What is the best movie of all time? Is it Vertigo as voted by critics? Or The Shawshank Redemption which has the highest rating on the IMDb? Or Avatar which took the most at the box office? You probably don’t think that any of those is the right answer (and you’d be right). What makes a great movie is a very personal thing and there isn’t one right answer. We all have our own expectations and requirements when we enter the cinema and what works for us, won’t necessarily work for the person in the seat next to us. The same is true for social data products.
Everyone looking for insights from social data has different requirements dependent on their job role, the industry they work in, the size of their organization and a host of other factors. This is why there are so many varied solutions out there in the marketplace – you just have to look at our Facebook topic data partners to see the variety in approaches and areas of expertise out there. If you have a little knowledge of the aggregated and anonymized nature of Facebook topic data, you might be asking yourself how these companies can come up with such different solutions (to so many different problems) from the same raw materials.
Answering that question was one of our key objectives when we were designing PYLON. At DataSift we are very proud of what we do, but we knew that we would not be able provide the insights that everyone needed right out of the box. We knew that we would rely on our partners to bring their expertise (in data science, in data visualization, in specific industries) into the mix in order to meet the needs of the market. So, with PYLON we let our partners bring their expertise right into the platform.
One way we do this is with VEDO. VEDO allows our partners to apply their intellectual property to Facebook posts and engagements, classifying the content in ways that are specific to the needs of the market segment they serve. This might be expertise in a particular industry, or for a particular use case or in text analytics. Whichever it is, PYLON is designed to let them apply their unique perspective to Facebook topic data and get unique insights for their particular customer segment.
The rich, self-declared demographic data that comes with Facebook topic data provides another opportunity for social data companies to differentiate themselves – baselining. As I mentioned in a previous post, baselining is a way of giving context to data by comparing results to a control data group. DataSift’s partners can use their specialist knowledge to build comparison datasets that represent the industries, markets or business areas they excel in and compare the results of a particular analysis to that baseline to identify the outliers. For example, you might be able to determine which demographic groups were less engaged with a particular campaign than you would expect, allowing you to adjust the campaign to appeal more to that group.
Social analytics firms can also build industry specific PYLON indexes, create an archive of topic data insights for predictive analysis and benefit from complex analysis queries to really dig into the data with their own data science techniques.
PYLON for Facebook Topic Data offers DataSift’s partners huge flexibility to build the products that meet their customer’s needs. I’m confident that somewhere amongst our ecosystem you will find the solution that is right for you. However, if you feel like the only movie showing is Avatar, please do let us know – we’d love to hear your Facebook topic data use cases.