Imagine you’re on a cruise and every preference and every need is anticipated. When you’re hungry, you’re offered the turkey club you were thinking about, and when you’re bored, you’re offered the best activity suggestions. That’s what Carnival Cruise Line is hoping to achieve with its new Ocean Medallion Class offering. The experience is built to be seamless and personalized so guests don’t have to think about anything else but enjoying their vacations.
More and more, consumers are demanding this level of personalization all the time and it’s more important than ever for companies to work tirelessly to deliver it. Why? Simple. Because if you don’t deliver it, consumers will go elsewhere. However, many brands are challenged with the scale of the undertaking required to deliver a truly tailored, one-to-one customer experience. The only way to achieve this is with sophisticated artificial intelligence (AI) and machine learning technology.
That’s why today we’re proud to announce new Adobe Target capabilities, powered by Adobe Sensei. These new enhancements give marketers the tools to optimize personalized experiences with one click, enhance customer recommendations and targeting precision, and automate the delivery of personalized offers.
At Last… One-Click Personalization
We’re on a mission to ensure brands deliver only the best experiences to individual customers at scale. Our solution? The new Auto-Target feature in Adobe Target Premium. Now with a single click, marketers can leverage powerful machine learning, powered by Adobe Sensei, to introduce as many experience variations as they choose in order to personalize across their digital properties. One beta tester in the financial services industry described it this way:
“Auto-Target allows us to do personalized A-B-C-D page level testing algorithmically. The advantage that we see over traditional testing is that the machine will take all variables and traits about a visitor into consideration—not just the traits and segments that we deem important.”
Auto-Target automatically determines the best experience for each consumer and continuously optimizes those experiences over time as the consumer takes additional actions. A hotel chain for instance can feature its tropical properties and content for a reward member, knowing the individual prefers to travel to warm destinations based on bookings and mobile app engagement. The end result is higher engagement and increased loyalty.
Auto-Target is also designed to improve experience performance over time by learning what does and does not resonate with consumers. This ensures customers receive only the most relevant experiences. As such, brands can go even further with their personalization efforts without having to worry or feel like they’re taking risks with their valuable traffic. Thanks to the backup policy feature, marketers can always be assured that no variation will do worse than their best control. The result is that the best experiences will only get better.
Auto-Target is now generally available today to all Adobe Target Premium users.
Powerful Recommendations Inspired by Natural Language Processing
Recommendations are one of the most popular and effective forms of personalization used in digital consumer experiences. In fact, Amazon’s recommendations reportedly drive 30 percent of its revenue. However, recommendation engines are not all created equal, and as a result, some fail to deliver real-time relevance that can scale across billions of consumer interactions.
Adobe Target already offers a robust set of out-of-the-box algorithms that predict the content, offers and products customers want. To bolster these algorithms, we’re proud to unveil new powerful technology for item and product recommendations using techniques based on natural language processing (NLP). An industry-first application, this technology uncovers the underlying intent of consumers’ behavior to better predict what content and products customers might want next.
Here’s how it works. Think of every digital interaction a consumer has with a brand, be it reading a blog post or watching a video, as part of a dialog. Now think of the sum of these actions as a query or a meaningful expression of intent. At the machine level, Adobe Sensei is interpreting these queries and figuring out how to respond. Adobe Target takes it from there by displaying recommended products or content—ones that are highly relevant to a consumer based on what we’ve learned about them throughout this dialog.
For example, a retailer can see that a customer watched its video on eco-friendly laundry techniques and purchased compostable dryer sheets. It can then provide a tailored recommendation about eco-friendly detergent based on what was inferred from the customer’s previous actions. Previously, the algorithm would have offered up a laundry detergent recommendation based on detergents other people viewed. The new recommendations technology will be available in beta this Fall.
Automate the Delivery of One-to-One Offers
Delivering the perfect offer requires tons of data culled from a number of sources. Going through and making sense of that data is simply too much for any human to handle. With the enhanced decisioning power in Adobe Target, marketers can now determine the right offer—out of potentially hundreds of potential offers—and automatically ensure it’s always shown at the right moment to the right person.
For example, a financial services company uses Adobe Target’s self-learning models to serve up dynamic offers like mortgages, credit cards and online bill pay—all based on each individual’s previous browsing paths, account status, search terms and other factors. A new homeowner who has recently secured his first mortgage will have a very different online experience than a woman approaching retirement. Adobe Target now provides automated offers for mobile apps and IoT experiences.
More Precise Targeting with Adobe Analytics Cloud
Developing a one-to-one connection with customers is the holy grail of personalization, but this cannot be done without building a complete 360-degree view of an individual. Marketers already utilize visitor behavioral data in Adobe Target to create comprehensive real-time personalization profiles. Now with tighter integration between Adobe Target and Adobe Analytics Cloud, marketers can utilize behavioral analytics and audience data to inform deeper segmentation. With up-to-the-second, comprehensive data, marketers can conduct more precise targeting to continuously serve the most relevant, personalized experiences possible.
Additionally, now with the new Experience Versions capability in Adobe Target, marketers can granularly A/B target specific content areas in an experience, like an offer box on a website, by applying multiple audience and behavioral segments from within Adobe Analytics Cloud to the experiment. For example, a global cookware company can develop a targeted offer on its website based on segments of people who’ve purchased a cast iron skillet in the last five months. That offer then automatically updates with the correct language or currency depending on the location of the customer, be it in the United States, France or Germany.
Our goal has always been to help our customers deliver incredibly spot-on experiences for their customers. And now, with these exciting advancements, we’re able to do even more, and help them move that personalization needle further than ever thought possible.
The post Adobe Unveils New Sensei Capabilities in Adobe Target to Power Personalization appeared first on Digital Marketing Blog by Adobe.
from Digital Marketing Blog by Adobe https://blogs.adobe.com/digitalmarketing/personalization/adobe-unveils-new-sensei-capabilities-adobe-target-power-personalization/
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