5 Ways Marketers can Start Using AI for Media Plans Today
5 Ways Marketers Can Start Using AI for Media Plans Today
There are a few moments in history where we can witness cutting-edge technologies propelling the advancement of society. These cultural touch points often usher in a new renaissance, sparking a period of excitement and curiosity as we begin to explore the capabilities of the latest innovation. One of the most recent technological monumental shifts in 2023 was the introduction of AI technologies.
AI databases have the potential to seamlessly fit into every facet of our lives, from simple quandaries to in-depth analysis, and have already expedited the research process ten-fold, distilling large quantities of data and providing solutions quickly. As marketers, we can use AI to streamline our workload and refine our research methods to understand our consumers in a greater capacity. Marketers who are not quick to utilize AI could fall behind the competition, but like with any new technology, it can be difficult to determine how to best use it.
How Can We Utilize AI Effectively In Our Line Of Work?
Since the launch of iOS 14 in 2020, in which iPhone users were granted the ability to opt out of personal data sharing, the marketing industry as a whole has struggled with understanding their consumer base at large. With the removal of personal data, marketers now have to solely rely on previous campaign performance and restricted platform data as a way to assess their primary demographic. And while many marketers have been able to get by using historical information gathered through research and trial and error, we continually strive to achieve efficient performance with as little optimizations as possible. AI is a tool that can be useful in meeting and exceeding those performance expectations.
With the help of machine learning, marketers can use AI to review previous results and help identify trends in consumer behavior which can be used to develop solid consumer personas. For instance, by supplying AI with sufficient data we can use its learnings to generate the following:
Customer Segmentation and Targeting
AI can use the data and details marketers feed it to identify overarching trends, patterns, and preferences in consumer behavior and then develop data-driven algorithms to disseminate people into categories based on their perceived loyalty and value. Additionally, AI can refine these audiences by segmenting users by other demographic measures like income, age, or personality and how much they’ve interacted with your brand. We can then take these suggested segments into consideration as we build our media plans testing their effectiveness against client provided audiences or UI generated groups to test their value and profitability.
This is a methodology that is used to build upon our understanding of customer personas by using the information previously collected. AI can then use our historical data to identify prospecting customers based on their behaviors and actions, and can also use those predictions to calculate consumers' anticipated churn rate and perceived loyalty to the brand. By incorporating AI driven predictive analytics into campaign strategies, marketers could not only save valuable time and resources, but also improve the effectiveness of campaigns and their return on investment.
After reviewing historical data trends and categorizing users based on demographics and intentions, AI can then analyze those segments more granularly by assessing where they are situated in the consumer journey. This can be helpful by adjusting various elements of the ad such as tailored messaging, product descriptions and offers, to meet consumers wherever they are in the consumer journey and encourage them to to move them further along in their cycle. Not only will including personalized advertisements encourage consumer engagement, it will improve a customers loyalty to the brand as they feel like they are being spoken to directly through unique messaging and product offerings.
In addition to learning about users' behaviors and preferences, AI databases can be used to assess how consumers feel about a particular brand as a whole. AI can comb through online reviews, social media posts, and comments to gauge consumers' sentiments and discover ways that they properly cater to their consumer base, and areas that can be improved upon. This is a helpful feature to implement in brand studies as these sentiments are unsolicited, which means they are the most honest and accurate view that a customer holds for a company, not just a generalized response. This gives the consumers the opportunity to address specific praises or concerns with a brand's image or offerings, and it allows brands to create particular strategies to improve their operations.
Similar to the way that AI can adjust content to meet consumers' needs at all phases of the funnel, AI can also analyze consumer behavior to understand what type of content would appeal to the ideal consumer base. AI can almost instantaneously create a wide variety of content from articles and advertisements to photos and posts.
These are just a few of the many ways in which AI technologies can be assistive in a marketer's day-to-day procedures. From helping uncover hidden trends, to strengthening our knowledge of our clientele and their markets, AI holds tremendous insights that we can glean from when developing strategies to maximize returns on profit.
AI is a product unlike anything we have seen before, and unlocking its full potential can be simultaneously a daunting yet rewarding expedition. It is a powerful tool that can help marketers streamline daily tasks, by expediting our research and planning, in turn offering the ability to allocate time and resources to other strategic projects. However, it should be noted that like most other assistive technologies, AI’s role for marketers still needs to have checks and balances in place.
While AI is capable of collecting, processing, and extrapolating data across multiple platforms in mere minutes, it’s critical to be aware that it, like everything else, is capable of error, and marketers should use judgment to assess whether its suggestions ring true. We can do this by simply examining the proposals that AI recommends and compare it to the data we have gathered from previous reports or campaigns.
For instance, if AI generates segments and identifies which products would be suited for a certain subsection of our customers, we can confirm whether or not its suggestions are true by reviewing previous campaigns that utilized those products to see if there is any correlation. Ultimately, by cross-checking and testing data against the machine's findings we can not only see if those recommendations hold any validity against our standard practices, but it will also aid us in analyzing and perceiving our consumers through various perspectives, which should in turn bolster our knowledge and prowess of our audiences, thereby making us more effectual marketers.
What Does the Future Hold For AI?
As machine learning continues to advance and become more agile, the routes in which this type of technology could be a helpful aid in the realm of marketing will become nearly endless. The introduction of AI has spurred on another turning point in our history, and it will be exciting to witness what new ideas are created as a result from this innovation. If you're interested in learning more about AI, contact us today.
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