The Three Types of Big Data That Matter for CMOs

C-level executives lack a clear typology of the digital data that can help marketing strategists unlock value.

With a few exceptions, the bulk of brands to date have mostly leveraged big data for short-term purposes. For instance, companies have learnt how to manage their online reputation by creating social media command centres that can detect and react to consumer chatter in real time. They’ve also learnt to track the recent online behaviour of customers, which has helped them run more targeted advertisements. But this makes C-level executives at best very effective bill posters (when they manage to attract their customers’ attention), at worst spammers (when their messages are misplaced or even worse, irritate customers).

This is due in part to the hype around big data, a less than adequate moniker for what’s just the acceleration of data collection and processing capabilities as a result of digital connectedness. Because big data is multi-formed, the initial approach of business thinkers and commentators was to break it into volume, variety and velocity.

Beyond these descriptive features, C-level executives lack a clear typology of the digital data that marketing strategists can leverage to produce novel and important competitive insights. This leaves them with steep challenges in how to think about these data and act on them. The 3S typology

What kinds of big data can best unlock value?In practice, we observe three broad types of big data that really matter in helping CMOs get a deeper understanding of their customers and competitive ecosystems: Social, Search and Site (Figure 1).

Figure 1: the 3S typology 1. Social footprints The first type of big data comprises consumers’ and companies’ footprints on social media and other public platforms, such as Twitter, Facebook, company websites, media or blogs. Massive by the sheer amount of content produced daily – for instance, one hour of video is uploaded every second on YouTube alone –  this body of content is the visible part of the iceberg: what people say and share in public or semi-public contexts. It contains very rich information, from public interest in a brand (reflected in the number of likes or comments) to consumers’ perceptions of a brand (expressed through emoticons or even competitive information). Practically speaking, these data can be easily collected via social media analytics solutions, such as those offered by Digimind, NetBase or BrandWatch, and are often shared within brand teams as dashboards. Social footprints reveal “public sentiment” around brands. While important to know, such visible content doesn’t always reflect actual behaviour. For instance, research shows that some product categories, e.g. cosmetics, yield a disproportionally high amount of online chatter, compared to other categories. Further, a recent study by Tsquared Insights for a leading luxury company revealed that while 61 percent of their social media content concerned their highly-priced line, the majority of online searches (68 percent) was about their entry-price collection. 2. Search footprints The second type of big data, even more massive, comes from search behaviour.