Consumers, by and large, have grown accustomed to being targeted by multiple touchpoints by a brand or advertiser. With this acceptance comes a greater demand that all these touchpoints are seamless. Makes sense from the consumer’s POV, naturally. For example, a potential customer sees an ad while scrolling or streaming, visits a physical or digital location to make a purchase, and chats with support or an agent for help. There’s a reasonable expectation from that consumer that, as they toggle through all those different channels, it should remain a single, cohesive experience with a brand.
Ensuring this level of cohesiveness has, historically, been a significant hurdle for brands to overcome. With the introduction of AI-powered audience systems, brands can solve this issue by connecting data, behavior, environment, and creative in real-time. The integration of orchestration, data observability, and personalization will enable brands to strategize and execute successfully across channels.
Unified orchestration
A proper omnichannel approach requires all segments to tie back to a single customer profile, a source of truth. AI orchestration engines are fast becoming a crucial connector for omnichannel audience management, specifically because they can provide this approach. They can manage the cadence, strategy, and delivery of potential touchpoints for each potential customer. By serving as the backbone for omnichannel management, AI orchestration enables faster routing and segment adaptation, delivering a higher return on ad spend and providing a true competitive differentiator.
Real-time adaptation
An omnichannel approach should not be static. The approach of looking at a user and assigning them a cohort and flight for a specific touchpoint is not an effective strategy. AI models now allow for dynamic behavior steering. A user’s live signals, such as app usage or a recent store visit, are continuously ingested by AI models in real-time and can help dictate which channel should be prioritized to deliver the next best experience. In essence, AI is eliminating the lag between an insight and the following logical action.
Data quality & observability
A significant obstacle in omnichannel management is data quality. Data pipelines can drift or break – for example, a latency issue between a point-of-service and the cloud. These potential lags or data mismatches can lead to misleading decisions and negatively impact personalization efforts, such as serving an offer to a user after they have made a purchase.
AI-powered audience systems are now providing brands and advertisers with an unmatched level of observability. These tools monitor for the freshness and completeness of user data across multiple systems, including POS, apps, and support sessions. A more informed trust layer in the data enables intelligent feedback loops that can detect any potential misfires in personalization.
Offline to online bridging
AI-powered audience systems enable the connection of in-store activity to digital audiences, facilitating omnichannel retargeting. Brick-and-mortar foot traffic, in-store app scans, and offline purchase logs enable brands and advertisers to retarget and present personalized offers or interactions. Several retailers have already begun deploying smart in-store media, such as displays or digital shelves, that integrate and synchronize with external ad platforms, allowing for an authentic, cohesive, and seamless offline-to-online experience for users.
AI creative orchestration
AI is not only allowing for fine-tuning and automatic adaptation in terms of when and where users are being targeted, but also enabling generative AI models to produce creative variants that are explicitly tailored to user traits and context. Leveraging unified orchestration, creative generation dovetails with user logic. Specifically, ‘what’ is being displayed moves in concert with the ‘where’ and ‘when’, keeping message and tone consistency intact. Brands can scale personalization to new levels without sacrificing unified messaging across channels.
Key Takeaway
AI-powered audience systems are transforming how brands execute omnichannel personalization. By unifying data, improving observability, and enabling real-time creative and behavioral adaptation, brands can finally deliver the seamless, contextually aware experiences consumers expect, and drive measurable revenue growth in the process.
Next Steps
AI-powered audience systems are revolutionizing omnichannel management, giving early-adopting brands a competitive edge. Brands seeking to optimize their current systems for AI integration should:
- Identify and address any potential data and touchpoint disconnects and develop a plan to integrate them for unified, real-time orchestration.
- Consider investing in tools and solutions that provide the level of data observability needed to identify potential blind spots.
Explore the Future with ADvendio
At ADvendio, AI is an integral part of our solutions moving forward. That’s why we’re exploring a future where AI transforms how teams sell, operate, and scale. Explore the possibilities and our latest vision for AI here.
