Digital Marketing Best Practices, Trends and Innovations

Tuesday, March 24, 2020

Understanding and Making Sense of the Coronavirus Pandemic Data in the US, Italy, and Worldwide.

It's nearly impossible to avoid the many articles, social media posts, graphs and newscasts as of late that portray the United States as being on the same course as Italy regarding the COVID 19 pandemic.  In reviewing these articles, I thought, “Wow, are we really that unprepared?  Did we not buckle down early enough?  After all, aren’t we the most successful and rich country in the world?  Don’t we have the best medical care?  How could this be?”  

Then I decided to take a look at the evidence and the data myself in order to make my own decision.  After all, I am a statistician and experienced data analytic professional. So let's begin.

Did you know that the Corornavirus data is available to anyone?

First of all, in case you did not realize, anyone can download all the Coronavirus data from the European Center for Disease Prevention and Control in an excel spreadsheet.  It is a time series data file beginning with the first occurrence in China in late December.  This data file gives you the daily number of COVID occurrences and the number of deaths by country for every country in the world.   The downloadable data used in this analysis was additionally augmented with data from other sources including each country’s population and their land mass (more to come on this).

Let’s answer some key questions, shall we?

What follows is a discussion of a few key questions that can be answered with the data.  It is important to remember that each country is unique to itself, so things like the availability of tests, regional practices of social distancing, usage of medicines to mitigate symptoms all impact the data, thus complicate making comparisons and drawing definitive conclusions.

Is the United States really on the same path as Italy?

One of the graphs circulating out there that concerned me the most is one that compares the United States to Italy.  This graph gives the impression that citizens in the United States are in for the same fate as the citizens of Italy in terms of the number of positive cases.  See below for the graph that has many worried, especially out on social media. This graph represents a replication of that chart using the same data.

The problem with this bar graph is that it is not scaled appropriately based on the size of each country. To compare Italy cases to US cases without making it proportional to our population differences is very misleading.  In fact, the US population is more than five times the size of Italy as seen in the population chart below.  The US population is over 330 million while Italy is just over 60 million.

Once we adjust this chart for differences in population sizes, the graph paints a totally different picture.

Another chart being disseminated online, including social media, is the one seen below showing our cumulative case rate in comparison to other country’s including Italy as well.  As one looks at this graph it appears that we are on a doomed course compared to all other nations.  Nothing could be further from the truth as you will soon see.

Similar to the bar chart comparing the United States to Italy, this data is not represented on a scale relative to the population of the country. 

The same data is shown below represented on cases per 100,000 population.

When scaled appropriately, the United States compares very favorably with other countries.  Note the data is current as of March 21, 2020.

Both of these charts must be put in perspective.  In general, you would expect countries with larger population to have more cases, all other things being equal.  But to present a narrative that we are on the same path as Italy, is irresponsible.  All that was required was an adjustment of the figures to represent cases on a per 100,000 population basis.  I find it very alarming that some media are presenting the data in such an irresponsible manner.

Data Limitations—number of confirmed COVID 19 cases

Another major concern I have with respect to the data being shown is the issue of accurately trying to show and predict positive COVID 19 cases and make comparisons between countries based on case data.  The key issues in terms of making accurate "case" comparisons across countries are:
  • availability of testing kits for running tests  
  • access by every citizen to get to a testing facility
Because the above two factors can vary across countries, the number of cases could be understated until the testing kits or access to tests “catch up” with unconfirmed cases.  In the United States for example, testing kits have been in short supply at the start and there are many areas (as with any country) where individuals of lesser means may not have easy access to transportation to get to a testing facility or the monetary means to be tested. 

As such, I have shifted to use the metric related to COVID 19 mortalities or deaths and not cases.  The charts below focus on this metric, with the baseline being at the first death for each country. 

So what do the mortality curves look like?

So, what does the incremental and cumulative death figures on a per 100,000 population basis look like 21 days out since the first occurrence for the US?  The mortality charts below show our data.

Incremental US mortality rates:

Cumulative US mortality rates:

On their own, these charts are not overly meaningful.  So, what do the mortality curves look like for the other countries and in comparison to the US?

As the charts below reveal, at this time, we are in a favorable position relative to other countries.  These line charts compare the US with Canada, Netherlands, Japan, France, South Korea, Italy and Iran all relative to each countries population.  But, please keep in mind, anything can change in a moment’s notice.  Nothing is constant here.

Incremental mortality rates:

Cumulative US mortality rates:

What about China's Mortality Curves?

Unlike the US and the other nations, China has run its course, and is much later in the life-cycle of the virus.  The charts below show its peak at about day 34 based on the incremental chart and where the flattening begins on the cumulative chart,

Incremental China mortality rates:

Cumulative China mortality rates:

The life-cycle of the virus

It would take just one super spreader or a major breach in hygiene to totally change our trajectory.  That is why the tight controls are in place at the moment in the US.  And, why the President's team is reluctant to make predictions.  We are still just too early in the cycle.  Anything is possible.

So the question begs, how do we compare to the China virus graphs?  Do we have another two months, two weeks, or two days to go?  Where are we in the life-cycle of this thing? 

To answer this question and assess where the United States and other countries are relative to China’s life-cycle, I have decided to overlay the “China incremental and cumulative mortality curves” on top of the prior two charts showing the same for the US and other countries.

NOTE:  When examining the charts below, the Y axis is not to scale for China but only the X axis to understand the time element of this virus.

Incremental mortality rates:

Cumulative mortality rates:

As these graphs show, China’s incremental deaths per day peaked in deaths at about 34 days following the first reported death.   Following that point the cumulative curve begins to flatten.  If the data maintains it current trends, it appears that Iran and France are also about to peak. As more data is reported we should know if this holds true.

Italy’s virus life-cycle has not matured fully nor has Spain’s.  Which is alarming given the steepness of their curve.

Differences by country—how has public policy impacted the depth and length of virus impact?

How did China get a strong hold on the Virus so quickly?  Why is Italy’s trajectory so steep?  What did Japan and S. Korea do to keep their mortality curve relatively flat? 

Below are just a few of many facts that point to these differences: 

  • First of all, we must remember that China is a totalitarian government.  And, as such, they quickly imposed very strict enforcement on their citizens by tracking their every movement via close monitoring of their every step and purchases.  To fully understand the extent to which the government monitors their citizens now and prior the virus, I advise you read the article by the AmericanAssociation for the Advancement of Science.  Regardless, this tightening of control certainly assisted in quickly getting this virus under control in China.  And, flattening out the mortality curve quickly.
  • S. Korea was quick to move based on their experience with the MERS virus several years back.  This made them ready to scale quickly as also reported by the AmericanAssociation for the Advancement of ScienceThey even send text message reminders to those that are "positive" regarding hygiene. 
  • Italy and some of the other European nations have been criticized as being slow to respond.  For more information on this see one can read the article by CNBC.

Does our mortality rate to date look favorable compared to other countries?
At this point in time the worldwide death rate of confirmed cases is at 4.4%.  This means of all confirmed cases, 4.4% result in death.  However, we know this number is overstating the rate since not all cases are being reported.  Why is that?
  • Many people do not have symptoms severe enough to cause them to go to the doctor to be tested;  
  • Some lack the means to be tested; and,
  • Some just do not like doctors. 
So, what is the real number?  2%?  3%?  We will never truly know. But we do know it is less than 4.4%.

For America, the death rate at day 21 (since our first case) is at 1.27%.  This is about 70% less than the national average and among the lowest of all nations as seen below at the same point in time. 

But unfortunately, we will not end up this low.  We will end up higher than this when all is said and done. 

How do we know this?  

We know this based on data from other countries.  As time progresses, the rate only increases.  China, for example, had a death rate of 2.19% at day 21.  At day 69 (the end of their cycle) their final death rate was 4.00%.  This is an increase of 83% from 21 to 69 days.  So, using this figure to index up our rate we can project our death rate will go from 1.27% at day 21 to 2.32% (1.27% X 1.83) at day 69.  Again, this is assuming it makes sense to use their data to make US projections.  But, what else do we have to use?

And keep in mind, with this number, we could extrapolate the number of beds and respirators we might need going forward.  A figure we definitely need to quickly get a handle on future demands of the health care system.

Are there other factors impacting our ability to make predictions?

As mentioned before, It is important to remember that each country is unique to itself, so things like the availability of tests, regional practices of social distancing, usage of medicines to mitigate symptoms all impact the data, thus complicate making comparisons and drawing definitive conclusions.

Population density matters

Another major variable that affects the spread of the virus within any given country is the population density of that country or city.  The more dense the population, the more rapidly a virus can spread if tight controls are not imposed.   The table below shows the differences in the land mass for various countries relative to their population size.  Given this, one needs to applaud S. Korea and Japan for maintaining such a low occurrence and death rate. 

And, in case you did not realize, the population density in New York City is 67,000 people per square mile.  So now you understand all the concern by NY Governor Andrew Cuomo. 

What about other factors?

The demographics and overall health of a population will also likely play a role in how quickly a virus can and will spread and result in different morality curves.  Below is a table showing the smoker penetration, median age and overall health score for the various countries.  As we can see there are vast differences in these data by country.  How that impacts each countries mortality curve is hard to say at this time.  

How does this virus compare to deaths caused by pneumonia and the flu?

To keep things in perspective it is important to remember that almost 60,000 Americans die every year due to the flu and pneumonia combined. That is an astonishing number. The Coronavirus, worst case, will most likely take the lives of around 6,000 Americans (assuming no changes in trends from what we are observing today). 


In summary, I think we can all agree that America is doing a good job at keeping this pandemic under control.  All the measures put in place appear to be working.  Within another week, as more data becomes available, we should be able to determine our fate.  But so far we are looking good.

So, let's keep doing what we are doing.  We are almost there. We have almost made it.  Let's keep maintaining our social distance, limiting our outside activities, washing our hands,  and stay safe and healthy.

When will the next update be?

We plan to update this report on Monday March 30th.  And, at that point in time, we should have a good sense of where we are headed and what our true needs will be.  And, if any other data has shifted.

To your health,

Perry D. Drake, PhD
     and Rhonda Knehans-Drake



Wednesday, May 1, 2019

Shopping Cart Abandonment Rates Continue to Rise

Wow, I can't believe all the money retailers are leaving on the table. As abandoned shopping cart rates continue to rise, e-commerce sites are not stepping up to the plate as aggressively as they could to recapture these lost sales. 

I realize that in part the reason the rates are rising is that consumers are becoming more sophisticated with respect to shopping and comparing prices online.  But that is no excuse for an e-commerce sites not to reach back.  Just unacceptable.

Lets look at the facts.

First of all according to Optinmonster, abandonment rates have been on an upward trend since 2008, and are expected to continue to rise into the foreseeable future.  See the chart below.

According to ReadyCloud, some of the top reasons consumers abandon their shopping carts an be seen below (multiple answers allowed):
  1. Extra costs = 61%
  2. Forced account creation = 35%
  3. Complex checkout = 27%
  4. Slow website load = 75%
  5. High shipping costs =55%
So given these reasons, what is a retailer to do?  Just sit back, wait, and hope the consumer returns?  Well I would hope not. 

Based on a study by Moosend roughly 10% of those consumers that receive a follow up email regarding their abandon cart will ultimately purchase.  So think of all the money left on the table for a given e-commerce site...even if they just recapture 10% of that lost revenue.

Lets run a few numbers.

Consider a modest retailer with sales of $500,000 annually and a 70% abandonment rate.  What are they leaving on the table?  Using the formula below they are leaving $1,166,666 on the table.

[$500K / (1 - .70) ] - $500K 

Assuming they convert just 10% of those that abandoned with triggered emails (a realistic number), that yields $116,666 in saved revenue.  This would certainly cover the cost of the automation of a trigger based email program.  So, there is no excuse.

And, what is more surprising, for those retailers who are reaching out to customers, they are not doing the best job possible.  Believe it or not, based on that same study by Listrak, only 25% of the trigger based emails linked back to the abandoned shopping carts and only 34% of the emails were personalized.

So what is an e-commerce site to do?  My answer...test, test, test.  The cost here is minimal, yet the rewards could be huge.

  • Test the approach (soft or hard sell)
  • Test the offer (discounts, free shipping)
  • Test the timing (wait one or two or three days)

In fact the optimal timing of a follow up email is within 24 hours according to many experts including SmartrMail.

As Nike says, just do it!

Perry Drake, PhD

Tuesday, April 2, 2019

The Purchase Funnel, Then and Now

The purchase funnel was first developed in 1898 by E. St. Elmo Lewis as a theoretical customer journey from the first point of contact with a brand to the final purchase decision.  As consumers traverse through the funnel the numbers lessen.  This is due to the fact that of all who first become aware of the brand, relatively few actually convert.  Understanding how changes in our marketing strategies at each of these steps impacts the bottom line is key to the success of any business.   Pre web and social media or post, the basics are still the same.

As shown in Figure 1 below, the marketing purchase funnel has been comprised of four main components over the years:  Awareness, Interest, Desire and Action.  This is known as AIDA.  What has mostly influenced the decisions at each stage were brand initiated and included such things as in store demos, TV and print ads, FSI's, coupons and billboards.

 Figure 1:  Purchase Funnel Pre Social Media

Due to the introduction of the web, search engines and social media, the definition of each are changing as is the relationship of each of these to one another.  However, the basic funnel concept still works.  Let’s discuss each of these concepts further in today’s world.

Awareness in today’s world has totally changed due to Social Media.  No longer are we made aware by simple push messages.  Brands are pulling us in and telling us what they have to offer.  And in some cases it is not even the brand that is directly making us aware of a product but rather our friends who are sharing their experiences with us on social media sites.

How a brand keeps our interest is also totally different thanks to retargeting of online ads or tailored web experiences due to cookie drops.

Once we have gained product awareness and shown sustained interest, a brand has many more options today to move us further along that path in order to increase our desire to buy.  Years ago we would have to call to request a sample or go into an automobile showroom to talk pricing.  Today those are no longer the only options available.

And then of course there is the purchase action.  Money is still needed for this to take place, but what has changed is how we can share our purchase experiences (good or bad) with our friends and family.  We can become advocates and make others aware of the product on behalf of the brand.

The new funnel is being depicted in many forms by various companies like Forrester Research as shown below in Figure 3. 

Figure 3:  New Model by Forrester Research

What this figure shows nicely is the “disruption” being caused in the purchase cycle by the abundance of information we can now gather at every step of the purchase process.
But at a high level the “funnel” concept still works.  It shows nicely how as consumers move along that journey their numbers lessen.  

Keep in mind, the funnel never was meant to depict a linear path.  What is vastly different today are the experiences or options we have at each of those steps from a marketers and consumers perspective.   What the funnel looks like today is as shown in Figure 3 below.  As you can see there are now many more things affecting the purchase decision.

Figure 3:  The New Purchase Funnel Post Social Media

The biggest difference in today’s world is advocacy.  Brands need advocates for their products.  They need to create them, find them and foster a good relationship with them.  Why?  Because they who the consumer turns to in order to gain information prior any purchase consideration.  Based on a recent Nielsen report, 92% of people trust brand advocates.  Remember, as said prior, control has shifted to the consumer in so many regards.  This makes brands a bit nervous.  Understanding that shift, as Sephora has done, and capitalizing on it will ensure a strong customer base full of advocates for your brand or offering for years to come.

Here is another thought on the new conversion funnel that I like:  https://curatti.com/a-new-marketing-funnel-is-taking-over/

I would love to hear your comments.

Perry D. Drake
Professor of Social and Digital Media
University of Missouri - St. Louis

Why Don't My Double Click Impressions Match My Google Analytics Numbers?

I get asked this question all the time. Not to worry, there is an easy explanation and a fix.

Here is the main reason.  DoubleClick is reporting impressions served or delivered to ad tags.  Analytics packages like Google Analytics of Adobe SiteCatalyst are counting the execution of page tracking code.

If your Google Analytics tracking code is at the bottom of your web page and placed right above the closing of the body section (see Figure 1 below) then you are definitely at risk for reporting discrepancies.  And, the bigger and heavier the page the more at risk you are. 

Figure 1:  Google Analytics code placed at bottom of web page HTML code.
Why is this an issue?  Because a person who clicks on your DoubleClick ad and bounces quickly will in all likelihood never trigger the Google Analytics or Adobe SiteCatalyst tracking code lying at the bottom of your page code.

And if you think about it, people will bounce more and more quickly on ads versus search results.  Right?

So, what is the solution?

One simple solution is to place your Google Analytics tracking code near the top of the page to minimize the risk.  Simple fix.

And, in fact, when you create a Google Analytics account today, Google tells you to place the code at the top of the page right before closing our the header section.  That is not what they used to tell us.   Hence that is why when viewing the source code for most websites you will see the tracking code at the bottom.

So, if you want to minimize the risk of your ad server impressions not matching your Google Analytics or Adobe SiteCatalyst figures, just move the code to the top of the page.  It will not remove the risk completely but will come close.

Here are two other articles on the same topic that also shed more light on this topic.

Good Luck!

Wednesday, February 20, 2019

Why Did Hashtags Disappear from the 2019 Super Bowl Ads?


Every year for the past 6 years I have had my digital marketing students at the University of Missouri – St. Louis do an assessment of the Super Bowl ads regarding their use of hashtags, social media icons and URL’s to help drive conversation.  This year, my students and I were shocked to see virtually no advertiser using hashtags.

Peak usage of hashtags in Super Bowl ads was 57% in 2014 according to MarketinglandSince that year, it has been in decline every year.  In 2015, 2016, 2017 usage of hashtags in Super Bowl ads were 50%, 45% and 30% respectively based on another report by Marketingland.

So why has hashtag usage in Super Bowl ads slipped to virtually none in 2019?  Are they just not effective any longer?  To prove or disprove this point I decided to examine brand mentions for the top five brands from 2018 and compare that to the top five brands from 2019.

For 2018, we can see in the graphic below, Avocados from Mexico had the most mentions during the superbowl at 137,000, followed by Pepsi at 38,000 according to Salesforce.  And, all five of the top brands used hashtags within their ads.  In addition, we should keep in mind this is not really reflective of the true reach which could easily be in the millions for some brands depending on the influence and reach of those that used the hashtags within their posts.

2018 Social Media Mentions, Top 5 Brands (Salesforce.com)

For 2019, virtually no brands used hashtags within their ads.  They all had campaign hashtags in play, but were only using them in their social media posts.  The top five most mentioned brands on social media during the Super Bowl according to Salesforce are shown below.  None of the top five used hashtags upon my examination of their ads. And, as a result we can definitely see much fewer mentions than the prior year.   

2019 Social Media Mentions, Top 5 Brands (Salesforce.com)

This year the most mentioned brand was Bud Light at only 31,500 in comparison to the top brand in 2018 (Avocados from Mexico) at 137,000 mentions.  A significant difference to say the least.

My students this semester thought that the Pepsi "More than OK" campaign was one of the best executed across the digital channels but felt they missed out on additional reach and exposure by not having the "morethanok" hashtag appear on the TV ad. They also felt that Pepsi missed out by not driving those not familiar with their abundance of fun social media content to their social media channels.

They also felt the Doritos "NowItsHot" campaign was a hit given how they ensured a large audience by mashing up Chance the Rapper with the Backstreet Boys.  This is a great way to grab the attention of the broadest audience possible across generations.  But they thought the hashtag strategy was a bit weak. Engagement could have been centered around how we eat the Flamin' Hot Nacho flavor or asking us if we prefer hot or regular.

So why did almost every advertiser not use a hashtag in 2019?  Why would you not toss your campaign hashtag (or a new one) at the end of your ad?  Why would you not want to drive significant conversation around your brand at a time when it will be seen by 103 millions viewers?   The benefit of a hashtag is to help evoke conversation and extend your voice around an event, cause, emotion and in that moment. Why would you not want to do extend your reach?  It seems crazy to me! 

So what happened?  Given recent marketing missteps by various brands like Dove and H&M and others were advertisers afraid this year of making a misstep themselves in front of such a big audience.  Were they all just playing it safe?  Did they lack the resources to monitor the conversation?   I am anxious to see what 2020 brings us, or should I say doesn't bring us.