(Last Updated On: September 22, 2021)

Hey. Welcome to the first part of this brand new two-part series on the indicators of digital analytics transformation.

If you are looking forward to know all about the basics of what is digital analytics terrain, take stock of your current maturity in the digital analytics scheme of things and understand how best you can improve, you would love this article.

If you are looking to find more on data / predictive analytics, we have another series lined up for indicators of digital transformation data analytics journey.

Meanwhile, continue reading this article to improve your digital analytics efforts.

In this article, we cover four reasons why your digital analytics needs transformation.

Let’s get started.

Digital Analytics Terrain

Web analytics has been around for over two decades.

It all started with Webtrends in 1993, followed by SuperStats in 1996 that was rebranded as Omniture in 2002.

However, only after Google bought Urchin in 2005 i.e. 12 years after the release of the first web analytics platform, web analytics started reaching the masses.

Over the years, Webtrends has lost its market share significantly and Omniture was acquired by Adobe, a decade ago.

Whether it is a coincidence or not, ever since Adobe’s acquisition of Omniture, the web analytics domain started to spread its wings and tools had capabilities that went beyond web analytics.

Today, we have analytical tools that not just report your web traffic, but have the ability to track conversion, help you analyze your audience engagement with mobile apps, your campaigns, etc.

By integrating themselves with advertising platforms, identity management platforms and targeting platforms, digital analytics tools help break channel siloes, create a single view of your audience and deliver personalized content at scale.

There are other digital analytics trends and niche platforms like social media analytics, behavioral analytics, testing, survey platforms etc. that have made the digital analytics domain wider.

And that’s how web analytics slowly transformed itself into digital analytics. The digital analytics definition states that the process of aggregating and analyzing digital data should include various sources including websites, mobile apps, etc. and provide a comprehensive view for improvement.

There are some big brands that have embraced all of these in an integrated manner and are reaping rewards. But, what about other brands? At what level of maturity are they?

Well! Hotjar released the State of Web Analytics report a few months ago and the results are quite shocking.

Here’s how Hotjar defines the stages of maturity -

Ignore: don’t collect or report on analytics data

Basic: use data to measure WHAT is happening

Intermediate: use data to measure what is happening + determine WHY

Advanced: use data to measure what is happening + determine why + make ONE-OFF data-informed changes

Elite: use data to measure what is happening + determine why + make ONGOING data-informed changes

Source: Hotjar State of Web Analytics 2020

The results are shocking as only less than half the brands surveyed leverage digital analytics process at the advanced level.

Astonishingly, more than 40% of brands have not even attained the intermediary stage as per Hotjar.

Do you think your brand will also fit in any of the first three levels?

If so, why the lag? What do you need to do now? Where should you start?

You should start by validating whether your digital analytics strategy indeed needs transformation.

Let’s jump right into the factors that indicate the need for digital analytics transformation.

#1. You can’t translate your business needs into analytical use cases

Implementing analytical tracking codes on every website that is developed has become a standard practice.

Remember that this is very basic and all you get with default tracking codes is basic traffic metrics.

But is that the real reason why you even invested on the tool, even if it is an open source or a free tool?

Nah! I’m sure you came across a lot of brands successfully using analytics and you wanted to emulate them.

You may also think that without a solid understanding of digital analytics fundamentals for your business, you can’t get there at all.

We, at Xerago also understand that this is such a unique skill that not every business person or analyst can do.

Is this a vicious cycle? Where do you start?

Well, here are 6 business objectives translated into analytical use cases. And I’m sure this is a good place to start with data analytics in marketing.

  1. You know your products will be a great hit amongst a specific segment. But you don’t know how to determine whether a pre-login user falls into that segment or not.
  2. You know your products are not bought impulsively. And your users will consume information in a sequence before they eventually buy. How do you ensure you provide the information in the right sequence to those users?
  3. You run a lot of digital campaigns to acquire customers. Some customers convert instantly. Some take time, come back to your website and then buy. How do you differentiate experiences for such users?
  4. You have your branding team, portal team, SEO team, digital advertising team and marketing automation team working in siloes. Every team claims responsibility whenever there is a success in terms of achieving acquisition targets. How would you attribute credit correctly?
  5. You are a creative marketer. You keep making creative changes in your portal. Some changes click and some don’t. You are doing this on a trial and error basis. How do you make changes with certainty?
  6. You don’t have big budgets to spend on campaigns. So, you had to acquire customers the organic way. There is good amount of traffic that you are getting from your SEO efforts. But there is little conversion. How would you diagnose and fix problems?

All these are real world business challenges that many of you might be facing during digital analytics implementation.

In fact, these are real business challenges that some of our clients threw at us which our analytics team solved.

When you communicate these to your / your partner’s digital data analytics team...

While these are good for a start, what would you do after you find solutions to those problems? Are these the comprehensive list of use cases that analytics can deliver?

Certainly Not! But, how do you keep this running?

Well! Here are 4 actionable recommendations to help you translate your business needs into analytical use cases and some ways how digital and analytics can drive new performance and growth

  1. List down all your business challenges / needs regardless of whether those can be solved with the help of analytics or not
  2. Throw these challenges at your analytics team. There will be a lot of counter questions probing you for more details
  3. Answer those. You will get any of the following responses for each of the challenges that you listed.
    1. Can be solved by digital analytics. We can immediately action
    2. Can be solved by digital analytics best practices along with inputs from few other teams
    3. Can be solved by digital analytics. But we aren’t capturing the required data right now
    4. The solution is out of the digital analytics domain
  4. Prioritize finding solutions based on business impact and the time needed for execution and you are done. The analytics team will come back with the solution that addresses your business challenges.

Note: When you are not sure of answers to questions thrown back by your analytics team, make calculated guesses. Let your analytics team know that the response is bound to change so that they know what to fix if the solution goes wrong later.

#2. You don’t get actionable insights on analytics reports

Well this is a problem. A big one indeed.

Reports are schedulable on the analytical platforms. Do it once and you will get reports automatically at the scheduled frequencies.

You don’t need an analyst every month for getting this.

So, in real life how a standard report and an insight differ?

Here’s a typical report that analysts from agencies deliver to their clients. I’m sure you too get these kinds of reports.

There is nothing wrong with the report. In fact, this clearly shows your traffic trends and a few other metrics.

Apart from this, what do you make out of this? Barely nothing.

Well, here’s a small insight captured from one of our reports sent to our client.

In comparison with the report above this, this is lot more specific and throws light on several aspects using which you can actually make decisions.

For instance, as a marketer you can make the following actions as per the insights shared.

  1. Continue current communication
  2. Provide differentiated content to existing and new audience
  3. Incentivize your audience with an alternate offer with a greater value to sustain lead rate
  4. Reassess keywords targeted by the SEO team as well as ensure whether the intent with which users landing on your portal are fulfilled

That’s the power of actionable insights vis-à-vis a standard report.

Actionable Recommendations

Let’s be honest. How many of you actually receive insights with such depth?

I’m sure there are not much.

So, what do you need to do to get actionable insights from your digital analytics team?

Here are 4 actionable recommendations.

  1. Define objectives to achieve from your portal in line with your business needs. For instance, increase organic traffic by <X>%, generate <X> leads for a specific product, increase user engagement and so on
  2. Define measureable KPIs for each goal. For the above example, these could be Traffic (Visits) from search engines, Number of leads generated & Traffic to leads and reduction in bounce rates respectively.
  3. Once defined, keep the analyst in loop on all changes that get made in the portal.

For each KPI, your analysts should be able to analyze the trend, perform impact analysis and present how each of your interventions have impacted the relevant KPI and what you need to do as a course correction measure.

Rinse and repeat.

#3. Your digital analytics is not comprehensive

Web analytics used to be an independent domain even during the meteoric rise of digital advertising.

But with the proliferation of mobile apps and social media, growing importance of customer experience and Omni channel customer journeys, web analytics in isolation is insufficient for the modern day marketing.That's when you need to know why digital analytics is important and can go beyond conventional web analytics to deliver key insights.

Let’s get a bit deeper into this.

Your website has a lot of calls-to-action waiting to be made by your audience.

Most times, your audience doesn’t just make those actions directly.

Many a time, they get stuck looking for some key information or are doubtful or require help etc., resulting in taking actions late or going back and forth between pages.

Conventional web analytics reports only tell you how many came to the page and converted or exited.

This is where behavioural analytics tools can help. They can give you a heat map, a visual representation of how they navigate within your website’s pages.

There is another set of visual replay tools that literally capture the mouse movements for you to review.

When you have such detailed insights, wouldn’t it be easy for you to optimize your conversions easily?

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In your website, not all of your audience travel the same path to conversion. In fact, not all of your audience will use the same device until conversion.

For instance, imagine you run an ecommerce company.

You have a new user x, who wants to buy a product. He does casual browsing during his free time in office and exits the session in a while.

Then, during commute he again starts comparing products and checks ratings and reviews.

Before he makes a purchase, he reaches home and exits the mobile session.

Later, leisurely, he finds the shortlisted product and completes the purchase from his personal laptop.

Typically, across all touchpoints in the journey, the “unregistered user” has to start from scratch whenever he switches devices.

Do you think this is a good experience that your audience relishes?

And this is not a random example. Your audience are hopscotching across channels as evidenced below.

Source: Invesp

In this context, if you are responding to user-actions only based on website data, here’s what will happen.

Despite the user having moved on from the consideration stage to the decision stage, which apparently happened in another device, when the user visits your portal next, you would still be providing him content with an aim to move him to decision stage which he has already moved on to.

Wouldn’t it be a dissonance for him, as the context is lost when he switches devices?

Wouldn’t it impact the customer experience, conversion and eventually your bottom line?

When your audience switches between multiple channels / devices before they eventually convert or make a purchase, how do you ensure you provide an experience that is not disjointed, throughout the journey?

This is where cross-channel journey analysis and cross-device targeting comes to your rescue.

Cross-device targeting helps you to provide a continuous experience regardless of devices your audience uses.

Your audience has become more local on social media. Be it a positive experience or negative experience, they instantly share in social media resulting in the feedback going viral.

Imagine how many from you audience will be talking about your brand on social media.

Don’t you think you need an integrated capability to analyze audience sentiments in social media?

This is where social listening tools help you.

When you build the capability to track your audience sentiments, you will get valuable insights which you can use to improve your customer service, product proposition, customer satisfaction and advocacy.

And it doesn’t just stop at social channels. You need to extend this to other channels such as app stores where your audience is vocal about their feedback.

The more you interact with your audience outside your portal, your brand’s Share of Voice increases and it also results in your brand being exposed to newer audiences.

You work hard and spend a lot to drive traffic to your portal.

You might think once you convert the incoming visitors into customers, your job is done.

But it’s not. Your visitors convert as customers because they like what you offer.

When they are in such a state of mind, don’t you think they are very likely to respond to feedback queries?

In fact, you can ask for feedback even from visitors that have not converted.

The more your expose you survey without annoying your users, the more you are likely to get responses.

And these responses would be very valuable which will directly impact customer satisfaction.

You have specific survey tools that can help you not just with executing surveys, but also with analysis.

Actionable Recommendations

Here’s a summary of what you need to do to make your digital analytics comprehensive.

  1. Deploy a behavioral analytics tool and visually see where they get stuck and remove friction
  2. Deploy a social listening tool to track every mention of your brand across the web, calculate sentiments and fine-tune your communication
  3. Integrate your analytical tools with your targeting platform, aggregate device ids used by same visitor and provide a continuous and seamless experience
  4. Use survey tools to frequently collect feedback and use it to improve your offerings

#4. You are paying more for your digital analytics tool

You didn’t expect this to be a data analytics and digital transformation indicator. did you?

If not for a large Malaysian Banking client of ours, this would not have found a place here.

If you are using an open source or free digital analytics platform such as Piwik, Google Analytics etc. you don’t need to be bothered about this.

But if you are using an enterprise digital analytics platform such as Adobe Analytics, then this is something that you should seriously look into.

Our client, a large Malaysian Bank approached us to help with their analytical needs. Our scope of work was limited only to delivering analytical insights on their portal.

But then, when we started the assignment, we were completely shocked to see that for capturing every user action two server calls were made where there should had been just one.

Here’s an illustration.

What’s the big deal here?

Well! The platform subscription cost is determined based on the number of server calls consumed.

Given the current rate, our client was incurring at least 2X the cost month-on-month.

Guess what? The client was unaware that they were paying extra.

When we intervened and told them that we could optimize these server calls and reduce the subscription cost, our point of contact literally jumped for joy as he was finding it challenging to demonstrate the promised Return on Investment to the Senior Management.

We reviewed the entire implementation and optimized server calls by performing the following:

  1. Optimized server calls that were executed on custom links and exit links
  2. Optimized the use of internal and external filters to restrict server calls to only where required
  3. Appended rules in tag manager along with conditions for making server calls.

Through the process, we also ensured this had no impact on the reporting frequency and most importantly we ensured the data was consistent.

Further to our interventions, the number of server calls went down by 50% resulting in saving thousands of dollars every month.

And our point of contact was able to demonstrate the promised ROI in the senior management meeting conducted that quarter.

The satisfaction in his face demonstrated the impact of our interventions that we extended voluntarily.

Imagine how many of other enterprise analytical platform users might still be paying 2X costs.

Actionable Recommendations

We at Xerago understand many of the marketers like you may be unaware of this challenge.

But what should you be doing to check whether you are paying your analytics vendor more than what you ought to?

Here are a couple of actionable recommendations. This might sound a bit technical / operational. Nonetheless, this is worth acting upon. You may even discover opportunity to save thousands of dollars like our Malaysian client.

  1. Custom links contribute majorly to the bulk of unnecessary server calls. Whenever you create a custom link, ask yourself these questions
    1. How important is the required data?
    2. How often will the triggers be initiated?
    3. How effective is the tagging that is done?
    4. What are the rules to be appended during Custom Link addition?
  2. Next to custom links, exit links are major contributor to unnecessary server calls. Ensure the external domains are correctly configured to prevent server calls being made by exit links.

Summary

With this, we have come to the end of the first part of this article series.

There are 5 more points discussed in the next part.

Here’s a summary of what we have covered in this article.

  1. When you understand analytics better, the value it will add to your business is immense. Work with your analyst to keep coming up with analytical use cases for the business challenges that you face.
  2. Encourage your analysts to provide actionable insights based on data analysis. Ensure that you keep them in the loop on all the changes that you make in the portal, so that he/she is aware of what is leading to the changes in outcomes.
  3. Having just a web analytics tool in your digital analytics stack is definitely not ok. Augment your digital analytics stack with a behaviour analytics tool, a visual replay tool, a social listening tool, a cross-device targeting tool and survey tools.
  4. Conduct an implementation review audit to find out whether your analytics tracking code makes unnecessary server calls that may impact your analytical platform subscription costs.

Click here to continue reading the second part of this series.