Big Data is Great, But Little Data is Better
When you’re a marketer who spends fourteen hours a day on the internet, you run across the words ‘big data’ an awful lot. A Google search on the term generates over 339 million results. To put that into context, a Google search for ‘Justin Bieber’ produces only 62 million results. That’s a 447% differential, which is amazing considering The Biebs can’t go more than 24 hours without getting involved in some kind of immature escapade. So, Big Data is more pervasive than the shirtless wunderkind and it leaves me scratching my head, because in my experience ‘little data’ is better than big. I think we’ve all forgotten the old adage, ‘less is more.’
We’ve all become accustomed to thinking in bigger is better terms. For years, our cable/satellite providers have wooed us with promises of even more channels, and we’ve bought in. The reality is that most of us watch less than 10% of the channels we have access to because we’ve learned to filter out the noise that is not meaningful to us and concentrate on the content that resonates. While we all have access to the massive data set of ‘big TV’ – we get the most value out of ‘little TV’ – the refined stream of programming that provides what we need.
Big Data is the driving force behind social listening and intelligence – but it’s helpful to get beyond the ‘firehose’ mentality. More is not necessarily more when it comes to the massive amount of content generated every second on the internet – particularly around trending keywords and topics. Data ends up being something businesses have – because someone told them it was necessary, but the reality is that data is not being leveraged. It’s too big, too unwieldy, and too intimidating. Here’s where filters come into play.
Over the past few months, the product team here at Synthesio has added a handful of powerful, new filters to our arsenal: Locations, Post Types, and Keywords. Each succeeds at slicing through massive amounts of social data to surface insightful, targeted, and actionable insights about the audiences creating this never-ending stream of mentions, comments, and interactions. These filters turn Big Data into Little Data. Here’s how:
- Location Filters allow you to categorize your social audience by country, city, state, or region. When combined with our filters for Age and Gender, Location Filters give insight into the specific demographic sweet-spots for your brand. This information can be leveraged to produce geo-targeted content for specific audiences, based on their history of affinity for the brand.
- Post Type Filters allow you to filter your brand activity into buckets for posts, comments, retweets, and retweets with comments. When combined with our Influence widget, Post Type filters provide brands with a more accurate methodology for identifying the people who are having the greatest proactive impact on a company’s online presence. Granular enriched data focused on audience members who are conversation starters and sparkers provides a company with a true accounting of the people who mean most to their brand.
- Keyword Filters allow you to search for any keyword within a dataset – big or small. This is incredibly helpful for determining the types of vocabulary your audience uses when talking about your brand or product – and provides the added benefit of helping to surface mentions or trends that might get lost within a much larger data pool. The best thing about keyword filters is that they are only limited by your creativity. Want to know how many times people mentioned your brand in conjunction with a trending current event that you hadn’t anticipated when building your dashboard? That’s what Keyword Filters are for.
Don’t get me wrong, I love Big Data – it’s as much a part of my life as my daily muffin and coffee. I just wish that people would start looking beyond the ‘big’. It’s the little data that matters to your brand – and you need to filter to find it.