Post-pandemic, a lot of marketing teams are experiencing the Great Resignation. We have seen some of our clients’ teams experience a 50%+ turn-over during the last 18 months and now many struggle to rehire and fill open roles. 

Over the course of the last 15 years in the agency world, I’ve seen the pendulum swing from most companies choosing to leverage agency partners as a key component of their team, to the other side of the pendulum, and instead try to build internal teams as the primary engine for execution while only using agencies for technical or time-consuming tasks. Right now, we see it swinging back the other way. Agencies are again a key component to marketing strategy development and execution. As companies struggle to fill their open roles with quality candidates, they are outsourcing to agencies they trust. 

If you’re in a similar position, Hedy & Hopp has helped countless clients in the healthcare space accomplish their objectives and launch or fine-tune their digital marketing efforts. You’re not alone – recruiting quality candidates is very difficult right now. If your campaigns can’t wait, I’m sure the next question you’re asking yourself is, “But how difficult is it to onboard a new agency partner?” 

How do you know it’s the right time to investigate a more meaningful relationship with a digital marketing agency? 

Here are a few signs to look for: 

  1. Your internal team and/or agency can’t tell you the exact patient revenue they drove. Even worse, they can’t tell you exactly how many new patients they drove last week/month/year. Accomplishing this task takes a very technical-minded team and is a common area we tackle first for clients.
  2. Your internal team and agency lack consistency in presenting ideas and new strategies to improve your marketing efficacy. From new brand awareness campaigns to patient acquisition programs, they’re not providing ideas for growth. We typically see this when your team is understaffed and spread too thin!
  3. When you call them frantic because you need to increase or decrease the budget and your internal team or existing agency isn’t able to provide reasonable, practical ideas based on data. 

If you’re struggling to solve staffing problems and your campaigns and objectives can’t wait, you need to level up your resources and make sure you’re using insights, not gut feelings. You need Hedy & Hopp. 

Connect with us today to chat more about how we help clients in the healthcare space.

2020 was quite a rollercoaster for businesses, but for medical device sales (which rely historically on conferences, trade shows, and in-office visits), it ripped the rug out from under them.

Since COVID started, Hedy & Hopp has helped a variety of medical sales businesses become more digital-savvy and update their marketing and sales processes to adjust to the new normal. Tactics have included everything from enhanced technology to better manage sales pipelines, automating lead nurturing, creating processes to educate prospects digitally, and much more.

We have heard from countless medical sales companies that they are all facing the same issues so we decided to conduct a webinar to provide some guidance as these companies finalize their 2021 strategies. While there isn’t a one-size-fits-all solution, there are definitely best practices that every medical sales company should be incorporating into their processes in 2021 that can help provide a more solid sales foundation moving forward.

You’ll learn the following:

Join Hedy & Hopp, a marketing agency that specializes in healthcare organizations and medical sales, in this informative and action-oriented one-hour webinar.

Yes, you read that correctly. Referencing performance on your website based on the number of visitors and pageviews has officially been killed by Google as they launched Google Analytics 4 (GA4) this quarter. 

It’s a huge shift for marketers. GA4 is a new version of Google Analytics. It completely reimagines how users and actions are tracked on websites.  GA4 was previously referred to as website + app beta, but since coming out of beta it will now be the new, officially supported version of Google Analytics. This means that all new developments and support will focus on this version, and older versions will eventually become obsolete. If you need to create a new property today, it will default to GA4.

How is GA4 different?

The biggest difference in how GA4 tracks a property’s performance is that it uses event-based tracking, versus user-based tracking (such as views). The system is reimagined to care more about what happens on your site, which is truly the most important data for marketers anyway, so we are excited for this development. It also will tackle tracking issues that the current Universal (now considered “old”) version of GA would have more and more often around cookies, which is currently the primary source of tracking in Universal Analytics.

What does this mean?

While many functionalities within GA4 are not fully built out, we are advising all of our clients to install GA4 on their websites now to begin tracking data. You will not be able to move data over from Universal Analytics to GA4, so in the future, if you want to run year-over-year reports, for example, you’ll want to install GA4 immediately.

It is important to note though, that functionality (such as eCommerce tracking and predictive modeling) will be added over the coming months, so our recommendation is to do a basic install but leverage the out-of-the-box reports for now. Over Q1 and Q2, we expect more functionality releases that will ensure we can set up the properties to best leverage all of the tools, and reporting can get more and more sophisticated. You can read more about this fundamental shift in website tracking on Google’s own blog post about the launch of GA4.

So, what next?

We are offering a special flat-rate fee to get GA4 installed before January 1. We never, ever do specials, but it feels like this is a situation that requires it. It’s a low-cost, easy task to cross off your to-do list that will ensure your data is solid. It will also give you access to GA4’s basic reports so you can begin to get used to how the data is going to be reported. It’s a pretty big shift for our industry, and we will continue to write updates as new features are released.

Reach out to us for details. 

We were excited to find out recently that Hedy & Hopp earned a spot (#1,726) on the Inc. 5000 list of the Fastest Growing Companies in the country! Being named to this list is a huge accomplishment for the entire team. 2020 has been a weird year, so we’re thrilled to take moments like these to celebrate.

About the Inc. 5000

In 1982, Inc. introduced the Inc. 500 list of the fastest-growing privately held companies in the United States. Since then, this prestigious list of the nation’s most successful private companies has become the hallmark of entrepreneurial success and the place where future household names first make their mark. Pandora, 7 Eleven, Toys ‘R’ Us, Zipcar, Zappos.com and numerous other well-known brands have been honored by the Inc. 5000. In 2007, the Inc. 500 list expanded to the Inc. 5000, giving readers a deeper, richer understanding of the entrepreneurial landscape and capturing a broader spectrum of success.

Today, the list is a distinguished editorial award, a celebration of innovation, a network of entrepreneurial leaders, and an effective public relations showcase. The Inc. 5000 ranks companies by overall revenue growth over a three-year period. All 5,000 honoree companies are individually profiled on Inc.com. The top 500 are featured in the September issue of Inc. Magazine, the leading entrepreneurial advocate for 38 years running. Inc. also ranks the fastest-growing companies by industry, metro area, revenue, and number of employees, and we also highlight women and minority run companies.

Learn more here.

Marketing and sales teams are the left and right hands of bringing new customers to your organization. We know they work hand-in-hand, but do you treat your organization’s data that way? Combining data is a challenge – we see it all the time. 

The truth is, many of our partners have faced this problem (maybe you’re in a similar boat). You know that multiple channels, such as Facebook and Google Ads, influence your marketing qualified leads (MQL) and sales qualified leads (SQL). You also know that sales activities like phone calls, emails and demos influence your SQL success rate and your close rate. 

But can anyone at your organization say confidently, with data, how all these factors work together? Does Facebook have a better SQL rate but lower MQL rate than Google? What about Facebook versus email? Helping you answer questions such as these is why we built our Multi-Touch Attribution Model for marketing and sales touches. 

The Multi-Touch Attribution Model takes into account both touches from Google Analytics (GA) and your customer relationship management system (CRM)*. Our model combines data from GA and your CRM to break out conversions equally between multiple touchpoints.

Now, not only can you see individual customer paths, but you can also see how each of your channels influence and interact with one another.

The best part is that we leverage technology that is easy to use. Hedy & Hopp takes care of the heavy lifting in terms of data extraction, storage and analysis. You will always have access to your data through Google BigQuery, and your data will automatically populate in a Google Data Studio report that you can customize and share. 

*Note: So far, we have integrated with Hubspot, ActiveCampaign, and SugarCRM. More CRMs to come! 

Attribution beyond the last click

If you use Google Analytics for reporting, you likely use the default attribution model called “last click.” More importantly, GA can’t account for any offline data in your CRM. Using the basic attribution models in most CRMs, you end up with an incomplete view of your customer’s journey.  

We work around this by building our model from scratch using the Google Analytics API data. We look at all of the digital marketing touches for a user, even ones before they convert. So, if a user comes to your site from Facebook, and then converts a week later on Google Ads, we will include both sources in our model. 

But the biggest advantage of our Multi-Touch model is that we integrate your Google Analytics property and your CRM to track the same user from Google into your CRM. We then look at all of the different touches in your CRM system and add that to the attribution model.

The process can be set up in two weeks, and as your prospects convert to customers, the data begins to populate! Depending on your prospect-to-customer lifecycle, you can start getting actionable data in just a few weeks.  

Imagine knowing that Facebook converts better with an introduction email, while Google Ads converts better with an early demo! 

By now, most people have heard of GDPR, but many are still confused about who it applies to and its implications for businesses. For those of you who haven’t heard of GDPR, it stands for General Data Protection Regulation. GDPR is a set of rules passed by the EU to give users more control over personal data online and protect against the misuse and mishandling of data. However, even if you aren’t from the EU, keep reading — GDPR may still apply to you. AND it is now looked up to as the gold standard for data privacy laws, so some of the regulations in GDPR will likely be popping up elsewhere. In fact, the California Consumer Privacy Act (CCPA) is a fantastic example of how this has already happened.

Who Does GDPR Apply To?

In addition to all EU companies, GDPR applies to any company worldwide that interacts with companies or individuals in the EU. This means if you market to EU businesses or individuals, GDPR applies to you. If you sell products in the EU, GDPR applies to you. If you have a form on your website that collects data about individuals or companies in the EU, GDPR applies to you. GDPR is more encompassing than many people realize. If, based on the above criteria, you believe you’re subject to GDPR, then start making compliance a priority. Large companies such as Equifax, Facebook, and many others have already been fined hefty amounts for their misuse or mishandling of personal data.

What Type of Data Does GDPR Apply To?

GDPR applies to all personal data. This includes information that can be tied back to you directly, such as a social security number, full name, home address, etc. It also includes information that can only be tied back to you when it is paired with other information about you, such as an IP address, an employer, a job title, race, gender, etc. Note: the examples above are only meant to be a guide for what could be considered personal data; they do not serve as a complete list.

What Needs to Be Done to Ensure GDPR Compliance?

There is much more to GDPR compliance than what we can cover in this short post, but here are some of the most common concerns we deal with in our office day to day:

  1. Look Internally and Document the Flow of Your Data

Organizations have data flowing in from all angles. Mapping out exactly how data was collected, what data was collected, why the data is needed, how it’s stored, and how it will be disposed of — this is all crucial in determining if you are GDPR compliant. Through this process, you will find data that you are not using that can be properly disposed of. You will find data you didn’t even know you were collecting. Plus, doing these things will make it easier to identify potential processes that put you at risk of violating GDPR. Implementing an action plan to help resolve these vulnerabilities and documenting them will help you maintain GDPR compliance.

  1. Update Your Privacy Policy and Terms and Conditions

One of the most important things you can do is to update the privacy policy and terms and conditions that are listed on your site. These should describe exactly how data is being collected, used, and stored. They should also mention the steps that you are taking to be compliant with GDPR.

  1. Add a Cookie Consent Banner

The #1 concern clients raise about GDPR is in regard to adding a cookie consent banner. If your site uses cookies, you are required to let users know what information is being collected and how it will be used.

What About Google Analytics?

If you are tracking user behavior on your site with the most basic Google Analytics setup, then you do not need a cookie consent banner. However, if you enable features like demographic reports, use the remarketing features, add custom dimensions for user IDs, or utilize other more advanced functionalities within GA (which we definitely recommend you do), then you will need to add a cookie consent banner to your site if you operate in the EU or directly market to EU residents. If your company is not located within the EU and you don’t directly target EU residents, we recommend that you consult your legal team for guidance around implementing a cookie consent banner, as the regulations are still unclear for most American companies. The cookie consent banner that is added to the site needs to provide users with an easy way to opt out of any tracking.

  1. Storing Personal Data in Google Analytics

No personally identifiable information should ever be stored in Google Analytics. Not only will it put you at risk from a GDPR perspective, but it is also against Google Analytics’ privacy policy. Personal data often gets pulled into Google Analytics through URLs or page titles. On some sites, data that is captured in a form will be appended as URL parameters on the thank you page after the form is submitted. This results in URLs that look like the following:

www.example.com/thanks/?first=Bob&last=Smith&email=bsmith@gmail.com

These parameters need to be removed from the URL completely, not just filtered out in GA. 

  1. Email Subscriptions

It is not uncommon for websites to have a pre-checked box on their forms next to a statement that reads something along the lines of “I wish to receive future promotions from [company name].” This puts companies at risk for GDPR violations. These boxes need to remain unchecked. Additionally, once a user has signed up to receive emails, they need to be presented with an option to unsubscribe from the email list at any time. The process to unsubscribe needs to be quick and easy for the user to initiate.

To Sum Everything Up…

GDPR has now been in effect for almost two years, and it is not going to fade away anytime soon. In fact, just the opposite is true. It is becoming the standard for other legislation around the world. Big-name companies have already been fined high dollar amounts due to non-compliance. GDPR is an issue companies need to address head-on to avoid the intense repercussions that come along with it. If you are concerned about how you are collecting, processing, storing, or using data, we highly recommend seeking professional guidance. 

This blog is meant to provide a starting point for your journey to become GDPR compliant. It is not a complete guide to ensure GDPR compliance.

If you’re unsure about your level of GDPR compliance, reach out to us to discuss an audit.

As marketers in the healthcare industry, it’s a fine line to walk to try to offer personalized and helpful digital experiences to patients while also ensuring tactics are HIPAA compliant. As an agency that specializes in helping our clients in the healthcare space improve their digital marketing and analytics practices, we have deep experience with sourcing and testing tools. We thought it would be helpful to aggregate a list of our favorite tools that we find ourselves leveraging time and time again.

Note: Currently there is no official training or certification for HIPAA compliance. At Hedy & Hopp, all of our employees go through HIPAA BAA training during their first week of employment (along with Google Analytics certification) to make sure every team member understands the fundamentals when dealing with PII and PHI. Our training platform of choice is www.hipaatraining.com.

Some of our favorite tools:

Website Analytics:

User Experience Optimization:

Business Intelligence and Data Storage/Management tools:

Call Tracking/Attribution:

Patient texting/messaging platforms:

Polling and Research tools:

Manage location listings, online reviews, social media:

Appointment Setting/Management Platform:

Form Submissions:

A final note: Even if you are using the best tools, it’s important to audit access to these tools on a regular basis. Who has login capability and why? Remove access for any non-essential employees and have plans in place to audit access immediately if required. Also, making sure all members of your marketing team have received training to identify PHI and feel comfortable raising potential issues is a really important step. Your legal department is likely focusing most of their attention on the clinical side of the business, so take steps to clean up the marketing and analytics tools before they become an issue.

Opportunity

A well-established professional association had a membership database containing a wealth of information on their 33,000+ members. The association wanted to use this data to help understand why some members were more engaged than others and boost membership attendance at events held by the association. However, with such a large database, the association didn’t know where to start when it came to turning all of that data into insights they could actually use to help accomplish their goals.

Solution

Our Analytics + Decision Science team recognized right away that this was the perfect type of problem to solve with machine learning. Broadly speaking, machine learning is the use of statistical algorithms to find patterns within large amounts of data. Machine learning has been the key to recent breakthroughs in artificial intelligence, and there are also lots of common applications that we encounter in our everyday lives, like when Netflix recommends something to watch or Google autocompletes a search query.

In order to solve our client’s problem, we used machine learning to analyze their membership database and organize the members into different groups, or clusters, based on a variety of attributes, including professional experience, membership tenure, past engagement, and others. After the machine learning algorithm broke the database into different clusters, our analysts drilled down on the results. Using tools like principal component analysis, we could see what attributes the computer weighted most heavily when dividing up the clusters.

The next step was to work with our Digital Marketing + Strategy team to identify which clusters had the most potential for growing engagement. In the end, we found five clusters that had clear potential based on their attributes. Then, we took those five clusters and created five distinct member personas, just like the customer personas we’re familiar with as marketers. Now, using these personas, the professional association can create personalized marketing campaigns with specific content tailored to each persona.

On top of this, we even worked on a proof-of-concept machine learning algorithm that would identify which individual members would be most likely to sign up for a new event. This tool could help our client avoid fatiguing members who are not likely to attend an event, as well as determine which members to potentially target using more costly marketing like direct mail.

Results

Our client was thrilled! 

With machine learning, we were able to parse and analyze a massive amount of data in ways that would have taken human analysts months or even years to do.

Our client was able to transform a large, unwieldy database into five actionable member personas built from real data.

We helped our clients develop sophisticated email campaigns that included 5 workflows and 20 unique paths, targeting each persona with personalized content to guide them toward registering for an event. This new structure is allowing our client to leverage their large database in a strategic, measurable way with a focus on engagement rather than volume of messages sent—a huge improvement of user experience for the organization’s membership.

If you have a big, difficult dataset that you know holds potential but you’re not sure how to get started working with it, give us a call. We’d love to help your team leverage machine learning to tap into the potential of your data.

Few tools are as ubiquitous in digital marketing as Google Data Studio. It’s simple to use, getting better and better every day, and free to boot.

Yet, as much as we at Hedy & Hopp have grown to appreciate sharing data and insights using Data Studio, we have never felt like any Data Studio dashboards are completely up to our standards. As a tool, it has some serious weaknesses that have limited what we thought we could do. Over the last few months, we have worked hard to overcome these weaknesses, because ultimately Data Studio is our best option for creating digital marketing dashboards.

I can be a perfectionist in my work, and when it comes to visualizing data, I have very high standards. I love the ability to make highly customized reports and dashboards with tools like Tableau, Power BI, or Python. Not only can you make very complex concepts easy to interpret, but these tools also allow you to customize the visual experience.

There were a few issues that made us at Hedy & Hopp wary of using Data Studio for a long time. Not only were we stuck with fewer options for visualizations, but it has limited data processing and a page-by-page format that was not very interactive.

We wanted to move away from Data Studio. But it has one powerful strength. It has a very low barrier to entry. Like crazy low.

Data Studio’s Strengths Outweigh Its Weaknesses

All of those other tools require some level of training. I can’t imagine anyone outside of our Decision Science team using Python, and we have worked with very few clients that have even used Power BI or Tableau.

Not only do these tools require you to learn their system, but they also have their own logins. Power BI’s complex user system is amazing for highly sensitive information but is generally overkill for Google Analytics and Google Ads data. Only our most data-savvy clients, with very complex data models, are using Power BI.

Data Studio is the opposite. All you need is a Google account to access and the interface requires very little training. If you can use a banking app on your phone, you would have zero problems using Data Studio in seconds.

Because it is so easy to use, it really expands our audience to practically anyone. This single feature makes Data Studio an awesome tool. If your audience can’t see your insights, it does not matter how powerful your tool is.

So, we decided we would tackle the biggest issues we have working with Google Data Studio.

#1 Make Data Studio Feel Like An Application

When you use your bank app or Instagram, you don’t click from page-to-page. It is not a slideshow. You use the navigation to get to where you need.

In Data Studio, the default navigation is not intuitive and feels more like you are clicking through slides or pages in a book. Not only that, but it can be hard to find a specific page without clicking a dropdown.

If you are using Data Studio to build a report, and you are telling a story in a specific order, I think this feature is great.

The second option is to move the navigation to the left. This is actually not so bad, and it feels a lot more like an application. We thought this would be a good alternative, but it also has some weaknesses.

First, it has no hierarchy. So, all pages are treated equally. This is not bad if you have a few pages, but it can get out of hand in a hurry. If you have 10 or more pages, the left navigation gets quite large. Not only that, but it can be hard to identify subpages.

Google Data Studio pages

Our solution was to build our own left-side navigation that uses the common conventions of standard navigation setups. Plus it looks nice!

Example Google Data Studio Dashboard

In addition to having top-level navigation, we used tabs to create secondary navigation when needed.

Google Data Studio Secondary Navigation

In order to make this navigation, we used a few different design elements including images that look like text, but the most critical part of the process is what we do before we build anything.

The first thing we do is design a sitemap. This allows us to identify all of the key pages we want to include and how they are connected.

Google Data Studio Sitemap

From there, we review with all of the primary stakeholders to make sure we have covered the key information needed. This allows us to build our dashboards a lot faster.

#2 We Created Our Own Visualizations

We also love the new Community Visualization tool in Data Studio. It allows us to build any type of visualization we want, and it can bind to any user’s data.

We loved this feature so much, we worked with the Data Studio team at Google to have two of our custom visualizations be featured in the community visualizations gallery in Data Studio.

If you would like to use our statistical significance tool “Stats Analyzer” or the “Data Target Card,” you can access them in any report in a few simple steps.

Anvil Visualizations in Google Data Studio Community Gallery

Not only can you find the two tools we built, but there are more than 20 others in the gallery from companies like Supermetrics, Bounteous, or even the great developers at Google Data Studio like Yulan Lin.

#3 Working with Relational Data

One of the biggest differences between Data Studio and other business intelligence tools is that it does not have robust features for handling relational data. A few years ago they created the blended data feature, but it is not nearly at the level of what something like Power BI can do using Microsoft Power Query.

That being said, there are a few strengths of Data Studio when it comes to modeling data. The biggest is with Google Analytics data.

With most tools, you have to pull in Google Analytics from multiple API requests and build that into a single relational data set. With Data Studio, that is all done for you. All you have to do is connect to Google Analytics, and your data is modeled. This is really amazing if you are working with a lot of web analytics data.

The second integration that helps us a lot is Google BigQuery. Data Studio has a very simple way to connect to data in BigQuery, and this has been a powerful tool for us to really make the most of the application.

For instance, BigQuery allows you to leverage SQL and to create views, so we have created some complex models in BigQuery and then pulled in a view where the data has already been distilled down to a single table.

This is really useful when we need to build customized attribution models for our clients. We can pull in different resources, like Google Analytics and CRMs like Salesforce, to create linear and even more complex models customized to the client’s business.

Overall, we love working with clients that are using Data Studio, because it means stakeholders are looking at the data. As a data-driven company, that makes us very happy.

If you’re interested in learning more about how to use an attribution model for effective reporting in Google Data Studio, please get in touch!

As we’re kicking off a new year, it’s a good opportunity to review your organization’s marketing goals and optimization strategies. If you’re still struggling with knowing how to prioritize the transition to becoming a data-driven marketer, here are six basic steps you should aim to accomplish this year:

  1. Review your business goals – do you have tracking tools in place to match marketing tactics to goals?
  2. If you’re already tracking all of your marketing tactics, consider how you can take measurement to the next level.
  3. Review how you’re preparing and presenting your marketing reports.
  4. Evaluate which reports you can automate.
  5. Delegate resources/time for Conversion Rate Optimization.
  6. Find time for ongoing training to deepen your analytics confidence. 

Here’s to a productive and measurable 2020!