As businesses navigate the dynamic landscape of e-commerce, the pursuit of strategies to refine their digital presence and enhance sales is never-ending. Among these strategies, remarketing has proven to be an effective method, and the integration of artificial intelligence (AI) and machine learning (ML) has driven its impact to unprecedented levels.
This seamless integration of technology and marketing strategies not only revolutionise how businesses reconnect with their audience but also establishes a new paradigm for optimising online conversions.
The Power of Remarketing
The software-as-a-service (SaaS) company, Appier, revealed that the global average conversion rate on e-commerce sites hovers around 2.6%. This underlines the great growth potential in online sales. Remarketing, a practice aimed at re-engaging with potential customers who have shown interest but not converted, stands out as a powerful strategy to boost return on investment (ROI).
Traditionally, remarketing involved targeting users with ads showcasing previously viewed products, encouraging them to return and complete the purchase. However, the emergence of AI has revolutionised this approach, offering more sophisticated and targeted methods to reconnect with audiences.
AI-Enhanced User Segmentation
Traditional segmentation for remarketing faces challenges in accurately linking individuals with the right products, especially after user log out. AI comes to the rescue by leveraging ML to interpret user data, analyse purchase history, and identify patterns predicting future behaviour.
Platforms like Appier’s CrossX Programmatic Platform use deep learning algorithms to analyse real-time user behaviours. This enables marketers to prioritise retargeting efforts towards users with a higher likelihood of converting, resulting in a more efficient and effective strategy.
Personalised Recommendations for Increased-Conversions
AI’s ability to analyse user behaviour and product information allows for the generation of personalised recommendations, significantly improving conversion rates. By distinguishing between genuine shopping behaviour and simple browsing, ML ensures that users are retargeted based on their likelihood to convert.
Benefits of optimising remarketing with AI include:
- Retargeting Real Shoppers: ML distinguishes between genuine shopping and casual browsing, allowing more focused efforts on users likely to convert.
- Capturing Fast-Changing Behaviours: ML identifies patterns and predicts changes in shopping behaviour, providing insights into short-term shifts and enabling timely retargeting.
- Precision in Retargeting: AI helps differentiate between serious purchase intent and casual online exploration, ensuring more relevant and targeted ads.
Adding Value across the Customer Journey
Remarketing, powered by AI, offers continuous value throughout the customer’s online journey. By making relevant recommendations based on past behaviour and data across e-commerce sites, AI expands the range of products exposed to the consumer. This helps marketers to retarget users with products similar in function, design, or other relevant attributes.
Cross-screen remarketing, eased by AI-powered platforms like CrossX, further strengthens the approach. It allows marketers to reach users on every screen they own, reducing the time between the initial visit and purchase.
Using AI in Remarketing
While the terms retargeting and remarketing are used interchangeably, retargeting typically refers to paid ads. Remarketing, on the other hand, is associated with email.
AI offers a smart “prediction machine” that processes and analyses data faster than humans. In retargeting, AI facilitates advanced targeting, testing, and predictions.
Improving Audience Targeting
AI’s segmentation capabilities allow for precise audience targeting based on factors like new vs. repeat customer, channel, page depth, and product interest. Custom audiences with individual predictions enhance the efficiency of retargeting efforts.
Dynamic Ad Creative
AI helps personalise ad elements, such as CTAs, headlines, visuals, and more. Real-time processing and scalability contribute to faster testing and iteration of creative elements.
Retargeting ads with personalised offers tailored to individual users can significantly impact the success of your digital strategy. AI helps in laser-targeting each offer, preventing ad fatigue and increasing engagement.
AI processes past and real-time data to optimise bidding strategies. It determines how much to spend on individual users, considering factors like ad type and the user’s position in the buying journey.
Time and Cycle Extensions
AI excels in determining Days to Sale (DTS), helping in crafting retargeting strategies around each user’s conversion timeline. Real-time insights allow marketers to adapt strategies based on individual behaviour.
Controlling ad frequency based on user behaviour and buying journey is crucial. AI enhances frequency capping by offering real-time adjustments and insights for more effective ad delivery.
Retargeting proves to be effective at reactivating users who have unsubscribed or show decreased engagement. AI tracks customer journeys and adjusts strategies in real-time, enhancing reactivation efforts.
Automatic Delivery Services
Retargeting can effectively target users for automatic delivery services. AI assists in identifying the optimal timing and creative elements for targeting users interested in subscription-based services.
Using retargeting to promote loyalty or rewards programs is a viable strategy. AI helps in pinpointing potential participants, creating personalised offers, and optimising the retargeting process.
AI facilitates extensive testing of different variables in retargeting strategies, including budgets, creative elements, messaging, and more. Real-time adjustments based on AI insights lead to improved advertising performance.
Tailoring retargeting efforts for social media users requires a nuanced approach. AI helps profile users and optimise retargeting efforts based on social channel behaviour.
AI can enhance visitor tracking initiatives by processing data in real-time and at scale. Combining AI with existing tracking methods allows for more effective and efficient retargeting.
Introducing merchandise-switching strategies involves testing different products based on user browsing and purchase history. AI helps in identifying suitable products and developing retargeting ads around new offerings.
AI-driven strategies in remarketing empower businesses to reconnect with their audience in more personalised and effective ways. By implementing these proven tips, marketers can optimise their retargeting efforts, enhance customer engagement, and ultimately drive higher conversion rates in the competitive landscape of e-commerce.
Check out our AI Hub to learn more about how to leverage AI for your digital marketing strategy!