Are You Paying Your Analytics Vendor More Than You Ought to?

What Should You Check to Ensure You Are Not Paying Your Analytics Vendor More

Boost your Analytical Tracking Functionality: Reduce Unnecessary Server Calls.

You might be having the best-in-class enterprise digital analytical tools, but are you making the most of the platform?

Are you able to demonstrate the promised ROI and reaping its real benefits?

Around 59% of organizations are currently using advanced and predictive analytics in their enterprise analytics initiatives. However, extracting meaningful business decisions and getting the best value for the money invested in advanced tools is the topmost concern for all businesses today.

According to reports, about 40% of organizations that have procured analytical platforms fail to harness their power and have not yet attained the advanced stage of digital analytics maturity.

Some common challenges organizations typically face when it comes to implementing enterprise digital analytics platforms are listed below:

  • Lack of in-house resources to implement, manage, optimize and maintain analytics tracking
  • Inflated platform subscription cost leading to difficulty in achieving ROI
  • Multiple systems, data silos, and inconsistent data collection makes reporting and gathering insights impossible

If any of these or something similar resonates with your situation, it’s time to act and evaluate your data and digital analytics performance to ensure that you are getting the best value for your investment. You should start by validating whether you are paying more for your enterprise analytical platform’s subscription costs than what you ought to.

Are you Paying Your Analytics Vendor More?

Turns out that most enterprise analytical platform users are not clearly aware of what goes into the platform subscription cost and end up paying more than 2x costs.

They either don’t’ have the resources to make the necessary optimizations or fail to run athorough implementation audit to uncover key insights that may impact their analytical platform subscription cost.

Here’s what you should do to discover if you are paying your analytics vendor more:

  1. Reduce Unnecessary Server Calls

Custom links and exit links are the primary elements that contribute to the bulk of unnecessary server calls. As the platform subscription costs tend to be determined based on the number of server calls consumed by the business, you can optimize server calls by performing the following:

  1. Evaluate the need for creating custom links and determine how often the triggers will be initiated, how effective is the tagging and what are the rules appended during custom link addition
  2. Ensure that the internal and external domains are correctly configured to prevent server calls from being made by exit links

Optimize Tracking Code

The ability of your analytical platforms to track user behavior would have grown drastically over time as your business scales up. Compared to the initial implementation of the system that used to track few users, the number of users and various user action sequences may have grown manifold times. Thus, you have to optimize your tracking codes for continued performance and strengthen analytical capabilities by continually assessing performance metrics, the range of variables used, and the range of events captured.

A large Malaysian banking institution approached us to deliver key analytical insights on their portal. The bank had procured and implemented Adobe Analytics. However, the bank was shocked to pay 10x more than the anticipated cost. This led to significant losses and difficulty in demonstrating ROI. After a thorough assessment of the tracking code, we found that to capture every user action, two server calls were made. After our timely intervention, here’s how we reduced the number of server calls by 50% that led to huge cost savings of thousands of dollars every month for the company.

Here is a checklist – for you to use to see if you have covered all bases.

  1. Have you clearly listed your goals? What do you hope to achieve? Are you trying to sell more of your product or services? Or are you trying to improve a certain function in your business?
  2. Have you defined key performance indicators once you know what your goals are? (Key performance indicators come in handy when you need to track and measure your efforts to see if you are indeed progressing in the right direction)
  3. Have you broken goals and your performance indicators into measurable actions – things you can do and subsequently measure?
  4. How about the tool? Have you picked the right tool for your arsenal? It would help to remember that it would all depend on your industry, your requirements, and various other factors, including data privacy and how you handle sensitive information about customers.
  5. While choosing your tool and building your analytics solution, did you ensure that it is flexible enough to accommodate future requirements and can stretch to accommodate scale?
  6. Once you got your tool, did you clearly define your expectations from it? (this would be very closely interlinked with the goals you set when you decided you wanted analytics in the system)
  7. Did you prioritize the list of features that you want to leverage once you implement it?
  8. It is important to define project / Implementation exclusions – what you don’t want to be included in your analysis of the data that you have.
  9. The UI, the various views, and the filters need to have been configured carefully
  10. Did you define who will use it? Give permission to only those who will need access to it? This is a vital aspect that needs to be checked, as anything can go wrong if the wrong people have access and the power to change basic settings.
  11. Dashboards, the segments, and the custom reports for each data view need to be created and checked.
  12. And make sure that every time you have a change in your goals or strategy, you make the corresponding changes in the tool as well so you can measure the effectiveness of it.

Data Analytics can help you make informed decisions that will lead to better outcomes. Eliminating guesswork will lead to effective marketing efforts. You understand and truly know your customers and so you can tailor your content and offerings to truly meet their needs. But for that, you need to track the entire customer journey – from leads right up to conversions. Only then can you truly understand customer behavior and also micro-segment your entire audience.

An important question it really helps to ask is if we are able to get a total, complete picture. The most prevalent problem in a digital analytics setup is a complete lack of correct cross-domain or subdomain tracking. This will affect everything.

And through it all, it is very important to keep an eye on what your competitors are doing. Effective competitor analysis goes a long way in firmly establishing your brand in the market.

Digital data and analytics management is crucial to managing data and deriving valuable insights from it. You might have the fanciest tool that can handle the sharpest modeling in the market. But it takes some careful planning and implementation to achieve the goals that you intended to achieve as you set out on this digital analytics journey.

There are times when you have a great analytics system in place and you track your website and your app, your portal, and your campaigns. You do what it takes to understand customer behavior. You even want to personalize your engagement with each of them and put a personalization tool in place. But the numbers are still plummeting. Ever wonder why?

We all know that analytics uses quantitative methods to derive meaning from data for businesses to make informed business decisions.

Mandate Periodic Analytics Audit to Give Your Analytics Implementation a Checkup

Once you implement an analytics platform, it’s not the end of the journey. You still need to conduct periodic audits to find out whether your analytics tracking code is working right and providing you accurate data you can rely on. Besides, unnecessary server calls are a common issue that elevates your cost and running an audit is the best way to make optimizations that ensure you are not paying more than what is necessary.

Despite best efforts, many organizations lack clarity in their current state of analytics. Often, there is a misconception that you are doing fine, when in reality you may be falling behind or shelling out more without achieving an optimal ROI. Thus, it’s best to understand where you stand and take the right measures for the digital analytics journey, and stay ahead of the competition.

Do you use the above or any other techniques to optimize the platform subscription costs of your analytical platforms? We would be happy to know. Write to us at