~ by Marty Shaw, Global-Z Director of Sales & Marketing

Our parents told each of us growing up to “never play with matches”, right? Sorry to inform the parents of Global-Z’s R&D team… they didn’t listen to you!

Each week the GZ team has ongoing training sessions which are often lead by our R&D team. Recently we have been focusing the training on our data matching services. As we go through the training it becomes evident very quickly how much the GZ R&D team likes playing with matches! “Here’s what happens when you include the phone number along with the address in the match.”, “Look when you then add the email address.” As they play with matches during our interactive training we see first hand how our clients’ varying use cases for data quality matching often necessitate the fine-tuning of the business rules to optimize the match results. The granularity of the match rules we incorporate into our services often necessitate different rules not only from one company to the next, but even within a company our clients benefit from inter-departmental match logic differences. What the team in the IT department considers a match may not necessarily be the same for the Marketing department.

Fortunately for the GZ Sales team… and more importantly for our clients… all this “data quality pyrotechnics” proves very beneficial. Keep playing with those matches, R&D team!



Recently, Global-Z had the unique opportunity to speak with Simon Daniels, Director, Marketing Operations Consulting at Percassity Marketing Data Solutions. Simon is a career-long specialist in marketing data strategy and marketing operations with experience spanning a range of sectors across Europe, North America and the Asia Pacific regions.

We hope you enjoy our interview with Simon.


Global-Z- Can “Big Data” ever be too big to handle?

Simon- In my more cynical moments, I sometimes describe big data as that amount of information that is just too much to handle conveniently, meaning almost anything is “big” if you want it to be! In reality though, the technology in terms of data storage and processing available today can essentially handle any conceivable quantity of data, albeit at a price. Big data is about more than just volume though, also encompassing variety and velocity (the so-called “Three V’s of Big Data”). So, even large amounts of data are not necessarily actually “big”. The limitations actually lie in the ability to do something useful with all this data and achieving clarity over its intended use. The temptation to collect data for the sake of it should be avoided and with it the risk of it ending up being too big to handle.

Global-Z- To move into this world of big data, what advice would you recommend to a company that feels overwhelmed by all the obstacles they face?

Simon- Well, you’ve hit the nail on the head with reference to becoming overwhelmed. So the first move is to take a step back and define the objectives for working with big data. What are the questions to be asked, where will the data come from and what will be the business impact? Then, start small, perhaps with standard tools that are entirely capable of managing very large data volumes and might even already be in use in an organization. Remember the three V’s and consider whether big data is really being dealt with at all. Once a true big data initiative has been identified though, ensure there is senior buy-in and that IT are fully engaged – true big data can’t be handled without substantial technology expertise.

[My recent BrightTalk webinar Big Data and Marketing: Small steps to get started might be of interest]

Global-Z – Consolidating data in a single view can be very complicated when you are collecting global data from multiple countries/cultures. What kinds of challenges does a marketer face when international data is involved?

Simon- One of the greatest challenges when working with international data is simply lack of familiarity. Recognizing issues such as missing address elements, incorrect formatting and invalid entries is considerably more challenging than working on data from familiar geographies, where such issues are immediately obvious. Involving local colleagues to review potential issues and advise on idiosyncrasies – ensuring reasonable time is allowed – is a good approach. At a technical level, non-Latin character sets (Kanji, Arabic, etc.) and diacritical marks (accents, umlauts, etc.) can pose difficulties and introduce corruption. Parsing files with Regular Expression tools can identify such issues, especially in larger data sets. At a process level, it can be challenging to manage data from multiple international sources as part of a consolidation initiative. It’s a good idea to track source and location separately – data supplied from the Munich office might not necessarily all be German!

Global-Z- New data quality procedures can become disruptive to normal business processes and this often can cause friction between people who have a difficult time adjusting to the new rules. What advice would you give to a company that faces these challenges?

 Simon- The overriding question to keep in mind is “What’s in it for me?”. When everyone in the organization can clearly see the benefit to them of observing data management policies and processes, they will be far more willing to adopt them. Also, try and make adherence to policy business as usual; for instance, where possible, build workflow for capturing new contact details in the CRM system that searches for possible existing instances of the contact being added as part of the entry process. This way, best practice duplicate avoidance can be combined with routine activities.

 Global-Z- What other resources about data quality for marketers would you suggest to our readers?

 Simon- Well, it goes without saying that a quick chat with the guys at Global-Z on matters surrounding marketing data quality is always a good place to start! I often turn to the excellent resources published by international data guru Graham Rhind, especially his Global Sourcebook for International Data. And for all things data quality related, take a look at Data Quality Pro , with extensive information, links and guidance on a range of data quality issues.

Simon Daniels can be reached at solutions [at] percassity [dot] com. You also can follow him on Twitter in his guise of Marketing Insight Guy for regular updates on marketing data and technology.