Finding yourself bogged down with digital analytics? Spending hours just collecting and organizing information from your websites and apps? Looker Studio could be the answer to all your problems (well, maybe not all of them, but at least where data analytics are concerned).

This business intelligence tool from Google is designed to solve one of the biggest headaches out there for marketers: turning mountains of website data into actionable insights. Anyone who’s ever gone down the proverbial rabbit hole scouring Google Analytics for the right metrics or manually inputting numbers from a spreadsheet into their business intelligence platform knows that organizing this data is no small task. With Looker Studio, you can consolidate and simplify complicated data, freeing up more time for actual analysis.

With so many customizable features and templates, it does take time to set up a Looker Studio report that works for you. Since Google’s recent switch from Universal Analytics to Google Analytics 4, you might also find that certain Looker Studio reports aren’t working the way they used to.

Not to worry: Our Oomph engineers help clients configure and analyze data with Looker Studio every day, and we’ve learned a few tips along the way. Here’s what to know to make Looker Studio work for your business.

The benefits of using Looker Studio for data visualization and analysis

Formerly known as Google Data Studio, Looker Studio pulls, organizes, and visualizes data in one unified reporting experience. For marketers who rely heavily on data to make informed decisions, Looker Studio can save precious time and energy, which you can then invest in analyzing and interpreting data.

Key benefits of using Looker Studio include:

How Oomph uses Looker Studio

As a digital-first company in the business of helping other digital-first companies, we’re big fans of Looker Studio. We think the platform is a great way to share trends on your websites and apps in an easy-to-digest way, making monthly or quarterly reporting much more efficient.

Whether you’re looking for basic insights or need sophisticated analysis, Looker Studio’s visualization capabilities can support smarter, more informed digital decision-making. Here’s a peek at some of the metrics we monitor for our own business, including:

Oomph Looker Studio sample dashboard

We also use the platform to drill deeper, comparing trends over time, identifying seasonal fluctuations and assessing the performance of specific campaigns. We leverage features like dashboards and filters in Looker Studio to give our clients an interactive view of their data.

How Looker Studio Works With GA4

Google Analytics, now known as GA4, is one of the primary tools we connect to Looker Studio. GA4 is the latest version of Google’s popular analytics platform and offers new features and functionality compared with its predecessor, Universal Analytics (UA), including new data visualization capabilities.

As many companies migrate over to GA4, they may be wondering if reporting will be similar between GA4 and Looker Studio – and if you need both.

While GA4 reports may challenge Looker Studio’s capabilities, Looker Studio provides a variety of features that go beyond what GA4 can do on its own. While GA4 dashboards and reports just include GA4 data, Looker Studio can import data from other sources as well. This means you can use Looker Studio to track trends in your site’s performance, regardless of the data source.

Looker Studio also has a unique feature called “LookML,” which allows users to create custom data models and transformations. This means you can tailor your data to your specific needs, rather than being limited by GA4’s built-in reporting. Finally, Looker Studio’s robust sharing and collaboration features allow teams to share data and insights easily and efficiently.

If your company set up Looker Studio before switching to GA4, you may notice a few metrics are now out of sync. Here are a few adjustments to get everything working correctly:

How To Set Up a Looker Studio Report

  1. Choose a template for your dashboard or create one from scratch. If you’re not sure, you can browse through templates to get an idea of what Looker can do.
A view into the Looker Studio template gallery
  1. Connect your data source. Looker supports a long list of sources, including Google, MySQL, AWS Redshift, and more. Don’t worry if your data isn’t in Google – Looker will likely be able to connect to it regardless.
Add data to a report using built-in Google connectors…
…or search for specific Conectors, some of which are provided by partners
  1. Choose your metrics. These are the specific data points you want to track and analyze in your report. You can customize your metrics to fit your specific needs.
  2. Build your dashboard. You can add charts, tables, and other visualizations to help you understand your data. Looker makes it easy to drag and drop these elements into place.
  3. Share it with others. You can either create a share link so that others can access the dashboard directly or you can set up automatic updates to be sent on a regular basis. This makes it easy for others to stay up-to-date on changes and progress.
Reports can be eamiled to participants on a schedule using Looker’s scheduling tool

A Powerful Path To Data Insights

The digital landscape is growing more fragmented and complex by the day, but tools like Looker Studio make it infinitely easier to find your path forward. Taking the time to configure and customize the platform can deliver major ROI by helping you understand user needs, pinpoint website strengths and challenges, and craft the right digital strategy.

Crunched for time or not sure where to start? Oomph can help take the hassle out of data analysis by setting up and monitoring your Looker Studio dashboards. Get in touch to chat about your needs.

Humans encounter thousands of words every day. As a website owner, that means your site content is vying for your user’s attention alongside emails from their colleagues, the novel on their nightstand, and even the permission slip scrunched at the bottom of their kid’s backpack.

How do you cut through the clutter to create site content that people actually want to read?

While you may already be choosing topics that are the most interesting and relevant for your audience, the structure of your writing may not be optimized for how people read. By understanding your audience’s reading behaviors following best practices for readability and accessibility, you can make sure your content works with people’s natural tendencies – not against them – to create a more engaging digital experience. An added bonus: Google shares many of those same tendencies, so content that’s designed well for humans is also more likely to perform well for organic SEO.

As a digital platform partner to many clients with content-rich sites, Oomph often works with brands to redesign their content for digital success. Here’s a look at the basic principles we apply to any site design – and how you can use them to your advantage.

How People Read Online

When we dive into a book, we typically settle in for a long haul, ready to soak up each chapter one by one. But when we open up a website, it’s more like scanning a newspaper or the entire bookshelf – we’re looking for something specific to catch our eye. We quickly scan, looking for anything that jumps out at us. If we see something interesting, then we’ll slow down and start reading in more detail.

Think of it like an animal following an information “scent,” identifying a mixture of clues that are likely to lead to the content you’re looking for. Most people will decide which pages to visit based on how likely the page will have the answer they’re looking for and how long it’s going to take to get the answer.

Users need to be hooked within a few moments of looking at a website or they’ll move on. They need to be able to identify and understand key factors like:

  1. The point of the information and why they should keep reading
  2. Whether they can trust the information and the source
  3. The type of content provided and any action expected from them, like signing up for an event
  4. How visually engaging and readable the content is

The takeaway for brands? Writing with your readers’ needs in mind is a way to show them you care and want to help them solve their problem. It’s also the key to achieving your site goals.

Your site content does more than just convey information – it’s about building trust, establishing rapport, and creating a connection that goes beyond the page. Whether you’re trying to sell a product or promote a cause, crafting content around your audience’s needs, desires, and preferences is the most effective way to compel them to take action. Here are four ways to set your website content up for success.

1. Put your data to work.

If you’re looking to refresh your current site, data can help you make informed choices about everything from your content strategy to your layout and design. Use digital reporting tools to answer questions like:

Google Analytics is a go-to tool for understanding the basics of who is visiting your site and how they’re engaging with your content. You can track metrics like session duration, traffic sources, and top-performing pages, all of which can help you better understand what your audience is looking for and what you want to tell them. (If you haven’t made the switch to Google Analytics’ latest platform, GA4, jump-start the process with our 12-step migration guide.)

Additional tools like Screaming Frog and Hotjar can give you even deeper insights, helping you track content structure and real-time user interactions.

2. Create a simple and consistent content structure.

When it comes to site content, consistency is like the foundation of a house (minus the power tools and hard hats).

A well-structured site not only helps users navigate and understand your content more easily, but also enhances the visual appeal and flow of the site. Think of it like a dance floor – you want your users to be able to move smoothly from one section to the next, without any awkward missteps.

That means focusing on shorter sentences, bullet points, and clear subheadings, all backed up by engaging visuals that serve as resting points for the eye. And while you’re at it, don’t forget to declutter your content — users don’t want to wade through a sea of unnecessary words just to find the nuggets of gold.

Ask yourself: Does this content flow smoothly, is it easy to scan, and does it make my key messages stand out? If the answer is yes, then you’re on your way to successful content.

3. Make sure visuals and content play nicely together.

When it comes to enhancing your content with visuals, the key is to strike a balance between style and substance. Your design should complement your content, not compete or distract from it.

Beyond their aesthetic appeal, well-designed visuals are important for creating a sense of credibility with users. Think back to the concept of information scent: If your design looks sloppy or inconsistent, users are less likely to trust the information you’re presenting. So make sure you’re using design elements wisely, creating ample white space, and avoiding anything that makes your content feel like a sales pitch.

4. Focus on accessibility.

When it comes to site content, accessibility can’t be ignored. Content should be engaging and informative and also conform to the , Website Content Accessibility Guidelines (WCAG). Tools like SortSite can help identify these issues and guide you toward accessibility success.

There are a number of things all sites need to consider:

Designing Engaging Content Doesn’t Need To Be a Full-Time Job

If you already have a library of content, auditing the content that already exists can be daunting. And sometimes, you need a little help from your friends. That’s where third-party experts (like us!) come in.

During our website discovery process, we use strategies like content and analytics audits, UX heuristics, and user journey mapping to help position client sites for success. We’ll help you identify areas for improvement, highlight opportunities for growth, and guide you toward achieving content greatness.

Ready for a fresh perspective on your content? We’d love to talk about it.

More than two years after Google announced the launch of its powerful new website analytics platform, Google Analytics 4 (GA4), the final countdown to make the switch is on.

GA4 will officially replace Google’s previous analytics platform, Universal Analytics (UA), on July 1, 2023. It’s the first major analytics update from Google since 2012 — and it’s a big deal. As we discussed in a blog post last year, GA4 uses big data and machine learning to provide a next-generation approach to measurement, including:

At Oomph, we’ve learned a thing or two about making the transition seamless while handling GA4 migrations for our clients – including a few platform “gotchas” that are definitely better to know in advance. Before you start your migration, do yourself a favor and explore our GA4 setup guide.

Your 12-Step GA4 Migration Checklist

Step 1: Create a GA4 Analytics Property and Implement Tagging

The Gist: Launch the GA4 setup assistant to create a new GA4 property for your site or app. For sites that already have UA installed, Google is beginning to create GA4 properties automatically for them beginning in March 2023 (unless you opt out). If you’re migrating from UA, you can connect your UA property to your GA4 property to use the existing Google tracking tag on your site. For new sites, you’ll need to add the tag directly to your site or via Google Tag Manager.

The Gotcha: During property setup, Google will ask you which data streams you’d like to add (websites, apps, etc…). This is simple if you’re just tracking one site, but gets more complex for organizations with multiple properties, like educational institutions or retailers with individual locations. While UA allowed you to separate data streams by geography or line of business, GA4 handles this differently. This Google guide can help you choose the ideal configuration for your business model.

Step 2: Update Your Data Retention Settings

The Gist: GA4 lets you control how long you retain data on users and events before it’s automatically deleted from Google’s servers. For user-level data, including conversions, you can hang on to data for up to 14 months. For other event data, you have the option to retain the information for 2 months or 14 months.

The Gotcha: The data retention limits are much shorter than UA, which allowed you to keep Google-signals data for up to 26 months in some cases. The default retention setting in GA4 is 2 months for some types of data – a surprisingly short window, in our opinion – so be sure to extend it to avoid data loss.

Step 3: Initialize BigQuery

The Gist: Have a lot of data to analyze? GA4 integrates with BigQuery, Google’s cloud-based data warehouse, so you can store historical data and run analyses on massive datasets. Google walks you through the steps here.

The Gotcha: Since GA4 has tight time limits on data retention as well as data limits on reporting , skipping this step could compromise your reporting. BigQuery is a helpful workaround for storing, analyzing and visualizing large amounts of complex data.

Step 4: Configure Enhanced Measurements

The Gist: GA4 measures much more than pageviews – you can now track actions like outbound link clicks, scrolls, and engagements with YouTube videos automatically through the platform. When you set up GA4, simply check the box for any metrics you want GA4 to monitor. You can still use Google tags to customize tracking for other types of events or use Google’s Measurement Protocol for advanced tracking.

The Gotcha: If you were previously measuring events through Google tags that GA4 will now measure automatically, take the time to review which ones to keep to avoid duplicating efforts. It may be simpler to use GA4 tracking – giving you a good reason to do that Google Tag Manager cleanup you’ve been meaning to get to.

Step 5: Configure Internal and Developer Traffic Settings

The Gist: To avoid having employees or IT teams cloud your insights, set up filters for internal and developer traffic. You can create up to 10 filters per property.

The Gotcha: Setting up filters for these users is only the first step – you’ll also need to toggle the filter to “Active” for it to take effect (a step that didn’t exist in UA). Make sure to turn yours on for accurate reporting.

Step 6: Migrate Users

The Gist: If you were previously using UA, you’ll need to migrate your users and their permission settings to GA4. Google has a step-by-step guide for migrating users.

The Gotcha: Migrating users is a little more complex than just clicking a button. You’ll need to install the GA4 Migrator from Google Analytics add-on, then decide how to migrate each user from UA. You also have the option to add users manually.

Step 7: Migrate Custom Events

The Gist: Event tracking has fundamentally changed in GA4. While UA offered three default parameters for events (eventcategory, action, and eventlabel), GA4 lets you create any custom conventions you’d like. With more options at your fingertips, it’s a great opportunity to think through your overall measurement approach and which data is truly useful for your business intelligence.

When mapping UA events to GA4, look first to see if GA4 is collecting the data as an enhanced measurement, automatically collected, or recommended event. If not, you can create your own custom event using custom definitions. Google has the details for mapping events.

The Gotcha: Don’t go overboard creating custom definitions – GA4 limits you to 50 per property.

Step 8: Migrate Custom Filters to Insights

The Gist: Custom filters in UA have become Insights in GA4. The platform offers two types of insights: automated insights based on unusual changes or emerging trends, and custom insights based on conditions that matter to you. As you implement GA4, you can set up custom insights for Google to display on your Insights dashboard. Google will also email alerts upon request.

The Gotcha: Similar to custom events, GA4 limits you to 50 custom insights per property.

Step 9: Migrate Your Segments

The Gist: Segments work differently in GA4 than they do in UA. In GA4, you’ll only find segments in Explorations. The good news is you can now set up segments for events, allowing you to segment data based on user behavior as well as more traditional segments like user geography or demographics.

The Gotcha: Each Exploration has a limit of 10 segments. If you’re using a lot of segments currently in UA, you’ll likely need to create individual reports to see data for each segment. While you can also create comparisons in reports for data subsets, those are even more limited at just four comparisons per report.

Step 10: Migrate Your Audiences

The Gist: Just like UA, GA4 allows you to set up audiences to explore trends among specific user groups. To migrate your audiences from one platform to another, you’ll need to manually create each audience in GA4.

The Gotcha: You can create a maximum of 100 audiences for each GA4 property (starting to sense a theme here?). Also, keep in mind that GA4 audiences don’t apply retroactively. While Google will provide information on users in the last 30 days who meet your audience criteria — for example, visitors from California who donated more than $100 — it won’t apply the audience filter to users earlier than that.

Step 11: Migrate Goals to Conversion Events

The Gist: If you were previously tracking goals in UA, you’ll need to migrate them over to GA4, where they’re now called conversion events. GA4 has a goals migration tool that makes this process pretty simple.

The Gotcha: GA4 limits you to 30 custom conversion events per property. If you’re in e-commerce or another industry with complex marketing needs, those 30 conversion events will add up very quickly. With GA4, it will be important to review conversion events regularly and retire ones that aren’t relevant anymore, like conversions for previous campaigns.

Step 12: Migrate Alerts

The Gist: Using custom alerts in UA? As we covered in Step 8, you can now set up custom insights to keep tabs on key changes in user activity. GA4 will deliver alerts through your Insights dashboard or email, based on your preferences.

The Gotcha: This one is actually more of a bonus – GA4 will now evaluate your data hourly, so you can learn about and respond to changes more quickly.

The Future of Measurement Is Here

GA4 is already transforming how brands think about measurement and user insights – and it’s only the beginning. While Google has been tight-lipped about the GA4 roadmap, we can likely expect even more enhancements and capabilities in the not-too-distant future. The sooner you make the transition to GA4, the sooner you’ll have access to a new level of intelligence to shape your digital roadmap and business decisions.

Need a hand getting started? We’re here to help – reach out to book a chat with us.

Was this blog written by ChatGPT? How would you really know? And what impact would it have on Oomph’s site if it were?

Yes, we know there are some great AI-detecting tools out there. But for the typical reader, picking an AI article out of a crowd can be challenging. And with AI tools like ChatGPT delivering better-quality results than ever, many companies are struggling to decide whether to hand their content and SEO reins over to the machines.

While AI can add value to your content, companies should proceed with caution to avoid some potentially big pitfalls. Here’s why.

Quality Content Is Critical to SEO

All the way back in 1996, Bill Gates said “Content is King.” This phrase became ubiquitous in the early years of SEO. At that time, you could rank well simply by writing about a search topic, then optimizing your writing with the right keywords.

Since then, search algorithms have evolved, and the Google search engine results page (SERP) is more crowded than ever (not to mention the new continuous scroll). While ranking isn’t as easy as it used to be, content – whether it’s a video, an image, a product, a blog, or a news story – still matters. When content ranks well, it’s an ad-spend-free magnet for readers that eventually become customers and subscribers. What else on your website can do that?

That makes your content special. It also puts a premium on producing a high volume of relevant content quickly. For years, brands have done this the old-fashioned way: with copywriters and designers researching, writing, revising, creating images, and publishing ad infinitum.

Until AI.

AI-Powered Content Generation Changes How We Make Content

There’s no point in denying it: AI will impact SEO. But it’s still up for debate just how deep that impact will be.

The rise of AI-powered language processing tools like ChatGPT and DALL-E makes quick content generation a reality. They can easily produce high-quality content that will likely only get better with time. ChatGPT can produce an article in minutes, not hours, and even suggest keywords for you.

For all those reasons, marketers have embraced these new tools – ChatGPT shattered records when it reached 100 million daily active users in a mere two months. As the saying goes, though, just because we can, doesn’t mean we should – especially if using it means compromising on quality or losing what makes us, well, us.

After all, AI is a tool, not a replacement human. If you’re considering integrating AI into your martech stack, here’s what to keep in mind.

4 Things to Know Before Using AI for Content

1. Google may ding you.

In August 2022, Google released an algorithm update called the “helpful content update.” You can read more on Google’s blog, but what’s important is this: Google prioritizes content by people, for people.


In other words, using AI solely to churn out articles that feed the search engine beast won’t work. You should continue to create content that puts your audience first, is genuinely helpful, and is 100% unique to your brand.


But Google’s stance does beg the question: Will they really know if you used AI to generate your content? Well, they do have a very special set of skills…

Animated gif of Liam Neesen mouthing the words “I will find you” from the movie Taken (2008)

While AI content can be good quality and easy to read, tools like Crossplag’s AI Content Detector and OpenAI’s GPT-2 Output Detector can detect whether something is written by a human or by an AI bot. That comes down, in part, to the fact that AI lacks EEAT – experience, expertise, authority, and trust – which is not just a major factor in SEO, but a major reason why people consume content in the first place.

2. AI isn’t always accurate.

AI culls information from across the web, and it’s remarkably good at it. But aggregating massive amounts of information isn’t the same as fact-checking. AI tools often get it wrong – even with easily verifiable, fact-based questions.

Take the question: What is the largest country in Central America that isn’t Mexico?

AI’s answer:

The largest country in Central America that isn’t Mexico is Guatemala. Guatemala has an area of about 108,890 square kilometers, making it the largest country in Central America by land area. It is bordered by Mexico to the north, Belize to the northeast, Honduras to the east, El Salvador to the southeast, and the Pacific Ocean to the south.

Source for AI’s answer

Google’s answer:

Nicaragua is the largest country in the subregion, with a total area of over 130 thousand square kilometers, followed by Honduras, with more than 112 thousand square kilometers.

(Hint: Google is right)

This is a problem for your business and for your SEO. Accuracy is an important part of EEAT. It’s especially critical for “your money or your life” (YMYL) content, like financial or medical advice. In these cases, the content you publish can and does impact real people’s lives and livelihoods.

Spotty accuracy has even prompted some sites, like StackOverflow, to ban AI-generated content.

3. You don’t have the rights to your AI-generated content.

AI-generated content isn’t actually copyrightable. Yes, you read that right.

As it stands, the courts have interpreted the Copyright Act to mean that only human-authored works can be copyrighted. Something is only legally defensible when it involves at least a minimal amount of creativity.

We’re all familiar with this concept when it comes to books, TV shows, movies, and paintings, but it matters for your website, too. You want your content and your ideas to be yours. If you use AI-generated content, be aware that it isn’t subject to standard intellectual property rules and may not be protected.

4. AI-generated content can’t capture your voice.

Even if you fly under Google’s radar with your AI content, it still won’t really feel like you. You are the only you. We know that sounds like it belongs on an inspirational poster, but it’s true. Your voice is what readers will connect with, believe in, and ultimately trust.

Sure, AI may succeed at stringing together facts and keywords to create content that ranks. And that content may even drive people to your site. But it lacks the emotional intelligence to infuse your content with real-life examples and anecdotes that make readers more likely to read, share, and engage with your content and your brand.

Your voice is also what sets you apart from other brands in your industry. Without that, why would a customer choose you?

AI and SEO Is a Journey, Not a Destination

AI is not the end of human-driven SEO. In reality, AI has only just arrived. But the real opportunity lies in finding out how AI can enhance, not replace, our work to create winning SEO content.

Think about content translation. Hand translation is the most premium translation option out there. It’s also costly. While machine translation on its own can be a bit of a mess, many translation companies actually start with an automated solution, then bring in the humans to polish that first translation into a final product. If you ask us, AI and SEO will work in much the same way.

Even in a post-AI world, SEO all comes down to this guidance from Google:

“If it is useful, helpful, original, and satisfies aspects of E-E-A-T, it might do well in Search. If it doesn’t, it might not.”

If and when you do decide to leverage AI, keep these tips in mind:

At Oomph, we believe quality branded content is just one component of a digital experience that engages and inspires your audience.

Need help integrating SEO content into your company’s website? Let’s talk.

There’s a phrase often used to gauge healthcare quality: the right care, at the right time, in the right place. When those elements are out of sync, the patient experience can take a turn for the worse. Think about missed appointments, misunderstood pre-op instructions, mismanagement of medication… all issues that require clear and timely communication to ensure positive outcomes.

Many healthcare organizations are tapping into patient engagement tools that use artificial intelligence (AI) to drive better healthcare experiences. In this article, we’ll cover a number of use cases for AI within healthcare, showing how it can benefit providers, their patients, and their staff in an increasingly digital world.

Healthcare Consumers are Going Digital

Use of AI in the clinical space has been growing for years, from Google’s AI aiding diagnostic screenings to IBM’s Watson AI informing clinical decision making. But there are many other touchpoints along a patient’s continuum of care that can impact patient outcomes.

The industry is seeing a shift towards more personalized and data-driven patient engagement, with recent studies showing that patients are ready to integrate AI and other digital tools into their healthcare experiences.

For instance, healthcare consumers are increasingly comfortable with doctors using AI to make better decisions about their care. They also want personalized engagement to motivate them on their health journey, with 65% of patients agreeing that communication from providers makes them want to do more to improve their health.

At the same time, 80% of consumers prefer to use digital channels (online messaging, virtual appointments, text, etc…) to communicate with healthcare providers at least some of the time. This points to significant opportunities for digital tools to help providers and patients manage the healthcare experience.

Filling in Gaps: AI Use Cases for Healthcare

Healthcare will always need skilled, highly trained experts to deliver high quality care. But, AI can fill in some gaps by addressing staffing shortages, easing workflows, and improving communication. Many healthcare executives also believe AI can provide a full return on investment in less than three years.

Here are some ways AI can support healthcare consumers and providers to improve patients’ outcomes and experiences.

Streamline basic communications

Using AI as the first line to a patient for basic information enables convenient, personalized service without tying up staff resources. With tools like text-based messaging, chatbots, and automated tasks, providers can communicate with people on the devices, and at the times, that they prefer.

Examples include:

Remove barriers to access

AI algorithms are being used in some settings to conduct initial interviews that help patients determine whether they need to see a live, medical professional — and then send them to the right provider.

AI can offer a bridge for patients who, for a host of reasons, are stuck in taking the first step. For instance, having the first touchpoint as a chatbot helps overcome a barrier for patients seeking care within often-stigmatized specialities, such as behavioral health. It can also minimize time wasted at the point of care communicating things like address changes and insurance providers.

Reduce no-show rates

In the U.S., patient no-show rates range from 5.5 to 50%, depending on the location and type of practice. Missed appointments not only result in lost revenue and operational inefficiencies for health systems, they can also delay preventive care, increase readmissions, and harm long-term outcomes for patients.

AI-driven communications help ensure that patients receive critical reminders at optimal times, mitigating these risks. For instance:

Close information gaps

Imagine a patient at home, alone, not feeling well, and confused about how to take their medication or how to handle post-operative care. Not having that critical information can lead to poor outcomes, including readmission.

Delivering information at the right time, in the right place, is key. But multiple issues can arise, such as:

By providing consistent, accurate, and timely information, AI-enabled tools can provide critical support for patients and care teams.

Minimize staff burnout

Burnout and low morale have contributed to severe staffing shortages in the US healthcare system. The result is an increase in negative patient outcomes, in addition to massive hikes in labor costs for hospitals and health systems.

AI can help lighten the burden on healthcare employees through automated touchpoints in the patient journey, such as self-scheduling platforms or FAQ-answering chatbots. AI can even perform triage informed by machine learning, helping streamline the intake process and getting patients the right care as quickly as possible.

This frees up staff to focus on more meaningful downstream conversations between patients and care teams. It can also reduce phone center wait times for those patients (often seniors) who still rely on phone calls with live staff members.

Maximize staff resources

When 80% of healthcare consumers are willing to switch providers for convenience factors alone, it’s crucial to communicate with patients through their preferred channels. Some people respond to asynchronous requests (such as scheduling confirmations) late at night, while others must speak to a live staff member during the day.

Using multimodal communication channels (phone, text, email, web) offers two major benefits for healthcare providers. For one, you can better engage patients who prefer asynchronous communication. You can also identify the ratio of patients who prefer live calls and staff accordingly when it’s needed most.

Leverage customer feedback

AI provides fast, seamless avenues to gather and track patient satisfaction data and create a reliable, continual customer feedback loop. Tools like chatbots and text messaging expand the number of ways patients can communicate with healthcare providers, making it easier to leave feedback and driving not only a better digital customer experience but potentially leading to better satisfaction scores that may impact payment or quality scores.

AI offers another benefit, too: the ability to identify and respond more quickly to negative feedback. The more swiftly a problem is resolved, the better the consumer experience.

A Few Tips for Getting Started

First, find a trusted technology partner who has experience with healthcare IT stacks and understands how AI fits into the landscape. The healthcare industry is distinctly different from other verticals that might use tools like chatbots and automated tasks. You need a partner who’s familiar with the nuances of the healthcare consumer experience and regulatory compliance requirements.

Next, start small. It’s best to choose your first AI applications in a strategic, coordinated manner. One approach is to identify the biggest bottlenecks for care teams and/or patients, then assess which areas present the lowest risk to the customer experience and the greatest chance of operational success.

Finally, track the progress of your first implementation. Evaluate, iterate, evaluate again, and then expand into other areas when you’re comfortable with the results.

Focal points for iteration:

Above all, remember that successful use of AI isn’t just about how well you implement the technology. It’s about the impact those digital tools have on improving patient outcomes and increasing patient satisfaction with their healthcare experience.

Interested in exploring the specific ways AI can benefit your care team and patients? We’re here to help! Contact us today.

Google Analytics 4, or GA4, is Google’s fourth iteration of its website analytics platform. This is no ordinary upgrade! Leveraging the power of big data and machine learning, GA4 offers entirely new ways to collect and analyze user activity data across websites and apps.

While GA4 provides access to robust new tools and features for data-driven decision making, it also sheds many of the metrics and reports we’re used to in Google Analytics 3 (a.k.a. Universal Analytics, or UA).

Google will be sunsetting UA properties in July 2023. Here’s what you need to know about GA4’s capabilities — and why you should start the transition sooner rather than later.


Not sure which platform you currently have (UA vs. GA4)? 

Take a look at this cheat sheet.


Key Benefits of Google Analytics 4

We’re living in a more privacy-centric world, and GA4 is Google’s answer to stricter data laws and browser regulations. GA4 is designed to function without third-party cookies, using machine learning and statistical modeling instead to collect data.

This change comes with a range of benefits, from more actionable user insights to enhanced reporting capabilities.

Broader Insights

Unlike UA, GA4 has the ability to track users across devices and platforms, combining all the data into a single property with a unified set of metrics and dimensions. This gives you a more complete picture of how users interact with your brand, whether they’re on your website, your mobile app, or both.

Another major advantage is that you can more effectively track conversions — particularly for users that might visit on their mobile, come back on desktop, and then download/purchase/register through your app. Because GA4 attributes actions to users across devices and platforms, you can see the entire journey a user takes from start to finish.

Predictive Metrics

Using machine learning, GA4 offers powerful new metrics to predict user actions and includes new data buckets like Acquisition, Engagement, Monetization, and Retention. These predictive metrics can help you better understand your audience and make more informed decisions, so you can do things like tailoring your website experience for different users or creating targeted marketing campaigns.

Customized Reporting

UA offers a set of standard reports with some customization options. By contrast, GA4 enables and encourages users to create custom reports with only the data they need.

With greater freedom to create reports, you can declutter your dashboard and make decisions more quickly by drilling down to the data that’s most important to you. You can even create a separate “Audiences” report with custom user definitions, further tailoring the data to support your business needs.

Key Features of Google Analytics 4

With comprehensive user tracking, predictive metrics, customizable reports, and more, GA4 promises to be much more powerful than any previous version of Google Analytics. Here are the core capabilities driving all of those benefits.

Event-Based Tracking

One of the biggest changes in GA4 is how user data is collected. In UA, data is collected via tags placed on each page of a website. Users are tracked via sessions, or set periods that begin and end when a user enters and exits a site.

Instead of relying on pageviews and sessions, GA4 tracks user interactions, known as “events,” as users complete them. This focus on individual user interactions provides a more complete picture of each user’s journey across your website or app.

This event-based model also makes it possible to track interactions that don’t happen on web pages but can be influenced by digital marketing, such as in-store visits or in-app purchases. And, it allows Google to more accurately deduplicate users.

Cross-Platform Data Consolidation

In UA, “properties” are where Analytics data is collected for individual websites and apps. You can then use views to see and report on the data in various ways.

GA4 uses individual data streams to combine data from different platforms into a single property. You can add multiple data streams into a property and create different views based on certain criteria.

For example, you could create a stream for all web traffic, a stream for all app traffic, or a stream for traffic from both that covers a given geographic area. By placing the same tracking code across different digital platforms, you can consolidate data to track users who move between the streams.

Advanced Analytics

Maybe the most exciting feature for data geeks like us, GA4’s Explorations Hub offers a suite of advanced data and analytical techniques that go well beyond standard reports. The Explore section lets you create custom analyses to uncover deeper insights about your website and app performance, with filters and segments so you can drill down even further.

GA4 also integrates with BigQuery, Google’s cloud-based data warehouse, where you can run complex analyses of very large datasets. Bonus: BigQuery offers near-unlimited data storage.

Machine Learning

In an increasingly cookie-less world, Google is attempting to balance privacy limitations with usable insights. Using machine learning, GA4 fills in data gaps and provides predictive insights about user behavior and trends.

Machine learning combines artificial intelligence (AI) and computer science to fill in gaps and make predictions. It essentially looks for patterns of activity that can be fed into an algorithm to understand and predict how users behave online.

As an example, GA4’s AI-powered insights can help identify user actions that are most likely to lead to conversions. Using metrics like purchase probability, churn probability, and revenue prediction, you can customize marketing campaigns or target specific audiences to achieve your conversion goals.

Why You Should Switch to GA4 ASAP

You’ll be able to collect and use platform data in your existing UA property until July 1, 2023. After that, you’ll be able to access historical data for only six months. That’s why we strongly recommend you implement GA4 as soon as possible.

Transitioning now will allow you to:

Feed The Machine

Many of GA4’s core features rely on machine learning, and in order for machine learning to be effective, the algorithm needs time to learn. The sooner you set up and start collecting data in GA4, the more time your models will have to analyze and learn, shaping the insights you’ll need down the road.

Train Your People

Those using GA4 will need time to learn the new terminology, user interface, and capabilities. Switching early gives your team time to get used to the new platform and work out new processes and reporting while you still have UA to fall back on.

Get Year-Over-Year Data

GA4 is forward-facing only, which means your new GA4 property will only collect data from the time of creation; it won’t import past data from UA. Once UA sunsets next year, you’ll be relying solely on GA4 for year-over-year data.

Why does that matter? Here at Oomph, when we launch client projects, we use Google Analytics data to analyze digital platform performance so we can develop the best possible user experience. By examining user flows, page visits, common search terms, engagement metrics, and more, we can very quickly get a picture of where a platform has strengths and weak points. And we need your historical data to do it.

Ready to switch to Google Analytics 4? It’s a relatively simple process. Just follow the steps Google provides, whether you want to switch from UA to GA4 or set up a GA4 property alongside an existing UA property.

If you’re not feeling confident about handling the transition alone, we’d love to help. Get in touch with us today.

You’ve just rolled out an important new feature on your platform, and it’s time to answer the all-important question: is it getting the results you want? If you’ve set up an analytics tool, you can look at performance indicators like registrations, logins, downloads, or shares. But that kind of quantitative data will only get you so far.

Let’s say that new feature isn’t having the impact you’d hoped for — maybe registrations are lacking or engagement is low. You have a problem you need to solve, but you don’t have any information about why it’s happening. And you may have an entirely different underlying problem you need to address.

Where can you find actionable information? Enter qualitative research.

By answering the why behind what’s happening, qualitative data provides context for problems that surface through quantitative analysis. It helps you uncover the root of the problem you have and can also reveal problems you didn’t even know existed.

In this article, we’ll cover how to use both types of research to inform your platform design.

First, the Numbers: Quantitative Research

When you’re evaluating the performance of a digital platform, a good place to start is the cold, hard numbers. Quantitative research provides numerical data that can indicate, at a glance, whether your platform is meeting your business objectives. It can also show the scale of any problems and help prioritize which ones to address.

One major benefit of quantitative data is benchmarking. Tracking your data over time reveals whether UI changes are producing the results you want — and can help you measure the ROI of your efforts. You can also compare your data to an industry benchmark or a competitor’s stats as a barometer for your own performance.

Here are some examples of quantitative research methods:

Web analytics

This data describes what people are doing with your platform: where they go, what they click on, what features they use. It’s good for finding problems and monitoring the performance of content or features.

A/B testing

Here, you’re using experiments to compare different UI designs. By creating two live versions of the same element, like a call-to-action button, you can see which one performs best. Learn more in our article on A/B testing.

Surveys and questionnaires

Surveys let you gather information about your users’ preferences, attitudes, and behaviors, and they can produce a combination of quantitative and qualitative data. For easy-to-capture numerical data, use techniques like ratings and multiple-choice questions.

Usability testing

By measuring user experience with hard data, you can test how easy (or not) a platform feature is to use. Let’s say you just released a reminder function, and you want to know if users can create a reminder in two minutes or less. You can run a test where you ask participants to set a reminder, and measure what percentage are able to complete the task within two minutes.

Now that you’ve got a sense of what users are doing on your platform, let’s look at ways to learn why and how they’re doing it.

Now for the Words: Qualitative Research

Qualitative research can help you investigate why something is happening, identify ways to fix problems, and even determine whether you should phase out a feature or redesign it. Using detailed, contextual descriptions of users’ experiences, you can dive deeper into exactly which elements are working well and which are problematic.


Quantitative and qualitative research both provide useful data, but they’re more powerful when used together.


Unlike with quantitative research, you don’t need a ton of data points to get usable info. For example, if you see five customers in a row walk into the corner of a display in a retail store’s entrance, you can safely assume that most visitors will do the same thing.

You may be avoiding qualitative data because it seems expensive. And some techniques, like focus groups, require a greater investment than others. But, because you don’t need an enormous amount of data, qualitative research can be very cost-effective. It might even save you money by helping you identify and fix problems faster.

Here are some examples of qualitative research methods:

User Interviews

There are a number of different ways to handle user interviews, depending on the type and specificity of info you’re looking for. Here are a few:

Focus Groups

These are similar to user interviews, but they’re done in a group setting. The advantage of a group is that it can often generate more feedback, as people tend to open up when they hear the experiences of others. Just be sure you have a moderator who gives everyone a chance to speak.

Field Studies

What people say they do… is often not what they actually do. Watching platform users in their natural environment can reveal gaps in your understanding of the user experience. You can use direct observation, interviews, contextual inquiry, and usability tests to learn how people do things and why they do them in particular ways.

Diary Study

This method asks users to document their experiences over time, making it useful for understanding longer-term behaviors. You can learn things like what motivates people to use certain features, what they’re trying to accomplish, how they feel, and what their overall journey looks like.

User Surveys

As opposed to quantitative surveys, qualitative surveys use open-ended questions to learn what users think and feel in their own words. One common pitfall: avoid leading questions. Instead of asking, say, “How easy was it to find the info you needed?”, ask “Describe your experience looking for that information.”

Like Peanut Butter & Jelly

Quantitative and qualitative research both provide useful data, but they’re more powerful when used together. Remember that quantitative data can tell you when there’s a problem with your platform design, but you’ll need qualitative data to know how to fix it.

Chances are, you’ll use them at different times. Qualitative research can be done during the initial design phase, once you have a working product, or during a redesign. It’s especially valuable at the beginning of a design process because it can help you focus on what your users need and why. Quantitative research is generally done only when you have a working product (either at the beginning or end of a design cycle), so you can measure the results of a design or change.

Want to learn more about how data-driven design can improve your platform performance? We’d love to help. Contact us today to schedule a call.

You may have heard the old adage, “A website is never done.” Even the best digital platforms go through multiple rounds of changes, updates, and a complete overhaul now and then. Because even if your platform is already good, there’s always something you can do to improve the user experience and better support your business goals.

The key is figuring out which changes truly result in improvements, and which are a waste of your money and time.

Why You Need A/B Testing

Here are a few use cases where A/B testing can deliver crucial info:

Whatever the business case, you must understand how users interact with your platform and how its features impact their experience, in order to make informed decisions about platform design and content.

Too often, companies evaluate changes with internal stakeholders instead of real users. In the end, you may go through a lot of development work without knowing if the changes you’re making will result in something impactful. Instead, with less time and fewer resources, __you can use A/B testing with your actual audience to find out definitively what’s effective and what’s not. __

How A/B Testing Helps Your Platform

In addition to helping maximize the effectiveness and minimize the resources invested in platform redesign, A/B testing provides invaluable short- and long-term benefits:

Increase Conversions

Probably the number-one goal for most redesign efforts, increasing conversion rate is one of the most robust uses of A/B testing. Rather than guessing at what makes users complete a registration form or take a desired action, you get hard data to confirm whether a change truly produces a lift in conversions.

Improve User Engagement & Retention

Bounce rate is often a key indicator of user experience and can have a significant impact on your conversion goals. Testing multiple elements of a particular page can help you find visitor pain points and improve their overall experience, ultimately getting them to spend more time on your site.

Learn About Your Audience

By progressively testing which elements your users gravitate to (or from), you can learn a little more about your audience at each step, and then use that data to inform future design and content.

Road-Test New Features

Before you introduce a new feature, launching it as an A/B test can show how your audience is likely to react. You’ll get hard and fast data in a real-world environment with less risk.

Personalize User Experiences

You can use A/B testing as a way to identify steps toward platform personalization, to understand which forms of personalization could potentially increase user engagement.

What Should You Test?

A/B testing can be used for everything from full page designs to single content elements. Even small and simple changes can significantly impact the user experience and, consequently, your engagement and conversion rates.

When Humana A/B tested a website banner, the version with pared-down copy and a different photo increased click-throughs by 433 percent! In a second test, changing the call-to-action (CTA) copy increased click-throughs by a further 192 percent, showing that even subtle word changes can boost engagement.

How do you figure out what to test? Examining quantitative or qualitative data will help you identify potential pain points and give you a basis for experimentation. Maybe your homepage has an unusually high bounce rate, or users are providing negative feedback on your sign up process. Once you’ve identified an issue, form a hypothesis to test: define a problem, propose a solution, and identify metrics for success or failure.

Whatever you include in your testing plan, focus on things that are most likely to impact the metric you’re trying to improve. For instance, if you want to increase conversion rate, you might test the design or placement of a CTA.

Here are some commonly tested elements:

One caution: if you’re testing multiple elements simultaneously, make sure they’re distinct enough that they don’t affect each other and impact the results of each test. Your results should be related only to the options you’re presenting, so there’s a clear understanding of what exactly is influencing your audience.

One Last Word of Advice

In the end, one form of testing alone is never a panacea for improving your platform. While A/B testing provides valuable data, it has limitations, too. Most importantly, unlike qualitative analysis, it doesn’t explain the why behind your measured results. Also, the data produced is only relevant to the specific area you’re testing, versus open-ended user testing that could surface other challenges hindering your platform’s performance.

That’s why qualitative feedback is still vitally important for your site — it surfaces things you can’t learn from numbers alone (like a user not finding you trustworthy or credible). A/B testing can give you relatively quick and easy ways to improve your user experience, but it doesn’t give you every answer you need.

Your business never stands still, and your audience is always evolving and changing. We’re here to help you keep looking forward. Contact us today to talk about optimizing your platform experience.

If you can’t measure it, you can’t improve it. It’s true for your business, and it’s true for your digital platform. Yet we’ve seen organizations from startups to enterprises neglect to incorporate measurement into their platform strategy.

Data shows you what is and isn’t working in your platform. And, unlike most websites, platforms provide detailed information about known users across specific touchpoints — accurate, first-party data that doesn’t rely on cookies or fuzzy analytics. Actionable insights await; you just have to know what you’re measuring for.

Here’s how to take a strategic approach to measuring platform performance.

Start From the Top

Measuring the success of your platform involves the same general principles used in strategic planning. Start from the top and work your way down:

Once you define your platform’s core purpose, you can identify which metrics to track. Just make sure that if you move the needle on those metrics, you’re truly moving the needle for your business.

Here’s an example: Let’s say you run a healthcare system whose primary goal is to save lives. To meet that goal, your employees need speedy access to your procedures for patient care. So, you build an intranet platform in order to provide the fastest possible access to that critical information. Your core purpose is to make sure this information is as easy to find as possible, so employees have critical information at critical moments.

What Should You Measure?

You’ve identified your platform’s core purpose. Next question is, what is the core interaction your platform relies on to achieve that purpose? What’s the single most important thing you need users to do? That action determines how you define an “active” platform user, and it’s the key driver for what you should measure.

Just like with social media, where the term “monthly active users” is widely used but has many different meanings, business platforms often have unique definitions of an active user. A company intranet focused on employee engagement might define an active user as someone who posts content a certain number of times per month. A business platform offering exclusive deals to attract new customers might define an active user as a customer who redeems at least one deal per year.

Whatever your platform’s purpose is, you need to be tracking metrics related to your definition of an active user, in order to optimize the core interaction that drives your business goals.

Examples of Useful Metrics

Before we dive into the list, there’s a caveat: Just because you can measure a ton of metrics doesn’t mean you should. Too much data can be distracting, and paying attention to too many metrics can create confusion and cause analysis paralysis. The goal of measurement isn’t to manage a dashboard; it’s to make decisions and take actions that drive positive business outcomes.

Choose a primary goal, define a core objective and active user, and aim for up to five core metrics to measure success. Here are some examples:

Growth

If your business goals depend on having a large number of platform users, you might use one of the following growth measures:

Reach

This is useful for platforms where you’re looking to engage a certain proportion of a population, such as your employees or your customer base. You might track:

Engagement

Engagement covers a lot of ground, and it’s easy to get lost in the weeds. Focus on the metrics that tell you how people are responding to your efforts to engage them at various touchpoints. Here are some examples:

Begin at the Beginning

It’s a mistake to think about measurement only after you’ve built your platform. Remember, platform measurement isn’t as easy as dropping in base Google Analytics code. Platform metrics are deep and nuanced, so you need to think strategically from the start. Plan the key metrics up front, and incorporate measurement into your platform roadmap from the beginning.

Your game plan, in a nutshell:

  1. Decide what to measure
  2. Implement tracking capabilities
  3. Measure platform performance
  4. Analyze the results and find actionable insights
  5. Make decisions: what’s working, and what needs to change?

Establishing measurement practices early on enables you to continually track, analyze, and optimize performance over the life of your platform. Already launched? Fear not. It’s never too late to implement measurement techniques to optimize platform performance.

If you’re thinking about how to be more strategic with platform measurement, we’d love to help. Feel free to reach out with any questions you have.