A recent Forrester studyOpens a new window found that COVID-19 has served as a wake-up call for decision-makers who realize they need the right data and analytics tools to achieve their goals. 

For example, while customer experience (CX) professionals understand the critical importance of data, they struggle to collect, curate, analyze and distribute insights to improve data-driven decisioning. Yet the motivation for improving the situation is clear, with 80% of CX leaders believing that data-driven customer experiences yield better business outcomes such as meeting customer expectations, increasing sales and revenue, and reducing customer churn. 

So what’s holding organizations back from addressing the problem? In part, vendors offering “free” solutions to collect, curate, analyze, and distribute insights based on reusing or repurposing existing tools and technology is part of the problem. Because more often than not, these are web analytics tools masquerading as Customer Data Platforms (CDPs), with long-term costs that are not often readily apparent. 

Marketers may be enticed by these free opportunities, especially as they are pressured today to switch their focus from the third party to first-party data. Challenges to third-party solutions as a result of privacy measures, such as Apple’s Intelligent Tracking Prevention (ITP), browser restrictions, and privacy legislation such as GDPR and CPRA, have rendered most platforms that rely on third-party data incapable of managing identity in a consistent and meaningful way.

See More: What a Successful CDP Implementation Actually Looks Like

Marketing teams are hungry for a comprehensive CDP that can make sense of both new and existing data streams in a true first-party manner, though not all platforms built for this task are created equal. Many teams struggle with cross-platform identity resolution and the ability to provide genuine real-time data capture and analysis, even if they won’t necessarily admit it.

In this article, I will explore why seemingly “free” approaches to data collection couldn’t be further from reality. Sadly, there’s no such thing as a free lunch, and this seemingly affordable option for your business will wind up costing far more. So let’s break down what repurposing your existing web analytics or tag management solution (TMS) will potentially involve and how this will quickly add up.

1.Implementation Costs

The first thing that’s needed to drive a truly personal customer experience is understanding what customers want. To do that, you will need to capture their current experiences through digital channels. In doing so, two major steps are required:

• Requirements gathering from all the teams that will need the data to deliver personalized customer experiences, such as digital, marketing, data science, CRM, reporting, and more. This effort will typically involve several people over several months.
• Implementation via the web analytics team, including items such as tagging and data layer design, documentation, testing and implementation. This, too, typically takes several months.

Your web analytics or TMS vendor may say, “don’t worry, we only require a single line of code,” which is true on its face, but that only captures basic information like a visitor ID (i.e., a 3rd party cookie), a session ID, and page views. To understand the really useful detail of how a visitor has interacted with all the different buttons, forms, fields and content on the page, extensive tag management and data layer design effort are required.

This typically takes at least 6-8 months, along with hundreds of thousands of dollars in associated resource costs, before the data starts to flow. But this is merely the beginning because, by this point, you are committed. The free offer has already cost you in terms of effort, and once you are locked in comes the high cost of maintenance. 

2. Maintenance Costs

During the design and implementation process, it is very typical for key pieces of information to be missed because the business doesn’t know what it needs until it starts using the data. Given this, it should come as no surprise when you then hear the stories of the business saying, “we also need this data,” and the reply from the web analytics team is something to the effect of “sorry, we didn’t tag for that.”

Additionally, websites and mobile apps are under constant development. When a page or app is changed, a minimum of two of the following three areas will immediately require attention: TMS rules, actual Java script written in the TMS, or report suite re-configuration. The key issue here is that the solution in question is fragile; it has already become outdated due to the ever-increasing complexity of digital and the flow of changes on the web and mobile.

This constant loop of break-fix-repeat will perpetuate as long as your websites and apps keep evolving, namely, forever. There’s no automated way of detecting whether something is even broken in the first place. So, unless you or someone else on your team stumbles upon an issue or problem or discovers that something is, in fact, broken, there’s a chance you may be relying on inaccurate data. Or worse yet, you might not even have the data. Additionally, business requirements change as new use cases get added (e.g., retargeting, predictive modeling, real-time decisioning, and more), so the problems are perpetuated.

The cost of maintenance for a large enterprise? Again, hundreds of thousands every year, but these may drive even be higher with continued innovation.

3. Data Activation Costs

With collection up and running, there is also the challenge of making data meaningful for the teams that need it, such as getting it into the right format for analysis and distributing it to the right downstream systems to manage the customer experience. All of this takes further effort to design, build, test, implement and maintain, further adding time and resource costs.

It is at this point that a large bill arrives, again in the hundreds of thousands of dollars, to pay for additional license costs, just to get your own data back out of the system that initially looked like quite the value! Getting data back out of the web analytics solution is critical, so there’s no choice involved because of the processes that rely on the solution already. Yet, this is where buyers’ remorse kicks in as key functionality for data science, or decisioning is lacking. These tools sit elsewhere; the data you’ve collected needs to be loaded and sent to these in the right format and at the right time, and restarting the process is probably not an option.

4. Lost Opportunity 

So, the costs have added up, and the solution is far from free. And unfortunately, this situation only gets worse from here. Most enterprises and organizations want to become data-driven to deliver exceptional personalized experiences, increase their net promoter score (NPS), realize revenue-generating opportunities, prevent fraud or reduce churn. The time delays in fully deploying a ‘free’ solution, plus the gaps created by the constant break-fix-repeat cycle, mean benefits come through slowly or are never optimized to realize their full potential. 

The potential cost of a delayed implementation is staggering. A recent study by GartnerOpens a new window found that poor data quality costs organizations an average of $12.9 million every year. However, if you are a large enterprise, the costs can be far higher. A study by BCGOpens a new window found that a retail bank with $100 billion in assets can generate as much as $300 million in revenue from personalization, and there is a similar calculation for retail. For a large enterprise, failing to deliver personalized experiences could cost tens of millions in lost revenue.

But it’s not just the delays that create lost opportunity. There are fundamental gaps in the data that undermine efforts to maximize the full potential of your CDP. For example:

• As mentioned above, the privacy war waged by Big Tech players like Apple, Firefox and Google is slowly managing out third-party party cookies. This is already reducing the ability of third-party web analytics solutions to profile your customers. Short-term DNS tricks such as CNames are being used to circumvent the rules, but these tricks pretty quickly get discovered and neutralized.
  
• Third-party party technologies do not collect personally identifiable information (PII), and rightly so, due to the security risk. But this breaks the link between you and your customers, making it nearly impossible to manage the customer journey over time and across devices.
• Activating customer insight in real-time is impossible when it takes hours or days to get your data back. In my experience, real-time decisioning beats 24-hour-old decisoning by at least a factor of x10, so real-time is key.

To summarize, there is no such thing as a free lunch. With all the threats outlined above, the $100m+ in benefits promised by your CX program will not be achieved. It is easy to look at the solution you have and decide to soldier on, given the investments already made in making it work. However, this approach continues to add costs in terms of time and effort, lost opportunity, and risk. When you want your data back, there’s another financial cost to consider. 

See More: 4 CDP Trends That Will Drive the Industry in 2022

The original purpose of web analytics tooling was reporting. While the requirements of the business to innovate has stretched the use cases into analytics, targeting, and more, the underpinning technology hasn’t changed. 

Organizations that want to innovate rapidly to deliver exceptional customer experiences should think again about how they collect, curate, analyze and distribute insights across the enterprise and carefully consider investing in a comprehensive, first-party CDP. Those looking for failed projects and barriers to innovation, soldier on!

Have you ever implemented free solutions instead of a CDP? What long-term costs have you incurred? Let us know on FacebookOpens a new window , TwitterOpens a new window , and LinkedInOpens a new window .

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