Digital analytics role defined and why they are in demand

Digital Analytics Role and Responsibilities include turning data into an asset and data into insights

Despite the shortage in digital marketing analytics talent, the demand for digital analytics role is exploding.  Many companies hire that one web analytics analyst, get great value out of them.  However, they need to keep in mind that that digital analytics discipline is getting more deeper and wider in its subject matter, and certainly more complex.

I strongly agree, super agree!,  with Avinash’s 90-10 rule where 90% should be about people/analyst than tools where it should be 10%. This post is not about that, but focusing on that 90% and really understand why we need smart engineers and analysts behind digital data.

Businesses who are new into web analytics or digital marketing analytics need to start thinking about analytics from end to end planning, and NOT just from hiring someone who can look at data coming out of Google Analytics, Webtrends, SiteCatalysts, etc.  Don’t hire people just because they know the tool.

What are the common digital analytics competencies companies should look out for?  Let’s come from an angle where the company is new to digital marketing.

Digital analyst’s disciplines and potential expertises require:

Web Analytics ( experience measuring outcomes rather than traffic and engagement, or the so called the vanity metrics)

  • Knowledge on how data and trackings are enabled
  • Media planning and buys.  Including but not limited to SEM, eMail, Banner Ads.
  • CRM.  Many companies are finding value and investing a lot in areas to onboard web analytics behavior data into marketing automation that ties data to user based data.
  • A/B testing.  Common knowledge on the process and assessing A/B test results.
  • Modeling (marketing mix, forecasting or predictive modeling)
  • VOC (voice of customer) or Consumer Insights.  This is important in marketing, as great marketers are great listeners.  Digital analytics person will need to know how to turn VOC into insights.  It is a gold mine.
  • Market analytics or Competitive insights.  Digital Analytics role will need to have a wide vision to take into account of market dynamics to explain any possible hypothesis based signals coming from the macro environment.

Imagine the engineering side of the digital analytics role. The engineering side needs the following acumen to help turn these data sources into usable data for these analysts.

  • Data integration: engineering skills required to bring various data into company’s environment.
  • Translation of data: Bad data in, Bad data out. You can still have “Good Data In and Bad Data Out” if the folks who are working on the logical data layer messing up the translation after data comes from the database. This is a critical piece to making sure analysts and businesses have good data to analyze.
  • QA and governance: experts who understand the business needs and making sure the implemented solutions are accurate, not breaking things, and checking to make sure business has good data on hand.
  • Expertise in infrastructure: Yes, all these stuff around data needs to be processed, stored, and reported. Where and how? Engineers need to understand the technical environment surrounding the data, and someone needs to own maintaining it.

Even if you’re not thinking about one head count for all of these disciplines, let’s look at where these data and where it comes from and ask you how many levels of expertises or resources are needed to “manage” all of these.

Web Site Analytics // Web Analytics Implementation Engineer:

Data typically comes from analytics platform’s given JavaScripts embedded on the website, and the analytics service provider would process the received data within a day to aggregate necessary data to report on visitors, sessions, page views, and tie all of these to user behaviors or action events.

These could be implemented by web engineers, but in most of the case, pure engineers would not understand what tracker means what to business. Dedicated implementation engineers usually require a strong business acumen so they can connect the dots between javascript to business needs.

Media Planners & Buyers:

Web Analytics data captures great post-click data, but not on the buy side. There are many companies specialize and are dedicated to the planning, buying, and executing the ads. In digital space, these data are planned in Ad Serve tools that aren’t web analytics.

In addition, recently, with YouTube gaining momentum replacing TV in gaining eyeballs at low cost, data around these platforms are becoming important as well. YoutTube impressions are replacing the TV GRP’s.

CRM manager - analysts -  data engineer:

In most cases, CRM data are stored in a form of database. In some cases, those in-house data are accessible by 3rd party depending on the company’s relationship with the agency. In other cases, the database is hosted and managed by third party service providers (sounds like a bad idea.. but you’ll hear it time to time).

Data needs are pushed into the database from somewhere. These managers should be the expert in the data management aspect as well as work with analysts to understand the lead process and operations.  This discipline has two required aspects, both technical side as well as the management side.

That is why it is really hard to find one person with both talents because database engineering and managements are two different skill sets.

Social Media Monitoring - Social Media Analysts - Operations Engineer:

Most of the social media monitoring tools enable the data through paid services (e.g. Radian 6, CrimsonHexagon, etc.) to collect certain phrases people are talking about and less about tagging. From a data standpoint, you’ll need operations engineer to bring the data into the data warehouse. Otherwise, you’ll be sitting on 3rd party tool collecting and hosting the data for you. Good luck to you when that company goes out of business.

Anyways, Social Data has many text inputs from the users, and to mine those data, it will be challenging and hard to bring in all those data into a data warehouse. But not a problem in an era where Big Data is a commodity right? Well, think about it, you still need data in-house if you really want to treat Social Data as your asset.

Conversion Rate Optimization Marketer - Growth Marketer - AB testing analyst:

Any website testing involves planning, and that means you need to have a good planner. Once a great plan is locked in or approved, assuming all creative assets are final, then you’ll need to have a technical person who can enable the test by setting it up the event tracker on site. Then test needs to be set up in the Testing Tool as well.

Any website testing involves planning, and that means you need to have a good planner. Once a great plan is locked in or approved, assuming all creative assets are final, then you’ll need to have a technical person who can enable the test by setting up the event tracker on site. Then test needs to be set up in the Testing Tool as well.

This is a lot of work, again, planning and engineering are two different skill sets. If you really want to test multiple times in a month, then business really needs a strong commitment to resources. Learnings from a test and the culture built will need to be an asset for the company, so make sure to have those knowledge and learnings stay (perhaps in an intranet, or corporate’s wiki site, etc.).

Learnings from a test and the culture built will need to be an asset for the company, so make sure to have those knowledge and learnings stay (perhaps in an intranet, or corporate’s wiki site, etc.).

VOC (or Voice of Customer) - Consumer Insights:

Quantitative data from analytics alone gives you an insight if you synthesize massive amounts of data into something actionable and insightful learning. However, you can not ignore or argue with what your customer directly tells you.

When that VOC data marries with quantitative data, it becomes super valuable. That means the data sources would come from these survey tracker implemented on the website while making sure you have well-designed survey questions to answer important business questions.

Someone needs to be able to plan the end to end aspect of the discipline. One analyst can not do that especially if you’re going to take VOC to the next level to best learn your customer’s pain points.

Market Analytics - Competitive insights:

Typically these data sources come from 3rd party paid services like ComScore, Compete, Builtwith, SimilarWeb, etc. You may think, no heavy requirements needed as it sounds easy.

Yes, if you end there, then web analyst could take on the rest. However, if you’re in a business like buying data from POS (point of sales) or analyzing market share, then it is a whole another level of manpower needed to make sense of it.

Web site analyst who looks at owned media alone may be missing the big picture when the market share of your company is increasing/decreasing. If you ever saw those data directly from NPD or GFK, and not just stuff, then you’re going to say ‘wow’ I need more time to analyze all these data and see how that is impacting consumer behavior online.  Market data is a very powerful data to have.

My intent of this article is to make sure analysts are thinking about the data beyond your one segment of your digital discipline.

Data experts are involved with many experts outside of marketers. Management who gets it and transformed businesses from Web Analytics 1.0 to 2.0, now needs to think about how to turn data into an asset, better govern data practice, privacy, security, the technicality of data warehousing, etc.  Very overwhelming…

Not to mention growing number of data and sources CMO thinks marketers already have, so take action before business demands it. Start by looking at the resource on hand and the reality of the data ecosystem.

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Kris Twitter

As a data journalist, I enjoy curating and analyzing marketing trends, and data. The things that fascinate me the most are the transforming business landscape due to evolving marketing technologies.