Product Communities

Authors: Justin Ross, Douglas Paton In this post, we look at how we helped customers move their data out of Adobe Experience Platform for use in other systems. We explore the challenges of working with an international team and how we used a generic solution that could be used by anyone. Users of Adobe Experience Platform produce incredible amounts of data. This data can help them get powerful insights into their customers across all channels. Once they get that data out of Adobe Experience Platform, that data can then be used to make decisions based on the insights gained from the data. The challenge was that, although there are many ways to get into Adobe Experience Platform to generate data, exporting the data to other systems wasn’t nearly as easy. There was not a good way of getting data out of Adobe Experience Platform. We needed to build a way to enable activation, which is the capability of exporting data into other platforms, on Adobe Experience Platform. We needed to come up

Authors: Manoj Thakur, Abhishek Shukla, Atul Shrivastava, Som Satapathy, Anup, Balaji K, Per Andreasen This post describes the experiences and outcomes of an intensive hackathon put on by Adobe Experience Platform India team. Adobe engineers came together to develop five innovative applications that secure better ROI, improve UX and strengthen machine learning. In December 2019, several developers from Adobe Experience Platform’s engineering team in India participated in an intensive internal hackathon. In just one workweek, five new and innovative platform solutions came to life. As developers, we can easily stick to proven routines, especially in times with high workloads. We knew that Adobe Experience Platform needed to be top of mind in our daily work lives as it can take customer experience to the next level and solve problems at scale in real-time. That is why we decided to organize a hackathon for Adobe engineers in India. But we had not dared hope for as much innovation as we

Authors: Keerthika Koteeswaran and Jenny Medeiros This post describes the challenges of data warehouse testing for Adobe Audience Manager and walks through the in-house functional test framework we developed to solve them. As a leading data management platform, Adobe Audience Manager processes billions of real-time and batch events every day. This data is then transformed into comprehensive reports to help marketers deliver custom experiences to the right audience. To ensure the accuracy and reliability that is expected of these reports, we must first verify that the data itself is correct, complete, and in the right format. This is achieved through diligent data warehouse testing. The testing process, however, is largely manual and notoriously difficult due to the tremendous scale of ingested data. As a result, comprehensive testing is practically impossible, which leads to weakened data integrity and a higher risk of bugs slipping into production. To counter these challenges, we dev

Authors: Costin Ochescu, Ciprian Barbieru, Cornel Creanga, and Jenny Medeiros This post describes how we proactively improved the cost and efficiency of data processing within Adobe Experience Platform by redesigning one of its key data processing services: Siphon Stream. Check out Part 2 here. Adobe Experience Platform is home to an increasing number of customers who rely on its ability to process tremendous amounts of data in real-time. To maintain the pace that new and existing customers expect, we set out to proactively improve Siphon Stream, a key component within Adobe Experience Platform that is responsible for much of the streamed data processing. This post details the challenge we faced, thought processes, and subsequent solutions that ultimately tripled our application’s performance and greatly reduced operational costs. What is Siphon Stream? Siphon Stream is a component within Adobe Experience Platform responsible for taking the streaming data sent by Adobe solutions (i.e.

    This post will walk you through how to use the merge endpoint to merge people in bulk with Python code that will allow you to set custom rules for how you want to prioritize conflicting values for the same fields on different people.     If it is your first time using the API or you need a quick refresher then check out the Quick-Start Guide to the API to see how to make your first API requests in Postman before transitioning to making requests in code or in the Zapier automation tool.   Also if you are looking for a course for learning the Marketo API then DM me 🙂   You can find the main Python script and all the supporting functions linked in the paragraphs below in the Bulk Merging Github repository.   Supporting Functions   Getting Access Token The getToken function makes a get request to the token endpoint, passing the client id and client secret, to return the API access token, and the length of time that t

Hey Guys, Happy to share with you the article part 3 out of 8 - OSGI Package Import and Exporthttps://www.techinnovia.com/package-import-and-export/1. Maven Bundle Plugin2. Bundle Customization in the Plugin3. Maven Version at the Same Time4. Bundles and Libraries5. Summary Feel free to share your feedback on blog 😉  Happy Learning!Cheers!

I think I have some dependency conflicts.  I am using asset share commons as a dependency in my project.  After a code change, I keep having this error :  I am using this version of asset share : 2.0.6 And sdk version : 2021.7.5662.20210726T181801Z-210600 Any help please ?? 

Hi, may I kindly request anyone to suggest on my issues,How can I track the canceled reservations or booking for a hotel website? As I can see, I couldn't see the accurate results of cancelations in the adobe report.I am new to adobe appreciate your support if anyone could help me to overcome the challenge.  RegardsAnil 

Authors: Rohan Kapoor, Biswajit Chakraborty, and Rameen Taheri In a previous post on Adobe Experience Platform Web SDK, we introduced our all-in-one JavaScript library designed to streamline how customers interact with the various Adobe Experience Cloud services. In this post, we explain how customers can safely transition to the new SDK and how to navigate common migration scenarios. The underlying technology for collecting users’ behavioral data online has evolved tremendously since the time of hit counters and log files. Since the pivotal introduction of JavaScript (JS) tags back in the late 90s, the web analytics industry continues to use them along with other languages to capture clicks and page impressions, track interactive video players, and build native mobile apps. On the front-end, however, customers increasingly expect simpler and more unified digital experiences across web and mobile. To fulfill this expectation, the industry must once again evolve the way it delivers and

Authors: Mathieu Hannouz and Douglas Paton In this post, we look at how we can create one-to-one experiences in real-time using Journey Orchestration on Adobe Experience Platform. We examine possible use cases for Journey Orchestration and explore what’s going on behind the scenes. In today’s highly competitive online world, being able to deliver a personalized online experience in real-time is increasingly important. Reaching users in a unique and personal way helps create a stronger connection between them and you and increases the likelihood that they’ll stay loyal to your brand. Offering these types of experiences to visitors on any of your properties gives you that competitive edge you need to stand out in this crowded world. Luckily, we live in a data-rich world. We can use that data to deliver unparalleled consumer-initiated experiences both online and offline. In the Adobe ecosystem, we use Journey Orchestration to make this happen. Journey Orchestration is a new application-s

Authors: Anup Kumar, Pankhri Singhai, Saurabh Gupta, Akshit Jain, and Per Andreasen A team of Adobe Campaign developers created a proof of concept for an exciting integration between Adobe Experience Platform and Adobe Campaign Classic at the Adobe India Hackathon 2019. Adobe Campaign Classic is a powerful tool for marketers. It lets you handle large audiences with personalized messaging on the platforms and at the time that each member of your audience prefers. The larger your audience, the greater the value Adobe Campaign Classic has. But the limit of your audience managed in Adobe Campaign Classic is 100 million members, which has kept many large marketers from taking advantage of it. So, a team of Adobe Campaign employees decided to take part in India Hackathon 2019 and show that Adobe Campaign Classic can be used as an activation channel for Adobe Experience Platform. Without the use of Adobe Experience Platform it takes roughly 48 hours to ship a segment from Adobe Analytics to

Authors: Yan Li and Jenny Medeiros Mentorship is a rewarding experience that can drive professional and personal growth for both mentor and mentee. As we all work from home without knowing when we will meet again, building on these precious connections is more important now than ever before. In this post, we share practical tips to help you enhance your mentoring relationship and accelerate your mentee’s development both in and out of the office. Mentorship can play a pivotal role in the success of a developer’s career. It’s not easy for newcomers to navigate the software industry, and pairing an early-stage developer with an experienced advisor can accelerate their professional growth, expand their network, and acclimatize them to the organization’s workplace culture. Within the Adobe Experience Platform mentoring program, we understand that mentors can guide, inspire, and empower developers to reach their full potential, which in turn brings greater success to the organization. Lead

Authors: Rares Vlasceanu, Florentin Simion, and Jenny Medeiros This is the first of a three-part series in which we re-introduce developers to Kotlin as an alternative for building server-side applications. In this post, we focus on the advantages of Kotlin and why we prefer it over Java for our own server-side app development in Adobe Experience Platform. With the rise of mobile and modern web applications, backends have evolved from monolithic web containers to a distributed mesh of data-driven applications. Web servers can no longer be limited to simply printing web pages, but must also receive, store and transform data destined to reach user devices in record time. Traditionally, Java was the language of choice for developers building server-side applications targeting the Java Virtual Machine (JVM). But with limited features for today’s modern requirements, Java often results in cumbersome developer experience and a painfully slow time-to-value for many applications. Kotlin is an

Authors: Som Satapathy, Mandeep Gandhi, and Per Andreasen This is a part of a series of Adobe Experience Platform innovations from our recent hackathon in India. In this post, a team of Adobe Experience Platform professionals describes how they used their time at Adobe India Hackathon 2019 to develop a solution to stream inference for real-time scoring to help our enterprise customers improve personalization. Imagine that $5,000 was just transferred to your bank account. Your bank would need to assess swiftly if the transaction was fraudulent or legitimate in order to comply with money laundering laws. In order to make your bank's security procedures truly efficient they have to be able to evaluate thousands or millions of transactions like yours in real-time. But your bank is not the only company that needs a swift security system. Most businesses need it in order to protect them and their employees from fraud, health risks, and many other threats. Machine learning models can score a

Authors: Tina Dilip Soni, Marina Mahtab, Althaf Kudiyama Kandi, and Douglas Paton In this post, we take a look at exploratory data analysis in Adobe Experience Platform. We talk about what it is and its importance to enterprise customers striving for better customer experience. This post describes how exploratory data analysis is done in Adobe Experience Platform. Exploratory Data Analysis (EDA) is a critical step in data science that allows us to perform initial investigations on the data to discover patterns, spot anomalies, and to test hypotheses and assumptions with the help of summary statistics and graphical visualizations. It’s analogous to a child exploring new surroundings or a detective investigating minutest details of a crime. There are two main goals with EDA: To get a first look at the data. To display the data in such a way that the most interesting features will become apparent. These features can be used for a machine learning objective. Some of the most important e

Authors: Pinkesh Badjatiya, Nikaash Puri, Balaji Krishnamurthy, and Per Andreasen At the Adobe Hackathon 2019, a team of Adobe developers started working towards a solution to let retailers use Adobe Experience Platform for real-time personalization. Despite all the data available today, even some of the largest retailers in the world are missing out on potential revenue because of slow personalization on their websites. Many retailers can only hope that website visitors who leave without making a purchase will return later and give them the opportunity to deliver a more personalized experience that might lead to a sale. There are two reasons that make real-time personalization challenging: Most personalization models today are built and updated in batch mode and can, therefore, take hours to account for recent user interactions. Personalization models deployed for real-time scoring often use aggregated events for each user. Aggregating these events to build a feature vector for real

Authors: Wouter Van Geluwe and Jody Arthur This post illustrates how brands can use all the available data in Adobe Experience Platform’s Real-time Customer Profile to impact the offline shopping experience with contextual in-store personalization. While consumers have access to an unlimited number of online shops, the importance of brick-and-mortar stores can’t be underestimated. With about 45% of consumers researching online but purchasing offline, it’s increasingly important for retailers to ensure that the offline shopping experience is as exceptional and personal as it is online. Over the last 5–10 years, most retailers have invested in personalizing the online experience through mobile and web with the use of personalization software like Adobe Target. According to the 2019 Consumer Content Survey, Adobe Target had a hand in generating $165 billion in revenue for customers (a 29 percent increase over 2017) and delivered personalized experiences to 73.4 billion visitors. Numbers

Authors: Costin Ochescu, Ciprian Barbieru, Corneliu Vasile Creanga, and Jenny Medeiros This is the second of a two-part series on how we redesigned Siphon Stream, a key data processing service within Adobe Experience Platform, to optimize costs and efficiency. In this post, we dive into the architectural improvements that dramatically enhanced Siphon Stream’s performance. Make sure to read part one here. Siphon Stream is an essential component within Adobe Experience Platform that channels data streaming in from Adobe solutions (e.g. Adobe Audience Manager) through the Adobe Experience Platform Pipeline and into the data lake. With billions of inbound data running through the application every day, we needed to find new ways to improve Siphon Stream’s processing capacity while cutting down on operational costs. In our previous post: Redesigning Siphon Stream for Streamlined Data Processing, we described the approach that led to a 3x improvement in performance. This follow-up post goes

Authors: Jaemi Bremner (#Jaemi_Bremner), Clément Delalande and Diptiman Badajena (#Diptiman_Badaje) In this blog, we investigate how to enrich Adobe Experience Platform Real-Time Customer Profile with indicators calculated from online behavioral data. Using Adobe Experience Platform Query Service SQL functionalities, it is easy to access and analyze raw analytics data to build aggregated key primary indicators (KPIs) which will later be useful for Marketing, Support, and Sales team. The method described below is a production-ready alternative to the computed attributes , which is currently an Adobe Experience Platform alpha feature. Adobe Experience Platform Query Service empowers any data engineer to analyze raw data collected at different steps of the customer journey. Direct access to the Adobe Experience Platform data lake gives the capability to experience makers to derive meaningful insights from customer browsing sessions on web pages or mobile apps to improve customer experien

Authors: Jaemi Braemner (#Jaemi_Bremner), Colin Ratcliff (#colinr75422720), and Rameen Taheri (#RameenT). If you’ve been reading our previous blog posts around how to prepare for the new Adobe Experience Platform Web SDK and the general benefits of the library, you probably have more questions around how this new library will impact each of Adobe’s SaaS products. For this article, we are going to dig a bit deeper and address what potential changes you can expect to see from the Adobe Target platform. What’s the immediate impact on Adobe Target when served through the Adobe Experience Platform Web SDK? First off, as you probably know by now, the Adobe Experience Platform Web SDK will be a unified library, which means there will no longer be a need to call AT.js. All calls will return faster, and as a single packet — drastically lowering load time and browser load. This abstracts Adobe Target calls allowing for a single code source, mean

Authors: Jaemi Bremner, Harsha Ravi (#harshar44917278), Rohan Kapoor (#rohank51858679), and Biswajit Chakraborty Adobe Experience Platform’s release of its new web SDK is bringing a revolutionary paradigm shift in web-based data collection. As you have been reading previous blogs on Adobe Experience Platform Web SDK and its benefits, you might have more questions around the impact on your current Adobe Analytics solution. This blog is going to enable you to deliver better customer experiences via the exciting changes around Adobe Analytics data collection integrated with Adobe Experience Platform. Implementing Adobe Experience Platform Web SDK is expected to significantly revamp the current Adobe Analytics data collection but is expected to bring a great set of benefits starting with faster page performance and reduced latency by using a single, unified JavaScript library. This minimizes data discrepancy as individual Adobe soluti

Authors: Jaemi Bremner (#Jaemi_Bremner), Nav Hothi, and Douglas Paton. In this blog, we continue our series on reducing cost on Adobe Experience Platform with a look at cost optimization. Enterprise CIOs are asked to do more with less and we want to share our learnings. We explore how cost-optimization differs from cost-cutting. And, we break down our process for finding areas we can reduce spend without sacrificing service for our customers. As we talked about in our post on cost management in Adobe Experience Platform, after six years of expansive growth with Adobe Experience Platform Pipeline, we needed to start finding ways to reduce the amount of money it costs to operate. To do this we used a cost optimization process. Cost optimization involves a continuous look at spending. The goal is to reduce spending, without sacrificing service. It differs from cost-cutting because it’s a proactive approach, rather than a reactive approach to reduci

Authors: Jaemi Bremner (#Jaemi_Bremner), Gina Casagrande (#ginabighouse) and Per Andreasen. In this post, Adobe Principal Evangelist Gina Casagrande  explains how demos help drive innovation within Adobe, and how you can level up your own demos to inspire your customers. The world’s largest trade shows and summits are moving online this year to prevent the spread of novel coronavirus. This makes it clear to most presenters and organizers, that it takes something extra to engage your audience from afar. At Adobe, the Evangelist team has been preaching the Adobe tech gospel for many years. Even though we miss the reverb and interaction with our choir of tech believers from a big stage, our years of experience with live demos benefit us now. Whether you are hosting an event that should reach thousands of people in lockdown or want to present new technology to all employees in your group, we want to help by sharing our approach with you. At Adobe Summit 2020 

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Authors: Jaemi Bremner (#Jaemi_Bremner), Wouter Van Geluwe (#wvg_adobe), Jenny Medeiros (#jennyl12901548), and Jody Arthur. This is the first post in a two-part series that explores the challenges faced by CIOs in deciding to build versus buy technology for the enterprise companies. This post provides a clear and comprehensive overview of this debate based on an organization’s needs and expectations, and what CIOs should consider before deciding on the best approach for their team, budget, and business goals. Digital transformation drives brands into the “Experience Era”, where personalized and consistent communication across all channels is no longer just a nice-to-have but a basic must-have requirement. Every organization today is exploring a better approach to designing and delivering exceptional experiences across online and offline channels. This exploration typically leads to an organization deciding to invest in a unified customer profile that relies on machine learning to