Twitter just launched its “Certified Products Program” to highlight “the best products and services to thrive on Twitter.” The program is meant to help companies find “the best tools to engage with their customers” and “understand what people are saying about them on Twitter.” To do so, Twitter is focusing on three product categories: engagement, analytics and data resellers. All of these, of course, are products that Twitter identified as tools it wants its developer ecosystem to focus on in its infamous blog post from earlier this month.

Today’s partners include Attensity, Crimson Hexagon, Dataminr, DataSift, ExactTarget, Gnip, HootSuite, Mass Relevance, Radian6, SocialFlow, Sprinklr and Topsy.

In the announcement, the company’s business development manager Doug Williams notes that “this is just the beginning” and that Twitter is looking forward to adding more companies in the future. Potential new partners can apply for certification here.

Here are the guidelines for products that want to become certified:

• Make Twitter more valuable to businesses and solve a need that Twitter does not address
• Help bring Twitter to new or underserved markets
• Twitter is a core part of your product and you make use of all applicable APIs and features
• Integrations behave as consistently as possible with Twitter’s own products
• Encourage meaningful engagement with the Twitter network
• You are working on an opportunity with significant impact
• Use Twitter Platform products rather than creating similar products

Certified products, of course, also have to follow all of Twitter’s attribution guidelines and display requirements.

Unsurprisingly, Twitter is not recommending any third-party Twitter clients in this list. These, after all, aren’t among the products Twitter wants to see in its ecosystem as the company argues that they don’t add enough value for its users.

Sprinklr, which describes itself as “the largest independent social relationship platform provider,” just announced that it has raised $40 million in Series D funding. It’s also launching its first “paid social media solution,” i.e., a product for managing ad campaigns on Facebook and Twitter.

With the new product, Sprinklr says its customers can plan, execute, and measure their social media activity (ad-related or otherwise) in one product. Early testers of the ad tools have supposedly seen a 25 percent increase in the return on investment of their campaigns, and general availability scheduled for six weeks from now.

The round was led by Iconiq Capital with participation from previous investors Battery Ventures and Intel Capital. It brings Sprinklr’s total funding to more than $77 million.

“The introduction of an integrated, paid social media module is a big step for Sprinklr, and will be welcomed by large businesses now struggling to patch together their own social solutions,” said Battery’s Neeraj Agrawal in the funding release.

The news follows Sprinklr’s acquisition of social media monitoring company Dachis Group earlier this year.

TrendKite, a startup promising to help brands and agencies measure the effectiveness of their PR efforts, has raised $3.2 million in Series A funding. It’s also announcing that it has a new CEO — Erik Huddleston, former CTO and executive vice president of product at social monitoring company Dachis Group.

Huddleston told me that when Dachis Group was acquired by Sprinklr in February, he was “fully committed” to staying on-board.

However, he was already an adviser with TrendKite, and shortly after the acquisition was announced, the startup’s founders took him to dinner and suggested that he join as CEO. It was, in his words, “a bit of an ambush.” And apparently it worked.

Those founders will remain involved in the company — former CEO Matt Allison is now chief product officer, while his co-founders AJ Bruno and Patrick Brannen continue to serve as president and CTO, respectively.

Huddleston said that even though companies like Sprinklr represent a broader shift in spending from IT to marketing, particularly toward data-focused marketing tools, most of those tools have been focused on advertising, leaving earned media (i.e. press coverage and consumer mentions that companies don’t pay for), “completely ignored.”

TrendKite says it can provide companies with the PR data they need, with features including custom dashboards (tracking things like the most popular articles about your company, mentions by top influencers, and general sentiment and share of voice compared with the competition), email news alerts, and shareable PDF reports.

Huddleston also praised the founders’ vision, as well as their experience in the industry and in sales: “The only thing they were really missing was the product component.” Not that he was criticizing the product itself (he recalled talking to customers who “raved” about it), just suggesting that the company needed someone with a strong product background at the top.

The company’s new funding was led by Mercury Fund and Silverton Partners. It follows last fall’s $1.2 million and will go towards expanding the company’s data infrastructure and its sales team.

Sprinklr just announced that it has raised $46 million in new funding, at what it says is a valuation of more than $1 billion.

The round was led by existing investors Battery Ventures, Intel Capital, and Iconiq Capital and brings the company’s total funding to $123.5 million. (Sprinklr’s last funding of $40 million was announced just under a year ago.)

The company is also officially launching its Experience Cloud, a platform that connects its existing social media management tools (with capabilities like publishing, advertising, and analytics) with what Mark Curtis, the company’s general manager of brand advocacy, called the “first-party experience” — namely, building communities and forums on your own website.

Curtis and other members of the Sprinklr team gave me a quick demo of the Experience Cloud, showing that it’s easy to build a website with drag-and-drop social widgets. However, the key piece that Curtis emphasized wasn’t the website builder, but rather the way that Sprinklr can then connect customer data across “all the different touch points that make up the brand experience.”

For example, if someone logs into a brand’s web community, the brand could pull data from social networks and personalize the content the user sees accordingly. Brands can also look at dashboards showing the activity of each customer across all their different platforms, and import the information into their sales databases.

“If [customers] are coming to our site and telling us who they are, let’s not be the goldfish that has no memory,” Curtis said. “Let’s use that information to provide the best customer experience possible.”

Curtis, by the way, joined Sprinklr last fall through the acquisition of Branderati. The company has actually made four other acquisitions in the past 12 months — Dachis Group, TBG, and Pluck.

Expanding through acquisitions has become standard practice for social media companies, but Curtis said:

When we bought TBG, we didn’t use a line of their code, and we didn’t use a line of Branderati code. All that functionality was added to the core Sprinklr code, and it’s the same for Pluck … The sustainable advantage that we have in terms of the Experience Cloud is that it’s not a cloud of cobbled together things.

Sprinklr, the social media management company that vaulted into the “unicorn club” last month after it raised $46m on a $1b+ valuation, is making an acquisition to expand into a new area, customer feedback. It is buying Get Satisfaction, makers of a platform that lets businesses connect with customers online and get feedback on their sites.

Terms of the deal have not been disclosed, and Carlos Dominguez, Sprinklr’s president, also declined to comment on the price in an interview. There are approximately 30 people at Get Satisfaction, all of whom are coming over to Sprinklr, bring its total up to about 750.

Get Satisfaction, founded in 2007 and based in San Francisco, had raised just under $21 million from investors that included SoftTechVC, InterWest, O’Reilly AlphaTech, First Round and Azure Capital Partners.

Get Satisfaction will be integrated into Sprinklr’s bigger cloud-based social media management business — dubbed “Experience Cloud” — which helps businesses track individuals wherever they are leaving feedback about a business, be it on social media sites or directly on their own websites, covering about 25 different potential feedback channels in all. But it is also a bolt-on acquisition of sorts: today Get Satisfaction already works with 1,000 businesses, Sprinklr says, with customers including P&G, Rabobank, SugarCRM and Service Rocket.

“This is our fifth so we’re getting it down,” Dominguez said. “They will continue to operate and we will continue to support and sell Get Satisfaction’s products for a period of time. But where the value lies for us is in build this into an enterprise-class platform.”

This deal makes a lot of sense for Sprinklr, for two main reasons:

First, there is the very basic fact that it gives Sprinklr clients one more way to connect with customers and collect feedback online — something that has only grown in importance as we as consumers become more social and prone to doing most of our transacting in the virtual world.

“You can’t market or sell to unhappy customers in a world of connected consumers. It is only a question of time before all brands recognize that the marketing of the future begins with great customer care,” said Ragy Thomas, CEO and founder of Sprinklr, in a statement. “It makes no sense for the marketing team to spend hundreds of millions of dollars driving acquisition while the head of customer service is compensated on reducing the time with your best customers.”

Interestingly, while today Sprinklr focuses on “public” feedback, by way of what people say in forums and social media pages viewable by others, it looks like over time it will look for ways of building more bridges into the kind of feedback that is provided in more direct, private messages.

“The whole notion of the Experience Cloud is that we’re taking care of the ‘front office’ but we’re also building APIs for the back office,” Dominquez said. A recent partnership with SAP that will help integrate with those more direct feedback sources is part of how Sprinklr hopes to “marry the front and back office together.” It will also help it compete more squarely against the likes of Oracle on this front.

Second, Get Satisfaction will mean that Sprinklr will be able to offer businesses more options for collecting feedback on their own sites, not just third-party networks like Twitter and Facebook.

Sprinklr — and others it competes against like Hootsuite and Sprout Social — have built their businesses largely on the idea of integrating with lots of other services and providing a dashboard to its customers to help manage that. In doing so they have filled a hole in the market: the rise of social media has led to the growth of a disparate, unconnected group of services where brands and businesses get discussed, and for businesses, having a dashboard to be able to monitor and analyse all of that can be indispensable.

However, what it has also meant is that Sprinklr and its rivals are also largely at the mercy of the services it monitors: all it takes is for one of the social media companies to, for example, cut off its API access — for instance, in the event that said social media company wants to offer its own social media monitoring service — to lessen the value of the third-party social media management service.

This is where Get Satisfaction becomes an interesting acquisition for Sprinklr. What it will give the company is the ability to collect data from customers, about businesses and brands, on its own platform, which it can then use to power its wider analytics services.

“We have to honor third party terms and conditions, and we do,” Dominquez said, but the data that Sprinklr will have greater control over will give it much more flexibility in how that data is used and also presented, he added. “You can provide a richer experience to people. This tech has benefits for the brand and their customers. It enhances the experience.”

(And remember, Get Satisfaction has been around since 2007, giving it eight years of data collected already that could be used for analytics.)

This is Sprinklr’s sixth acquisition.

Social media company Sprinklr has acquired Booshaka, a company aiming to give businesses a better understanding of their audience.

Specifically, Booshaka has built “one-click connectors” to pull customer data from services like Marketo, Shopify and Stripe, then use that data to build audience segments for ad campaigns on Facebook and Twitter.

Simon Mansell, Sprinklr’s general manager of paid and services, said that by integrating Booshaka technology, the company can bring in customer data from, say, ExactTarget, then combine it with social listening data to create “a profile of that person,” putting them in a segment based on their interests and likely business value. That, in turn, allows Sprinklr to improve social ad targeting, and over time, the data could be used in areas beyond advertising.

“The macro thing is that marketing tech and ad tech should come together,” Mansell said. “The bridge between ad tech and marketing tech is audience management — basically, bringing in customer data and enhancing it with social listening data and then using it for effective media targeting and better quality customer care.”

The financial terms of the deal were not disclosed. Booshaka founder and CEO Erik Ober said his entire 10-person Booshaka team will be joining Sprinklr.

Sprinklr recently raised a $46 million round of funding at what it says was a valuation of more than $1 billion. It has also been active on the acquisition side, with eight deals in less than two years, most recently the acquisition of NewBrand in June.

Mansell said this will follow the pattern of other Sprinklr acquisitions: “When we acquire companies, we basically rebuild the code. The main reason we do that is so that [the whole platform is] truly one code.”

Booshaka investors include SV Angel, PivotNorth Capital, FF Angel, Palantir co-founder Joe Lonsdale and others.

If there’s one technology that promises to change the world more than any other over the next several decades, it’s (arguably) machine learning.

By enabling computers to learn certain things more efficiently than humans, and discover certain things that humans cannot, machine learning promises to bring increasing intelligence to software everywhere and enable computers to develop new capabilities –- from driving cars to diagnosing disease –- that were previously thought to be impossible.

While most of the core algorithms that drive machine learning have been around for decades, what has magnified its promise so dramatically in recent years is the extraordinary growth of the two fuels that power these algorithms – data and computing power.

Both continue to grow at exponential rates, suggesting that machine learning is at the beginning of a very long and productive run.

As revolutionary as machine learning will be, its impact will be highly asymmetric. While most machine learning algorithms, libraries and tools are in the public domain and computing power is a widely available commodity, data ownership is highly concentrated.

This means that machine learning will likely have a barbell effect on the technology landscape. On one hand, it will democratize basic intelligence through the commoditization and diffusion of services such as image recognition and translation into software broadly. On the other, it will concentrate higher-order intelligence in the hands of a relatively small number of incumbents that control the lion’s share of their industry’s data.

For startups seeking to take advantage of the machine learning revolution, this barbell effect is a helpful lens to look for the biggest business opportunities. While there will be many new kinds of startups that machine learning will enable, the most promising will likely cluster around the incumbent end of the barbell.

Democratization of Basic Intelligence

One of machine learning’s most lasting areas of impact will be to democratize basic intelligence through the commoditization of an increasingly sophisticated set of semantic and analytic services, most of which will be offered for free, enabling step-function changes in software capabilities. These services today include image recognition, translation and natural language processing and will ultimately include more advanced forms of interpretation and reasoning.

Software will become smarter, more anticipatory and more personalized, and we will increasingly be able to access it through whatever interface we prefer – chat, voice, mobile application, web, or others yet to be developed. Beneficiaries will include technology developers and users of all kinds.

This burst of new intelligent services will give rise to a boom in new startups that use them to create new products and services that weren’t previously cost effective or possible. Image recognition, for example, will enable new kinds of visual shopping applications. Facial recognition will enable new kinds of authentication and security applications. Analytic applications will grow ever more sophisticated in their ability to identify meaningful patterns and predict outcomes.

Startups that end up competing directly with this new set of intelligent services will be in a difficult spot. Competition in machine learning can be close to perfect, wiping out any potential margin, and it is unlikely many startups will be able to acquire data sets to match Google or other consumer platforms for the services they offer. Some of these startups may be bought for the asset values of their teams and technologies (which at the moment are quite high), but most will have to change tack in order to survive.

This end of the barbell effect is being accelerated by open source efforts such as OpenAI as well as by the decision of large consumer platforms, led by Google with TensorFlow, to open source their artificial intelligence software and offer machine learning-driven services for free, as a means of both selling additional products and acquiring additional data.

Concentration of Higher-Order Intelligence

At the other end of the barbell, machine learning will have a deeply monopoly-inducing or monopoly-enhancing effect, enabling companies that have or have access to highly differentiated data sets to develop capabilities that are difficult or impossible for others to develop.

The primary beneficiaries at this end of the spectrum will be the same large consumer platforms offering free services such as Google, as well as other enterprises in concentrated industries that have highly differentiated data sets.

Large consumer platforms already use machine learning to take advantage of their immense proprietary data to power core competencies in ways that others cannot replicate – Google with search, Facebook with its newsfeed, Netflix with recommendations and Amazon with pricing.

Incumbents with large proprietary data sets in more traditional industries are beginning to follow suit. Financial services firms, for example, are beginning to use machine learning to take advantage of their data to deepen core competencies in areas such as fraud detection, and ultimately they will seek to do so in underwriting as well. Retail companies will seek to use machine learning in areas such as segmentation, pricing and recommendations and healthcare providers in diagnosis.

Most large enterprises, however, will not be able to develop these machine learning-driven competencies on their own. This opens an interesting third set of beneficiaries at the incumbent end of the barbell: startups that develop machine learning-driven services in partnership with large incumbents based on these incumbents’ data.

Where the Biggest Startup Opportunities Are

The most successful machine learning startups will likely result from creative partnerships and customer relationships at this end of the barbell.

The magic ingredient for creating revolutionary new machine learning services is extraordinarily large and rich data sets. Proprietary algorithms can help, but they are secondary in importance to the data sets themselves.

What’s critical to making these services highly defensible is privileged access to these data sets. If possession is nine tenths of the law, privileged access to dominant industry data sets is at least half the ballgame in developing the most valuable machine learning services.

The dramatic rise of Google provides a glimpse into what this kind of privileged access can enable.

What allowed Google to rapidly take over the search market was not primarily its PageRank algorithm or clean interface, but these factors in combination with its early access to the data sets of AOL and Yahoo, which enabled it to train PageRank on the best available data on the planet and become substantially better at determining search relevance than any other product.

Google ultimately chose to use this capability to compete directly with its partners, a playbook that is unlikely to be possible today since most consumer platforms have learned from this example and put legal barriers in place to prevent it from happening to them.

There are, however, a number of successful playbooks to create more durable data partnerships with incumbents.

In consumer industries dominated by large platform players, the winning playbook in recent years has been to partner with one or ideally multiple platforms to provide solutions for enterprise customers that the platforms were not planning (or, due to the cross-platform nature of the solutions, were not able) to provide on their own, as companies such as Sprinklr, Hootsuite and Dataminr have done.

The benefits to platforms in these partnerships include new revenue streams, new learning about their data capabilities and broader enterprise dependency on their data sets.

In concentrated industries dominated not by platforms but by a cluster of more traditional enterprises, the most successful playbook has been to offer data-intensive software or advertising solutions that provide access to incumbents’ customer data, as Palantir, IBM Watson, Fair Isaac, AppNexus and Intent Media have done. If a company gets access to the data of a significant share of incumbents, it will be able to create products and services that will be difficult for others to replicate.

New Playbooks

New playbooks are continuing to emerge, including creating strategic products for incumbents or using exclusive data leases in exchange for the right to use incumbents’ data to develop non-competitive offerings.

Of course the best playbook of all — where possible — is for startups to grow fast enough and generate sufficiently large data sets in new markets to become incumbents themselves and forego dependencies on others (as, for example, Tesla has done for the emerging field of autonomous driving).

This tends to be the exception rather than the rule, however, which means most machine learning startups need to look to partnerships or large customers to achieve defensibility and scale.

Machine learning startups should be particularly creative when it comes to exploring partnership structures as well as financial arrangements to govern them – including discounts, revenue shares, performance-based warrants and strategic investments. In a world where large data sets are becoming increasingly valuable to outside parties, it is likely that such structures and arrangements will continue to evolve rapidly.

Perhaps most importantly, startups seeking to take advantage of the machine learning revolution should move quickly, because many top technology entrepreneurs have woken up to the scale of the business opportunities this revolution creates, and there is a significant first-mover advantage to get access to the most attractive data sets.

New York marketing tech firm Sprinklr has acquired Portland-based Little Bird, according to Sprinklr founder and CEO Ragy Thomas.

Little Bird was founded in 2011 to help researchers quickly find the top experts and influencers on any given subject via Twitter. It raised from Mark Cuban, Jason Calacanis, Oregon Angel Fund and other individual investors $4.8 million in venture capital to build its analytics platform.

Little Bird chairman and co-founder Marshall Kirkpatrick, formerly a TechCrunch writer, said his company’s technology today is exactly what his team set out to build initially. Here’s how it works:

“Little Bird discovers the most influential people in any field, with influence measured by connections a person has built with other experts in their specific field using a ‘9 out of 10 dentists recommend’ model.

Once a big map of influencers and experts has been built, which takes under 5 minutes, then the system tells our customers which of those influencers are already part of their community online, who competitors are connected to, what the hottest conversations among those influencers is, and we deliver alerts over time whenever something important happens.”

Sprinklr plans to integrate Little Bird into its broader, social media management platform, Ragy Thomas said, namely its “influencer and advocacy management solution.”

For those not familiar, Thomas describes Sprinklr today as “the most complete social media management platform for the enterprise.” He explained, “We help the world’s largest brands do marketing, advertising, customer care, sales, research and commerce on Facebook, Twitter, LinkedIn and 21 other social channels globally.”

Those activities used to be managed by siloed teams and with disparate software and systems, Thomas said, but with the advent of social media, the trend has been toward collaboration and even centralization in large companies.

Little Bird’s six full-time employees will stay in Portland but become part of Sprinklr’s global team, said Kirkpatrick.

Executives did not disclose the terms of the deal. The acquisition marks the 11th for Sprinklr, a robust number for a company that’s just seven years old. In November last year it acquired Booshaka, an audience-targeting tech firm.

Sprinklr has raised $230 million in venture capital to date, and employs 1,300 people full-time. Thomas says the last round of funding saw his company’s post-money valuation rise to $1.8 billion, putting the company squarely on the “unicorn” list.

Its clients include more than 1,200 brands, Microsoft, Nike, Dell and P&G among them.

Little Bird had racked up some impressive clients, too, including large media companies, nonprofits, retailers that Kirkpatrick did not have permission to name, as well as Microsoft, LinkedIn, IBM, Dun & Bradstreet and Pitney Bowes.

Ultimately, Kirkpatrick said, “Becoming part of Sprinklr means the learning our customers do with Little Bird can become actionable.”

Sprinklr, the unicorn startup with a valuation of $1.8 billion, announced a major update today, which shifts the company’s focus from a pure social signals platform to customer experience management. While it still uses social as a central processing point, the idea is to bring a typical set of marketing tasks under a single umbrella they are calling the Experience Cloud.

If that sounds familiar, it’s because Adobe released a product with the same name a few weeks ago. Sprinklr is taking a similar approach with a unified platform, but with the goal of being able to manage the customer through what you know about them from a social perspective.

For CEO Ragy Thomas, it’s about finding more creative ways to use the social information they have been collecting for the past 7.5 years the company has been around.

The newly expanded platform adds five modules including marketing, advertising, research, customer care and eCommerce, in addition to the social component that has been at the center of the company’s approach up until now.

It’s worth noting that the company released the platform notion in 2015, but it had just the social piece back then. This is an entirely new bundle of options, according to the company. Being a platform play, as you would expect there is a set of shared capabilities underpinning each of the categories such as asset management, APIs, reporting, security and collaboration.

Photo: Sprinklr

Thomas doesn’t actually see his company competing with Adobe’s product in spite of the identical names. Instead, he sees it as complementary, something that could work alongside Adobe’s offering. “When you think about Adobe’s Experience Cloud, when you take their core offering, they’ve got content creation capabilities, web management, web analytics and campaign and email capability,” he said.

He contrasts that with the offerings on his platform. “For influencer marketing, we have included content marketing, listening insights, visual insights and community care. These are things you don’t find in other places,” he claimed.

Many of the platform pieces came by way of acquisition. Sprinklr has quietly purchased 10 companies since 2014, all with the ultimate goal of building out the social signals platform into something more.

Chart: Crunchbase

The company wants to give customers this broad set of tools to help manage customer experience across a variety of roles. Thomas believes that each platform category can feed off of the social information, whether that’s an ad you’re delivering to the customer or a product you’re selling them online. There’s no doubt it’s ambitious and is attempting to take the company in a much more extensive direction.

There has been chatter over the past couple of months that Sprinklr itself was an acquisition target. When asked about this Thomas would only say, “We’ve not been commenting on that.” He added, “In our history, we’ve passed on multiple acquisition proposals.” For now at least, today’s release signals that the company is not sitting still waiting to be bought.

Thomas sees customer experience management, a notion that has been around for some time, finally beginning to take off, and he believes this new platform puts them in a position to capitalize on it.