Kris

How embedded forms within content increase content reads

By Kris on August 4, 2016

I came across this article and read the research Microsoft did with Contently’s Document Analytics, thought it was insightful findings.

Here is the part that caught my attentions, quoted as:

Microsoft discovered that landing pages requiring email addresses in exchange for downloadable content were 25% more effective at capturing email leads, but that embedded email forms within freely accessible content were more effective at capturing content reads. Subscribers who entered their emails in embedded forms were 51% more likely to read the entire piece of content, according to a Contently case study.

Here are the images of the difference on where and how the email address was asked by the site.

In the first example, it is a standard deployment you usually come across where you land on the page, provide an email address, and then you get the PDF file.

The second example is the delayed gate, where you download the PDF file or the material of interests, then after few pages in, you’re asked to provide your email address in order to access rest of the material.

delayed-gate-082016

As stated in the quote above, it’s fascinating how human psychology plays into different outcome just by asking the email address in different timing.

It might not be surprising to some people, but it is interesting from a standpoint where this may give more ideas to how we A/B test and optimize landing pages to drive results that match certain business outcomes.

It is common to find marketers obsessed with putting out content to capture more traffic and leads, but in many cases, the value of the material is really within the file and what’s written.

A lot of money could have gone into the research, write, and distribute. What good is an email address if people are downloading and not reading it because that’s how end users understand the positioning and value of the companies who provide these materials.

That doesn’t mean every marketing objective is to make people read the entire thing. Capturing user attention and gain volume of quality leads as you get in front of your audience are not a bad marketing objective. So if you can pull it off with the standard landing page and gating it, then that’s fine.

I guess this opens up more ways for us to test ideas beyond CTA, creative, message, but also “timing” of how we capture leads or reach our audience.

I thought I’d share some interesting read that I came across. Enjoy!

Here is the original article, check out.

source: http://www.mediapost.com/publications/article/280860/contently-launches-document-analytics-for-tracking.html

Top 5 Things to Consider When Building Marketing Analytics Stack for Marketing

By Kris on August 2, 2016

How you manage data on the website and its analytics stack is super critical to your marketing success. More data are leveraged in marketing to better improve various digital marketing strategies, including but not limited to the user experience on the site, test user behavior, improve conversion rate, optimize ad targeting to your key audience, etc.

One of the challenges I’m realizing is that data are all over the place. If you have tons of data, then that is a pretty nice problem to have as we live in a world where data is never enough. However, as we track many ads and obtain all the behavioral activities through the tag on your website, unorganized and siloed data will cause more issues for analysts. You may also have web analytics tag independent from the media ad pixels, such as Google Analytics, Mixpanel, KissMetrics, etc. Multiple trackers collecting different data and having it sit on various environments or databases are not going make analyst lives easier.

Marketing automation tools allow further tracking and segmentation on its own platform enables a marketer to be robust on how they reach their users without web analytics tool. That said, it’s important to understand where your marketing data sits and managed, especially when various stakeholders are accessing data and acting on it from siloed sources.

Data could be either centralized or decentralized. Data could be even owned by different departments and even owned by media agencies. So my first top consideration point is:

#1 Know your marketing technology stack end to end.

I really love this mobile analytics stack framework because it shows you different areas of marketing efforts, and how various marketing tactics and analytics stack co-exists in the marketing ecosystem.

#2 Align marketing technology tools to your business priorities

One of the rookie mistakes you can do as analytics expert is to invest in a tool that doesn’t meet business needs. People over rely on tools to solve their problem and what could be worse is you end up buying a solution to a temporary problem marketers have at the time. First thing first, understands your business priorities and plan for the year, and look ahead beyond the first year as well. Some tools require some good amount of time to onboard and calibrate before you start taking advantage of its features.

If you do plan to run A/B testing, and conversion rate optimization is your priority, then you might want to assess what’s needed beyond tools. Keep in mind, tools aren’t the only thing. It’s also people, process, and technology. That said, need to assess if you got the right people and process in place to drive marketing, and not to rely on tools too much.

#3 Plan for near future and help solve problems

A lot of the analytics tools that go on the website require certain amount time for it to collect data and report on. So when you commit on a certain availability of data for analysis and reporting, keep in mind that it will not be another month to start using those new capabilities. That means you have to set the right expectation on the analytics stack you manage.

Many businesses rely on year-over-year analysis to take into consideration of seasonality, or capture growth in general. So the analytics tools and tech stack you chose, make sure you’re planning ahead, so you know exactly what you’ll be looking at on a year-over-year basis.

In my recent experience with the marketing attribution tracking tool that I implemented, marketers were dying to know how digital touchpoints were contributing to lead generation, pipeline, and the deal closed. Immediately the desire to know how it worked month-over-month, quarter-over-quarter emerged, but the data collection was only available from when it was implemented.

Google Analytics is another great example, understand your business needs well and make sure you got great profiles, filters, customer dimensions, and other possible data structures are in place. This is to assure great data quality for reporting and insights.

Another important point would like to make is, turn your challenges into something you want to solve as a project for next year, and the key is to ask for the budget or do plan for the requests. In many cases, it takes some time to build a case, because everything should be based on data right?

#4 Communicate your plan

One of my favorite thing my prior manager told me, “People, Process, and Technology” are key elements in the successful organization. Applying this thought to digital marketing, I think “People” piece really defines how every marketing analytics analysts and managers really need to step up and communicate the marketing stack clearly. It’s background on what, how, why, and who it was designed to solve the problem for can build a sense of trust in between analytics and marketing folks.

I never like tools to dictate the conversation, but it never hurts for people know context around the data collection and reporting sources.

Also if marketing has a roadmap, then analytics should have a plan as well. Example, mobile app marketing is going to be key in upcoming quarters, then analytics needs to be ready to track and report on it. Same goes for any other marketing strategy and tactics. Get you plan out and communicate your plan.

#5 Use it or lose it

Marketing analytics tools usually don’t come by cheap. Enterprise-grade tools could cost you a great amount of money and time starting from evaluation all the way through to completing the contract. It involves a lot of people and their time. We should respect everyone’s time and make sure these tools are leveraged and answering important business questions.

A lot of the major software vendors who are doing well in their space has great community and training programs. Also, it’s important to leverage their documentations and really read through to learn it. Sooner or later those knowledge gained will become part of your expertise. As an analytics person, you should take every opportunity to learn the tool you’re exposed to.

Multi-device attribution analysis and how it works

By Kris on December 20, 2015

Several years ago, the topic of mobile was huge. If you look at this data, it may indicate that marketers are not excited about mobile as an opportunity area, when compared to last year. I wonder why. Is it because the data is so bad, marketers and analytics folks couldn’t accomplish getting the mobile marketing right?

eMarketer Exciting Opportunity 2014

This research by Google (a while back in 2012) shows that in eCommerce purchase journey, multi-device touch points play a key role in how consumers navigate digital content to get to that final decision point to buy. “90% of customers use three different devices to complete a single task”.

Sequential Screening Between Devices

What does your analytics say about your users? It is very likely that your mobile traffic has grown from prior years, but how significant is that traffic volume?

I also find it interesting that if you look at different acquisition channels, you might see a different mobile traffic distribution. This particular image shows, overall site traffic from mobile and tablet is X%, but when you look it by Google CPC (paid search ads), mobile and tablet visitors accounted for X% of its traffic.

20151220-mobile-traffic-cpc

Some of the key questions we need to be asking from this data are:

Is your landing page optimized for mobile visitors or desktop visitors
What does it mean to see different traffic volume in desktop Vs? mobile. Are mobile visitors exploring the product and desktop visitors are existing customers? Customers are in different part of their moments/journey so content should be optimized for that different moments.
What kind of mobile ads is resonating with your users? Is it any different from the desktop ads? Mobile has a very small screen for users to view and recall the content within the banners. Are your users responding to the text or actual creative, are few key things to check if you want to optimize for the mobile visitors.

In order to attribute conversion of a user to its original touch point, you’re going to need to plan it well to capture the right data. A common tactic to do this is to make sure you’re able to stitch back your converted customer ID back to its original source or touch points, which could be either a campaign id, content viewed, etc. This visitor stitching technology is probably unique to various analytics vendors you work with, but you would want to make sure you have a strategy to do this right.

Tealium said this right in one of their product description:

“Typical analytics data often shows multidevice visitor interaction as coming from three visits and three different people, but, in reality, it is likely that those visits are from just one visitor using different devices.”

Once you’re able to normalize your data to be able to track your customer level data and stitch to user’s historical touch point data, then you apply whatever model you please to allocate conversion credits. First click, last click, linear, U shape, W shape, etc.

Would like to hear what you guys are doing to make multi-device attribution analysis better.

Measure Engagement, Gain Insights, and Optimize

By Kris on September 8, 2015

We always hear about marketers stressing to drive better user experience, and measure engagement on the website.

Have you ever wondered what that means?

I think in digital marketing it means several things. Note that, ultimately, you and your team will need to decide what engagement really means for your business.

Following are a list of basic measures that could classify as ‘engagement’ metrics. Instead of just listing it out, I thought it’d be interesting to ask possible questions where these measures could fall under.

Are people staying on the site or with your app, Yes or No?

Bounce Rate

How long are people staying on your site or app?

Time spent on site

By how much do people love your site?

Net Promoter Score (NPS)
Customer Satisfaction Index (C-Sat)

Are your users going to come back, and how many people are coming back?

Visits per Unique Visiters
Returning Visitors

How soon or frequently users are coming back to your site?

Days since the last visit
Count of sessions within a given reporting period

By how much content are being consumed by your users?

Pageviews / Visit
Page depth
Where are users dropping off in the marketing funnel?
Funnel measures

These metrics that could describe ‘engagements’ are pretty basic stuff, a lot of them are standard measures straight out of Google Analytics.

These metrics alone probably doesn’t mean much without additional context. What do I mean? Let’s take one of the questions as an example by adding additional questions to “By how much content are being consumed by your users?”.

Let’s add these two additional considerations to this question: “for those who converted on your website”, and “for those who don’t convert on your website”.

Engagement Segmentation in Google Analytics

As you can see from this basic measure Pageviews per Visit, and the segmented views comparing people who converted Vs. people who have not converted. This immediately tells you the amount of content or pages accessed consumed by the users are very different. Basically, the engagement level is different from these two different segments.

Now you can do further analysis to determine the actual differences and try to understand what that means.

What’s next? You have to know what is good or bad, by setting up a target or goal. By setting a target, you’ll know if your marketing or optimization efforts are moving in the right direction or not.

To set a goal is no easy task as you have to gain alignment from the team, business partners, and managers. Even if you and your team can’t commit to a target you want to hit, at least you can find a line to aim for as something to improve too. The assumption here is that you’d like to improve marketing performance. Example, improve conversion rate from last year, or 3-month average, etc.

So what are the good segmentation points to track that ties well with engagement measurement? [Example only]

by Page accessed
by certain outcome events like form submits, shared on social networks, sign ups, purchased, not purchased, etc.
by Geo locations, like your region Vs. other regions
by traffic sources: Organic Vs. Paid
campaign programs (acquisition, loyalty, referral program)

In the marketing funnel it is common to view in three steps: acquire, engage, and convert.

So from that perspective engagement metrics are key to understand what’s working or not working in the middle. Very common for marketers to report traffic and conversions figure, and engagement metrics tends to be the fluffy one. It has to be the measures that tell you where are the leaks are happening and understand the things that are driving the experience leading to a conversion.

That said, when you couple the engagement segments and tie it to people who converted and didn’t convert, then you’ll likely going to get some pretty good insights into the differences. Differences between what people engage, in that, leads to conversions Vs. that don’t.

2015 09 engage segment landing page google analytics

This image is a cut out of landing page segmented by people who spent over 60 sec and viewed pricing page Vs. didn’t view pricing page. You can see that the difference in new users count and % of traffic hitting the key page is quite different on certain pages. What does this difference mean? And what does this user behavior indicate? What would you do more to gain better insights and dig deeper?

Hopefully, you’re getting some ideas around how to look at engagement measures and see how you can use that to gain insights on user behaviors the allows you to generate better hypothesis against the problem you’re trying to solve for business. Engagement measures could be very powerful if you combine it and use it right.

The difference in the engagement and behavior outcomes will be a great start to help you generate more thoughts and ideas for your digital analytics analysis exercise.

By getting the data and insights, you just have to analyze your way so you’re tackling the problems that allow you to hit your business goals. Remember to set that goal!

Great analysis goes further to explain WHY

By Kris on April 11, 2015

A lot of the data analysis revolves around the business questions that people bring to you. Horrible questions are like when analytics people gets a simple data pull type of requests, but no background information or explanation of why they would be needing a data. Hopefully, that is the not the case for you, and we hope to believe in a perfect world where all marketers and business folks are asking great business questions.

Typically, marketers are trying to achieve something out of their marketing efforts, and we (analysts) are trying to meet their needs by providing data and insights back. A lot of times what’s lacking in this analysis or the challenges from the marketers lack the awareness of probing into the ‘why’ factor in the change in the data trend.

What does this mean?

For example, when paid search traffic goes down, a typical analysis would look at the traffic, ad spends, it’s associating pages, the list of keywords, conversion rate, etc. Usually, great analysts go far more because awesome managers, executives, and business people ask challenging questions. That means, showing ad spends going down or conversions going down is not just enough, they’ll ask “why” several times.

Heavey web analytics users will find over time that just using Google Analytics alone will not give you the answers you’re looking for. Here are few ideas to use help you get better underlining reasons to why things go up or down in traffic.

Segmentations, filters, drill down and add columns

Use macro data like Google Trends, Webmaster Tools, etc.

Look at competitor’s data

Use surveys

Perform A/B testing

Segmentations, filters, drill down, and add columns

As an exampleHere is a sample view of the detail filters and segmentations you can build our of google analytics. Segment generation is a pretty powerful feature as you can create a rule that applies to your entire reports and compare. The segment applied is sticky so you don’t have to always have to think about adding when you switch between reports. Much other analytics tools has a similar feature, but it is something you have to take advantage of.

ga-traffic-segment-042015

The segment could be a cumbersome feature especially if you want to play around to quickly find something that sticks out. The secondary dimension helps you quickly add a column, so you can sort and compare by different date range. Typically that could give you something interesting that explains more details in your data trend.

ga-traffic-2nd-dimension-042015

Here is a basic filter feature within google analytics, but it is pretty helpful when you want to exclude or include certain data sets so that you can narrow down to particular data that may explain the cause of the traffic changes

ga-traffic-filter-042015

Use macro data like Google Trends, Webmaster Tools, etc.

Checking out data on Google Trends and many other market data could give you a broader sense of what could be happening.

A hypothetical example here: Despite allergies, queries are going up peaking at April/May, yet the search on major allergy relief pills brands are flat? What’s happening here? Is something taking away your search/interests share away? Are natural remedies growing? Definitely a good context of data if you want to look at a more higher level explaining traffic trends.

google-trends-allergies-042015

Look at competitor’s data

Site’s like SpyFu (note: there are many other similar tools out there), allows you to see what’s happening on site’s that you don’t control. Let’s take a peek at Nike golf site. They’re kicking ass in branded terms in Organic Keywords, no surprises here. But it looks like in Paid Keywords, you’ll find ‘Callaway gold drivers’ as one of term Nike is bidding on.

It is pretty common for brands to buy competitor’s terms to steal traffic or interests. Idea is to watch out of potential changes in competitor’s marketing strategies because that could explain changes in your traffic or business performance.

Use surveys

I’m a big fan of Qualaroo because it gives me that flexibility to whip out a quick survey to place on a page and control the survey introduction timing. It helps us ask site visitors directly and answer potential questions that quantitative data that Google Analytics couldn’t answer.

I won’t write much about this because it is pretty no-brainer, but this is some powerful stuff if you ask the right questions. I like using the open text questions and take advantage of that initial insights to help me structure better questions next time.

voc-qualaroo-042015

Perform A/B testing

The reason why we test is because “We don’t know what the outcome is going to be”. You can spend in a meeting room all day, but at the end of the day, you are not going to know if it is going to work. Go test it out! Tools like Optimizely will allow you to whip out some basic A/B testing on the site.

If setting up A/B testing and putting that JS code is too much for you, then try tools like UsabilityHub.com. You can basically test your idea during your conception phase by asking users to perform some action to get data. You can link your existing page and ask users to perform certain tasks. See if your site sucks or does its job.

userbilityhub-jira-example-042015

How to Select the Right Digital Marketing Analytics Tools

By Kris on March 27, 2015

While a lot of us are working hard with digital marketing data to find that actionable insight, let’s not forget the importance of selecting the right digital marketing analytics tools.

I’ve talked to many people, including marketers, marketing managers, CXO, etc. Many times, I come across about the discussions around tools.

Even cases where people talk data before it is even collected. This situation is what I refer to as:

Marketers firing before they aim their strategies to the target.

I come across this situation a lot from many marketers. People talk about collecting data, or even tools or data vendors to purchase too many times. Even blaming the tools for lack of data discipline.

It is very important to really start the planning, and define your business’s objectives and goals. So that you have a clear guidance on what tools you need to solve your digital marketing problem.s

Maybe even before that, you have company’s vision and mission, that many employees are trying to contribute towards. Let’s make sure to recognize all of that.

In marketing, you have to have a plan and a goal. As you may know, Google Analytics and many other tools do well in providing click, event, traffic data on digital properties, but it is not until someone makes sense of it to bother digging deeper into it to find those “insights”.

This is why I like to refer to this process that I use to frequently approach optimizing the digital experience and run much more a/b tests while transforming the team into a data driven organization.

Just as if you’d ask a professional photographer, “what camera are you using to take that nice photo?” What about his/her skills?!.

In a digital data world, I hear marketers talk about tools and data collection, but not enough to the action or the strategies built around the hypothesis generated from the analytics.

Something is really missing here. Sorry, data is not going to solve problems, it is you or the people who need to solve the problem will. With a massive amount of marketing technologies out there, marketers are saying that they’re not getting the full benefits of the data.

By the way, I’m not making this up. According to Econsultancy’s survey on marketer’s top data challenge shows, the key theme is turning data into actionable insights.

I’m glad, happy, and proud to say that I have had excellent leaders who managed me, and it is such a blessing to have their guidance.

When I moved from Japan to California in 2006, I knew data landscape was changing and disruption was happening in the marketing space with the internet.

It was going to change how marketing and eCommerce adjust the course of the business, just like how traditional business analytics have done for businesses.

While data have become widely available and accessible, it has given a more fuzzy feel for marketers that they can wear multiple hats to do everything including (not limited to) sales, A/B testing, analytics, data management, media buying, etc. This is dangerous. When resources and expertises spread thin, especially while the direction is not clear, data is pretty meaningless.

Brainstorming and data discoveries are fun exercises. Yes, it is fun, but at the end of the day, we’ve all got jobs to help business perform. So at some point you really have to select the critical few must have data points that differentiate ‘great’ from ‘good’ to know data.

So, the tools and data, all of that good stuff should come from good planning and requirements,

I wrote this in my previous blog post “Converting Customer Behavior to Business”, but a lot of people follow the process of “Fire -> Aim”.

Instead of “Ready -> Aim -> Fire -> Debrief”. So if you really want to focus on the data, tools, that will bring insights to help your business perform, you have to know what you’re measuring for.

People need to understand what is the problem we’re trying to solve for the business.

One manager has mentioned to me (not in exact words..) “People working within constraints, even that means working very few resources, budget, or tools, people actually can learn quickly about what is missing and required to drive performance”.

That meant to me it is, there are very important critical few that you should be focused on and solve that problem. Same goes with digital marketing analytics tools selection.

My basic suggestion that I recommend approaching selecting tool is following these steps:

Map and understand your business model. How is your customer is going to engage with your business?
Design your marketing funnel
Select your marketing technology tools

For #3, I would look into the solutions around:

Quantitative data
Qualitative data
A/B testing
Capture, manage, known user information (CRM or Email Service Provider)
Data Manager (e.g. Tag Manager, automation tools, productivity tools)

These are super key to start with.

That is because when you have constraints you have to focus on the critical few to act quick and deliver results while really feeling the exposed pain points. No fancy big data stuff here.

Quantitative Data

You want basic analytics around measuring your funnel. Conversion rate, revenue, traffic, AOV, engagements, etc.

Qualitative Data

Quantitative by itself does not give you all the insights, you have to listen to your customers and have the capabilities to track and gain feedback from your customers.

A/B testing

Doesn’t have to be a tool, but idea is to track and use your analytics tools to measure your tests so that you can iterate on changes to improve your business performance.

User Information (CRM)

You need to be able to understand your customer by their name, email, address, profile, etc. Typical web analytics tools aren’t designed to help you manage your customer data. So you’ll need a tool to help you manage that.

Data Manager // Productivity Tools

Tools acting in silos aren’t very helpful. There are tools out there that will help you track, scale your resource by automating many tasks you could be avoiding. Like tag manager, automation tools like IFTTT or Zapier.

Only with many options, time, budget, and all that happy stuff, people will tend to lose sight, explore, and wonder off from the core problems.

To me, that made a lot of sense. In fact, I had to go through painful business transitions during the bad market conditions. Learned that focusing on the critical few helps you find the important things to work on and fix fast.

And when you have few goals with a very high bar to hit, then it creates a sense of urgency. Stressful, but a good one. And it helps you prioritize and be selective about the tools you’ll need to solve the problem.

I think this is why Growth Hacking mindset is really interesting as fundamentally you’re collaborating with peers under the constraints of resources or budget. Then you really have to grow and perform, otherwise, startup’s fund goes dry.

So you end up picking that one or two KPI, putting heads down and optimize the crap out of it by looking at the important things that matter to gain insights, to then act on it.

Here is a great article about consumer insights on Huffington post “What Are Consumer Insights and How Do They Impact Marketing Effectiveness”. Article’s concept shows that it’s key to getting insights out of data, because a lot of time when analyzing data in web analytics tools, performing A/B testing reading the results, we as analysts are trying to find that story, and the “why” factors on why things have turned out a certain way.

Point is, consumer insights, having that mindset to think like a customer is important, so you’re not just saying things like “traffic is up because we spend more money on Google’ Paid Search Ads”. So go beyond measuring traffic and conversion rate.

My favorite line of text from that article.

“Consumer insights provide understanding that leads to marketing on a more direct and personal level.”

We’re all obsessed with data and tools, but let’s really try to focus on the “why” factor and follow a process that makes sense.

See if that helps you set the right expectations and be part of the fun journey in finding that “insights”, and add awesome tools to your portfolio of capabilities after understanding what it takes to solve your business problems.

Kris

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