There are already a number of resources available for mapping the spread of confirmed COVID-19 cases both in the U.S. and globally, but IBM and its subsidiary The Weather Company have launched new tools that bring COVID-19 mapping and analysis to more people via their Weather Channel mobile app and weather.com.
Existing tools are useful, but come from fairly specialized sources including the World Health Organization (WHO) and Johns Hopkins University. This new initiative combines data fro these same sources, including global confirmed reported COVID-19 cases, as well as reported data from sources at both the state and county level. This is collected on a so-called “incident map” that displays color-coded reported case data for states and counties, as well as on state-wide trend graphs and through reporting of stats including relative percentage increase of cases week-over-week.
On top of these sections built into the core, consumer-facing Weather.com products, IBM has also launched a more in-depth analytics reporting dashboard, providing views of global reported COVID-19 cases, as well as rate of spread based on available data, county-by-county stats and more.
This information from IBM, which runs on its Watson and Cognos Analytics tools, are intended for use by both researchers and public officials – but they’re also meant for general public consumption. IBM is also providing resources including fact-checking resources and practical guidance for both COVID-19 patients and the general public, to help not only inform people about the spread of the virus, but also the steps they can take to protect themselves and others.
One of the key elements of COVID-19 mitigation is making sure that the average American has access to reliable and accurate information, including the most up-to-date guidelines about social distancing and isolation from trusted experts including the WHO and the Centers for Disease Control and Prevention (CDC). That makes this a key resource in the ongoing efforts to curb the spread of the coronavirus, since it resides in an app that is among the most popular pieces of software available for smartphones. There are around 45 million or so monthly active users of the Weather Channel app, which means that this information will now be readily accessible by a large percentage of the U.S. population.
Oribi, an Israeli startup promising to democratize web analytics, is now launching in the United States.
While we’ve written about a wide range of new or new-ish analytics companies, founder and CEO Iris Shoor said that most of them aren’t built for Oribi’s customers.
“A lot of companies are more focused on the high end,” Shoor told me. “Usually these solutions are very much based on a lot of technical resources and integrations — these are the Mixpanels and Heap Analytics and Adobe Marketing Clouds.”
She said that Oribi, on the other hand, is designed for small and medium businesses that don’t have large technical teams: “They have digital marketing strategies that are worth a few hundred thousand dollars a month, they have very large activity, but they don’t have a team for it. And I would say that all of them are using Google Analytics.”
Shoor described Oribi as designed specifically “to compete with Google Analytics” by allowing everyone on the team to get the data they need without requiring developers to write new code for every event they want to track.
In fact, if you use Oribi’s plugins for platforms like WordPress and Shopify, there’s no coding at all involved in the process. Apparently, that’s because Oribi is already tracking every major event in the customer journey. It also allows the team to define the conversion goals that they want to focus on — again, with no coding required.
Shoor contrasted Oribi with analytics platforms that simply provide “more and more data” but don’t help customers understand what to do with that data.
“We’ve created something that is much more clean,” she said. “We give them insights of what’s working; in the background, we create all these different queries and correlations about which part of the funnels are broken and where they can optimize.”
There are big businesses using Oribi already — including Audi, Sony and Crowne Plaza — but the company is now turning its attention to U.S. customers. Shoor said Oribi isn’t opening an office in the United States right away, but there are plans to do so in the next year.
When Google announced that it was acquiring data analytics startup Looker for $2.6 billion last June, it was a big deal on a couple of levels. It was a lot of money and it represented the first large deal under the leadership of Thomas Kurian. Today, the company announced that deal has officially closed and Looker is part of the Google Cloud Platform.
While Kurian was happy to announce that Looker was officially part of the Google family, he made it clear in a blog post that the analytics arm would continue to support multiple cloud vendors beyond Google.
“Google Cloud and Looker share a common philosophy around delivering open solutions and supporting customers wherever they are—be it on Google Cloud, in other public clouds, or on premises. As more organizations adopt a multi-cloud strategy, Looker customers and partners can expect continued support of all cloud data management systems like Amazon Redshift, Azure SQL, Snowflake, Oracle, Microsoft SQL Server and Teradata,” Kurian wrote.
As is typical in a deal like this, Looker CEO Frank Bien sees the much larger Google giving his company the resources to grow much faster than it could have on its own. “Joining Google Cloud provides us better reach, strengthens our resources, and brings together some of the best minds in both analytics and cloud infrastructure to build an exciting path forward for our customers and partners. The mission that we undertook seven years ago as Looker takes a significant step forward beginning today,” Bien wrote in his post.
At the time of the deal in June, the company shared a slide, which showed where Looker fits in what they call their “Smart Analytics Platform,” which provides ways to process, understand, analyze and visualize data. Looker fills in a spot in the visualization stack while continuing to support other clouds.
Looker was founded in 2011 and raised over $280 million, according to Crunchbase. Investors included Redpoint, Meritech Capital Partners, First Round Capital, Kleiner Perkins, CapitalG and PremjiInvest. The last deal before the acquisition was a $103 million Series E investment on a $1.6 billion valuation in December 2018.
Placer.ai, a startup that analyzes location and foot traffic analytics for retailers and other businesses, announced today that it has closed a $12 million Series A. The round was led by JBV Capital, with participation from investors including Aleph, Reciprocal Ventures and OCA Ventures.
The funding will be used on research and development of new features and to expand Placer.ai’s operation in the United States.
Launched in 2016, Placer.ai’s SaaS platform gives its clients to real-time data that helps them make decisions like where to rent or buy properties, when to hold sales and promotions and how to manage assets.
Placer.ai analyzes foot traffic and also creates consumer profiles to help clients make marketing and ad spending decisions. It does this by collecting geolocation and proximity data from devices that are enabled to share that information. Placer.ai’s co-founder and CEO Noam Ben-Zvi says the company protects privacy and follows regulation by displaying aggregated, anonymous data and does not collect personally identifiable data. It also does not sell advertising or raw data.
The company currently serves clients in the retail (including large shopping centers), commercial real estate and hospitality verticals, including JLL, Regency, SRS, Brixmor, Verizon* and Caesars Entertainment.
“Up until now, we’ve been heavily focused on the commercial real estate sector, but this has very organically led us into retail, hospitality, municipalities and even [consumer packaged goods],” Ben-Zvi told TechCrunch in an email. “This presents us with a massive market, so we’re just focused on building out the types of features that will directly address the different needs of our core audience.”
He adds that lack of data has hurt retail businesses with major offline operations, but that “by effectively addressing this gap, we’re helpiong drive more sustainable growth or larger players or minimizing the risk for smaller companies to drive expansion plans that are strategically aggressive.”
Others startups in the same space include Dor, Aislelabs, RetailNext, ShopperTrak and Density. Ben-Zvi says Placer. ai wants to differentiate by providing more types of real-time data analysis.
“While there are a lot of companies touching the location analytics space, we’re in a unique situation as the only company providing these deep and actionable insights for any location in the country in a real-time platform with a wide array of functionality,” he said.
*Disclosure: Verizon Media is the parent company of TechCrunch.
One of the enduring truths of big companies is that they aren’t innovative. They are “innovative” in the marketing sense, but fail to ever execute on new ideas, particularly when those ideas cannibalize existing products and revenues.
So it often takes a real competitor to force these incumbent, legacy businesses to evolve in any meaningful way. Usually that change leads to disruption, in the classic way that Clayton Christensen describes in “The Innovator’s Dilemma.” An upstart company creates a new technology or business model that is better for an under-served segment of a market, and as that company improves, it competes directly with the incumbent and eventually wins over its market with a vastly superior product.
Unfortunately, real life isn’t so easy, as WeWork and MoviePass have shown us over the past few years.
In both cases, there were incumbents. In movie theaters, you had AMC and the like, which built a business model around ticket sales (shared with movie studios) and food/beverage concessions that targeted occasional customers at a high price point. Meanwhile, in commercial real estate, you had large landowners and family holders who demanded extremely long rent terms at high prices, often with personal financial guarantees from the CEO of the tenant firm.