By Senthil Ayyappan, Chief Sales and Marketing Officer at Qualitest
In the last year or so, there has been pressure for digital marketers to find new ways to leverage zero-party data for marketing campaigns and product development. A clearly defined audience will have lasting benefits for any business, and with a wave of cookie redaction already on the horizon for 2024, marketers can take advantage of this new surge of artificial intelligence (AI) and not rely on third party data. To make the most out of the technology when defining an audience, maximize and build upon data already available, choose AI systems carefully, and uncover valuable audience trends.
Build AI From Existing Cookies
Cookies may soon be obsolete, but that doesn't mean the data collected until now will vanish with them. Google has an extensive database of our preferences, places we've visited, people we talk to, products we want, and more. Businesses can use their existing user databases and AI to try out new messaging through offers on email or social media. For instance, create two versions of an email with different subject lines – one emotional and the other factual – and test which one yields higher engagement rates.
To carry out these tests, you can use email marketing platforms that have built-in A/B testing and tracking features such as Mailchimp, Sendinblue, and HubSpot. A few examples of subject lines to include in your tests are:
- Emotional: "Shh, don’t tell!! Exclusive discounts just for you!"
- Factual: "Limited time offer: 50% discount on all items in our store."
- Emotional: "Unlock your full potential with our life-changing course!"
- Factual: "New online course available: Improve your skills and productivity."
Learn How to Collect Your Own Valuable Data
Once you’ve utilized existing data from cookies, it’s important to consider how to actively gather your own data for further use. Be proactive in your approach and have the right systems in place to collect, sort, and store data. Platforms like Bright Data can capture web page content, structure and meta tags, and user journey details. Meanwhile, Dataloop, an AI-powered data annotation and management platform, is useful for labeling and managing data for machine learning projects.
Collecting ground truth data, or data collected directly by observation or measurement, is essential for developing and improving AI systems. This involves setting up data collection points across your organization, implementing rigorous data validation processes to ensure quality, and securely storing and organizing the data in a structured manner. Once the data is collected and cleaned, it can be analyzed using advanced data analytics and machine learning techniques, such as clustering and classification algorithms, to identify customer segments based on behavior, preferences, and purchase patterns. With a deeper understanding of our audience and a refined customer segmentation, these insights can then be used to create targeted campaigns that resonate with each customer segment and drive better results.
Integrate AI Systems
Shifting from personalized cookies to registration-based systems for data collection requires a strategic use of AI. Encourage customers to register, share their details, or claim an offer to facilitate the collection of first-party data. AI systems play a vital role in this process, predicting customer behavior and enriching segmentation for enhanced personalization. For example, Netflix's recommendation engine and Amazon's personalized shopping experience leverage user behavior data to provide personalized content and product suggestions, enhancing user engagement and satisfaction. Similarly, Starbucks' "Deep Brew" and Spotify's "Discover Weekly" use AI to tailor menu options and music recommendations, respectively, based on user preferences, improving the overall customer experience. Motivate customers to register, share their details, or claim an offer to facilitate the collection of first-party data. Remember to add value for customers by using progressive forms that continually collect new information during each subsequent website visit. Implement AI chatbots to gather nuanced customer preferences and provide a more curated shopping experience.
Simultaneously, add value for customers by using progressive forms that continually collect new information during each subsequent website visit. Implement AI chatbots to gather nuanced customer preferences and provide a more curated shopping experience. This customer data, collected with the help of AI, can significantly improve targeted marketing efforts. You should also leverage artificial assistance platforms such as Amazon Rekognition to weed out synthetic data and interact with genuine customer profiles. These AI platforms augment your ability to understand customers, guide team strategies, and maintain an authentic database.
Predictive analytics, another crucial AI tool, uses historical data to anticipate future customer behavior and preferences. This empowers marketing teams to design effective campaigns, ranging from customer retention drives to targeted product promotions. Platforms like HubKonnect further enhance this process by using digital insights for precise audience targeting and creating detailed customer personas, which is particularly beneficial for businesses with a global footprint and multiple retail locations.
Identify Audience Trends
After your AI systems are up and running, focus on identifying specific audience trends – a pivotal step for a thorough definition of your audience, helping you understand their evolving preferences and guiding our marketing strategies.
Traditional demographic factors like age and geography are becoming less relevant. It's now possible for a wealthy twenty-year-old and a forty-year-old with the same means, living on opposite sides of the globe, to share similar interests in terms of products, experiences, and content consumption. Their world views may differ, but in terms of sales, marketers are more concerned about their consumption patterns.
Use AI platforms like Sprout Social for social media analysis, OTT platforms like Netflix's recommendation system, and consumer apps like Amazon's AI-enabled features,
to help identify user segments, behavior patterns, and preferences based on various characteristics including age, gender, occupation, education, and geographic location. You'll be able to identify content trends for each audience group and search-related trends, enabling more targeted marketing and advertising campaigns. For example, an online clothing store, may discover that:
- Users aged 18-24 from urban areas prefer trendy streetwear and are most active on Instagram and TikTok.
- Users aged 25-34 with office jobs show interest in formal wear and are primarily active on Facebook and LinkedIn.
With these insights, the store could create targeted marketing campaigns for each user segment:
- For the 18-24 age group, it could create Instagram and TikTok ads featuring its latest streetwear collection, with influencers modeling the outfits.
- For the 25-34 age group, it could run Facebook and LinkedIn ads showcasing its range of formal wear, highlighting quality, and emphasizing work-appropriate styles.
Leveraging AI for a Future-Proof Marketing Strategy
Artificial Intelligence serves as a compelling resource for marketers looking to define their audiences precisely. It can help anticipate customer behavior, identify untapped user segments, and customize content to match prevailing trends. More importantly, through the transition from the era of cookie-based data to an AI-driven approach, marketers will find that the ability to understand and engage with audiences only becomes richer. By exploiting the wealth of first-party data and leveraging AI, information is able to be transformed into actionable intelligence, ushering in a new era of audience definition that transcends traditional reliance on cookies.
About the author:
Senthil Ayyappan is Chief Sales and Marketing Officer at Qualitest, the world’s leading AI-powered quality engineering company. A digital transformation expert with a client record as diverse as HP, Bank Of America, American Express, Cadbury, Albertsons, GAP, Young Living, AIG, and AT&T. He has spent a good part of his career helping retail and consumer goods enterprises transform Omnichannel customer experience and use bespoke technology solutions to gain a competitive advantage. His dedication to Qualitest has helped the company gain global recognition, including two Stevie Awards in 2023 for “National Sales Team of the Year” and “Sales Turnaround of the Year.”
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.