What does social location data reveal about regional culture?

Every marketer needs to know where their audiences are, how they behave, and how to tailor their campaigns to suit consumers’ regional preferences. Greg Lee, Head of Agency at social media monitoring company, Brandwatch, explains how social location data can help.

All brands can use social media to reach audiences across the world. But social is only powerful if you reach the right audiences with the right messages. That’s where you’ll find maximum social ROI.

Location data gives brands a powerful foundation for identifying these audiences. But while many forward-thinking companies have already started using this kind of information, far fewer are clear on how to get the best value from it.

Used correctly, social location data can help brands deliver location-based advertising, differentiate between markets, spot popular areas, and determine where their brand’s presence is strongest geographically. Tying that data in with cultural markers helps marketers predict how their audiences will respond.

Determining location

We can use multiple data points to determine social location by country, state, region and even below city level. These include:


This is information provided by the user, often from GPS-enabled mobile devices. This location information is very precise and is currently the best way of defining user location. It allows us to pinpoint users down to street-level.

Profile location

If someone doesn’t have location enabled on their device, we can check their profile location. This relies heavily on the amount of information a user provides. For instance, a person may include a city, country or both on his Twitter user profile.

Time zone

Not all social media posts are tagged with geo-coordinates, and not all users provide their location information.  In these cases, time zones can prove very helpful in determining the country or sometimes the region or the city where the message was posted.

Top-level domains

If we don’t know which time zone a user is in, or if they haven’t provided any information themselves, we can refer to the country of the site’s top-level domain. For instance, a ‘.fr’ website is likely to be in France.


Finally, where we cannot verify the country of a site from the top-level domain (for example, .com sites can be United States or United Kingdom), we can use the Geo-IP of the website host. This uses the location of the host server of the site.

What location reveals about audiences

Once we’ve determined where our audiences are, we can begin to understand how and why these consumers behave as they do.

We know that location data helps marketers:

  • Measure market share worldwide
  • Understand the success of a campaign in different regions
  • Pinpoint customer service issues relating to a particular brick and mortar location • Refine their targeted advertising and location-based marketing
  • Track location-based events in real-time
  • Discover regional trends

At Brandwatch, we use the clusters identified by Hofstede’s cultural research to identify common behaviour across groups of countries. These six clusters are defined as: Contest; Network; Family; Pyramid; Solar System and Machine.

The chart below identifies the countries that belong to these clusters and the typical characteristics they exhibit: We can see how much these different clusters behave online by looking at how customers talk about the features and characteristics of consumer technology.

Country Clusters

The data here covers English language mentions of specific brands (globally recognised) and types of technology (e.g. smartphones, smart TVs and more). In this analysis, we’ve used percentages rather than raw volume to try and counter the natural language bias (for example, the Contest group includes more English speaking countries and will, therefore, have a much higher volume of activity).

How culture affects online consumer tech conversation

As the graph shows, the Solar System and Network countries typically talk about innovation more than any other clusters. This fits the group’s suggested cultural characteristics of being open to change and innovation. They are happy to consider new tech and ideas.

How culture affects consumer tech features mentioned

In this graph, we can see that countries in the Family group deliver a significantly higher number of mentions relating to ‘durability’. With further research, we might find this correlates with national GDP, disposable incomes or other relevant economic factors.

Using the same data set, we can also see how users in each group interact with brands. Monitoring the levels of which each group @mentions brands, replies to owned Twitter feeds, and retweets posts, we get a good indication of engagement potential of each cluster. It is interesting to see different groups leading in different types of interaction.

Graph 03: How culture affects interactions

We can see that:

  • Users from countries in the Pyramid group retweet brand posts most
  • Solar System countries are more likely to engage in direct contact through @mentions (which possibly reflects this group’s more individualistic mentality — they prefer engaging 1-on-1)
  • Network countries display a much higher rate of replies and conversation (which possibly reflects this group’s desire to discuss and make decisions by consensus)

Putting data into action

Even when used in isolation, it’s clear how location-based social data can help inform marketing campaigns targeting these groups. But when combined with other cultural research, sales data and product development insights, it becomes even more valuable.

Highly-accurate location data lets digital marketers answer questions like: where are specific campaign types best received? What content resonates in specific areas? Does social chatter actually correlate to sales in nearby stores? That can be vital information when planning future campaigns.

Location insights add value to both brands and consumers. They provide a new layer of intelligence to brands’ campaign strategies, and give those engaging with these campaigns the chance to say “that’s me, I was there”.

Image AI: How brands can benefit from neural networks
Being funny is a serious career move