Homer leverages Amazon QuickSight to help solve marketing challenges attached to digital privacy

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Ironside is an Enterprise Data and Analytics firm and Advanced AWS Partner specializing in building innovative solutions leveraging AWS native analytics services. In a recent project, we worked with Homer Learning to build and launch a solution leveraging Amazon QuickSight to assist their marketing department gain greater visibility into the attribution and conversion of digital marketing spend. 

As a provider of digital education products to children via mobile and web, recent changes by the major industry ecosystem vendor data privacy terms & conditions (Apple & Google) have made tracking usage of Homer’s products very challenging. For the growth of their business, they needed to understand which digital advertising and marketing efforts were converting new customers and driving user consumption. 

Partnering with Homer’s data and analytics team, Ironside engaged to implement Amazon QuickSight Dashboards and Reports sourced from their data lake of advertising spend and user product usage information. The solution required close coordination with various business users within their marketing department and Homer analytics technical leadership to determine the effectiveness of advertising spend for both new user acquisition and user attention. 

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Exhibit A:Homer Learning Marketing Attribution Amazon QuickSight Dashboard and Reporting

Ironside’s Practice Lead for Business Intelligence, Scott Misage, shared, “The Homer Learning solution is interesting as it brings the headlines in the newspaper to customers engagement with the requirements, with Homer leveraging AWS to house their data analytics platform, Amazon QuickSight ”

Understanding the data elements from their variety of advertising and product platforms is essential for Homer’s marketing decision makers and is what Amazon QuickSight delivers. Ironside worked closely with business users to understand how they were looking to consume the data and align that to traditional and advanced features within Amazon QuickSight. Jin Chung, Sr. Architect, Analytics Platform at Homer shared, “The Ironside team worked closely with our business stakeholders to understand how they have interacted with the data previously and put forward solutions that could enhance that experience with some of the new features in Amazon QuickSight.” 

The Homer Amazon QuickSight environment is integrated to many other AWS analytics and management platform services that provide data processing and security capabilities. A key component of the platform is the aggregation of 3rd party data delivered to Homer via AWS S3 and blended in Databricks Delta Lake.  Ironside worked to create a secure and functional solution that integrated QuickSight to the Delta Lake with AWS Athena. 

About Ironside

Ironside helps companies translate business goals and challenges into technology solutions that enable insightful analysis, data-driven decision making and continued success. We help you structure, integrate and augment your data, while transforming your analytic environment and improving governance.

About Homer

The journey of parenthood begins without a map. As parents, we want the best for our kids. We want them to grow up to be confident lifelong learners who are ready to take on the world. At HOMER, our purpose is to give kids the best start to their learning journey during the window of opportunity—before the age of 6—where 85% of brain development takes place. We guide and champion children through this pivotal time as they build their skills and deepen their love of learning, and we partner with parents to provide the support that all kids need.


Ironside’s smart, time-bound, and ROI-focused approach to AI

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Be sure to check out our Take30 webinar this Thursday around the approach and features of Ironside’s AscentAI.

Artificial Intelligence, at its core, is a wide ranging tool that enables us to think differently on how to integrate information, analyze data, and use the resulting insights to improve decision making.

With the current shift to digitization (which has been accelerated by the pandemic), customer behavior has changed significantly, along with the expectation around accuracy of AI-based predictions. We all are used to “What to Watch Next” recommendations from streaming channels like Netflix or “Suggested Products” to buy from Amazon, but now with most businesses offering the expected “Wait Time” before your a haircut, or pickup time for the food you ordered online, it is critical to manage the queue to ensure timely service that begets customer satisfaction & retention.

Many organizations want to leverage AI but are unable to mainly due to following reasons

  • High cost & Time to Market
  • Complexity & Lack of expertise
  • Uncertainty of success of the AI outcomes

Because one of our goals is to help our customers benefit from the AI revolution, derive real business value,  improve their, all in a timely fashion we at Ironside have introduced a product-style approach to Data Science called AscentAI: 

As with any project, the first steps are to identify and prioritize the business use case, define the objective, and clearly specify the goals. Next, we offer a rapid viability assessment (RVA),  which ensures the model provides sufficient signal to justify productionizing the machine learning model in under three weeks.

The activities during RVA involve:

  • Data collection & preparation
    • The quality and quantity of the data dictates the accuracy of the model
    • Split the data into two distinct datasets for training and evaluation
  • Feature engineering
    • Identify & define features for the models
  • Model training & evaluation
    • Choose different models and identify the best one for the defined requirements
  • Make & validate predictions
    • Measure prediction accuracy against real data sets

RVA is a decision phase, where if the AI provides more noise than actual signal, then it would not provide value in developing production-ready machine learning models. This gate-based approach ensures the customer has clear visibility into expected outcomes, and can take an informed decision on either pursuing the current use case or moving on to the next one.

If the RVA provides meaningful insights, then part of the next step is to productionize the best model, integrating it into existing business processes to start consuming the predictions.

The final step includes a performance monitoring dashboard, which is provided to monitor the performance of the models, identify the need to tune, and optimize the model due to the naturally expected skew over time. Finally, we strongly recommend model “retraining” over time at a predefined frequency to ensure the AI consistently delivers on the expected ROI.

Below is a snapshot of a real implementation of AscentAI for a customer with 1800+ stores to predict accurate “wait times” in real time in a very high volume setting on AWS cloud platform.

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Modern Analytics Framework Series – Part 5: Our approach is as fluid as data itself

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Your data needs are different from those of any other client we’ve worked with. Plus, they’re ever-changing. 

That’s why we’re fluid in our approach to creating your framework and why we ensure fluidity in the framework itself. 

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Whether your current investment in assessments, governance, and technology is heavy or light, we can meet you where you are, optimize what you have, and help you move confidently forward. 

These steps are all necessary, but don’t happen in a strict sequence. Each of them is an iterative process — taking small steps, looking at the results, then choosing the next improvement. You need to start with assessment and governance — unless you already have some progress in those areas. 

Analytics are constantly evolving, and the Modern Analytics Framework is designed to evolve more readily as users discover new insights, new data, and new value for existing data. There will be constant re-assessment of the desired future state, modifications to your data governance goals and policies, design of data zones, and implementation of analytics and automated data delivery. Making these changes small and manageable is a key goal of the Modern Analytics Framework.

Can we ask you a few questions?

The better we understand your current state, the better we can speak to your specific needs. 

If you’d like to gain some insight into how your organization can move most effectively toward a Modern Analytics Framework, please schedule a time with Geoff Speare, our practice director.

Geoff’s Calendar
GSpeare@IronsideGroup.com
O 781-652-5758  |  M 484-553-1814

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Learn about our proven, streamlined approach to taking your current analytics framework from where it is to where it needs to be, for less cost and in less time than you might imagine.

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Check out the rest of the series.