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Data Management & Analytics

Management applications, websites, social media platforms, mobile applications, and other technologies generate an unprecedented amount of data. The key to business growth and deeper profitability lies in understanding what that data means. Analytics tools like Adobe Analytics, and Google Analytics brilliantly organize this data into schema that is easy to understand and report on.


Even out of the box, a good analyst can use these tools to interpret customer behavior and drive change. A highly skilled analyst will also push for customized event tracking to augment blind spots in your data. 

Initial Analytics Set Up

Specifically, these analytics applications can help you measure the results of a marketing campaign or application feature release by reporting how traffic to and behavior on your application changes after a business decision has been made. Web and application analytics provide information about the number of visitors, page views and events completed. It helps gauge traffic and popularity trends which are useful for market research and discovering growth opportunities.

To get the most out of analytics software I tend to do the following:

  1. Set up Advanced Segmentation to split users into behavior types

  2. Populate Custom Dimensions with Event Data to deep dive user segments 

  3. Set up Goals & Goal Funnels to see how well the applications UX and UI are leading to goal conversion

  4. Build Custom Reports & Dashboards to quickly track key performance indicators

  5. Integrate with Google Ads to visualize paid ad performance in relation to custom segments

  6. Set UTM and Tagging Taxonomy to segment and understand the performance of various ad campaigns

  7. Export Data to a Business Intelligence Platform particularly when combining data from multiple apps

Data Aggregation & KPI Reporting

Although I have a great deal of experience using business intelligence tools like Microsoft Excel & Access, I prefer to connect very large data projects to more powerful tools like Tableau or Power BI.  Analytic platforms like Google and Adobe are great at helping you understand general performance metrics, however, to really pinpoint opportunities for your company, you need an analyst that knows what data to collect and how to structure your data to discover performance indicators for each process your company engages in that ultimately leads to a customer touchpoint and a win or loss of conversion.


I am partial to Power BI because of its power query editor that lets you transform, join, merge and append data without the need to complex SQL statements and unlike Tableau, each BI file can support a massive amount of records & directly importing the data into a BI file via the query editor means less memory is used to visualize and filter your data.

The result is powerful & interactive visualizations that can be built based on goals and key performance indicators specific to your company, product vertical, or business unit. This is especially useful for companies that collect data from multiple analytic platforms, and have Salesforce, lead management, CRM, or transactional database tables that need to be mapped to one another via unique keys or key-value pairs.

Once you've joined your data together in a meaningful table, Power BI can slice up that data into 100s of visualizations to help the executives and leadership team make data-driven business adjustments that can be easily measured for continual improvements.

Multi-Platform email channel integration and validation project combining analytics profiles for 100 e-commerce websites and 3 campaign databases to provide interactive email channel KPI model. 

Recent Data Project

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