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Cutting Across Adobe Experience Products with Machine Learning to Elevated User Experience

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NimashaJain
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NimashaJain
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24-10-2021

Authors: Abhishek Shukla, Sidharth Chaturvedi, and Per Andreasen

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This post describes the experiences of the ExCelerate team in the 2019 Adobe India Hackathon. This user experience-focused team did their best to deliver a more personalized user experience for customers on the Adobe Experience Platform.

This blog details a single implementation or customization on Adobe Experience Platform. Not all aspects are guaranteed as general availability. If you need professional guidance on how to proceed, then please reach out to Adobe Consulting Services on this topic.

When you log into Adobe Experience Cloud, you are typically met with the same landing page that varies a bit depending on the products you have access to. This makes it easy for novice users to get the hang of setting up their user interface and navigating through it, taking advantage of some of the basic features on the platform.

However, as each user gains more knowledge and experience working on Adobe Experience Cloud, they could grow tired of seeing the same guides. To keep these users engaged in learning new skills, it is important to inspire them with complex and unusual use cases. For instance, an expert in Adobe Analytics might want to learn how to integrate with Adobe Campaign or Adobe Target to leverage multi-product use-cases.

When users have completed the suggested guides, they need new ones to level up their proficiency. If they cannot find them easily, their user experience suffers. That is why one of the Adobe Experience Platform product managers reached out to us before Adobe India Hackathon 2019 and asked us to look at the user interface of the platform. The net promoter score and our customer advisory board alike helped us learn that there was indeed a need for more personalization.

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The current home screen on Adobe Experience Cloud has a very low degree of personalization. It shows learning content relevant to the products the user has access to.

Intermediate and expert users of Adobe Experience Cloud have to search through the platform’s help content to find more learning content relevant to them. Some users have found that some content they wished for was completely hidden. It goes without saying that this makes for a less than optimal user experience. Instead of spending their time making better solutions with Adobe Experience Cloud, users risked wasting a lot of time just searching for the knowledge they needed.

That is why we decided to take part in the Adobe India Hackathon 2019 and come up with a way of improving the user experience. We wanted to use the powerful machine learning capabilities within Adobe Experience Platform to bring the most relevant learning content to each user.

Making users more effective and content

With our hack, we wanted to help Adobe Experience Cloud users get superior user experience and higher value out of time spent on the platform. By adding simple “like” and “dislike” features to each learning content card, we wanted to let users dismiss cards that they see as irrelevant or repetitive. The machine learning within Adobe Experience Platform is really impressive and gets better as each user advances through documentation and tutorials. The extra feedback of dismissal of the content doesn’t add a lot of valuable feedback to the machine learning, but it does improve the user experience tremendously by taking unpredictable personal preferences into account.

A mock-up for the like vs. dislike feature to help users tweak their experience.A mock-up for the like vs. dislike feature to help users tweak their experience.

Our team consisted of Abhishek Shukla, a senior product manager with Adobe Experience Cloud, and Sidharth Chaturvedi, an experienced engineer. The other participants in the Adobe India Hackathon 2019 all represented specific Adobe products. We’re different. In our daily work lives, we are part of the team we call “ExCelerate”. We’re close to 100 employees strong division within Adobe Digital Experience and focus solely on user experience solutions that cut across all Adobe platforms. This meant that our approach to and outcome from the hackathon was quite different from those of the other groups.

Just like our fellow hackathon participants we wanted to leverage the possibilities in Adobe Experience Platform and prove the feasibility of our solution on the platform. But unlike them we also wanted to build something that could work for any Adobe Digital Experience product. Usually, we work with Adobe Experience Cloud, so our knowledge of Adobe Experience Platform was very limited until we began to prepare for the event. We did look into the features that we could leverage on the platform and found it easy to get started on the platform.

Cleaning huge data sets with machine learning

The hackathon gave us a unique opportunity to come together with colleagues from all over the world — in real life and virtually via video connections. It was an amazing and fun experience to be in a room with other passionate Adobe employees each working hard on their own exciting solutions. All the participating groups accomplished a lot in a very short time. This also helped make it clear to us that there is great potential in collaborating on Adobe Experience Platform.

In the “ExCelerate” team, we had captured the user behavior data in Adobe Experience Cloud and streamed it into Adobe Analytics that then passed it on to Adobe Experience Platform. The platform makes it easy to get an overview of accessed content, time spent on each solution and much more. We leveraged Adobe Experience Platform to cleanse the huge dataset that we collected and apply machine learning to create user classifications. Based on the classification we could check how each user was scored as either novice, intermediate or advanced.

We knew ahead of the hackathon that we might not reach a live demo before the end of the week. But our hope was to use the time validating the use case and creating a roadmap. Even though we would have liked to go a lot further, we were happy with the progress we made. It also made us excited to see the other Adobe engineers so aligned with our hypothesis and supportive of our efforts. We got a lot of valuable learnings and enthusiastic support of all our colleagues that we can use in the work ahead of us.

A clear road map to production

Personalization is now part of the product roadmap and is expected to be further developed in the second half of 2020. Because this solution cuts across products, we will enjoy additional collaboration with product managers for the relevant Adobe platforms.

Our first target will be the Adobe Experience Cloud home page, where we are very eager to see the solution working.

Follow the Adobe Experience Platform Community Blog for more developer stories and resources, and check out Adobe Developers on Twitter for the latest news and developer products. Sign up here for future Adobe Experience Platform Meetups.

Resources

  1. Adobe Consulting Services Adobe Consulting Services
  2. Adobe Experience Cloud — https://www.adobe.com/experience-cloud.html
  3. Adobe Analytics — https://www.adobe.com/dk/analytics/adobe-analytics.html
  4. Adobe Campaign — https://www.adobe.io/apis/experiencecloud/campaign.html
  5. Adobe Target — https://www.adobe.com/dk/marketing/target.html
  6. Adobe Experience Platform — https://www.adobe.com/experience-platform.html
  7. Net promoter score — https://blogs.adobe.com/digitaleurope/customer-experience/using-net-promoter-score-in-a-customer-exp...
  8. Customer Advisory Board (CAB) — https://theblog.adobe.com/3-ways-to-get-more-from-your-customer-validation-program/
  9. Machine learning — https://www.adobe.com/sensei.html

Originally published: Apr 23, 2020