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1. Data Domination or Ruination

Are you gearing for Data-Driven Marketing?

As a data marketer and analyst in South Africa, I have found it an interesting place to review the way in which SMMEs understand, use and interpret data. Interestingly,  the upper end of the SMME scale companies seems to have the greatest challenge in understanding Data Marketing, using it and determining the impact from it.

In general, this seems to be endemic for these organisations whose Data sources can be wide and varied. What we have seen as the most common aspects of this include:

Data blindness – This state occurs when an organization has undertaken to capture data but has no internal or external means of actually understanding and interpreting the data. The business has undertaken to collect data for the sake of collecting data. It is much along the lines of lemmings diving off a cliff together.

Purposeless data collection – Much the same as Data Blindness, Purposeless Data occurs when there has been no planning or understanding of the need to collect, process and interpret data. These organisations may well have resources for the understanding, interpretation and application of data but have absolutely no direction or planning regarding the collection of data.

Data verbosity – This occurs when an organization is so hell-bent on collecting as much data as possible that the volume becomes more important than the value. At this point, an organization has so much data that it is difficult to sort through, to understand, and can often create conflicting insights. This also leads to compliance-related issues where there is the risk that Personally Identifiable Information of customers can be mishandled leading to legal consequences

Disparate data sources – This is an apple and oranges scenario. Data is collected from many sources but without a common understanding of the connection between data sets and the uses of said sets. Sometimes data will act in a vacuum but generally, there need to be lines of connection between the data collected, that helps create a far more in-depth, accurate and useful view of the collected data.

Interdepartmental Disconnect – I have to say, of all the aforementioned issues, this is one that literally blew my mind as it has little technical requirement with regards to the understanding of data collection and analytics. In this instance, the departments who should be working and planning together at a business level simply do not or, much to my disbelief, refuse to. An interesting dynamic I discovered is that the perception of Data between departments is that it will be used a measurement of performance and that it could potentially be used against the department in question. As a result, the data is siloed to a business segment, meaning the majority of its usefulness has been discarded. This is not specific to the data but, most likely, endemic of Although not specific to Data, it is a common issue that can occur within a business.

There are many technical factors that would affect the data collection process but the above mentioned are just the ones I have come across recently.

To deal with these you could look at doing the following:

Data blindness

“If you are going to do something right, get the right person”. I know that many people will be internally saying, “that’s not how that saying goes…you need to do it yourself”. That’s great but not a reality.

Looking at the spectrum of making data useful, you need people who can create, manage, interpret and apply the insights generated by data. Having only one of those resources available is not going to help. Make sure your chosen person can look at, understand and interpret the data into usable insights. This could be a Data Scientist, a Business Analyst or similar. Don’t just hand the data off to your marketing intern and expect some amazing insight.

Purposeless Data Collection

As with doing anything in life, collecting data for the sake of collecting data is a wasteful exercise. Many organisations do this for the purpose of simply being able to show…something.

Collecting Clicks, Likes, Shares and impressions because, well, you read an article that one time, is a pointless exercise. With a little planning and understanding of what you want to take out of the data, a business can usually reduce the collection of wasteful data and focus on high return information that actually provides insights. This means getting the people responsible for business decision making around a table and asking them, “What will make this clock tick faster?”. Using this information you can begin to build a data collection roadmap to reduce wasted time and create more meaningful data.

I strongly recommend using the KISS principle here. Unless you are a “mathematical statistician actuary unicorn hell bent on determining the meaning of life by cross referencing all known social media data points along a continuum of the human psyche”, being simple will help most. Ask

  1. What are we doing?
  2. Why are we doing it?
  3. How do we plan on doing it?
  4. Who are we aiming at?

Getting answers to these questions and then simply saying, “what defines success?”, is a great place to start and help the organization in creating a more useful and robust data set.

“Don’t create your own black hole of misunderstanding”

Data Verbosity

Remember where I said it is pointless to collect data for the sake of collecting data? Well not only is it pointless, it can be dangerous. What happens when a company goes out of its way to collect as much data as possible just to show something? Well, something becomes apparent but no one can see what it is because its layered in useless muddy information.

Again we come back to the fact that data needs a purpose for a business. Without purpose, it’s pointless and muddies whatever potential insights you may have been able to retrieve. The information and insights are still there but it will take you 100 times longer to find it and, potentially, the layers on layers on information have created false positive or skewed results.

This usually results in valuable information being trashed because it appears to be exactly that – trash.

Plan for success they say, so plan for heaven’s sake!

Collect what you need or at least know what parts of the collected data are most important and how to segment and analyse them. You may find the issue is not the volume of data but the forethought on why and how you are going to use it. Remember, data is stored, you can come back to the many possibilities of it at a later period AFTER you have what you need at the beginning.

The last, and possibly most important, note on Data Verbosity is compliance. If you are collecting this plethora of data using a multitude of processes, managing compliance can become a minefield. If you yourself have any online profiles you most likely have received an email or notification regarding data compliance changes as a result of the GDPR. This new legislation paves the way for significant consequences for the mismanagement and abuse of users data. It is not unique legislation, but this combined with the approaching enactment of PoPI and the promise of harsh consequences for companies who fail to be compliant means all business need to quickly and thoroughly assess their data policies.

Disparate Data Sources

Businesses are often collecting data from many sources at the same time without knowing that there is value in connecting these systems to generate greater insight. This siloed outcome results in potential lost opportunities for business.

Connecting these sources is not an easy feat, however. It requires a good understanding of strategy, KPIs and technical knowledge needed to bridge the data between systems. Depending on the level of complexity of the systems there may be good opportunities to compare these data sources against each other.

A simple example is a business who is running a Facebook and Twitter campaign. They can see the independent performance of the platforms and what is working in each. However, they could be linking these datasets together to generate greater overall insight. Both systems collect similar demographic data such as gender and age and both platforms measure performance similarly (users, engagements etc). This means you could combine the attributes of both to get a more overarching view of your user set demographics.

This deepens the meaning of your data and can help your strategic planning at a higher level than just platform-specific outcome-based plans.

Interdepartmental Disconnect

At this level having a strong systems manager is essential. This manager needs to be a champion for connecting the disparate datasets, have a strong grasp of the technical requirements to do so and the analytical ability to interpret the collected information.

Preferably the end information should go through a Business Analyst or Business Intelligence Officer who can take the, now connected, data to develop a deeper understanding of performance and what different variables exist that impact this.

I am afraid to say that I may leave you high and dry here. In reality, this needs to be a leadership and management process whereby all stakeholders are educated on, and encouraged to share their data and KPIs for greater overall insight and, therefore, performance within the business.

Having a strategic planning session with open discussion may help the departments understand how by sharing information they can actually make their lives easier and create greater performance, rather than being fearful that the reason for data collection and sharing is to evaluate their individual departmental performance.


We are in the age of Data. There is no doubt about it. We are collecting more data at greater rates each year. You need to be ready for this but being ready has many aspects.

When you look at collecting data, start by looking at your business. You have been doing what you are doing for years most likely. That means you have your first dataset at your very fingertip – your own knowledge and a team with experience.

If you start with what you know you can begin to understand what you WANT to know. From here, you can begin the process of planning to collect useful data that can be interpreted for meaningful insights that create actionable outcomes.

Ensure that you are up-to-date with the latest changes in regulation and compliance as you begin to grow your data sets.

Keep in mind you can’t know everything and technology changes rapidly which affects the way and types of data collected. Do yourself a favour and find a trusted partner to help you walk the road of robust and effective data collection.

In the next article, we will discuss some possible processes for getting yourself going in an effective data marketing direction.

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