Data Collection & Cloud Analytics
Recognize. Centralize. Utilize.
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Data Identification & Collection
One of the biggest mistakes organizations make is not considering what data they will need to understand and grow the business. Alfred speaks with your business stakeholders to understand what means success or failure for each of them, then works to uncover the data needed to support success. Once the data's usefulness and sources have been identified, we can focus on getting that data ingested into a format and location that maximizes its utility.
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Alfred has worked in dozens of platforms, UI, and source systems to discover and unlock access to critical business data. This can take the form of API calls, data capture forms, direct relational table access, FTP automation and more. Whether you work in a mature data environment such as Azure, AWS, or Google Cloud Platform, together we can identify the most efficient way to collect your critical data and integrate it. Coupled with the creation of reliable data collection event triggers that are meaningful to the way you do business, digital transformation will take on a whole new meaning.
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Data Integration & Centralization
The world defines data integration as the process of combining data from different sources into a single, usable format. In an API driven world, shifting data from 100s of source systems to a unified source for your business is easier than ever. The key is to data integration lies in defining each critical piece of data and layering critical pieces across systems.
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Your business information must be then housed securely, efficiently, and in a location that allow it to be used in every application and automation that supports the business. In the past, this meant working with a DBA to create a transactional tables and attribute tables in relational models (OLTP). In today's world, this practice is coupled with complete data table orchestration that allows for optimized querying and analytic discovery (OLAP). Ensuring your source data contains all critical information needed to power, APIs, dashboards, machine learning, and strategic decision making is one of Alfred's specialties.
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Data Analysis & Recommendations
Your data can do so much more than power reporting, and automations. It can also help you uncover areas of your business to optimize. By looking at your now-clean, centralized, and accessible data through the lens of your business pain points, we can use it to uncover root causes and optimize performance across all areas of business. Pinpointing behavioral trends of your customers can lead to better promotions, improved product offerings, enhanced communication methods. Uncovering, low margin offerings, or time-consuming and inefficient processes can save your organization millions in annual costs or eliminate previously unforeseen risks. The answers are in your data. You just need someone skilled at unlocking them & providing recommendations based on what's uncovered.
Tracking Smarter, Not Harder.
Tag Manager Implementations
Google Tag Manager​
1. Add header and footer code to each managed page.
2. Add the Google Analytics Tag.
3. Create tags, triggers, & variables
4. Publish tags and triggers to the tag management container
Adobe Launch​
1. Add header and footer code to each managed page.
2. Add the Adobe Analytics Tool.
3. Create data elements, rules and conditions, and actions.
4. Publish tools and rules to the production server.
Your web or phone application contains mountains of user data. IT teams can build extensive telemetry analytics tools to capture and order this data for business use. In my experience, this is a cumbersome, siloed, and costly way to begin collection and analysis. Your stakeholders are closer to your business data than your developers. As such, providing these stakeholders with tools and training to enhance data collection increases data fluency, reduces development cost, and limits collection to those data points critical to the decision makers.
There are a lot of platforms that exist to aid businesses in tracking and understanding user behavior. I have spent my professional career working primarily with Google's and Adobe's analytics platforms though I do have experience working with Snowplow Analytics. In general, I recommend companies use Google Analytics or Google 360 (formerly Analytics Premium) to track users coming to and activities within web and mobile applications.
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Google Analytics Vs Adobe Analytics
For smaller businesses, Google Analytics is a pretty powerful tool that can be used to capture all kinds of useful user data. For larger businesses that can afford Google 360 and have extensive marketing divisions, you just can't beat the attribution modeling of Google. Knowing where your marketing efforts can be optimized is critical to most marketing organizations.
For organizational intranets and internal or proprietary applications, Adobe Analytics (Formerly Omniture) has an ability to create variables and metrics with custom expirations that gives analysts unmatched schema control and a level of user behavior analysis that can help Development Teams, IT teams, and Problem Managers rapidly asses problem areas and deploy updates.
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Ultimately, the best tracking platform to use of course varies from company to company, and no platform will provide actionable insights if it hasn't been implemented properly. After 10 years of analytics implementations, I can say without a doubt - using a tag manager to deploy tracking codes is the best way to implement.