Adobe has today unveiled Intelligent Services, powered by the AI capabilities of Adobe Sensei. Built on Adobe Experience Platform, the new services will help brands overcome common challenges associated with AI, including the lack of AI expertise and implementation complexities.
The new Intelligent Services will be able to stitch together unstructured data under a common language. Strict governance features available in the platform help brands more easily stay ready for industry regulation and corporate policies for consumer safeguards. And a self-service interface delivers flexibility, allowing users to configure the services for use cases specific to Customer Experience Management (CXM).
Visual computing company NVIDIA, one of the first to leverage Intelligent Services, is using Attribution AI service to understand the effectiveness of their marketing programmes, using insights to drive five times more registrations to event campaigns. With Customer AI, NVIDIA is gaining a better understanding of how consumers are engaging with its gaming products and drive more personalised content for users. Lastly, NVIDIA also enjoyed a 14% lift in email open rates after using Journey AI’s predictive insights to enhance the effectiveness of email campaigns.
“There’s no denying that AI is already empowering brands to deliver more relevant experiences. But the truth is, they still haven’t reached full potential within most organisations,” said Steve Allison, Head of Product Marketing, Audience and Platform Technologies, EMEA. “Our new Intelligent Services will empower brands to dig even deeper into their data and generate statistical insights that will benefit the entire customer experience – and because they’re available in one centralised area on Adobe Experience Platform, teams can make changes to campaigns with more agility and speed than ever before.”
New Intelligent Services on Adobe Experience Platform will include:
- Customer AI: Brands often do not have resources to dig deep into their data and understand the underlying reasons behind customer actions. Customer AI helps them analyse historical and real-time data across the business to address this, creating propensity scores for key events like churn or conversion. A subscription service for example, could receive a segment of users likely to unsubscribe due of price sensitivity and engage with a custom promotion.
- Attribution AI: Marketers have multiple touch points with customers (e.g. web, email or social) that require resource and time investment. Attribution AI empowers teams to quantify the incremental impact of each touch point, using an advanced approach to measure true marketing effectiveness and inform budgets. It is unique from rules-based methods, where often too much credit is given to “first-touch” (e.g. web visit) and “last-touch” (purchase event), leading to artificial rules that could skew decision-making.
- Journey AI (Beta): Even loyal customers have a patience threshold when it comes to marketing. With more channels than ever, knowing when to engage and managing fatigue has become a bigger focus. Journey AI will help brands predict the best time, frequency and channel to market to customers. This includes a fatigue score, which can be used to gauge engagement for consumers. A retailer for example, can use this ahead of festive shopping seasons to manage promotions.
- Content & Commerce AI (Beta): Brands have embraced the idea that creative also needs to perform well. Content and Commerce AI delivers guidance on variables that result in high performance, such as colours or subjects. It also takes on the task of automatically tagging assets, for better searchability in the production stages. On the eCommerce side, the AI will automate product recommendations based on real-time signals and customer preferences.
- Leads AI (Beta): B2B marketers have unique challenges when it comes to engaging prospects and existing customers. Long sales cycles make it difficult to see the impact of ongoing marketing and where prospects are in the purchase journey. Leads AI uses real-time behavioural signals to help brands predict leads that are likely to turn into tangible opportunities. It can enable an enterprise software vendor for instance, to drive targeted campaigns with better personalisation. .
Adobe has been leveraging Intelligent Services internally as well and we have seen some great results. It powers our data-driven operating model (“DDOM”), a framework that drove our transformation from box software to the cloud. Over 1.5 billion propensity scores are produced daily, showing how likely customers are to take a particular action (e.g. unsubscribe) and generating target audiences that have been up to five times more valuable.