Adobe Experience Platform vs. Amperity vs. AWS Elastic Beanstalk

The Adobe Experience Platform is well suited for companies that are maturing or have matured in their digital offerings and are looking for very sophisticated tools to elevate to the next level. It's also for well resourced teams, both financially and head count to take advantage of the deep functionality and integrations.

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I think Custora is a great fit for B2C companies that are trying to take their relationship marketing programs to the next level and outside of basic segmentation. It's a great platform to consolidate all customer, order history, and campaign history type data into one platform to obtain a 360 degree view of the customer. Additionally I would say, if an organization is resource constrained from an analytics perspective, the platform also makes great sense to invest in. It provides out of the box predictive analytics, and custom lifecycle triggers to align a retention marketing program around. Outside of the upfront work to get the platform up and running, it's very marketer friendly to utilize

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I have been using AWS Elastic Beanstalk for more than 5 years, and it has made our life so easy and hassle-free. Here are some scenarios where it excels -

• I have been using different AWS services like EC2, S3, Cloudfront, Serverless, etc. And Elastic Beanstalk makes our lives easier by tieing each service together and making the deployment a smooth process.
• N number of integrations with different CI/CD pipelines make this most engineer's favourite service.
• Scalability & Security comes with the service, which makes it the absolute perfect product for your business.

Personally, I haven't found any situations where it's not appropriate for the use cases it can be used. The pricing is also very cost-effective.

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• Host online/offline data with common IDs
• Ease of profile activation to destinations
• Flexibility around how many sources and destinations can be used to move data

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• Real-time insights are spot on with minimal millisecond differences
• Customer profile creation is on point with very good data unification capabilities
• Data ingestion from multiple sources and cleaning of PII data
• The insights engine is highly refined even having behavioural insights capability

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• Getting a project set up using the console or CLI is easy compared to other [computing] platforms.
• AWS Elastic Beanstalk supports a variety of programming languages so teams can experiment with different frameworks but still use the same compute platform for rapid prototyping.
• Common application architectures can be referenced as patterns during project [setup].
• Multiple environments can be deployed for an application giving more flexibility for experimentation.

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• the slowness of the website sometimes
• the structure

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• Currently there are limitations with the number of personas that can be built in the instance, it would be great to have more flexibility here
• We occasionally see issues with lists delivered to our ESP from the platform. Not a major problem, but could be an area of improvement

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• Limited to the frameworks and configurations that AWS supports. There is no native way to use Elastic Beanstalk to deploy a Go application behind Nginx, for example.
• It's not always clear what's changed on an underlying system when AWS updates an EB stack; the new version is announced, but AWS does not say what specifically changed in the underlying configuration. This can have unintended consequences and result in additional work in order to figure out what changes were made.

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It is useful when executed properly

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As our technology grows, it makes more sense to individually provision each server rather than have it done via beanstalk. There are several reasons to do so, which I cannot explain without further diving into the architecture itself, but I can tell you this. With automation, you also loose the flexibility to morph the system for your specific needs. So if you expect that in future you need more customization to your deployment process, then there is a good chance that you might try to do things individually rather than use an automation like beanstalk.

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Overall I really like the Adobe Experience Cloud after a couple years of figuring out various tools. They are extremely powerful. The time commitment to learn them is high since it's not a tool you can easily begin using without much training.

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The overall usability is good enough, as far as the scaling, interactive UI and logging system is concerned, could do a lot better when it comes to the efficiency, in case of complicated node logics and complicated node architectures. It can have better software compatibility and can try to support collaboration with more softwares

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Adobe has support at all levels and for each product but beyond tool questions you'll often be told they can help but it requires some paid consulting hours. So you either hire Adobe consultants or find 3rd part consultants who know their products well.

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As I described earlier it has been really cost effective and really easy for fellow developers who don't want to waste weeks and weeks into learning and manually deploying stuff which basically takes month to create and go live with the Minimal viable product (MVP). With AWS Beanstalk within a week a developer can go live with the Minimal viable product easily.

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- Do as many experiments as you can before you commit on using beanstalk or other AWS features. - Keep future state in mind. Think through what comes next, and if that is technically possible to do so. - Always factor in cost in terms of scaling. - We learned a valuable lesson when we wanted to go multi-region, because then we realized many things needs to change in code. So if you plan on using this a lot, factor multiple regions.

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We are more integrated with other Adobe products and so it was an easy decision

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Amperitiy's data model is much more refined compared to the competition which makes it ideal for firms looking for a no-nonsense CDP. However, it lacks campaigns and delivery features when compared to some other CDP providers like mParticle and Clevertap. The pricing is good and the usage-based pricing ensures that even small to mid-sized teams can afford it. Support can be improved though.

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We also use Heroku and it is a great platform for smaller projects and light Node.js services, but we have found that in terms of cost, the Elastic Beanstalk option is more affordable for the projects that we undertake. The fact that it sits inside of the greater AWS Cloud offering also compels us to use it, since integration is simpler. We have also evaluated Microsoft Azure and gave up trying to get an extremely basic implementation up and running after a few days of struggling with its mediocre user interface and constant issues with documentation being outdated. The authentication model is also badly broken and trying to manage resources is a pain. One cannot compare Azure with anything that Amazon has created in the cloud space since Azure really isn't a mature platform and we are always left wanting when we have to interface with it.

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• More leads from profile activations and lookalike audiences
• Better understanding of our data with CJA
• Better journey orchestration using AJO
• Higher conversions and sales due to better understanding of customer pain points

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• Overall we have been able to increase the mix of triggered related revenue in email from 20% to 50% of total revenue after implementing Custora's lifecycle triggers
• We've also seen one off email tests with incremental conversion rates up to 75% when utilizing Custora personas to personal communications

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• till now we had not Calculated ROI as the project is still evolving and we had to keep on changing the environment implementation
• it meets our purpose of quick deployment as compared to on-premises deployment
• till now we look good as we also controlled our expenses which increased suddenly in the middle of deployment activity

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