The best things in life aren’t free: Why no-cost data management tools bring hidden charges

Lindsay McEwan, VP and managing director EMEA, Tealium

In two years, the number of global connected devices will almost double - that’s 2.4 billion smart objects all collecting data about consumers, including the websites they visit, content they view and products they buy. Little wonder data is being touted as the new oil. 

For the marketers and IT professionals keen to harvest this abundance of insight, intelligent tools capable of managing it have become a necessity. What’s more, many see the so-called “free” tools offered by technology giants as the most preferable option. 

Even so, while complimentary tools might seem like a bargain, they often bring hidden costs. In fact, their negative impact on resources and productivity can even be higher in the long run. 

So, which is the better choice for optimising data usage: free or paid-for platforms?

Key data considerations 

Amid increasing interconnectivity, companies are adopting more tools that allow them to use data insights as a means of providing engaging, real-time experiences. Typically, these tools - such as analytics, advertising and personalisation platforms - require companies to integrate a piece of JavaScript code (tag) into their sites, so information about consumer behaviour can be captured and translated into tailored ads, live chats or recommendations. 

However, when using such platforms, there are two factors companies need to consider. Firstly, that a new set of data laws, the General Data Protection Regulation (GDPR), will soon put the way consumer information is collated, stored, and processed under greater scrutiny than ever before. And, secondly, the vendors and tags they use don’t necessarily enable them to manage this data efficiently, securely or accurately, especially if they’re free.  

The pitfalls of no-fee tech

Free tools are an undeniably attractive prospect. Requiring no up-front financial investment and providing useful tech, they appear to be the ideal data management solution. But appearances can be deceiving. Let’s take a look at the top three common pitfalls: 

1. A lack of support

The chief problem with most free platforms is their low level of support. Although set-up is simple - with plug-and-play installation and no license fees - there’s minimal advice about implementation and deployment, and limited on-going assistance. With no external support to call upon, companies frequently assign platform management to dedicated teams. 

But, in doing so, they remove vital resources from other projects and put pressure on employees. For example, while trying to avoid unbudgeted-for costs - such as using consultancy services - individuals are likely to take on extra tasks, like manually adjusting vendor tags, trawling online forums to answer technical questions, and developing workarounds for platform issues. 

As a result, workplace satisfaction and productivity are inevitably affected with late nights at the office reducing time spent at home, and the strain of constant fire-fighting weakening performance. What’s more, inadequate support also means there’s a high chance key aspects of implementation will be overlooked. 

So, the insights that platforms produce and the business decisions they inform are likely to be inaccurate. That’s not to mention the operational inefficiencies caused by dividing data processing across siloed teams. 

2. Restricted performance capacity 

Every company wants to build the perfect tech stack: a compilation of the best solutions and vendors for their unique goals. Unfortunately, this isn’t always possible with free tools. Often, available turnkey integrations are limited to just a handful of choices, either because the tech giants powering platforms have specific preferences or small-scale developers don’t have the capacity to add further integrations. 

Consequently, the tech stacks companies can build with free tools regularly fall short of their requirements, as well as limiting the scope of activities. Plus, attempting to overcome this hurdle by adding more vendors is risky - with each vendor comes a tag that adds weight to websites and can slow down page loading time, thereby diminishing consumer engagement, conversions and revenue. 

3. Insufficient data protection

When downloading free tools, it’s easy to look at the many pages of terms and conditions and decide a skim-read is enough. But such a lax approach to security is hazardous. 

By signing service terms that have not been read thoroughly - or assessed by legal and procurement teams - it’s possible companies will be agreeing to conditions that have a detrimental impact on consumer privacy. For instance, there may be clauses that allow vendors to leverage data and sell it on for advertising purposes, or even give them total ownership of all data produced by their tech.

Furthermore, this uncertainty will not stand companies in good stead for GDPR compliance. GDPR states that any organisation processing the data of EU citizens is accountable for its safety, which means they must be able to control and secure its flow in every direction, as explained in this report by DataIQ and Tealium.  

How can paid-for tools solve these issues?

In comparison to the numerous potential hazards of free tools, the long-term advantages of paid-for solutions more than justify the short-term outlay they require. 

The primary benefit is the support they offer. For instance, most enterprise platforms will allocate a team of engineers, project managers and deployment advisers to assist companies during implementation, and beyond. Employees can instantly access expert assistance to solve any problems and fine-tune systems: no more unnecessary late nights and frustration. And, with tech quickly and efficiently integrated - without oversights that can cause data errors - it can start boosting company revenue and performance faster, too. 

A close second is data governance and security. In addition to working with companies as they evaluate terms and conditions, the majority of enterprise platforms also provide extra data privacy safeguards. In the light of the upcoming GDPR, for example, many have built elements, such as privacy by design, into their software, alongside flexible controls for user-level permissions and data handling, and transparent reporting on data usage, all of which make it easier for companies to ensure compliance with GDPR rules and avoid its large fines. 

Last, but not least, they provide diverse capability. For example, by partnering with a paid-for tag management system - which acts as a control centre for embedding, maintaining and adjusting vendor tags, while centralising the data they produce - companies can streamline operations and build more flexible tech stacks. The ability to share selected data sets across the organisation, rather than holding it in silos, will improve inter-departmental efficacy and allow companies to deliver unified experiences for users. Moreover, easy tag adjustment and a wider range of turnkey integrations will also make for versatile and tailored tech stacks. 

Free tools have their place: they are undeniably a good starting point for helping smaller businesses get to a better place with data management. But their utility only goes so far, and it’s regularly outweighed by their drawbacks. 

With almost no support, flexibility or security, low-cost appeal is quickly eclipsed by the price companies will pay in poor performance, lost sales, ineffective data handling and security. When it comes to the tech companies entrusted with asset, data, and tag management, it’s worth keeping in mind the lasting value paid-for solutions can provide. 


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