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A Digital Analytics Reference

Last Updated on 09/05/2023 Author: Tarek El-Sadek8 mins reading or less each

Digital Analytics in Practice - Activations & Planning Personas

Whether you are planning, activating, or revamping your digital analytics practices and solutions, registering a persona for each beneficiary role will maximize the adoption and smooth the adaptation. Given the major key features of any modern/matured Digital Analytics solutions (Data Layer/Elements/Tags, Tag Management System, Compliance & Monitoring), we can identify the following roles:

Analytics Developer
Data Analyst
Data Architect
CMS/DAM/Telemetry Developer
CMS/Content Developer/UX
Business Owner, Enablement
Business Owner, Privacy
Business Owner, Marketing
Business Owner, Marketing Analytics
Business Owner, Personalization/Experimentation

Now let's register the appropriate personas per each key feature based on its engagement and/or beneficiary role.

Data Layer/Elements/Tags

“As a [Analytics Developer], I want to utilize a data layer, so that analytic implementations are sustainable and scalable.”
“As a [Data Analyst], I want to utilize a data layer, so that data analysis is trusted and sustainable.”
“As a [Business Owner, Marketing Analytics], I want to have assurance of our data, so that the analyst can instantly pull data and provide actionable insights.”

Tag Management System Rules & Platform Integrations

“As a [Analytics Developer], I want to utilize a tag management system so that I can implement tags and 3rd party pixels compliantly and independently.”
“As a [CMS/DAM/Telemetry Developer], I want to utilize a tag management system that a centralized approach to deploy, audit and govern implementations.
“As a [Data Architect], I want to utilize a tag management system architecture that standardizes implementation, models and best practices.
“As a [Business Owner, Enablement], I want to enforce data engineering governance that aligns with business strategy and data policies.

Compliance & Monitoring

“As a [Analytics Developer], I want to react on collected data against the defined KPIs and goals so that I can modify implementations effectively.
“As a [CMS/DAM/Telemetry Developer], I want to verify scripts implementation across all pages/domains so that my implementation best practices of data collection, standardization, compliance and campaigns are stable.
“As a [CMS/Content Developer/UX], I want to collect traffic patterns so that it influences the design improvements and page performance."
“As a [Business Owner, Marketing], I want to find out whether a campaign was effective enough so that I generate a satisfactory ROI."
“As a [Business Owner, Privacy], I want audit implementation so that I can signoff as PI compliment and reduce the risk of legal penalties.
“As a [Business Owner, Personalization/Experimentation], I want to reveal customer interest in a page/product/service listing so that offering, and pricing can be personalized."

Digital Analytics in Practice - A Data Governance Toolkit

To better assess a data governance practice model and activation, let’s start from the roots. Data Governance, in practice, encompasses the strategies and technologies used to ensure data is in compliance with regulations and corporate policies with respect to data usage. This shows a need for a way or tool to assess all that. Simply, a categorized questionnaire-driven self-assessment tool can be used here to evaluate and monitor data governance health and to help plan next steps actions and align strategies. This self-assessment questionnaire focuses on evaluating and monitoring 4 categories that make the pillars of this data governance toolkit. They are:

Organizational Readiness
Data Collection Strategy: measures the well-being of the process of gathering, measuring, and analyzing accurate customer data that will then be used for marketing and decision-making. A strong scoring here would allow us to collect more information of a higher quality at a lower cost
Data Health: evaluates how well the organization’s data supports the business objectives. In definition, Data is healthy if it is easily discoverable, understandable, and of value to the people that need to use it, and these characteristics are sustained throughout its lifecycle.
Data Democratization: offers an insight of how well is the ongoing process of enabling everybody in an organization, irrespective of their technical know-how, to work with data comfortably, to feel confident talking about it, and as a result, make data-informed decisions and build customer experiences powered by data.

Once answered, you should act and frequently re-evaluate and re-act. Some next steps actions should be:

Share the output data with executive stakeholders for review and compare against goals, strategy and plans
Setup/modify action plans for how to improve and move toward "Great"
Work on those where you answered "Strongly Disagree" or "Disagree" to strengthen those aspects of the data governance
Apply any or all the runbook phases that was setup along with this data governance toolkit

Digital Analytics in Practice - Core Principles

Digital Analytics is not a tool nor an analysis process. It’s a set of business and technical activities that define, create, collect, verify, or transform digital data into reporting/visualization, analysis, optimizations, simulations, predictions, automations and insights that enable business values and opportunities.

In a highest and best usage model, Digital Analytics helps businesses to drive a continual improvement of any user journey or experience, which translates into increasing revenue and/or a reducing cost.

Speaking about the user journey and experience, it's any business' or marketer's ultimate goal to be able to track potential customers/users and understand their Acquisition channels, measure Conversion successful touchdowns and thus foresee how good their efforts are to Retain their business.

Strategically speaking, in general, Digital Analytics could be used for different goals by different people:

To an executive, Digital Analytics can help to determine if the digital entity and contents have been worth the financial investment. Does it produce results? Are these results improving over time, especially after a redesign?
To product managers, it can help to reveal customer interest in an array of products and, consequently, affect product offering and pricing
To an IT manager, it involves determining how much traffic the web, mobile and/or native apps entities experience so that manager can ensure that servers can deliver digital content flawlessly
To a marketing professional, it helps finding out whether an ad campaign (SEM, display, mobile, shopping, or Video) was actually effective and generated a satisfactory ROI
To a web content developer, it collects traffic patterns that influence the design improvements
To a sales person, it tracks which individual customers and prospects have been visiting the digital entities in order to narrow the sales channels and approach for a given customer or prospect

From a mechanics perspective, a Digital Analytics is based on a three step process that is:

Collect digital activity data
Analyze the data that interests you
Create meaningful reports and visualizations on that data

However, choosing a digital data analytics strategy is a business decision that must be made by the corporate leadership that, in a best practice, should consider balancing cost-effectiveness and quality with delivery time, especially when the question is whether to keep, buy or build an analytics solution.

Digital Analytics in Practice - Core Lifecycle

The Measurable Life Cycle is a simple repeatable process that will help you NOT only optimizing your web, mobile and native apps contents by following a few proven steps to find gaps, but also would enable you to find opportunities and innovate products and services that would maximize your user experience and browsing behaviors to the level of personalization and thus generating more revenues and boosting your campaigns ROI. This repeatable process creates a continuous improvement loop in which efforts are repeatedly refined through measurement.

Whether you are starting fresh or re-architecting your data structure, it all starts with gathering business requirements, defining goals and KPIs (Key Performance Indicators), designing the solution, and implementing it before you can start collecting the data. Having the data would allow you to generate analytics reports, illustrate trends visualizations and ultimately tell a story around numbers and findings. For that, you would need to dig into the data, analyze it to find gaps and opportunities and thus gain actionable insights. Those insights would become the core of any experimentation and testing during optimization phase. Based on the optimization outcomes, you should react and come up with innovative products or services to satisfy the voice of your customers. Then, re-measure again for your success keys.

Following this process will help you focus your benchmarks and make critical adjustments to your digital contents by optimization scenarios and traffic/segments simulation models, helping you to improve each time you complete the cycle.

An Engagement Governance Model is a Key for Your Success

The Governance and Engagement Model is the agreement among all parties that are involved in leveraging and using the Digital Analytics entities and/or services whether they are developers, digital architects, IT admins, business practitioners or agencies. This agreement is focusing on "Who's doing What, When, Where and How?" and enables the regulation of this practice. It could go from a simple framework into complex, but well laid-out, process.

Why A Measurement Plan?

The Measurement Plan is the document that translates your top-line business objectives into metrics and dimensions you can measure on your website. It provides a framework not only for a customized configuration of your web analytics, but also forms a vital part of your wider digital marketing strategy.

To create a Measurement Plan, follow these simple 5 Steps:

Document Business Objectives
Identify Strategies and Tactics
Choose KPIs
Choose Segments
Choose Targets

A free Measurement Plan template can be downloaded here.

Solution Design Reference (SDR) Approach for A Solid Tracking

The Solution Design Reference (SDR) is in essence the blueprint of any digital analytics implementation best practice. It defines criteria identified by stakeholders throughout your organization, and translates them to variables within any given digital analytics tool (i.e. Adobe Analytics, Google Analytics, etc). This document often layout the tags and DataLayer variables used across your digital entities and map them to the contents of your digital entities in more inventory like list. This document is also called the Solution Design Document (SDD), or is called the Technical Design Specifications (TDS) in less rich versions.

Digital Analytics Center of Excellence (CoE) Framework

The Digital Analytics Center of Excellence (DACoE) establishes, identifies, develops, and harnesses the Digital Analytics cross-functional processes, knowledge, and expertise that have tangible benefits for the business. The Digital Analytics CoE continually generates and refreshes knowledge, competencies, practices, and skills with the goal of informing and guiding internal partners/clients benefitting from the Digital Analytics services. That being said, the Digital Analytics CoE has the power of centralizing Digital Analytics efforts or keep them focused and surrounded by Digital Analytics experts who have in depth knowledge (decentralized).

The mission of the Digital Analytics Center of Excellence (DACoE) is to raise awareness in the enterprise, provide consultancy and implementation of relevant digital analytics using state of the art tools, practices supporting the organization's analytics needs.

The core improved objectives and functional model when centralizing the DACoE are:

Centralized approach where Digital Analytics CoE can either provide guidance and consultation directly to various units/teams (indirect contribution to projects), or engage directly in digital analytics implementation projects (direct contribution to projects)
Sharing experiences and best practices by establishing Digital Analytics community where members learn from peers
Aid in development and implementation
Empower members to asses corporate analytics needs and prioritize projects
First point of contact and toward coordination
Promote digital analytics community learning, and skills development

Digital Analytics & Maturity Path

As Digital Analytics industry is emerging, you should mature your data collection, analysis and optimization into more sophisticated and customer-centric information about your customers. The maturity of Digital Analytics, from Descriptive to Perspective through Predictive Analytics, is taking us to a totally different level of customer intelligence and segmentation. This intelligence is truly leading us on a path from vague, general statistics to a sharp picture of who your customers really are.

On the Future of Digital Analytics & the Impact on User Experience

Have you ever wondered why every time you search the web, watch a video, browse products in an online store, or even voice search something through your mobile phone, an ad would popup on your social media page? Well, this is the future that digital analytics and marketing is bringing to you. Maximum personalize user/client experience. Soon, you don't need to find anything yourself, but with an enhanced machine learning and the data collected about you and your interests via many digital data sources and analytics will allow your interests come true so you don't need to make much efforts to find what you like, but rather online marketers will compete to get you the best products or services with the best prices.

Technically, the mechanic of this emerging technology is that every time you voice search, for example, that connects to CDP (Customer Data Platform) and serves you back related products through customer relationship management (CRM) technology that marketers uses to leverage their inventories. And this adds up to the machine learning about you and your interests that the more you search the more segmentation and interests groups that you will be added to, and thus more varieties of products or services and much more simplified probabilities at the machine learning side. This is the newest phase in maximizing customer experience.

This is what so called the Customer Experience Marketing Personalization. In simple words, this allows marketers to only serve you the items that within your interest. That's a win-win, so they catch your attention and they convert it into business opportunity and thus make money while you get what you need is very competitive price, less efforts and probably instantly.

Moreover, Social Network Marketing is another way of personalization and advertisements that follows the same framework and uses same technology. And again that's another win-win case so while you are enjoying communicating with family, friends and other outer-world in general via social media Facebook like networks & other marketers are making money from advertisements and generating leads that could be converted into purchase/business opportunities that would bring revenue. Let's put it this way, everything that you use for free (no money charge) is a money generator to the company that owns it even the non-profit organizations, otherwise they would go out of business.

Although you may think that Google and Apple track everything about you (geolocation, search behavior, phone use times, etc.) through your mobile device or any other smart device, but let's be fair here. They are not spying for the sake of spying, but mainly aim to enhance your user experience and brings you what you need smartly with as less efforts as possible. It could be that your data is used by advertisers, but in which they use a technology called Beaconing to push you ads and services within your interest and location.

Anyway, always remember that you have the right to disable all this as a customer. You can modify your privacy settings to stop all this if you don't like it. You can block this through editing the privacy settings in FB or even in you mobile phone. That's why I would always recommend that you read your mobile application agreement and mobile phone terms of service for your privacy rights, before saying okay.