Using Social Analytics for Insight
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How can you discover insights within social media data? Why apply analytics at all? What can you expect to gain from digging into social media? This presentation from Social Data Week 2013 (SDWK13) at Tableau Software HQ goes into the benefits of working with social media data, and how you can go about it.
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Using Social Analytics for Insight
- 1. ©2013 Tableau Software Inc. All rights reserved.
- 2. ©2013 Tableau Software Inc. All rights reserved.
- 3. ©2013 Tableau Software Inc. All rights reserved. How does it help me? source: www.netbase.com/social-media/what-can-social-media-be-used-for
- 4. ©2013 Tableau Software Inc. All rights reserved. How does it help me? Surveys • Low participation • Guarded responses • Limited audience • Set questions • Costs and $ • Delayed • No response Social Media • High volume • Candid responses • Varied audience • Open-ended feedback • Low $ or free • Instantaneous • Respond, Engage
- 5. ©2013 Tableau Software Inc. All rights reserved. How can we get it? Web interface for each service API’s Aggregator s
- 6. ©2013 Tableau Software Inc. All rights reserved. How can we get it?
- 7. ©2013 Tableau Software Inc. All rights reserved. How can we get it? 1. Capture 2. Filter & Organize 3. Infer Context
- 8. ©2013 Tableau Software Inc. All rights reserved. How can we get it?
- 9. ©2013 Tableau Software Inc. All rights reserved. Let’s get started!
- 10. ©2013 Tableau Software Inc. All rights reserved. Questions?
Notes de l'éditeur
- ---here’s a small sampling of how other are doing just that – using social media to drive business value through:Lead generationProduct innovationHot issue identificationNew product developmentCompetitive intelligenceCrisis managementand what I think are the 2 most universal: Community participationAnd measuring Consumers satisfaction
- Now you may say there are other ways to measure consumer satisfaction – we’re all quite familiar with surveys – we’ve all received them in the past, but if you’re like me you’ve probably rarely filled one outThis means-their response rate is typically low, while social media has extremely high volumes of voluntary commentsYou’ll also find that survey results typically have a negative slant - that’s because customers who have a strong negative opinion are the most likely to take the time to respond to a surveyYou can’t reach everyone with a survey – you typically sample a subgroup of your customers and their one disconnected experience – with social media you’ll often see conversations between customers – some that will even defend your brand for youThe longer your surveys the less responses you’ll typically see – so you have to keep things very short and focusedThere’s also the cost and logistics of setting up surveys and then crunching the results – which still only procudessurvey results that are aggregated, anonymous and typically delayed by several weeksThis all means you can sample but you can’t respond to customers that had negative experiences - something that Social Media let’s you do quickly and easily … and in fact more and more customers expect you to do as part of customer serviceSo now that you see the value of social media and the advantages it can give you business - the natural next questions is ---- How can you get it…
- How can you get it…As with everything – you can do things the hard way – manually combing through each service; checking facebook posts, tweet mentions, google+ entries, yelp scores – or Programming an API to do the harvesting part for you, but you’ll need to know Python or PHP or Ruby and then determine how to automate the process – but then there’s always the chance that the API’s you’re using get changed or deprecated – this is what happened with Twitter earlier this yearThe key is that both of these options require you to interface with each social media service or API separately – keeping separate passwords and logins is just part of the hassleNow you can address a few of these issues by using 3. aggregators that combine media feeds from several services into a single view – one such service we use at Tableau is Tagboard – you can see it in action at our social media command centerBut … if you have lots of social media volume and you want to analyze and customize these feeds yet still avoid having to write and maintain automated applications - you’ll need to get the data directly – in the case of Twitter this is known as the
- Firehose!If you’re thirsty for data there’s no better way to satiate your thirst– but connecting to this much volume creates some of its own challengesThese include -----
- Capturing all of that data – the daily bandwidth is staggering – Twitter recieves ½ billion tweets every day In that same time facebook processes 500 TB of dataAnd that’s just the raw data – no analytics, no sentiment, no salience, no KloutAfter you get the data you’ll need to:2. filter and organize it– pick out what is important, select it and save it for later – but with these staggering volumes this can be costly and slowNext- if you want to start analyzing the data and generating business intelligence– you’ll need to query and operate on all of that data, meanwhile preserving the metadata your analysis createsThe more you try to do the more costly, laborious and slow it becomes – that’s where DataSift comes in – it’s an official Twitter firehose provider and a Tableau Partner
- Now let’s drill down a bit deeper and see the preferred way of getting your social media data into Tableau – first you’ll need to create your DataSift queries – either visually with the Visual Query builder or programmatically with the CSDL code editor. Once you create the “Stream” in Datasift you can choose a destination for your “recording”, in this case sending your data to Google Big Query will allow you to leverage the storage and processing power of the cloud Then you can connect and run live queries against that data directly from Tableau, sharing your dashboards on Tableau Online … a true cloud to cloud social media analytics solution.
- So let’s see how this is done –