According to Adobe’s 2019 Consumer Content Survey, 83 percent of consumers say they’ve received content from brands that aren’t personalized, with more than one-third of consumers saying this happens constantly or frequently. For brands, this is a huge opportunity missed. Especially considering approximately half of those consumers say they’re more likely to become loyal to the brand if the experience is personalized.
To successfully deliver personalized experiences, our Adobe Target customers are doubling down on their experience optimization programs and leveraging the power of Adobe Sensei, our AI, and machine learning technology, for faster results. And they’re seeing success. Last year, Adobe Target had a hand in generating $165 billion in revenue for customers (a 29 percent increase over 2017) and deliver personalized experiences to 73.4 billion visitors.
We’re excited to introduce new innovations in Adobe Target that help marketers deliver more impactful, personalized experiences to their customers, and help IT professionals collaborate more effectively with marketing teams on delivering those experiences.
Recommendations are one of the most powerful personalization tools that marketers can use to increase sales and customer engagement. Yet scaling personalized recommendations to a variety of audiences is a consistent challenge. To help marketers overcome this, Adobe Target is developing a new ‘Weighted Relevance’ algorithmic logic that extends beyond the traditional product use cases, providing greater recommendation customization and precision for marketers.
The new ‘Weighted Relevance’ rules leverage sophisticated profile-matching and relevancy weighting capabilities to further refine recommendations based on specific search criteria. For example, a job seeker will see positions most related to their skills and experiences on a job opportunities website. Not only will this feature better allow brands to execute their personalization strategy at scale, it will also empower them to make people-centric decisions that drive consistently better actions.
Last year, we announced the availability of the new Personalization Insights Reports, which transparently shows the work that the Automated Personalization and Auto-Target algorithms are doing. Now with new enhancements to the Personalization Insights Reports, users will be able to see the actual relative lift the algorithm is delivering based on a specific experience it delivers. For example, a marketer for an airline will be able to see the relative conversion and revenue lift that each offer or recommendations carousel is delivering above the default mobile page or app screen. This informs better optimizations for audience-level and individual experiences with guidance from machine-learning insights.
We’re thrilled to see significant, broader adoption of mobile app personalization as companies see improved app retention, engagement and conversion for their most loyal customers through delivering a tailored app experience. For example, a drugstore is using automated personalization to automate the ranked-order of their app’s navigational icons based on an individual’s primary uses. We’re also seeing great strides in location-based personalization services. For example, a major hotel chain is using Adobe Target to trigger personalized screens with recommendations of amenities and upgrades throughout their property.
We want all of our customers to achieve maturity in their personalization programs and are excited to release the next version of the Adobe Target Personalization Maturity Model.
With our latest Maturity Model, any marketer – Adobe Target customer or not – can assess the current effectiveness of their personalization efforts or programs. The updated maturity model and self-assessment include enhancements that enable customers to better evaluate their progress and set benchmarks for growth. The end result is a detailed report with clear suggestions on next steps in terms of governance, process and expansion of use cases. We’ve also updated the language and suggestions within the maturity model to support greater speed and scale.
Our Consumer Content survey also unveiled more than one-third of consumers say slow page loads frustrate them most when it comes to digital content experiences, and more than half would stop viewing the content all together if it takes too long to load. So, it makes sense that companies are turning to single page application frameworks (SPAs) to increase the speed, fluidity and responsiveness of certain areas within a digital experience to enhance customer experiences. We’re excited to release a new solution for SPAs within Adobe Target that includes:
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