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Podcast industry aims to better track listeners through new analytics tech called RAD
Internet users are already being tracked to death, with ads that follow us around, search histories that are collected and stored, emails that report back to senders when they’ve been read, websites that know where you scrolled and what you clicked and much more. So naturally, the growing podcast industry wanted to find a way to collect more data of its own, too.
Yes, that’s right. Podcasts will now track detailed user behavior, too.
Today, NPR announced RAD, a new, open-sourced podcast analytics technology that was developed in partnership with nearly 30 companies from the podcasting industry. The technology aims to help publishers collect more comprehensive and standardized listening metrics from across platforms.
Specifically, the technology gives publishers — and therefore their advertisers, as well — access to a wide range of listener metrics, including downloads, starts and stops, completed ad or credit listens, partial ad or credit listens, ad or credit skips and content quartiles, the RAD website explains.
However, the technology stops short of offering detailed user profiles, and cannot be used to re-target or track listeners, the site notes. It’s still anonymized, aggregated statistics.
It’s worth pointing out that RAD is not the first time podcasters have been able to track engagement. Major platforms, including Apple’s Podcast Analytics, today offer granular and anonymized data, including listens.
But NPR says that data requires “a great deal of manual analysis” as the stats aren’t standardized nor as complete as they could be. RAD is an attempt to change that, by offering a tracking mechanism everyone can use.
Already, RAD has a lot of support. In addition to being integrated into NPR’s own NPR One app, it has commitments from several others that will introduce the technology into their own products in 2019, including Acast, AdsWizz, ART19, Awesound, Blubrry Podcasting, Panoply, Omny Studio, Podtrac, PRI/PRX, RadioPublic, Triton Digital and WideOrbit.
Other companies that supported RAD and participated in its development include Cadence13, Edison Research, ESPN, Google, iHeartMedia, Libsyn, The New York Times, New York Public Radio and Wondery.
NPR says the NPR One app on Android supports RAD as of now, and its iOS app will do the same in 2019.
“Over the course of the past year, we have been refining these concepts and the technology in collaboration with some of the smartest people in podcasting from around the world,” said Joel Sucherman, vice president, New Platform Partnerships at NPR, in an announcement. “We needed to take painstaking care to prove out our commitment to the privacy of listeners, while providing a standard that the industry could rally around in our collective efforts to continue to evolve the podcasting space,” he said.
To use RAD technology, publishers will mark within their audio files certain points — like quartiles or some time markers, interview spots, sponsorship messages or ads — with RAD tags and indicate an analytics URL. A mobile app is configured to read the RAD tags and then, when listeners hit that spot in the file, that information is sent to the URL in an anonymized format.
The end result is that podcasters know just what parts of the audio file their listeners heard, and is able to track this at scale across platforms. (RAD is offering both Android and iOS SDKs.)
While there’s value in podcast data that goes beyond the download, not all are sold on technology.
Most notably, the developer behind the popular iOS podcast player app Overcast, Marco Arment, today publicly stated his app will not support any listener-tracking specs.
Yes. I understand why huge podcast companies want more listener data, but there are zero advantages for listeners or app-makers.
I won’t be supporting any listener-behavior tracking specs in Overcast. Podcasters get enough data from your IP address when you download episodes. https://t.co/mplhnrmCsc
— Marco Arment (@marcoarment) December 11, 2018
“I understand why huge podcast companies want more listener data, but there are zero advantages for listeners or app-makers,” Arment wrote in a tweet. “Podcasters get enough data from your IP address when you download episodes,” he said.
The developer also pointed out this sort of data collection required more work on the podcasters’ part and could become a GDPR liability, as well. (NPR tells us GDPR compliance is up to the mobile apps and analytics servers, as noted in the specs here.)
In addition to NPR’s use of RAD today, Podtrac has also now launched a beta program to show RAD data, which is open to interested publishers.
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Sisense hauls in $80M investment as data analytics business matures
Sisense, a company that helps customers understand and visualize their data across multiple sources, announced an $80 million Series E investment today led by Insight Venture Partners. They also announced that Zack Urlocker, former COO at Duo Security and Zendesk, has joined the organization’s board of directors.
The company has attracted a prestigious list of past investors, who also participated in the round, including Battery Ventures, Bessemer Venture Partners, DFJ Venture Capital, Genesis Partners and Opus Capital. Today’s investment brings the total raised to close to $200 million.
CEO Amir Orad says investors like their mission of simplifying complex data with analytics and business intelligence and delivering it in whatever way makes sense. That could be on screens throughout the company, desktop or smartphone, or via Amazon Alexa. “We found a way to make accessing data extremely simple, mashing it together in a logical way and embedding it in every logical place,” he explained.
It appears to be resonating. The company has over 1000 customers including Expedia, Oppenheimer and Phillips to name but a few. Orad says they are actually the analytics engine behind Nasdaq Corporate Solutions, which is the the main investor relations system used by CFOs.
He was not in the mood to discuss the company’s valuation, an exercise he called “an ego boost he doesn’t relate to.” He says that he would prefer to be measured by how efficiently he uses the money investors give him or by customer satisfaction scores. Nor would he deal with IPO speculation. All he would say on that front was, “When you focus on the value you bring, positive things happen.”
In spite of that, he was clearly excited about having Urlocker join the board. He says the two spent six months getting to know each other and he sees a guy who has brought several companies to successful exit joining his team, and perhaps someone who can help him bring his company across the finish line, however that ultimately happens. Just last month, Cisco bought Urlocker’s former company, Duo Security for $2.35 billion.
For now Sisense, which launched in 2010, has another $80 million in the bank. They plan to add to the nearly 500 employees already in place in offices in New York, Tel Aviv, Kiev, Tokyo and Arizona. In particular, they plan to grow their international presence more aggressively, especially adding employees to help with customer success and field engineering. Orad also said that he was also open to acquiring companies should the right opportunity come along, saying “Because of talent, technology and presence, it’s something you have to be on lookout for.”
When a company reaches Series E and a couple of hundred million raised, it’s often a point where an exit could be coming sooner than later. By adding an experienced executive like Urlocker, it just emphasizes that possibility, but for now the company appears to be growing and thriving, and taking the view that whatever will be, will be.
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Twilio’s contact center products just got more analytical with Ytica acquisition
Twilio, a company best known for supplying a communications APIs for developers has a product called Twilio Flex for building sophisticated customer service applications on top of Twilio’s APIs. Today, it announced it was acquiring Ytica (pronounced Why-tica) to provide an operational and analytical layer on top of the customer service solution.
The companies would not discuss the purchase price, but Twilio indicated it does not expect the acquisition to have a material impact on its “results, operations or financial condition.” In other words, it probably didn’t cost much.
Ytica, which is based in Prague, has actually been a partner with Twilio for some time, so coming together in this fashion really made a lot of sense, especially as Twilio has been developing Flex.
Twilio Flex is an app platform for contact centers, which offers a full stack of applications and allows users to deliver customer support over multiple channels, Al Cook, general manager of Twilio Flex explained. “Flex deploys like SaaS, but because it’s built on top of APIs, you can reach in and change how Flex works,” he said. That is very appealing, especially for larger operations looking for a flexible, cloud-based solution without the baggage of on-prem legacy products.
What the product was lacking, however, was a native way to manage customer service representatives from within the application, and understand through analytics and dashboards, how well or poorly the team was doing. Having that ability to measure the effectiveness of the team becomes even more critical the larger the group becomes, and Cook indicated some Flex users are managing enormous groups with 10,000-20,000 employees.
Ytica provides a way to measure the performance of customer service staff, allowing management to monitor and intervene and coach when necessary. “It made so much sense to join together as one team. They have huge experience in the contact center, and a similar philosophy to build something customizable and programmable in the cloud,” Cook said.
While Ytica works with other vendors beyond Twilio, CEO Simon Vostrý says that they will continue to support those customers, even as they join the Twilio family. “We can run Flex and can continue to run this separately. We have customers running on other SaaS platforms, and we will continue to support them,” he said.
The company will remain in Prague and become a Twilio satellite office. All 14 employees are expected to join the Twilio team and Cook says plans are already in the works to expand the Prague team.
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Outlier raises $6.2 M Series A to change how companies use data
Traditionally, companies have gathered data from a variety of sources, then used spreadsheets and dashboards to try and make sense of it all. Outlier wants to change that and deliver a handful of insights right to your inbox that matter most for your job, company and industry. Today the company announced a $6.2 million Series A to further develop that vision.
The round was led by Ridge Ventures with assistance from 11.2 Capital, First Round Capital, Homebrew, Susa Ventures and SV Angel. The company has raised over $8 million.
The startup is trying to solve a difficult problem around delivering meaningful insight without requiring the customer to ask the right questions. With traditional BI tools, you get your data and you start asking questions and seeing if the data can give you some answers. Outlier wants to bring a level of intelligence and automation by pointing out insight without having to explicitly ask the right question.
Company founder and CEO Sean Byrnes says his previous company, Flurry, helped deliver mobile analytics to customers, but in his travels meeting customers in that previous iteration, he always came up against the same question: “This is great, but what should I look for in all that data?”
It was such a compelling question that after he sold Flurry in 2014 to Yahoo for more than $200 million, that question stuck in the back of his mind and he decided to start a business to solve it. He contends that the first 15 years of BI was about getting answers to basic questions about company performance, but the next 15 will be about finding a way to get the software to ask good questions based on the huge amounts of data.
Byrnes admits that when he launched, he didn’t have much sense of how to put this notion into action, and most people he approached didn’t think it was a great idea. He says he heard “No” from a fair number of investors early on because the artificial intelligence required to fuel a solution like this really wasn’t ready in 2015 when he started the company.
He says that it took four or five iterations to get to today’s product, which lets you connect to various data sources, and using artificial intelligence and machine learning delivers a list of four or five relevant questions to the user’s email inbox that points out data you might not have noticed, what he calls “shifts below the surface.” If you’re a retailer that could be changing market conditions that signal you might want to change your production goals.
Outlier email example. Photo: Outlier
The company launched in 2015. It took some time to polish the product, but today they have 14 employees and 14 customers including Jack Rogers, Celebrity Cruises and Swarovski.
This round should allow them to continuing working to grow the company. “We feel like we hit the right product-market fit because we have customers [generating] reproducible results and really changing the way people use the data,” he said.
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Swim.ai raises $10M to bring real-time analytics to the edge
Once upon a time, it looked like cloud-based serviced would become the central hub for analyzing all IoT data. But it didn’t quite turn out that way because most IoT solutions simply generate too much data to do this effectively and the round-trip to the data center doesn’t work for applications that have to react in real time. Hence the advent of edge computing, which is spawning its own ecosystem of startups.
Among those is Swim.ai, which today announced that it has raised a $10 million Series B funding round led by Cambridge Innovation Capital, with participation from Silver Creek Ventures and Harris Barton Asset Management. The round also included a strategic investment from Arm, the chip design firm you may still remember as ARM (but don’t write it like that or their PR department will promptly email you). This brings the company’s total funding to about $18 million.
Swim.ai has an interesting take on edge computing. The company’s SWIM EDX product combines both local data processing and analytics with local machine learning. In a traditional approach, the edge devices collect the data, maybe perform some basic operations against the data to bring down the bandwidth cost and then ship it to the cloud where the hard work is done and where, if you are doing machine learning, the models are trained. Swim.ai argues that this doesn’t work for applications that need to respond in real time. Swim.ai, however, performs the model training on the edge device itself by pulling in data from all connected devices. It then builds a digital twin for each one of these devices and uses that to self-train its models based on this data.
“Demand for the EDX software is rapidly increasing, driven by our software’s unique ability to analyze and reduce data, share new insights instantly peer-to-peer – locally at the ‘edge’ on existing equipment. Efficiently processing edge data and enabling insights to be easily created and delivered with the lowest latency are critical needs for any organization,” said Rusty Cumpston, co-founder and CEO of Swim.ai. “We are thrilled to partner with our new and existing investors who share our vision and look forward to shaping the future of real-time analytics at the edge.”
The company doesn’t disclose any current customers, but it is focusing its efforts on manufacturers, service providers and smart city solutions. Update: Swim.ai did tell us about two customers after we published this story: The City of Palo Alto and Itron.
Swim.ai plans to use its new funding to launch a new R&D center in Cambridge, UK, expand its product development team and tackle new verticals and geographies with an expanded sales and marketing team.
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Bannersnack makes it easy to punch the monkey (and more)
An app like Bannersnack is something you never think you need — until you do. Designed by a digital marketer from Romania, Gabriel Ciordas, the app was originally called FlashEff and was used to create Flash banners for online marketers. Over time, however, HTML5 and graphics overtook Flash and the company pivoted to offering easy-to-use design tools for marketers and business owners.
The service is free to try and costs $7 a month 30 static images; $18 a month gets you embedded banners with full analytics. The company is completely bootstrapped and has been working in the space since 2008.
“Bannersnack has always been self-funded. We built our resources step by step, as our business grew together with our efforts. We think it’s fair to say that we worked for every penny we’ve ever gotten and further invested it back into growing our business,” said Ciordas.
The service has 100,000 monthly users who create 180,000 visuals a month. They offer standalone graphics as well as responsive HTML5 images. The most interesting tool, the Banner Generator, creates banners in multiple sizes instantly, freeing business owners up to do what they do best: sell stuff.
Again, it is rare to see a product so focused on a single, important niche, and Bannersnack fits the bill. While you could fire up Pixelmator and try to make your own banners, this tool is surprisingly pleasant to use and works quite well.
“Our main objective is to empower marketers, designers, and business owners, while reshaping the way agencies and businesses create visuals for their marketing purposes,” said Ciordas. After all, not everyone has the skills or talent to create flashing banners featuring exciting mortgage reduction opportunities and free iPad sweepstakes.
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Tableau gets new pricing plans and a data preparation tool
Data analytics platform Tableau today announced the launch of both a new data preparation product and a new subscription pricing plan.
Currently, Tableau offers desktop plans for users who want to analyze their data locally, a server plan for businesses that want to deploy the service on-premises or on a cloud platform, and a fully hosted online plan. Prices for these range from $35 to $70 per user and month. The new pricing plans don’t focus so much on where the data is analyzed but on the analyst’s role. The new Creator, Explorer and Viewer plans are tailored toward the different user experiences. They all include access to the new Tableau Prep data preparation tool, Tableau Desktop and new web authoring capabilities — and they are available both on premises or in the cloud.
Existing users can switch their server or desktop subscriptions to the new release today and then assign each user either a creator, explorer or viewer role. As the name indicates, the new viewer role is meant for users who mostly consume dashboards and visualizations, but don’t create their own. The explorer role is for those who need access to a pre-defined data set and the creator role is for analysts and power user who need access to all of Tableau’s capabilities.
“Organizations are facing the urgent need to empower their entire workforce to help drive more revenue, reduce costs, provide better service, increase productivity, discover the next scientific breakthrough and even save lives,” said Adam Selipsky, CEO at Tableau, in today’s announcement. “Our new offerings will help entire organizations make analytics ubiquitous, enabling them to tailor the capabilities required for every employee.”
As for the new data preparation tool, the general idea here is to give users a visual way to shape and clean their data, something that’s especially important as businesses now often pull in data from a variety of sources. Tableau Prep can automate some of this, but the most important aspect of the service is that it gives users a visual interface for creating these kind of workflows. Prep includes support for all the standard Tableau data connectors and lets users perform calculations, too.
“Our customers often tell us that they love working with Tableau, but struggle when data is in the wrong shape for analysis,” said Francois Ajenstat, Chief Product Officer at Tableau. “We believe data prep and data analysis are two sides of the same coin that should be deeply integrated and look forward to bringing fun, easy data prep to everyone regardless of technical skill set.”
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Google Cloud gives developers more insights into their networks
Google Cloud is launching a new feature today that will give its users a new way to monitor and optimize how their data flows between their servers in the Google Cloud and other Google Services, on-premises deployments and virtually any other internet endpoint. As the name implies, VPC Flow Logs are meant for businesses that already use Google’s Virtual Private Cloud features to isolate their resources from other users.
VPC Flow Logs monitors and logs all the network flows (both UDP and TCP) that are sent from and received by the virtual machines inside a VPC, including traffic between Google Cloud regions. All of that data can be exported to Stackdriver Logging or BigQuery, if you want to keep it in the Google Cloud, or you can use Cloud Pub/Sub to export it to other real-time analytics or security platforms. The data updates every five seconds and Google promises that using this service has no impact on the performance of your deployed applications.
As the company notes in today’s announcement, this will allow network operators to get far more insight into the details of how the Google network performs and to troubleshoot issues if they arise. In addition, it will allow them to optimize their network usage and costs by giving them more information about their global traffic.
All of this data is also quite useful for performing forensics when it looks like somebody may have gotten into your network, too. If that’s your main use case, though, you probably want to export your data to a specialized security information and event management (SIEM) platform from vendors like Splunk or ArcSight.
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AI game trainer Gosu.ai raises $1.9M to give gamers a virtual assistant
If you play hardcore and competitive games, you want to win, so it would be useful to have someone leaning over your shoulder giving you tips on how to play better. Someone who knows all your moves and behaviors, for instance.
That’s the thinking behind Gosu.ai, which has developed an AI assistant to help gamers play smarter and improve their skills. It’s now raised a $1.9M funding round led by Runa Capital, with participation from Ventech and existing investor, Sistema_VC. Previously, the startup was backed by Gagarin Capital, a new Silicon Valley-based early-stage VC firm focusing on AI investments, which invested in Prisma and MSQRD, which exited to Facebook and Google, respectively.
Gosu.ai provides tools and guidance for users to improve their skills in competitive games. It analyzes their matches and makes personal recommendations. It also helps players prep, suggesting gear sets, starting items and offering ideas on how to take on a particular opponent. The platform currently works with Dota 2, with plans to support CS:GO and PUBG in the near future.
The company was founded by Alisa Chumachenko (pictured), who was the creator and former CEO of Game Insight, a big gaming world player. She says: “There are 2 billion gamers in the world now and 600 million of them play hardcore games, such as MOBAs, Shooters and MMOs. We can help those players reach their full potential with our AI assistants.”
Gosu.ai’s main competitors are Mobalytics, Dojomadness and Moremmr. But the main difference is that these competitors make analytics of raw statistics, and find the generalized weak spots in comparison with other players, giving general recommendations. Gosu.ai analyzes the specific actions of each player, down to the movement of their mouse, to cater direct recommendations for the player. So it’s more like a virtual assistant than a training platform.
In addition, Gosu works in the B2B field, as well, by offering gaming companies a variety of AI tools, for example a predictive analytics.
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S&P Global snares Kensho for $550 million
S&P Global announced today that it will acquire Kensho, a Cambridge, Massachusetts startup that has concentrated on artificial intelligence and analytics for big financial institutions. The total value of the deal is $550 million in a mix of cash and stock. Kensho, which counted S&P Global as a client/partner and an investor, launched in 2013 and has raised $67.5 million, according… Read More
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