In the age of growth hacking, CEOs are more focused than ever on marketing leadership and partnering to drive growth. Meanwhile, marketers are agile to the demands of adjusting strategies, fine-tuning tactics, and cutting redundancies to drive near-term growth and prepare brands to thrive in the brighter times ahead. It corresponds to
Marketers already know that AI, especially Gen AI, can enhance capabilities in the field with its rich insights, automation, and even authoring capabilities.
Most of them are still coming to terms with one of the less flashy and relatively undiscussed benefits of AI for brands: synthetic data (i.e., imitating real data from real sources). and how AI-generated data) can accomplish the same thing.
Unlike real data, which may be difficult to obtain in some segments, biased, painstakingly researched and time-consuming, or required to be kept private under data laws, synthetic data It's fast to access, balanced, and useful for amplification missions. It has the potential to increase marketing creativity, personalization, and campaign effectiveness virtually on demand. Let's see how.
Bringing creativity to life with intuition
Running a campaign across the clutter means developing fresh ideas and compelling messages. However, these must be tested and refined before being scaled, and everything must be brought to market quickly. Brands can now predict the potential appeal and effectiveness of their messages, ideas, and campaigns by effectively testing them on synthetic populations before actually deploying them.
Marketers can A/B test and refine their content and segmentation strategies to ensure that even the most innovative and surprising campaigns deliver predictable, positive results.Currently, retailers <リンクはデータを共有する小売業者とは関係ありません> already shares representative copies of consumer data or synthetic data with manufacturers and advertisers to help them better manage their messaging and outreach. Insights aside, brands are making pretty smart use of synthetic data media (in the form of deepfakes) directly in their campaigns.
When Dove released a video of a mother repeating the influencer's harmful rhetoric, it became a hot topic in marketing circles. The real mother and daughter then watched the deepfake video. The result was personal reflection and inspired action to #DetoxYourFeed.
Intelligence for personalization
Leading companies like American healthcare giant Anthem started early on generating synthetic data such as medical histories, insurance claims, and other healthcare data to help customize care for their customers.
Marketers can similarly train algorithms with synthetic data to personalize marketing content and deepen the personalization of customer experiences. This is a world where cookie-less personalization is the only way for marketers and brands looking to develop privacy-compliant and future-proof strategies to deliver relevant brand experiences. In particular, it will prove to be extremely valuable.
Insights into effectiveness
Data-driven insights from surveys and polls are essential for marketers to sense changes in customer behavior and make timely decisions such as realigning talent, channels, messaging, and budgets. Creating moments that matter for your customers requires a powerful insights engine and discovering customer intent, interests, and unmet needs at a consistent, fast clip.
With so much data being generated, along with a huge budget to get it all done, speed and focus are extremely difficult to achieve reliably. Synthetic data provides a great way for brands to stay on top of real-world trends and for marketers to allocate critical resources to programs and campaigns that create the most value. This is not much different from how German insurance company Provinzial uses synthetic data to identify the needs of its more than 1 million customers and predict what services and products they will buy next. .
Like all AI, synthetic data is not without its drawbacks. Data and models are only as good as the prompts used to create them, unbiased, and inherently no better than traditionally collected data.
So if you already have good data, stick with it. Synthetic data is faster to access, but running with it still requires careful planning and monitoring. Using synthetic data responsibly to fill data information gaps is how most of the value is created.
This article first appeared on Performance Marketing World.
