can turn around such analyses at super-speed, allowing advertisers and brands to test and validate a range of strategies and zero in quickly on the “just right” one.
This is where advertisers are looking to step into the future of advertising technology and bring on-board innovative tools like the Aroscop DART (Data Analytics for Response & Targeting).
Using intelligent predictive analytics and machine learning, DART empowers advertisers to forecast target audience behavior and deploy campaigns with more precision and engaging content. They can drive personalization to larger audience pools by leveraging the predictive modeling capabilities of DART.
In simple terms, DART enables advertisers to identify the top-performing audience segment based on an analysis of historical interactions. With the help of machine learning, the platform builds a lookalike audience pool wherein advertisers can launch and track custom targeted ads. They can further scale and automate the end-to-end process based on the results, thereby greatly improving efficiency at lower conversion costs.
By setting up a target lookalike audience base, DART allows advertisers to experiment, do A/B testing, and predict the ROI on advertising campaigns while consuming a wide range of own and 3rd party data streams to make the most efficient targeting.
Such platforms allow advertisers to build new machine learning and data analytics models for their unique target audience base. They can even leverage pre-built models for faster insight generation and use the knowledge to train and scale their efforts. Through advanced data analytics combined with intelligent machine learning, advertisers can predict audience behavior more accurately and align their marketing efforts to realize the maximum ROI. For example, a small batch of a few 1000s customers can be modeled into a more extensive prospect base. Through successful iterative analytics and targeting, the marketing efforts can be scaled to reach millions of new prospects having similar behavioral patterns.
It is time for advertisers to overcome the fear of the unknown. It’s time to leverage the range of analytical and AI-powered advertising capabilities that help foster transparency while at the same time addressing the needs of custom targeting for better results. With such powerful technology on the job, the “unknown” can be as valuable as the “known.” For marketers, the promise is to deliver better outcomes with more efficient and targeted ad campaigns. Get in touch with us to explore more about building a resilient programmatic advertising landscape for your brand strategy by leveraging the latest technologies.