5 Stages of Web Analytics in a Company

By now, most companies should have already gotten themselves acquainted with web analytics. To them, having web analytics means they now have a better understanding of their online users, opening up more possibilities for reporting. Number of site users, number of sessions, bounce rates, yada yada.

Is that really what web analytics is about? Or is there more to it?

5 stages of Web Analytics

In terms of adoption, web analytics is similar to most technologies out there. Companies would try it out before attempting to figure out how it can fit into the big picture.

What makes web analytics unique is that, it is currently one of the most misunderstood technology that has been around for ages.

Ever read those articles telling you that you are using everyday products in the wrong way? Yeap, the same goes for web analytics.

Stage 1 – Getting Feet Wet

Main Goal – Get familiarized with Web Analytics

Parties Involved – Vendors

Outcome – Obtain a huge amount of data

I believe most companies with a decent website would already have some sort of web analytics in place.

Many would have started off with Google Analytics, while for those with more ambitious goals to support end-to-end personalization, they probably would have Adobe Analytics in place.

Regardless the tool, Stage 1 companies would engage vendors to come up with a web analytics plan and give them the green light to implement the tags accordingly. And usually, the plan will be to “tag everything”. Yea.

What do we get? A huge amount of data that might or might not be useful and not much else.

Stage 2 – Value Seeking

Main Goal – Getting value out of the data collected

Parties Involved – In-house analytics person & vendors

Outcome – High-level reporting

Now that you have access to a whole new set of data, what’s next? Typically, the vendors would provide some basic reports and dashboards. Most of which are… not very useful.

Number of users. Number of sessions. Overall bounce rate. Page views. Demographics. Device types.

Not saying those metrics are completely useless, but on their own, there’s really nothing much you can get out of them.

Congratulation, you are now at Stage 2!

Not wanting to let the data go to waste, you hire an analytics person to make sense out of it.

More likely than not, you will get more reports and dashboards out of him. This brings us to the next stage…

Stage 3 – Major Cleanup

Main Goal – Ensure data accuracy and consistency

Parties Involved – Data governance team

Outcome – Data that can be trusted for safe consumption

“Why is the conversion rate greater than 100%?”

“Why are there 3 different names for the same product?”

“What does XXX represent?”

“Is the bounce rate really only 0.7%?”

Sound familiar? Don’t worry, you’re not alone. As more and more stakeholders look at the reports and dashboards, they will realize that the numbers are not exactly dependable.

This is mainly due to the “tag all” mentality, and poor implementation practices. In web analytics, it is especially important to have a game plan upfront. Most importantly, a data governance strategy.

There are 4 desired traits that we are looking for in our web data:

  1. Accuracy
  2. Completeness
  3. Consistency
  4. Timeliness

I shall not go into details, and if you are interested, here’s a good article for you.

Characteristics of Good Data

Realizing that in order to unlock the value hidden within your web data, you will first need a data governance team to ensure that you have data you can trust.

The tasks involved will include:

  • Full audit of existing data and implementation
  • Data governance strategy
  • “Fixing” the existing implementation
  • Rebooting the data collection process

With these, you can look forward to working with accurate, complete, consistent and timely data. Phew, that’s a mouthful.

Stage 4 – Ready… Action!

Main Goal – Generate actionable insights

Parties Involved – Analytics person

Outcome – Insights that you can act on

Getting to this stage is never easy, as most companies do not get past Stage 3.

For some, after years of frustration trying to get value out of their web data, they throw in the towel and write it off. There are also companies that fail to see the value of data governance, companies that are contented with sub-par, biased reporting. The list goes on.

Eventually, for those who managed to fight through the pain and figured things out, there is still that one last step… getting the right person to generate actionable insights.

These are the companies that have looked past reporting and started to ask, “What can we do with these insights other than putting them in a deck that will never be opened again?”

Actionable insights are hard to come by, and appear in different forms for different companies. I’ll just use insurance as an example.

For most insurance companies, the main purpose of the website is to generate leads. Understanding where users drop off during the leads conversion journey is important. This will allow us to identify specific areas to improve, reducing the overall drop-off rate.

If you possess a great understanding of the business and human psychology, you would realize that every user who lands on an insurance website carries a certain level of intent, either to carry out research or to make a purchase. You can then classify each of these users into different tiers of leads. Through iterative experimentation, you will discover new lead sources and determine their effectiveness. Gone are the days where you need users to fill up your painfully long forms to be considered as qualified leads.

Therefore, this analytics person you are looking for should not only possess technical skills (for implementation), but should also possess great business acumen to identify hidden opportunities.

Stage 5 – Utopia

Main Goal – Generate new business-impacting ideas

Parties Involved – Analytics team

Outcome – Insights that give you an edge over your competitors

If you are at this stage… congratulation! You should now have teams that are constantly making data-driven decisions, improving their KPIs with the help of data. A/B testing is now commonplace, not just for UI/UX, but also for campaigns and comparisons of vastly different ideas.

Being at the front of the pack doesn’t mean you should stop there. Now is the time to be creative and seek out opportunities that will generate greater ROI for the company. Come up with complex strategies to nurture your customers. Think about how you can make use of data to transform a weekly email blast into something highly personalized.

Remember, the possibilities are endless. With great data comes great responsibility 😉

 

About admin 30 Articles
Analytics Consultant who loves numbers and data! In love with Adobe Analytics.

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