About Tim Barker
Tim Barker is the Chief Product Officer of DataSift, a big-data platform for social data. DataSift is cloud platform that that aggregates, enriches and filters the world’s social data - enables enterprises, entrepreneurs and agencies to find the relevant conversations and content from billions of Tweets, posts and clicks - then deliver that as structured, ready-to-analyse data into the business. Using DataSift, companies are able to ask bigger questions about their market, industry and customers.
On Twitter: @timbarker On LinkedIn: http://linkd.in/12qOhJ6
What is "Big Data' and why is it such a buzzword these days?
Fuelled by social networks, mobile apps and internet-enabled devices, the volume and variety of data we create as individuals has exploded; 90% of the data in the world today was generated in the last 2 years. For companies, this represents a huge challenge and huge opportunity – how to organize and analyse vast volumes of different types of data to identify trends and insights that can help create better products, improve the customer experience, and win more business.
Although Big Data is a new term, companies like Facebook, Google and Amazon have used Big Data for years to power their analytics and user-experience – every product recommendation, friend suggestion and ad-placement is powered by big data. What’s happening now is that technologies like Hadoop have made this kind of analysis available and affordable to the wider market. Companies can now analyse diverse types of data that were unmanageable and unthinkable in the past.
For CMOs, the potential for Big Data is huge and transformational. As CMO’s evolve to become more data-oriented in their decisions, companies are competing on analytics. Every social customer interaction creates a breadcrumb of data that, in volume, enable businesses to better understand their customers, tailor the customer experience, and measure and effectiveness of their marketing efforts in high-definition.
What kind of insights can brands generate from applying the principles of Big Data to social media?
Once companies start socially listening, they start to ask bigger questions about their brand, industry, products and customers. For example, brands can build company-specific models to identify their influencers or most-valuable advocates to help them tune their influencer-relations programs. But what’s most exciting is the fast growing ecosystem of companies that are using social, big data to answer very specific, big questions – companies like Metavana (which measures Social Net Promoter Score), LocalResponse (which targets ads based on social-signals) and GoodData (which analyses trends across social data plus click and business data) are flourishing to help CMOs get more out of social.
With seemingly limitless data, the trick seems to be in the ability to come up with the right questions. What kinds of questions should companies be asking of the ocean of social data?
That’s exactly where companies need to start – with the right questions. With more than 50% of the entire population of the UK on social networks, the opportunity is there to listen to the interests, intent and feedback from customers at an unprecedented scale. What would you do if you had all the data you wished for? Here’s a few examples of some of the areas that are top of mind for our customers at the moment:
- - “How do I maximize the impact of my product launch?” : What can you learn with hindsight from competitive product launches using social data? Which influencers and publications drove not just the most buzz, but the most traffic to the news? Who should I pre-brief? Who should I avoid? Are people socially interested in my product category? Who are they and what web-sites do they love most so I can potentially advertise on them?
- - “Who are my social advocates and what impact to they have on my business?” : Who are my most social passionate ambassadors and VIP customers? How has their opinion changed over time? Have they referred a customer to me? Who are the advocates for my top competitors? What could I do to win their business?
- - “How do I design and measure my Content Marketing strategy?”: If I look at my current followers, what kind of content are they interested in and sharing? What’s the social click-through rates of similar content? What other content could I curate that would be interesting to my prospects? What topics should I write more/less about?
How does it work in practice?
Every second, our platform aggregates around 12,000 items of social data from Twitter, Facebook, Bitly and millions of blogs and news sites. Every one of these items of data is evaluated and exploded into other data, for example if a Tweet contains a link, we’ll follow the link and extract details from the website. All in, we add about 100 items of data in around 200 milliseconds during this process! With this wealth of detail, we can identify and extract the key social data from our Big Data platform that matches what a business is tracking, then deliver that ready for analysis into an application or business intelligence tool. The nice thing about this approach is that it leverages the tools that marketing teams are familiar with, and enables them to integrate social with other data they have like web traffic or sales data.
And what are the key metrics should marketers focus on?
While fans and followers are great to get, they aren’t the metrics that the business manages to. The goal should be to integrate social into your existing marketing metrics. For example, companies are increasingly investing in content marketing as a key initiative, with the goal of educating and influencing customers as the top of the funnel. The social metric for each piece of content you create should include metrics on not just the #shares and potential audience you reached, but the social click-through rate, the target segment you reached, and the conversion rate for other offers/content they took up.
Social data is also making transparent (and measurable) things that may have been invisible before. For example, PR used to be measured by “number of clippings’. Now it can be measured by the number of people that clicked-through and read the news, and the social response to the news. Likewise, word-of-mouth marketing was impossible to measure. On social networks, markets can now measure this directly as a recommendation or customer referral.
Can the insights generated from this kind of analysis be used beyond the marketing department?
Of course. One of my favourite examples is one of our retail customers that is optimising their supply-chain planning by analysing social conversations around a range of topics and correlating it to retail-sales data. Using this approach, they are able to predict demand for their products, and manufacture the right amount to meet demand, all using social signals.
What role does (social) data play for Marketing today? How will it change in the next few years?
We’re entering the second-phase of social maturity in the enterprise. Where stage 1 was about listening to people talking about your company, the next phase is about using social data to better personalize the customer experience and adapt your marketing to the individual customer. A major challenge for marketers has always been to understand the context of the customer they are talking with - to provide the right offer, right place, right time. Social is helping companies and will help customers build a better context.