Adobe Analytics Articles

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Building an Adobe Analytics Metrics & Dimensions definitions page with the Adobe Analytics API

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AI in Real Estate

Real estate is one of the world’s most productive businesses. According to MSCI, the value of business acquisitions worldwide will rise to $9.6 trillion in the coming years. Like many other industries, the real estate industry is switching to a “data-driven” world and is creating use cases of artificial intelligence. AI is entering the real estate business from consumer buying and selling strategies to investing in the construction of large commercial projects. However, the real estate sector remains in the early stages of deploying AI services. With the advancement of technology, AI in real estate will become apparent.

ai in real estate graphic

AI is increasingly being used in the real estate market to streamline and improve various processes, such as property valuations, lead generation, and property management. Here are some examples:

  • Property Valuation: AI is used to analyze data such as property size, location, amenities, and recent sales prices to provide accurate property valuations.
  • Lead Generation: AI is used to analyze data such as property listings, social media profiles, and user behavior to identify potential leads for real estate agents and brokers.
  • Property Management: AI is used to analyze data such as maintenance requests, lease agreements, and tenant feedback to improve property management processes.
  • Smart Homes: AI-powered smart home devices are being integrated into new construction homes and existing homes to provide homeowners with more efficient and convenient ways to control their homes.

Overall, AI is poised to revolutionize the real estate industry in many ways, including improving the accuracy of property valuations, streamlining property management processes, and providing more efficient and effective ways for real estate agents and brokers to generate leads.

Real Estate AI Tools


Maket.ai

Maket leverages AI to quickly generate thousands of architectural plans instantly based on programming needs and environmental constraints to help architects, builders and developers find the best floorplan for their clients

https://www.maket.ai/

Interior.ai

Get interior design ideas using Artificial Intelligence and virtually stage interiors for real estate listings with different interior styles.

https://interiorai.com/

AI Room Planner

AI Room Planner is a great tool to generate interior design ideas. It can give you an idea of how a space could look and feel like.

https://airoomplanner.com/

GetFloorPlan.com

Getfloorplan creates 2D, 3D floor plans and 360° virtual tours at no time. With our materials your ordinary listing can be turned into a picture of a dream house for your clients

https://getfloorplan.com/

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Chat by Copy.ai Review

Chat by Copy.ai is the smarter ChatGPT that helps you get more done. Scrape websites for public data, generate personalized copy, summarize YouTube videos into key bullet points, and so much more with the next generation of AI chat.

copy.ai logo

I can say without hesitation that copy.ai is a fantastic tool that can help anyone create high-quality content in no time. The platform is incredibly easy to use and provides a wide range of features that make it stand out from other content creation tools.

Whether you need to create social media posts, blog articles, or product descriptions, copy.ai can help you do it quickly and efficiently. The platform uses advanced AI algorithms to analyze your inputs and generate content that is both engaging and relevant to your target audience.

Another great feature of copy.ai is its ability to generate multiple variations of a single piece of content. This allows you to test different versions of your copy and find the one that performs the best. Additionally, the copy.ai user interface is incredibly user-friendly, making it easy for anyone to create great content regardless of their skill level.

Chat by Copy.ai Big Picture Taste of What’s Possible:

  • Write: any content you need
  • Summarize: websites, YouTube videos, articles and more
  • Repurpose: long-form content in social media posts and vice-versa
  • Research: companies, people, and topics with cited sources
  • Brainstorm: new ideas and approaches to any problem

More specifically, here are some fun copy.ai prompts to try!

  • Write a blog about <topic>
  • Summarize <full YouTube URL link> into 10 bullet points
  • Turn <article or blog post URL> into a LinkedIn post
  • Write a personalized cold email to <LinkedIn profile URL> selling <product description>
  • Review <LinkedIn profile URL> and generate a 10 bullet point summary
  • List 10 unique perspectives on adobe analytics <trending topic>

Overall, I highly recommend copy.ai to anyone looking for a powerful and easy-to-use content creation tool. Whether you’re a content marketer, blogger, or social media manager, copy.ai has everything you need to create engaging and high-quality content that resonates with your audience.

 

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What is the equivalent in Adobe Analytics to record count in Adobe Experience Platform?

In Adobe Analytics, the equivalent to record count in Adobe Experience Platform would be the “hit count” or “request count” for a specific report suite or data source. A hit or request is a unit of measurement in Adobe Analytics that represents a single user interaction with a website or mobile app.

The hit count in Adobe Analytics is the number of hits or requests recorded for a specific time period, such as a day, week, or month. This metric can be used to track the volume of traffic to a website or app and to measure the effectiveness of marketing campaigns.

To view the hit count in Adobe Analytics, you can create a custom report that includes the “hits” metric, or you can navigate to the “Traffic” report in the “Site Metrics” section of the Analytics interface. You can also use the Adobe Analytics API to programmatically retrieve hit count data.

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Explaining Google Analytics 4

Google Analytics 4 (GA4) is the latest version of Google’s web analytics platform. It was introduced in 2020 and is designed to provide marketers and website owners with a more complete and accurate understanding of user behavior and website performance.

Google Analytics 4 logo - GA4 logo

GA4 is different from the previous version of Google Analytics (Universal Analytics) in a few ways.

Google Analytics 4 Data Model

Firstly, GA4 uses a different data model that is event-based rather than session-based. This means that GA4 is better suited for tracking interactions and behaviors across multiple devices and touchpoints.

This fundamental difference in data models has several implications for how the two platforms work. For example, GA4 is better suited for tracking user behavior across multiple devices and sessions, and provides more granular data on user interactions. It also has more advanced machine learning capabilities and predictive analytics features that allow users to gain insights into user behavior and anticipate future actions.

GA4 Stronger Focus on Privacy

Secondly, GA4 has a stronger focus on privacy, with enhanced data controls and a more sophisticated approach to data collection and processing.

Another key difference between the two platforms is their approach to data privacy. GA4 includes more advanced data controls and is designed to be more privacy-friendly than previous versions of Google Analytics. For example, it includes built-in consent controls and automatically detects and excludes traffic from bots and spam.

GA4 Machine Learning and Predictive Metrics

Finally, GA4 includes new features such as machine learning-powered insights and predictive metrics, which help users better understand and anticipate user behavior.

Some examples of these features:

  • Automatic insights: GA4 can automatically surface insights and trends in your data, using machine learning algorithms to identify significant changes in user behavior. These insights can help you understand what’s driving changes in your metrics and where to focus your optimization efforts.
  • Predictive metrics: GA4 includes several new predictive metrics, which use machine learning algorithms to forecast future user behavior. For example, the “Purchase Probability” metric uses historical data to predict the likelihood that a user will make a purchase in the future. These metrics can help you identify high-value users and take actions to optimize their experience.
  • Enhanced analysis capabilities: GA4 includes more advanced analysis capabilities, such as the ability to analyze user behavior across multiple touchpoints and devices. For example, the “User Lifetime” report allows you to track the long-term behavior of individual users, and the “Pathing” report allows you to visualize user journeys across multiple sessions.
  • Improved integration with Google Ads: GA4 includes deeper integration with Google Ads, allowing you to track and analyze the performance of your campaigns more effectively. For example, you can now see the impact of your Google Ads campaigns on user behavior across multiple touchpoints, and use machine learning to identify the most valuable traffic sources.

Overall, Google Analytics 4 represents a significant upgrade from previous versions of the platform, and provides marketers and website owners with more powerful and sophisticated tools for understanding and improving their digital experiences. Other article on Google Analytics.

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Explain the Difference Between Web Analytics and Email Analytics

Web Analytics

Web analytics (aka: digital analytics) refers to the collection, measurement, and analysis of data about visitors and their behavior on websites. It provides insights into the number of visitors, their sources, behavior on the site, and which pages they interact with. The goal of website analytics is to improve the website’s performance and user experience.

Digital analytics and marketing analytics are related but distinct fields. Website analytics is focused on measuring and analyzing data about website traffic, user behavior, and other online metrics. Marketing analytics, on the other hand, is a broader field that encompasses web analytics, as well as data from other marketing channels, such as email, social media, and paid advertising.

Marketing analytics provides a more holistic view of a company’s marketing performance and helps marketers make data-driven decisions about their marketing strategy and budget. Digital analytics, by contrast, is more focused on website-specific data, and is typically used to optimize website performance and user experience.

In summary, digital analytics is a subset of marketing analytics, and marketing analytics is a more comprehensive approach to measuring and analyzing marketing performance.

web analytics graphic

Leading Web Analytics Companies:

Note: The ranking can vary depending on the specific use case and the size of the organization.

Email Analytics

Email analytics, on the other hand, refers to the measurement and analysis of data related to email marketing campaigns. This includes metrics such as open rates, click-through rates, conversion rates, and subscriber engagement. The goal is to understand the effectiveness of email marketing efforts and make informed decisions about future campaigns.

graphic depicting email analytics

In summary, web analytics focuses on website performance and visitor behavior, while email analytics focuses on the performance of email marketing campaigns.

Leading Email Analytics Companies:

  • Google Analytics
  • Adobe Analytics
  • Mailchimp
  • Klaviyo
  • Pardot
  • Campaign Monitor

Note: The ranking can vary depending on the specific use case and the size of the organization.

 

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Promises from a Manager

11 Promises From A Manager to Employees

Outlined below is the kind of relationship managers should try to forge with employees who report to them directly. As I see it, the manager-employee relationship should emphasize clarity and trust while also prioritizing the individual worker’s needs.

I’ve managed some great people since I first started. At some point I discovered the idea of servant leadership, which for me means that leaders should center the needs of their people rather than themselves.

  1. We’ll have a weekly 1:1. I’ll never cancel this meeting, but you can cancel it whenever you like. It’s your time.
  2. Our 1:1 agenda will be in the meeting invite so we remember important topics. But you’re always free to use the time for whatever’s on your mind.
  3. When I schedule a meeting with you, I’ll always say *when I schedule it* what it’s meant to be about. I will not schedule meetings without an agenda.
  4. When I drop into your DM’s, I’ll always say “hi and why.” No suspense, no small talk while you are wondering what I want.
  5. News or announcements that significantly impact you, your work, or your team will come from me directly in a 1:1, not revealed in a big meeting.
  6. You’ll get feedback from me when it’s fresh. There will be no feedback in your performance review that you’re hearing for the first time.
  7. I trust you to manage your own time. You don’t need to clear with me in advance your time AFK or OOO.
  8. Your work gets done your way. My focus is on outcomes, not output. Once we’re clear on where we need to go, how to get there is up to you. If I ever find it necessary to suggest a specific approach, I will supply an example.
  9. A team is strongest when it’s working together, looking after one another, and taking care of each other. Please look to your left and to your right for opportunities to help your colleagues. Please ask for help when you need it. Nobody works alone.
  10. I trust you to skip level and talk to my manager or other senior management about anything you feel is relevant. You don’t need to clear it with me, and I’m not going to get weird about it when you do.
  11. I will attribute credit appropriately to you and your team. I will never exaggerate my own role or minimize your contribution. I’ll be especially certain to nail down attribution when senior management are hearing of our accomplishments.

I ask only that my direct reports reciprocate by giving me in return what I need most: The truth.

I want them to give me their feedback, tell me when I’m wrong, and tell me their ideas for how we can do better. If we trust each other, we can learn and grow together. That’s how I want to work with my direct reports.

This is what good leadership can look like. Read the full article here. Follow Matthew Rechs @MrEchs

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Science of Persuasion Video

Robert Cialdini, considered the leading social scientist in the field of influence, was initially drawn to the topic because he saw how easily people could step over an ethical line into manipulation or even abuse. His 2001 book Influence, which laid out six principles of persuasion, was eloquent about the dangers of persuasive techniques in the wrong hands. A best-selling article he wrote for HBR the same year, “Harnessing the Science of Persuasion,” looked at the positive side of persuasion: how managers could use those principles to run their organizations more effectively.

Extensive scholarly training in the psychology of influence, together with over 30 years of research into the subject, has earned Dr. Cialdini an international reputation as an expert in the fields of persuasion, compliance, and negotiation.

His books including, Influence: Science & Practice and Influence: The Psychology of Persuasion are the results of more than 30 years of study into the reasons why people comply with requests in business settings. Worldwide, Influence has sold over 3 million copies and has been published in thirty languages. Additionally, USA Today lists Influence in their 12 Best Business Books of All Time.

Cialdini is the Regents’ Professor Emeritus of Psychology and Marketing at Arizona State University and the president of the consulting firm Influence at Work.

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Succeeding as a Virtual Team

graphic representing a virtual team with a person at a computer and virtual team members encircling him

The earliest virtual teams were formed to facilitate innovation among top experts around the world who didn’t have time to travel. Today teams of physically dispersed employees are more often just a necessity of doing business.

Creating and Leading an Effective Virtual Team

There’s a lot of advice out there, but research concludes that there are four must-haves: the right team, the right leadership, the right touchpoints, and the right technology.

The Right Team

  • People – Hire the right people who are suited for remote work. Good communication skills, high emotional intelligence (EQ), the ability to work independently and the resilience to recover from negative situations are all important things to possess. Also important is awareness and sensitivity to other cultures.
  • Size – The most effective virtual teams are small ones…fewer than 10 people. Beware of “social loafing” which is when team members reduce effort when they feel less responsible for output. It takes only 10 conversations for every person on a team of five to touch base with everyone else, but that number rises to 78 for a team of 13.
  • Roles – When projects require the efforts of multiple people from various departments, create relevant and appropriate sub-teams. Our approach is similar to the MIT professor Deborah Ancona advocates an X-team strategy which defines three tiers of team members: core, operational, and outer. The core consists of executives responsible for strategy. The operational group leads and makes decisions about day-to-day work but doesn’t tackle the larger issues handled by the core. And the outer network consists of temporary or part-time members who are brought in for a particular stage of the project because of their specialized expertise.

The Right Leadership

The best predictor of success for managers leading dispersed teams is experience doing it before. Novices can excel by practicing some key behaviors that, while also critical in face-to-face settings, must be amplified in virtual ones: Fostering trust, Encouraging open dialogue, Clarifying goals and guidelines.

  • Observable Candor = Push members to be frank with one another. Model “caring criticism”
  • Official Advocate for Candor-Noticing = A tactic for conference calls is to designate one team member to act as the official advocate for candor-noticing and speaking up when something is being left unsaid and calling out criticism that’s not constructive. On the flip side, you should also occasionally recognize people for practices that improve team communication and collaboration.
  • Establish a Common Purpose or Vision = The importance of establishing a common purpose or vision is paramount, while also framing the work in terms of team members’ individual needs and ambitions. Explain to everyone why you are coming together and what benefits will result, and then keep reiterating the message.
  • Establish a few Rules = Rules reduce uncertainty and enhance trust in social groups, thereby improving productivity. Agree on how quickly team members should respond to queries and requests from one another, and outline follow-up steps if someone is slow to act. Insist that requests be specific. Make it clear that multitasking is NOT OK.

The Right Touchpoints

Virtual teams should come together in person at certain times. The stages at which it’s most critical are Kickoff, Onboarding, Milestones.

  • Kickoff = An initial meeting, face-to-face if possible and using video if not, will go a long way toward introducing teammates, setting expectations for trust and candor, and clarifying team goals and behavioral guidelines.
  • Onboarding = Fly new team members into headquarters. Pair newcomers with a mentor.
  • Milestones = Get people together to celebrate the achievement of short-term goals or to crack tough problems.

The Right Technology

Even top-notch virtual teams—those with the most- talented workers, the finest leadership, and frequent touchpoints—can be felled by poor technology. We recommend using team communication platforms that integrate all types of key components such as: Conference calling, Direct calling, Discussion forums, Easy recording, etc.

Virtual teams are hard to get right but the appeal of forming virtual teams is clear. Employees can manage their work and personal lives more flexibly, and they have the opportunity to interact with colleagues around the world. Companies can use the best and lowest-cost global talent and significantly reduce their real estate costs.

The good news is that research now indicates that well-managed dispersed teams can actually outperform those that share office space. So if you lead a virtual team or are a member of one, realize there are methods and tactics you can use to give your team the best chance of success.

Additional Resource:

From McKinsey.com: Revisiting Agile Teams after an Abrupt Shift to Remote
Agile teams traditionally excel when their members are co-located. Here’s a great article by McKinsey on how to ensure they’re effective after COVID-19 forced them to work remotely.

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Adobe Analytics and Google Analytics Terminologies [Repost]

Great resource for Adobe Analytics and Google Analytics terminologies for mapping GA variables to AA variables and vice versa.

Original Post: https://yuhuisdatascienceblog.blogspot.com/2020/05/adobe-analytics-and-google-analytics.html

When going from an Adobe Analytics world to a Google Analytics world or vice versa, you’re bound to face terminologies that you’re unfamiliar with, mainly because of how both products have evolved in their functionality over time.

But never fear! Here’s a handy cheat sheet to help you know what something in Adobe Analytics is similar (but not always equivalent!) to in Google Analytics, or the other way around.


Base Terminologies

Adobe Analytics Google Analytics Remarks
Report Suite Property Besides data storage, an Adobe Analytics Report Suite provides the primary reporting interface.

A Google Analytics Property does not have a reporting interface. Instead, its reporting interface is a View.

Virtual Report Suite View An Adobe Analytics Virtual Report Suite is based on applying a segment to a Report Suite.

A Google Analytics View is based on applying many filters to a Property.

Visitor ID Client ID Modern implementations of Adobe Analytics rely on the Adobe Experience Cloud ID Service to provide the Visitor ID, which is a common visitor ID across all Adobe Experience Platform products.
Unique Visitor User
Visit Session Learn more about the measurement differences.

 

Traffic Source

Adobe Analytics Google Analytics Remarks
Referrer Source when Medium is “referrer”
Tracking Code (Campaign) Source / Medium / Campaign / Ad Content / Keyword Strictly speaking, this is not comparing like-for-like.

In Adobe Analytics, Tracking Code is a special kind of Conversion Variable. It does not replace the Traffic Source.

In Google Analytics, Source / Medium / Campaign / Ad Content / Keyword are synonymous with Traffic Source.

Marketing Channel Channel Group

 

Site Content Pages

Adobe Analytics Google Analytics Remarks
Page Page
Entry Page Landing Page
Exit Page Exit Page
Page Not Found N/A
Server Hostname
Site Section (Channel) N/A
Hierarchy N/A Google Analytics derives a hierarchy (Content Drilldown) from Page.
N/A Content Group In Adobe Analytics, a Traffic Variable can be setup to record this.
Page View Pageview
N/A Unique Pageview In Adobe Analytics, “Visit” can be used in place of this.
Bounce Rate Bounce Rate

 

Site Content Links/Events

Adobe Analytics Google Analytics Remarks
Custom Link Event Category/Action/Label Adobe Analytics provides one field name, whereas Google Analytics provides three field names.
Download Link Event Category/Action/Label when used to track a download link Adobe Analytics provides one field name, whereas Google Analytics provides three field names.
Exit Link Event Category/Action/Label when used to track an exit/outbound link Adobe Analytics provides one field name, whereas Google Analytics provides three field names.
Custom/Download/Exit Link Instance Event
N/A Unique Event In Adobe Analytics, “Visit” can be used in place of this.
N/A Event Value In Adobe Analytics, a “Numeric” Success Event can be setup to record this.

 

Custom Dimensions and Metrics

Adobe Analytics Google Analytics Remarks
Traffic Variable (prop) Custom Dimension (hit-scoped)
Traffic Variable (prop) Custom Dimension (hit-scoped)
Traffic List Variable N/A
Conversion Variable (eVar) with “Most Recent” allocation and “Hit” expiry Custom Dimension (hit-scoped)
Conversion Variable (eVar) with “Most Recent” allocation and “Visit” expiry Custom Dimension (session-scoped)
Conversion Variable (eVar) with “Most Recent” allocation and “Never” expiry Custom Dimension (user-scoped)
Conversion Variable (eVar) with other allocations and/or other expiries N/A
Merchandising Conversion Variable (eVar) with “Most Recent” allocation and “Hit” expiry Custom Dimension (product-scoped)
Merchandising Conversion Variable (eVar) with other allocations and/or other expiries N/A
Success Event of “Counter” type and “Record Once Per Visit” Goal Conversion The Adobe Analytics Success Event must be set in the tracking code.

Google Analytics’ Goals are configured in the Admin interface based on Pages, Events, Page Views per Visit or Time on Site.

Success Event of “Counter” type Custom Metric (hit-scoped) of “Integer” type with value “1”
Success Event of “Counter” type set with Products Custom Metric (product-scoped) of “Integer” type with value “1”
Success Event of “Numeric” type Custom Metric (hit-scoped) of “Integer” type with any value
Success Event of “Numeric” type set with Products Custom Metric (product-scoped) of “Integer” type with any value
Success Event of “Currency” type Custom Metric (hit-scoped) of “Currency” type
Success Event of “Currency” type set with Products Custom Metric (product-scoped) of “Currency” type
N/A Custom Metric (hit-scoped) of “Time” type In Adobe Analytics, a “Counter” Success Event can be used in a Calculated Metric with a “Time” format to report this.
N/A Custom Metric (product-scoped) of “Time” type In Adobe Analytics, a “Numeric” Success Event can be used in a Calculated Metric with a “Time” format to report this.

 

E-commerce

Adobe Analytics Google Analytics Remarks
Category Product Category Google Analytics allows for drilldowns in Product Category (with Enhanced E-commerce only).
Product, if product name is set Product Adobe Analytics does not dictate if the “Product” field should be the product’s name or SKU.

If “Product” is used to record the product name, then a Merchandising Conversion Variable can be setup to record the product SKU.

Product, if product SKU is set Product SKU Adobe Analytics does not dictate if the “Product” field should be the product’s name or SKU.

If “Product” is used to record the product SKU, then a Merchandising Conversion Variable can be setup to record the product name.

N/A Product Brand In Adobe Analytics, a Merchandising Conversion Variable can be setup to record this.
N/A Product Variant In Adobe Analytics, a Merchandising Conversion Variable can be setup to record this.
N/A Product Coupon Code In Adobe Analytics, a Merchandising Conversion Variable can be setup to record this.
N/A Product List View (Product Impression) In Adobe Analytics, a “Counter” Success Event can be setup to record this.
N/A Product List Click (Product Click) In Adobe Analytics, a “Counter” Success Event can be setup to record this.
Product View Product Detail View
Cart N/A In Google Analytics, a hit-scoped “Integer” Custom Metric can be setup to track this.
Cart Addition Product Add
Cart Removal Product Remove
Cart View N/A In Google Analytics, a hit-scoped “Integer” Custom Metric can be setup to track this.
Checkout Product Checkout
Order Transaction
Unit (when reported with Order) Quantity
Unit (when reported with Product) Product Quantity
Revenue (when reported with Order) Revenue
Revenue (when reported with Product) Product Revenue
N/A Average Price In Adobe Analytics, a Calculated Metric (based on Revenue / Unit) can be setup to report this.
N/A Tax In Adobe Analytics, a “Currency” Success Event can be setup to record this.
N/A Shipping In Adobe Analytics, a “Currency” Success Event can be setup to record this.
N/A Transaction ID In Adobe Analytics, a Conversion Variable can be setup to record this.
N/A Affiliation In Adobe Analytics, a Conversion Variable can be setup to record this.
N/A Order Coupon Code In Adobe Analytics, a Conversion Variable can be setup to record this.
N/A Internal Promotion Name In Adobe Analytics, a Conversion Variable can be setup to record this.
N/A Internal Promotion ID In Adobe Analytics, a Conversion Variable can be setup to record this.
N/A Internal Promotion Creative In Adobe Analytics, a Conversion Variable can be setup to record this.
N/A Internal Promotion Position In Adobe Analytics, a Conversion Variable can be setup to record this.
N/A Internal Promotion View (Internal Promotion Impression) In Adobe Analytics, a “Counter” Success Event can be setup to record this.
N/A Internal Promotion Click In Adobe Analytics, a “Counter” Success Event can be setup to record this.

Is this list missing something in Adobe Analytics or Google Analytics? Leave a comment to let me know, and I’ll do my best to update this list with your suggestion(s).

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