At DataSift we are obsessed with making it easier for companies to access Social data, analyze it, and get value from it. This week we are proud to announce the launch of a new way to access/use the Social Data produced by the DataSift platform. Starting today, DataSift customers will have access to new Record and Export features, that allow even non-technical users to extract their social media data direct through our website into easy to use files like Microsoft Excel.
Creating customized Social Data streams with DataSift is already easy.
Thousands of DataSift customers are already using the DataSift platform to create personalized streams. DataSift created a special filter creation language called CSDL which enables users without a technical background to set up complex filters in a matter of minutes. You can immediately build a stream using CSDL, define the time and date you want to start and stop the recording, then extract it, the whole data set or just the specific time segment or data types that interest you.
Rapid access to Twitter data sets for your research and social media monitoring.
It takes seconds to set up an account with DataSift and there’s no need to invest in a specific application or dashboard for consuming the data. This feature lets anyone start using social media intelligence without any prior investment, training or time delay.
How to turn your data stream into an excel file in 3 easy steps:
1) Set the time that you want the recording to start and end.
2) Once the recording has started you can see the volume of data that you’ve gathered through your stream.
3) When you’ve gathered all the data that you want for this particular recording, then extract it by selecting the format that you would like to receive it in and wait for it to be delivered.
It’s Free
Try out these new features for free with $10 free credit that DataSift gives to every new user and start using social data to inform your strategic decision making.
Get Started Now with a Free Trial.
Find more detailed information about recording and exporting a stream.
Haters Are Going To Hate…But They Aren’t Always Right
Here at DataSift we are big fans of YouTube and really love the new UI they launched a few weeks ago. At the same time that our team was admiring the sleek new site design that You Tube had just launched, we noticed YouTube was taking a hammering from online commentators and press. It seemed like EVERYONE hated the new UI! Were the “haters” right that the UI was terrible, or was a minority of “haters” not representative of the YouTube user base? We turned to Twitter to find out. The results will surprise you.
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Our Inital Read: Lots of Complaints!
Our first step was to take a look at the The YouTube blog. We were really surprised at how the boards seemed to be full of complaints and calls for a return to the original layout that users were familiar with. All the while we were left thinking ‘well, actually we kinda like it’.
We thought the complainers might be wrong, and set out to find out what the truth was.
The main rollout of the new YouTube UI went live on the 2nd of December. We used the DataSift platform to quickly set up some streams to capture the real-time public reaction of You Tube users to the new design. (Our platform is so easy to use that someone from our Marketing team actually did most of the work.) The rule we set up for this stream captured any tweet that contained the word “YouTube” AND a word relating to the redesign, such as layout, style, interface, etc. We also added sentiment tagging to see how people generally felt about the redesign. We ran a filter for about 40 hours, and collected over 35,000 tweets from all over the world commenting about the YouTube UI update.
We found the “Haters” were wrong–a lot of people actually liked the design.
While one might have gotten the strong impression from online blogs of widespread public disappointment with the changes, a quick analysis of the tweets that the stream gathered over a 40 hour period told a different story. We found that there was actually a greater expression of positive rather than negative sentiment expressed by Twitter users in reference to the changes. 32.25% of the Tweets captured by our stream expressed positive sentiment, 57.26% of the tweets were neutral and only 29.30% expressed any negative sentiment. 29.30% is still high—but we wondered if there will always be a percentage of users who hate any new change to a UI.
The big surprise – most of the tweeting was being done by influential people!
Although the average Klout score of Twitter users is close to 10, we were fascinated to find out that 53.5% of the individuals tweeting within this stream had a Klout score of 26 or higher. This meant that not only was there a strong expression of positive sentiment but most of the tweets featured in the stream were also being written by highly influential Twitter users. It seems to us that YouTube must definitely be doing something really well if so many highly influential Twitter users were tweeting about the new UI.
What did we learn?
1. Twitter is a great place to get a complete picture of what users think about a new product.
If as YouTube say on their blog, they ‘rely on your feedback to figure out when we’ve gotten it right and when it needs further tweaks’, it’s important that it’s not just the views of a passionate minority of extreme YouTube lovers posting on the company blog, rather than the opinions of the greater YouTube user base, that drive forward future site developments and strategy.
2. The US is important, but so is the UK and Brazil!
The 37,385 tweets that DataSift collected deliver an objective image of the spread of public reaction immediately after launch. A broad data set such as this gives a reliable aggregate view of how people are responding online. This data can be be consumed though our API in real time and funneled through any application (CRM solution, dashboard etc.) or simply recorded and extracted as an excel file. It can also be analyzed by geographical region, gender, degrees of positive and negative sentiment and social influence level, url content as well as the trends within those streams. For instance one insight that we gleamed was that the tweets within this stream came mostly from the US but also the UK, and perhaps surprisingly Brazil.
3. DataSift is a great platform for mining Twitter content.
The DataSift platform is so easy to use were able to set up trackers in just a few minutes that were able to provide very insightful information. With all the noise that comes with the real-time web, extracting the information that will drive productive changes in your company’s communication with it’s customer base requires heavy duty technology. DataSift was architected for enterprises to manage the unstructured data of real-time social media with finesse so they get just the information they need to confidently derive effective strategy from the data.
4. For the daily price of a Starbucks Latte, YouTube could get really interesting insights into their users.
See the stream running live here. This stream costs $4.80 per day to run (not including licensing costs at 0.10 cents for 1000 tweets). Have a product launch coming soon? Set up your own stream on DataSift in less than a minute.
“Those that fail to learn from history, are doomed to repeat it”
- Winston Churchill
Today DataSift is excited to announce the launch of signs-ups for alpha access to Twitter Historical data. You can sign-up and reserve a space on our alpha list and be one of the first to test drive this new functionality when it is available in January. The Alpha Program will give you full access to 60 days of the entire Twitter feed. When the Twitter Historical program goes into a full commercial launch next year, even more historical data will be available.
“We have been flooded with customer interest from lots of different industries in Twitter data. Twitter is not only an incredible source of real time information, it also provides a very rich history of trends, customer interactions, consumer opinions, and other information. We want to make that information available to customers,” said Rob Bailey, CEO of DataSift.
DataSift will not only provide access to historical data, but also offer customers the most powerful platform for deriving value from that data. They can can now apply all the DataSift filtering tools that they currently use to manage real-time content, to extract and analyse streams from our archive of the entire Twitter output. In short, DataSift now makes accessing historic Twitter data rapid and easy.
The applications of historical Twitter data are immense. For example, if a brand manager missed a customer review or thought of a campaign that needs evidence to support it, they can now gain access to the data that they need retrospectively in minutes not weeks and use DataSift’s powerful tools for getting the information they need quickly and cost effectively. This includes filtering the historical data on a given topic by sentiment levels, links, demographics and social influence, as measured by Twitter user Klout scores.
DataSift’s Historic data access provides a huge leap forward for customers. Until now customers wanting historical acccess were limited to very simple keyword searches or other limited filtering methods. The overwhelming feedback from customers is that these search methods were not sufficient.
“We kept hearing from customers how valuable historical Twitter data was, so we wanted to offer that to them,” said Nick Halstead, founder and CTO.
With 250+ million tweets being published every day, extracting meaningful data sets from this immense archive is even more challenging technologically than doing so for real-time data. DataSift’s platform architecture simplifies the historical data processing using our CSDL language to make Big Data simple. Based upon the Cloudera Hadoop stack our solution gives immense scalability to our customers to be able to process data on demand.
UPDATE: coverage from Techcrunch
Start tracking and analyzing Twitter data for your organization in less than 10 minutes!
DataSift, the most sophisticated platform for managing and filtering social data, is live today at 2pm GMT. We invite you to explore this revolutionary new platform that has been designed to make tracking and analyzing Social Media data easy. DataSift offers access to the complete range of Twitter content, but you only pay for the tweets that are actually useful to you that are found using filters that are fully customizable. Getting started is easy-you can start setting up filters very quickly without having any technical knowledge.
We’d like to thank you for supporting DataSift during testing and through the development of our platform during the past few months. Our Beta was a lot more successful than we expected and we are excited for our full commercial release.
During the coming years the engine of growth for DataSift will be the US market. With this in mind, today we are proud to announce the elevation of Rob Bailey as the new CEO of DataSift in preparation for our full US launch later this week. Rob has already been working with DataSift for the past few months as the GM of the US, and in the first few months has already closed revenue-generating customer deals and expanded our relationship with partners like Twitter, Klout and Endeca. Rob has spent more than a decade building experience building organizations in tech, including time at Yahoo! in the Mobile and Broadband group, and at eScene (Acquired by Inktomi) and SimpleGeo (acquired by Urban Airship). Rob has an extensive network of relationships throughout the tech world which will help accelerate DataSift’s growth in the US. DataSift plans to begin hiring aggressively in the US and will be launching an office in San Francisco. Rob also has proven experience working with developers, while at SimpleGeo and as an advisor to numerous start-ups, something that will be critical for DataSift’s growth.
Founder Nick Halstead will assume the Chief Technology Officer which you can read more about on his personal blog. Nick will continue to drive the technology and product vision for the company.
DataSift will be integrating with TrendSpottr to provide customers with the ability to deride early and predictive insights from their real-time curated data streams
TrendSpottr is a real-time data analytics and business intelligence service that identifies and predicts trends from Twitter, Facebook and other real-time data streams. It works by improving the signal-to-noise ratio by identifying the most timely, relevant and trending information from a firehose of streaming content.
Through DataSift, TrendSpottr users will receive trending issues as real-time enriched data with added augmentations (including social influence scoring and geo-location amongst others) that can be analyzed for deep demographic and commercial insight.
“DataSift offers one of the most robust and advanced data curation platforms for social media data sources. By integrating with the DataSift platform, TrendSpottr will be offering DataSift customers access to relevant real-time trends from their curated data streams. This real-time intelligence will provide DataSift customers with early and predictive insights about major trending events, social behaviors, customer preferences and impending crises.” – Mark Zohar, Founder and CEO of TrendSpottr
“DataSift is pleased to integrate TrendSpottr into the DataSift platform to offer our customers real-time predictive coverage of trending issues on 100 percent Twitter feed and other sources…..DataSift and TrendSpottr’s partnership will give trend hunters deep insight into the issues driving specific trends.”
- Nick Halstead, Founder and CEO of DataSift
The full Press Release can be found here.
Real-time Challenge
The value of big data such as social media decays rapidly with time. Companies that are able to draw insights from their data and act fast and correctly in response, can realize valuable strategic advantages over their competitors.
“Learning that a web campaign from last week created negative sentiment in viewers is useful, but being able to alter corporate communication in real-time is what makes the difference. And this is exactly what the partnership between DataSift and HStreaming allows. Companies can realize the full value of social media by overlaying the data with other data sources, such as sales data, marketing data or web logs, to look in real-time for insights in the form of patterns or outliers. Once a pattern is identified, companies can programmatically react, such as issuing email notifications, alerts, and requests to web-based services.” explains Jana Uhlig, CEO of HStreaming.
DataSift excels at giving easy and comprehensive access to social media with data enrichment, such as sentiment analysis, Klout scoring, and language identifiers. HStreaming enables the running of advanced analytics in real-time to create live dashboards, identify and recognize patterns within one data stream or across multiple data streams, and trigger action based on predefined rules or heuristics. HStreaming can handle even the most challenging data volumes and complex analytical problems leveraging the scalability of Hadoop and MapReduce.
The partnership between DataSift and HStreaming allows users to:
Draw insights quickly
HStreaming query language allows writing advanced analytics queries fast and efficiently against any structured or unstructured data feeds.
Display real time dashboards
Rich built-in web-based tools enable users to quickly visualize complex data to get fast insights through real time dashboards.
Identify and recognize patterns
Leverage HStreaming’s scalable analytics platform to look over one stream or combine social media streams with other data such as sales data, marketing data, or web logs to identify and recognize interesting patterns.
Trigger actions
Built-in connectors enable analytics jobs to automatically trigger actions such as email notifications, alerts, and send requests to web-based services.
The full Press Release can be found here.
DataSift, a provider of aggregated real-time social data feeds, has entered into a partnership with Endeca that will allow organizations to react to the “big data firehose” of social data. Organizations are demanding a way to understand how their customers react to them and their competitors in social media. To do that, they must aggregate external content in real-time, and then search and analyze it in relation to their own internal content.
Endeca Latitude gives business analysts an easy-to-use interface to discover, analyze, and visualize that content in relation to the structured, unstructured, and semi-structured sources found inside the enterprise; while giving IT a way to rapidly add new content and visualizations. These combined technologies give businesses the most powerful and cost-effective platform to mine the business value in the torrent of new social data. Through research with customers and prospects who had pursued the use of first generation generic social media solutions, it was found that there was a lack of integration available between internal and external business’ critical data, therefore restricting their view of the customer.
Legacy relational technologies have failed to manage Big Data like social media, which is why new approaches are needed. Relational technologies require businesses to model data in advance of analyzing it, but the variety, velocity, and volatility of social media precludes this. Endeca Latitude is ideally suited to consume this type of data, without going through the painful and expensive process of creating and modeling complex relational models, that will require constant change.
The full Press Release can be found here.
We are very pleased to announced today in partnership with Datameer a new product DataSift Insights. DataSift is extremely powerful at extracting content and augmenting that content in real-time, what it cannot do is perform any kind of analysis on that data. Datameer has a platform that brings the power of Hadoop to every user through the use of a spreadsheet like interface which then in turn generates a pipeline of map-reduce tasks.
We have spent the last year working on building out a significant Hadoop storage solution in which we can store customers streams and also record many of our real-time partner feeds including the whole Twitter Firehose. We currently have over 400Tb of storage available for our customers to record data and for us to store the Twitter Firehose. So far that Hadoop cluster has purely been for storage. Now via the power of Datameer we can perform massive computational tasks on those datasets for our customers.
What inspired me the most about the Datameer platform was how the editor works. Given that a typical dataset for DataSift can be in the 100′s of millions of rows, it would of course be unwieldy to work on that volume of data. What Datameer have revolutionised is that they take a small but statistically relevant part of that data and allow you via a spreadsheet style interface to manipulate the data and simulate the results completely in real-time. The spreadsheet supports all the usual functionality like grouping, sorting, filtering, inner joins, outer joins. In total they have over 180 different functions.
Lastly Datameer also has a suite of visualisations built into a dashboard that with a couple of clicks allows you to take results of the map-reduce tasks and quickly visualise them into a whole host of charts.
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