The marketing technology landscape is vast. Perhaps you’ve seen this dauntingly complex supergraphic on chiefmartec.com. As of last year, there were over 8,000 technology vendors, with 1,258 vendors in the data space alone.
The “island of audience and marketing data technology” in the 2020 Martech landscape (see if you can spot us!)
What this graphic doesn’t show, is what markets these vendors operate in. Typically, it’s only a few.
How many of those 1,258 data companies can help you reach your target audience segments on a global scale? And how is a global marketing strategy different from a local one?
A multinational company faces a unique set of challenges. They need to manage close and intricate relationships with a host of business partners in many markets. The orchestration of audience and customer data is especially complex. When planning a global, data-driven marketing strategy, there are several challenges that multinational companies have to deal with.
Firstly, they need to make sure that the data and solutions that they use are privacy-compliant in all the markets that they operate in. You’re probably aware of GDPR in Europe, but countries like Brazil, Vietnam and Australia are all developing similar data privacy regulations in their own markets. So you need to know your way around the local legislation.
Secondly, you need to have audience data that has a consistently high level of quality across all of those markets. For example, you need to trust that people labelled as “Healthy Food Buyers” are likely to buy healthy food at roughly the same rate regardless of whether they are in New Zealand or Norway. The problem is, it’s difficult to verify the trustworthiness of local data partners without the right expertise.
And thirdly, and most importantly, you need to find right identification methods in each market. This is especially important for matching online data with offline data — a process called onboarding.
For example, global companies like Equifax and Mastercard have a wealth of transactional information in their databases. This tells you what consumers are buying. But how do you match that information with behavioral data collected about consumers online? The kind of data that predicts intent and likelihood of taking certain actions in the future. If you can match online and offline data about specific consumers, you have a much more powerful data set.
In the US market, many companies have got good at this. But other countries still have a way to go. To understand why, we need to drill down a bit into the technical details.
In the US, almost every app and website wants your email address before you can do anything useful. And people are generally OK with using the same email address across multiple platforms. Data companies then use an algorithm to convert each email address into a hash — a hexadecimal number of a specific length (for example 40 characters long). And voila, you have a unique identifier for a consumer that you can use to combine data from multiple sources such as dating portals (online) and financial services providers (offline). Which is fine if you operate only in the US.
But it doesn’t work like that in many other countries. There just isn’t the critical mass of reliable hashed email addresses to do data onboarding with on a similar scale with the same degree of quality. This is a real problem many brands who want to onboard data globally are facing. How can you collect enough personally identifiable data in a privacy compliant and scalable fashion? It’s hard enough just to find enough data providers in a fragmented market and to get enough identifiers together.
So anyone who wants to call themselves a “global” data provider needs to solve these three problems in all markets: transparency/privacy, quality and scale. And we’ve spent years building up the right technology and partnerships to do just that.
For example, to solve the problem of scale with personally identifiable data, we don’t rely exclusively on hashed email addresses for matching and onboarding. We have a unique toolbox of methods that can take multiple attributes into account and we select the most effective method for each local market — often with the help of local data matching partners.
And in the case of transparency and quality, we’ve spent the last few years adapting our technology to the requirements of GDPR. But we’ve also made it flexible enough to meet the needs of any other privacy regulations that might come along. Concretely, this means being able log and report on any data collection details for any auditor who asks for them. We have to make sure that we can do that not only in the UK and Germany and the US, but also in Brazil, Vietnam, Malaysia or Australia. It’s a lot of work, but it’s well worth doing because it gives our clients and the industry the visibility and assurance that everything has been collected in the right way.
So you see why it’s still very difficult for major brands to roll out a global data strategy. It’s complicated and it’s resource intensive. There are too many partners and technology vendors to deal with. But there’s no need for global brands to manage these relationships directly. We’re one of the few providers that have built up a global network to solve those scalability problems, so that brands can have one trusted data partner no matter how many markets they operate in.
That’s why we call ourselves a “global data technology” provider. It’s not just a fuzzy slogan — we really mean it. We’ve helped global brands onboard and activate their data in up to 35 international markets. If you want to know more about building a global, data-driven marketing strategy, feel free to pick our brains.
You can start by getting in touch with one of our onboarding specialists who will be happy to answer your questions.
