Marketing Technology Ecosystems, Part 3 of 6: Amazon Web Services

Warning: this content is older than 365 days. It may be out of date and no longer relevant.

In this series, we’re examining the underpinnings, the infrastructure that gives rise to marketing technology. Today, we’ll examine the oldest of the cloud-based marketing technology infrastructure platforms: Amazon AWS.


Amazon Web Services

Amazon Web Services (AWS) is by far the most mature of the technology infrastructure platforms, offering a bewildering array of technologies. When you use a new startup’s application or service, chances are good at least part of it is built on AWS. Which parts of their massive cloud should you investigate for marketing technology uses?

Data Platforms

Great data platforms help us maintain clean, compatible data and permit us to choose just the right data from enormous raw pools.

Inside Amazon’s cloud, we care most about these data offerings:

  • Structured data storage with cloud databases like RDS and RedShift
  • Unstructured data storage with EC2, S3/Glacier, and DynamoDB
  • Email data from Simple Email Service

Most major SaaS-based marketing technology apps leverage at least one of these services; developing at least a cursory understanding of their offerings and how your marketing technology efforts could benefit from them is essential. For example, suppose you’re tired of paying exorbitant fees for many of the ‘data backup services’ in the world. Look into S3 and Glacier for a potentially lower cost solution.

Suppose you’ve got marketing analysts in multiple locations, all processing social media data. Offering connectivity to RDS or RedShift could cut down on data conflicts.

Analysis Platforms

Great analysis platforms take in many different kinds of data, clean it up, normalize it, and spit out answers in multiple formats, from reports to charts to interactive visualizations.

Inside Amazon’s cloud, we care most about these analysis offerings:

  • ElasticSearch for processing large, structured data files like logs, social media analytics, etc.
  • Mobile Analytics for collecting and processing data from mobile apps we deploy
  • Elastic MapReduce for analyzing vast quantities of structured or unstructured data
  • Kinesis for dealing with streaming data such as social media firehoses

Most marketers have dealt with or indirectly interacted with at least one of these services behind the scenes; services like MapReduce are an integral part of many large analytics platforms.

As with the data offerings, a fair number of expensive SaaS analytics services are built atop these core functions; some vendors are nothing more than a nice looking user interface over an AWS analytics service. Thus, if you’re looking to save money or innovate faster, consider working with one of these services directly.

Marketers will benefit most from learning about MapReduce and Kinesis, as we tend to face huge quantities of unstructured data and real-time firehoses (thanks, social media!).

Insight Platforms

Insight platforms combine our analysis of what happened and blend it with analysis of unstructured data to help us explain why something happened.

Inside Amazon’s cloud, we care most about these analysis offerings:

  • Amazon machine learning offers trainable computing power to learn patterns and make predictions from data sets in nearly any format

Note that Amazon’s offerings in language processing and other insight-driven services are very thin. Amazon doesn’t currently have many competitive insight tools.

Strategy Platforms

Strategy platforms help us to understand what to do next. This is the pinnacle of modern computing, artificial intelligence.

As of now, Amazon has no offerings in artificial intelligence.

Conclusion: Amazon is foundational

When we examine the various offerings in Amazon’s infrastructure from a marketing technology perspective, we see that Amazon is incredibly strong in foundation technologies. Amazon can offer us boundless storage and heavy data processing capabilities.


Where Amazon falls short is as we work our way up the hierarchy of analytics; once we need to seek greater insights or prescriptive, proactive marketing technology solutions, AWS shows where it lags behind.

In the next piece, we’ll examine the big G: Google Cloud.

You might also enjoy:

Want to read more like this from Christopher Penn? Get updates here:

subscribe to my newsletter here

AI for Marketers Book
Take my Generative AI for Marketers course!

Analytics for Marketers Discussion Group
Join my Analytics for Marketers Slack Group!


Leave a Reply

Your email address will not be published. Required fields are marked *

Pin It on Pinterest

Share This