After a delay due to server hacks at Rutgers University, I finally got my grades while I was vacationing in Ireland. My final grade was a B+ for my Digital Marketing class! While in recent years, I have had a reputation of having a straight A average with my grad school level classes, I was not disappointed in this grade. As I may have mentioned in a previous post, I got an 82% on my final exam. The test was one where it was one shot at 50 multiple choice questions. If I hadn’t studied the quizzes and taken the quizzes multiple times to practice (they weren’t graded), I wouldn’t have passed. Most of the questions on the test were the same as the quizzes! So there’s that. Some of the questions, as they were worded, were NOT easy. Even so, with the fact that I got an 82/100, I was greatly relieved.
As for my Capstone project which involved more work and thought towards the practical application of the information we learned, I got a 95/100, or an A. I was happy about this, as this is the part of the grade I actually fretted over more. I knew it would be difficult, because I didn’t have any clear cut projects from work or situations to base my digital marketing strategy on. So, in my mind, this was an educated shot in the dark. I decided that I would base my project on something that was real for me. I’ve mentioned that I had been thinking of starting my own consulting business, and so I based my project on the idea of my proposed reality–I needed to come up with a plan to promote my fledgling company to gain brand recognition and acquire customers. That’s fairly straightforward. As I’ve mentioned many times before, I understood how to approach the digital part of the strategy, but not as clear with the marketing. So, I did the best I could, and labored over this project. It paid off. The commentary of what was missing was minimal, mostly about re-evaluating after gaining clients and reassessing the stats taken based on that. That makes sense, but let me get some clients first!
So, once the exam was averaged with the Capstone, I got an 88.5% for the class, also known as a B+. Considering that this was not an easy subject for me to study, I still think I did well. I did not think much of giving equal weight to the test and Capstone then averaging the grades. The test, while it tested students on concepts, wasn’t well written and it was not really practical. Ultimately, the Capstone project was a practical use of the information and more of a projection of what I’d really have to do in “real life”, thus it should have been worth more, because these kinds of strategies are what need to be brought into the real world. So in my mind, while it’s not official, I still got an A for the class because that was what I got for the Capstone.
So there you have it. I got a B+.
Would I take this course again? Probably. The experience was very different from doing my online Masters at NJIT. My studies at NJIT were much more structured and directed than this course at Rutgers. This online digital marketing course was 10 modules of about 10 videos per module. The information in the modules was excellent, and the instructors were top notch. I wouldn’t trade that. When I was able to go to the “virtual office hours”, the instructors were approachable. However, I had to stay super-disciplined in watching all the videos (3-4 hours’ worth of information that could be dry content at times) every week. I didn’t have the chance to interact with fellow students almost at all to exchange ideas. It wasn’t as rich of an experience as I had enjoyed with NJIT. Despite the lesser things about this course’s delivery, I know that I will definitely use this information going forward.
So, I will shortly receive my mini-MBA in Digital Marketing from Rutgers soon in the mail. I suppose the question will be–what will the next course I take be, and when? I don’t know yet. I’m the eternal learner, so I look forward to that answer, too.
Anytime I think of any kind of tech comm analytics, I don’t think of Google Analytics or Web Trends, but my mind races back to the first time I heard Mark Lewis speak and how my mind was blown at the idea that tech writing was measurable in any form. Now, a few years later, I’m looking at this latest module in my online Digital Marketing course at Rutgers about Web Analytics and ROI, as taught by Rob Peterson of the marketing firm, BarnRaisersLLC.
The idea of analytics and ROI (return on investment) sends a shiver down my spine. While I understand the function of analytics and some basics, it makes me think of complicated mathematical formulas, and that in itself makes me anxious. (I was a decent math student in school, but it was not my forté.)
Peterson started his course with a quote that I could swear I’ve heard either Mark Lewis or Joe Gollner repeat (I think it was Joe) by Peter Drucker to frame the objective, in which Drucker said, “If you can’t measure it, you can’t manage it.” So, the first question was, what is “it”? “It” could be almost anything. But Peterson feels that “it” is success–that your success (or lack thereof) is what needs to be measured. He also felt that the verbs “measure” and “manage” were the keys to understanding the material for this module.
Peterson broke down these by 6 steps to demystify web analytics:
Know why your site exists
Identify who you want to attract
Find out how they find your site
Know the action(s) you want them to take
Create an actionable scorecard aka figuring out your KPIs (Key Performance Indicators)
Listen to your digital ecosystem
You want to do these steps because the buying cycle has changed due to the internet. The buying “funnel” has been replaced by a flatter, more circular course of evaluation and re-evaluation before buying, but there is a subsequent loyalty to a brand after the initial buy that shortens the cycle the second time around.
Petersen then talked about how to make your digital ecosystem thrive, describing it as the intersection of earned (sharing), owned (web properties), and paid (advertising) media. People come before software in analytics, he insisted, stating that there’s a 10/90 rule for analytics, namely 10% of the marketing budget should go towards the analytics software, and 90% towards getting good people to analyze the results. We use measurement to understand our role, which is understanding the customer journey with the goal of optimizing the customer experience and find more customers.
To do this, there are several (he said 12, but I could figure out which were the specific 12) measurements to know.
First, you have to understand how consumers find you. This is primarily done through keywords and links. It was emphasized that page rank (aka “SERP”- Search Engine Rank Page) mattered because the first listed item in the ranking outweighs subsequent 5 ranks combined, usually. The metric that mattered most with paid media? He gave these two equations to show how this worked:
CPC (cost per click) = CTR (Click thru rate–this makes the click relevant)
He noted that a good conversion rate is actually low–2% is considered good!
So, once you’re at the website–now what? To analyze this, you need to look at sessions and users (which were recently renamed by Google, and formerly known as visitors and unique visits, which I understand better). Usually the period of time usually measured is looking at the last 30 days. An important metric in this is looking at the bounce rate, which is a percentage that means the number of people who only viewed one page then left. It’s important because it shows if the site is relevant or not. A good bounce rate depends on your goal or objective. If you wanted people to come to a specific page to sign up for something only on that page, then you achieved your goal, but if not, then you have to figure out why they didn’t stay. Petersen noticed that if you notice that your bounce rate is high for the wrong reasons, it’s not easy to change a bounce rate overnight.
One also has to understand where users people come from and what they do. Traffic resources are organic, direct, or paid searches, but can also be referral and social media sources.
The focus then turns on the key content (aka the webpages) by determining how many take the actions that you want. Conversion, here, is an important metric. There is the macro conversion, which is revenue generating, such as person to person, B2B, B2C, WebEx to WebEx, and the like, versus micro conversion, in which users would subscribe to the blog or a newsletter or participate by making a comment on a blog, and so on. This can also be done through word of mouth, more specifically “likes”, comments, shares, people talking about the site, followers, retweets, reviews and rating, sentiment, text analytics, and email open rate. The conversion rate is determine with this equation:
Conversion rate=(Desired outcomes/total visits) X 100
There are several online tools to help you listen that are generally free tools and work better on bigger sites, but easily available to use, according to Petersen:
Google Trends – This tool uses keywords. It can compare two different topics to see where they’ve been and where they are predicted to go. The example given was the buzz between Justin Bieber and the anticipated Samsung Galaxy 4 among teenagers as potential buyers. Fortunately for Samsung, the Galaxy 4 was trending more than Bieber!
Compete.com – This is a paid tool focused on doing competitive intelligence. It lets you see how you compare to your competitors so you can figure out your strategy.
Alexa.com – This is another tool that looks at the competition, powered by Amazon. It can use to compare your competition by providing ranking and metric information.
Marketing.Grader.com – This is a HubSpot tool that grades your website on several levels from social media marketing, blog posts, SEO, lead generation and mobile. I tried this tool and this blog got an 82/100, mostly because I’m not really trying to generate leads, and the mobile aspect of using WP needs help, so I considered that pretty good. I like this tool because it was really easy to use and understand. At the time of the recording of the lesson, Petersen’s business website had an 81! And I had an 82? Hah! I must be doing something right!
The course continued by using a case study using Google Analytics. The objective of this part of the lesson was to learn what to look for and how to use it. It was pointed out that it only will look up your own company due to admin rights, and to make it work optimally, you need to get specific code and embed it in all of your page (perhaps in the header, for example) so that Google Analytics can track it correctly by the correct administrators.
The main focus in using Google Analytics is looking at the audience figures. Look at the Engagement section to see who is really spending time on your pages. It helps you to understand the bounce rate. Petersen pointed out that on average, 95% of the audience never views more than 5 pages, and 95% don’t spend anymore than 5 minutes on a website. You can also look at location for geographic data, drilling down from national to town level. The section labeled “Mobile” can let you see how the site is being accessed.
This information helps to frame the marketing “funnel” that is often talked about, which is where marketers start with the action of acquisition, narrowing the focus to engagement, which further narrows to conversion. If it circles back to the engagement, this signals that there is loyalty to the brand, and this cycle begins again.
Google Analytics can also identify how your audience finds you, which is mainly through acquisition, behavior, and e-commerce. Behavior metrics can show what pages they are going to. Channels section knows keywords even if analytics don’t tell, as it shows keywords that people are using to access the site. You can find out about keywords from the Site Search section. All this information helps us understand the conversion rate by allowing us to see what’s been bought and look at average order value if you offer goods on your site.
For better information on keywords, Google Webmaster Tools is a better choice. It can tell you if your website is set up correctly so that the webcrawlers can find you, and helps correct errors on your site, providing rich depth of information on keywords.
So, you have all this information–what do you do with it? You do a lot of testing, because it’s an activity and a philosophy in which you build and test and repeat the cycle, using lots of small steps continually. Surveys are one way to do this, as they are essentially a tool that acts as the “voice of the customer”. Surveys use simple questions regularly executed such as, “Why did you come to this website?”, “Did you find what you were looking for?”, “Would you come back?”, and “What would make your next visit better?” There is also what is known as A/B Testing, in which you show two different versions of an ad or webpage to customer groups, and then seeing which people went to the goal page based on the two different models. A third way to find out some of this data directly from customers is looking at reviews, as they help searches and sales for other customers.
This is when the talk steered towards the ROI part of the discussion. Petersen started by letting us know how much a “like” on a site was worth. Research showed that among 150 brands researched, it was worth $71.84. Fans of a brand are 28% more likely than non-fans to continue using the brand, while fans are 41% more likely than non-fans to recommend a fanned product to their friends.
What does it tell us about “Like”-ability? It tells us how we can learn from social media audiences, which can be achieved through Facebook surveys and provides sentiment analysis.
KPIs (Key Performance Indicators)are crucially important as they are the “scorecard” needed to keep a strategy on track. Petersen defined KPIs using a quote by Avinash Khaushik of Google, saying that KPIs are “Measurements that help you understand how you are doing against your objectives.” Petersen also used the quote by Laurence Peter, saying, “If you don’t know where you’re going, you’ll probably end up somewhere else.” This, Petersen decreed, is where you define the “success” using metrics to measure.
There is a difference between KPIs and metrics, namely that a KPI is a metric, but a metric is not a KPI. More specifically, KPIs:
Relate to a business objective
Are chosen by the people accountable
Provide context by being tracked over time
Are based on legitimate data
Are easy to understand
Create meaning that gives control
The role of KPIs, per Petersen, is that “KPIs are an actionable scorecard that keeps your strategy on track. They enable you to manage, control, and achieve desired business results.”
How do you choose the best digital marketing measurements? Start with a KPI scorecard that compares raw numbers against progress against the percentage of change.
# of new customers
22% increase in sales
From there, you create a dashboard for the scorecard that should include both web and offline metrics that looks something like this:
Sales Metric #1
Sales Metric #2
Website Metric #1
Website Metric #2
Social Media Metric #1
Social Media Metric #1
The KPI dashboard shows key areas and results from metrics, and can help you to figure out what the key points are to create a KPI report for management.
During: visitors, segmentation, bounce rate, traffic sources, key pages, conversion rate, average value
After: reviews, surveys, A/B tests, social promotions
Starting from KPIs to deriving ROI is about the “Show me the money!” You need to look at the results from latent effects to direct effects. Direct online effects usually make up 16%, latent online effects makes up 21%, while latent offline effects makes up 63% of the results.
What is ROI (Return on Investment)? The equation given for this was:
(gain from investment-cost of investment)/cost of investment ($)=ROI
ex. ($500,000-$100,000)/$100,000=400% or 4-to-1 ROI
ROI is important because it reflects the idea of good management of money. Examples of gains and investments include:
Gains: sales increase, shorter purchase cycle, more leads, higher close rate, lower internal operating costs
Investments: marketing, advertising, promotion, PR, customer service, staff, overhead, time and energy
Metrics we use to create both annual and lifetime customer value and help us be better marketers include:
Mass Marketing (Mass media, like TV, radio, magazines, newspapers, billboards — create awareness, interest, trial, sales)
Direct marketing (leads, conversions, retention, sales)
Digital marketing (unique visitors, downloads, register, redeem, convert, buy)
What ROI calculation can and can’t do:
Can: identify direct effect, provide relationships between direct and latent effects, give insights how to drive ROI higher, define consumer value
Can’t: define ROI goals and expectations, establish a baseline, identify a timeframe
What’s in store for the future? More data (aka BIG data) is growing exponentially coming in. “Big Data” is large amounts of data from web-browser trails, social network communications, sensor and surveillance data that form unstructured data stored in computer clouds, not servers.
The course was concluded with the statement, “It’s not the data, it’s what you do with it.”
Overall, this module was pretty good. I feel less anxious about web analytics and how to analyze the information provided, and I now have some more robust tools to use as well. The only thing I didn’t like about this module was that while Mr. Petersen was obviously knowledgeable about the topic, the structure of the module wasn’t completely clear. At the top of the course, he said from the beginning that there would be a top 12 things, but they really weren’t defined as “this is #1, this is #2, this is #3,” and so on. While there was a good progression, part of this came off as scattered because I felt like I didn’t understand how he was going from Point A to Point B and why, and no clear outline on how he planned to cover the lesson. Call it the content strategist in me, but that structure was something I just needed. Other than that, it was a module that I definitely needed for a better understanding of the topic, and the information was sound.
The last module is coming up, which looks like it will tie all the previous modules together! Until then…
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