Ecommerce Tricks

Bill Gates joined us at TechCrunch Sessions: Climate 2022 last week to discuss his priorities in terms of investment projects and technological breakthroughs needed to effectively address climate change. Gates provided an updated picture of where we’re at compared to the context in which he wrote and published his 2021 book, “How to Avoid a Climate Disaster.”

Gates started off by providing his thoughts on the relative performance metrics of the world as it faced another global threat — the ongoing COVID-19 pandemic:

Well, the pandemic — it's very easy. It's 1,000 times easier to stop things from becoming pandemics than it is to solve climate change. And you have some countries who have less than 10% of the deaths of, say, the U.S. Yeah, so the U.S. was expected to do the best, and we did a terrible job. We didn't diagnose people early … in the first 100 days we'd let it become widespread. Whereas people like Australia, New Zealand, Taiwan, a bunch of exemplars got into action, even though they spend way, way less money on their public health systems.

The framing of the pandemic as a far “easier” challenge to address than climate change would seem to indicate a degree of pessimism about our chances, but Gates then pointed out the progress in certain areas that has occurred since he hosted a site gathering at the 2015 global climate talks in Paris. That led to the formation of Breakthrough Energy, the umbrella organization founded by Gates to foster climate action in a number of ways, including through its venture subsidiary, Breakthrough Energy Ventures:

Twitter's board wants the $44 billion Elon Musk takeover completed, which is why it's asking its shareholders to approve the deal, according to a new regulatory filing.

The board states in the document filed with the U.S. Securities and Exchange Commission on Tuesday that it “unanimously recommends that you vote (for) the adoption of the merger agreement.”

The company's board also unanimously recommended the shareholders to approve “the compensation that will or may become payable by Twitter to its named executive officers in connection with the merger” and “the adjournment of the special meeting, from time to time, to a later date or dates, if necessary or appropriate, to solicit additional proxies if there are insufficient votes to adopt the merger agreement at the time of the special meeting.”

At the time of writing, Twitter's share price is around $38.12 — much lower than Musk's offer price of $54.20 a share. Notably, the company's market cap has dropped below $30 billion. So a $44 billion deal is really beneficial for all existing shareholders.

The deal is still hanging in balance over the issue of the number of bots on the platform. Earlier this month, Twitter gave Musk access to its full “firehose” — a stream of Tweets without any restriction — to check for the percentage of bots on the social network.

Earlier on Tuesday, speaking at the Qatar Economic Forum, Musk said that there are still “unresolved matters” over the deal.

“There is the question of, will the debt portion of the round come together and then will the shareholders vote in favor,” he noted.

The Tesla CEO said that he doesn't want to head Twitter, but wants to focus on “driving the product.” This echoes a similar sentiment to his statements at the Twitter all-hands meeting last week.

Flagstar Bank, one of the largest financial service providers in the United States, has notified more than 1.5 million customers of a data breach in which Social Security numbers were stolen — its second incident in two years.

In a letter sent to those affected, Michigan-headquartered Flagstar revealed that hackers breached its corporate network between December 3 and December 4, 2021. After an investigation, the bank discovered on June 2, 2022 that the threat actors accessed sensitive customer details.

“Flagstar recently experienced a cyber incident that involved unauthorized access to our network,” the company said in the letter. “Upon learning of the incident, we promptly activated our incident response plan, engaged external cybersecurity professionals experienced in handling these types of incidents, and reported the matter to federal law enforcement.”

TechCrunch asked Flagstar why it took the company almost six months to detect the data breach but the company declined to answer. It also declined to confirm which of its systems were breached during the incident or the specific number of customers affected.

However, based on information submitted to the Office of the Maine Attorney General, the data breach affected 1,547,169 people in the United States.

This isn’t the first time Flagstar has been compromised. In January 2021, the company became one of the many victims of the Accellion hack that saw vulnerabilities in the vendor’s legacy file transfer appliance (FTA) exploited to steal corporate documents. In the case of Flagstar, stolen data included names, Social Security numbers, addresses, tax records, and phone numbers.

The Accellion breach, which also claimed Morgan Stanley, cybersecurity firm Qualys and grocery giant Kroger as victims, has since been linked to the notorious Clop ransomware gang.

Data quality has been shaping up as a salient and increasingly critical part of the world of data science: enterprises are sitting on growing troves of information, but it's only useful if we can trust it to be accurate and usable. To that end, Validio, a startup building tools to improve and ensure data quality — specifically with tools that let users clean up data both stored in data warehouses and elsewhere, as well as in real-time — is announcing a seed round to mark its emergence from stealth. The Stockholm-based company has raised $15 million, funding that it plans to use for business and product development, R&D and to hire more talent.

Lakestar — the London-based VC that made early investments in companies like Facebook and Airbnb but has largely focused on backing promising-looking startups out of Europe (it also backed Skype, Spotify, Revolut and many others) — led this round, with J12 and several high profile individuals also participating.

(The list includes footballer (soccer player) Zlatan Ibrahimović, Snowflake's CMO Denise Persson, MongoDB's co-founder Kevin Ryan, Neo4j co-founder Emil Eifrem, DeepMind's head of product Mehdi Ghissassi and Kim Fai Kok & Dara Gill of angel collective Framtid.)

As with a lot of enterprise startups in stealth these days, Validio has been using the time since being founded in 2019 to work quietly on its product while also signing up customers for live deployments. Its clients range across the usual suspects in the big data game — those in marketing and commerce, security companies, and business intelligence. Validio doesn't disclose a lot of names but notes a few: Budbee and Babyshop in the e-commerce space; e-scooter company Voi; and electricity startup Tibber.

The challenge that Validio has identified an is addressing is one that CEO and co-founder Patrik Liu Tran said he encountered early on in his working life. A math and computer wiz, he graduated aged 16 from school and also accelerated his time at university, going to work in 2014/2015 while still a teenager consulting companies on AI projects. It was still a nascent endeavor in most places (frankly, it still is), and one of the big issues, apart from having few in the field prepared to go into companies to work on their problems, was the lack of integrity and quality in the data that they were trying to use in their machine learning models, he said.

“At every company that I was advising, the thing that caught my attention was the lack of trust in data, so much that people did very little with it, and there were no tools really to help with that,” he said in an interview. He added that the first efforts in identifying the issue and trying to deal with it (such as the Great Expectations open source project, created by the people who are behind Superconductive), were promising but do not focus on real-time information as much as data in warehouses.

“But machine learning resides in streams, not the warehouse,” he said. 

Beyond that, they are generally too reliant on rules that engineers and data scientists need to set and regularly monitor and tweak.

Validio's approach is to create not exactly low code tools. “We’re building for data engineers. It's very technical,” Tran said, slightly surprised with my question about that. “But we are focusing on a smooth user experience.”

That includes using machine learning and statistical analysis to “teach” a users' system to find and respond more quickly to the data coming through the pipeline; sets of rules that are created automatically for an engineer to use or to complement with customized rules; automated thresholds and auto-resolution capabilities, and more.

“We want to make it as seamless as possible for data engineers to do their work,” he added.

The company doesn't have a larger set of rules that it applies across the platform, but has built it to be tailored to individual organizations.

“‘Data quality' is hard to define. What is good for one company might be bad for another,” Tran said. “Data is never perfect and companies also need to start to accept that.” But the list of its investors (including some of those attached to strategic names) is a sign that others may well be singing the same tune with that kind of thinking, and how Validio specifically is building to address that: tools to improve data quality, but built for the real world.

There are a few other companies that have identified the market for data quality and are building to address that — including Great Expectations creator Superconductive, which raised $40 million earlier this year; along with heavyweights like Microsoft, SAS, and Talend — but for now Validio's approach is one that seems to be striking the right chord, enough to expand bets in what is still a young space.

“As data teams are increasingly shifting their focus toward data quality, we believe that Validio is uniquely positioned to become the next big global software player from Europe,” noted Stephen Nundy, Lakestar partner, in a statement. “Validio has built its platform with a unique architecture, enabling the management of data quality in data warehouses, lakes and streams both on the actual data and metadata in real-time. We look forward to supporting the stellar Validio team in their journey building a global data infrastructure leader.”

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Paige Thompson, a former Amazon employee accused of stealing the personal information of 100 million customers by breaching banking giant CapitalOne in 2019, has been found guilty by a Seattle jury on charges of wire fraud and computer hacking.

Thompson, 36, was accused of using her knowledge as a software engineer working in the retail giant's cloud division, Amazon Web Services, to identify cloud storage servers that were allegedly misconfigured to gain access to the cloud stored data used by CapitalOne. That included names, dates of birth, Social Security numbers, email addresses and phone numbers, and other sensitive financial information, such as credit scores, limits and balances.

Some one million Canadians were also affected by the CapitalOne breach.

Thompson also accessed the cloud stored data of more than 30 other companies, according to a superseding indictment filed by the Justice Department almost two years after Thompson was first charged, which reportedly included Vodafone, Ford, Michigan State University and the Ohio Department of Transportation.

Thompson was convicted under the Computer Fraud and Abuse Act, which prohibits a person from accessing a computer system without authorization. There was some question about her motives, which some said classed Thompson as a potential ethical hacker — the Justice Department said in May that it would no longer prosecute good-faith security researchers — but prosecutors said Thompson “exploited mistakes to steal valuable data and sought to enrich herself,” including using the servers she hijacked to plant and mine cryptocurrency.

The Seattle jury found Thompson not guilty of identity theft and charges relating to device access fraud.

The breach of CapitalOne's cloud data, much of it stored on Amazon's cloud, was one of the biggest hacks of the decade by size alone but also because of the sensitivity of the financial information. CapitalOne's security chief was replaced a short time after the breach became public, and in 2020, the banking giant was fined $80 million by U.S. federal regulators and ordered to improve its cybersecurity defenses, and was later ordered by a judge to pay close to $200 million in class action damages. CapitalOne made $28.6 billion in revenue during 2019, the year of its breach.

Thompson is expected to be sentenced in September.

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Share Mobility, which provides transportation solutions for companies, today announced that it closed a $12 million Series A led by Iron Gate Capital and Renewal Funds with participation from Employment Technology Fund, JobsOhio, Seamless Capital, and others. CEO Ryan McManus said that the goal with the new cash will be threefold: supporting growth, people, and product.

“The funding allows us to grow into our enterprise customers’ more than 2,000 locations across the country, and hire the right people to make it happen,” McManus told TechCrunch in an email interview. “We are well-positioned to expand our footprint in the areas they are asking us to expand, as well as add more features to our platform.”

Founded in 2016, Share was initially focused on autonomous vehicles. But it later pivoted to “mobility-as-a-service”; McManus says that the company found a product-market-fit during the pandemic.

“When people started to return to work and companies were in dire need of workers, we quickly realized that if companies are able to hire people that don't own cars, their hiring pool increases from 20% to 60%. And that was the revelation — to offer a service that helps employers get employees to work, to fill those job openings, and retain them,” McManus said. “We showed enterprise companies that they can solve their workforce shortage by providing transportation as an employee benefit. Companies like Google were already providing it as a perk for employees in major hubs, but as more enterprise companies stake their claim into regions like the Midwest, the need for reliable commuter transportation was clear.”

Transportation is a common employee perk among tech giants (excepting those under pressure from activist investors, perhaps). As of 2020, there were an estimated 1,020 private commuter shuttle buses in the Bay Area — a private transportation system worth more than $250 million. Some Silicon Valley buses travel as far as 55 miles from San Francisco to pick up workers daily.

The dramatic expansion of private shuttle programs reflects the pressures that the tech industry has put on major cities. In Silicon Valley in particular, high salaries have driven up housing prices, forcing white- and blue-collar workers to move farther away from their jobs. Absent affordable public transportation or shuttles, employees are forced to pay out of pocket to get to work. This disproportionately impacts low-income workers; according to the U.S. Department of Transportation, low-income Americans spend 37% of their income on commuting — a percentage that's likely to increase with rising gas prices.

Share develops tools designed to help smaller companies build their own shuttle-based transportation solutions, in a nutshell. The platform leverages a company's data to create and schedule routes and works with local fleet operators to provide vehicles and drivers, delivering a toolkit that allows for real-time vehicle tracking. (No word on whether drivers can opt out of tracking if they're concerned about the privacy implications.)

All the drivers Share works with are salaried, McManus said, and use different vehicles depending on a company's requirements. Customers get a dispatch team and rider hotline with live agent support.

“The workforce shortage is one of the biggest challenges facing enterprise companies today. HR departments have never before tapped into where their employees live to attract talent and better retain its current workforce,” McManus said. “We are enabling companies in any part of the country to have better, expanded access to talent through employee data that shows directly where their workers are coming from.”

The mobility-as-a-service market is expected to grow from $182.12 billion to $210.44 billion by 2026, according to Fortune Business Insights. Per McKinsey, investors have poured nearly $330 billion into more than 2,000 mobility companies since 2010.

But it isn't always smooth sailing. In 2020, Share lost 96% of its revenue nearly overnight as the pandemic put a halt to operations, McManus said. Even amidst the broader slowdown in tech, however, he asserted that Share is in a place to scale through its enterprise model, particularly as companies expand into Midwestern and Southern states. The company has expanded to 11 states with customers planning to add Share-powered routes in over 100 locations this year.

On the horizon is expanded work with municipalities. Share can work with cities to create mobility-as-a-service programs that function like on-demand ride-sharing, but with fleet vehicles, McManus explained. Cities can use their own vehicles or Share partners, mixing public and private transit to provide transportation to business parks and other places that municipal busses won't go.

Startups like Via are already doing this. But McManus thinks that Share's platform is sufficiently differentiated.

“As enterprise companies continue to battle inflation, worker shortages, supply chain issues, and other factors that directly impact its bottom line, it’s evident that the need for an economical, scalable solution to workforce challenges are critical. Improved access to transportation and commuter benefits can help close these gaps,” McManus said.

Tapping the new cash, Columbus, Ohio-based Share plans to increase the size of its workforce from 35 employees to 75 by the end of the year. To date, the company has raised $19 million in venture capital.

In the customer service arena in particular, enterprises are facing a historic labor shortage. Owing to burnout, flexibility, and customer satisfaction challenges, agents are quitting at a faster rate than in the past — a problematic trend in a high-turnover industry. According to a February 2022 Salesforce report, 71% of customer service agents have considered leaving their job in the past six months. The impact is becoming clear. Forrester's annual study on customer service found that 19% of brands in the year through April 2022 saw their customer experience rating fall — the highest proportion to drop in one year since the study's inception.

Vinay Saini and Niken Patel, the cofounder of Neuron7, say that they observed this firsthand — Patel in advisory roles at Deloitte and Fujitsu and Saini as the CFO and COO at Oracle software partner Serene. (Patel also worked at Serene, moving his way up from the role of EVP to CEO.) According to Patel, the organizations he and Saini consulted with often collected massive amounts of customer service data yet struggled to use it effectively, leading the data to become stale and unused.

“The real insight on how to [address customer] issues was spread across multiple silos — and, usually, in experts’ heads,” Patel told TechCrunch in an email interview. “They’d spend tons building knowledge bases, and search applications on top of the data, but those systems just weren't sophisticated enough to find resolutions to customer issues quickly and consistently.”

Frustration led Saini and Patel in 2020 to launch Neuron7, a startup that parses customer service records to help agents and technicians resolve product issues. As Patel describes it, Neuron7 uses natural language processing to guide users step by step, analyzing metadata from knowledge bases, product documentation, customer support call logs, and transcripts to create a “collective intelligence” that can help diagnose and solve problems.

Neuron7 isn't the first to market with a recommendation engine for customer service — far from it. Beyond incumbents like Salesforce, the vendor has rivals in Zingtree and Talla, which combines customer content with automation and machine learning to help agents get at information they need. Ultimate.ai also provides an AI-driven service that delivers real-time help to staff dealing with customer queries.

It's not surprising that the segment is rife with competition. According to one estimate, customer service is a $350 billion-a-year industry — and the stakes are high. Ninety percent of Americans responding to a 2020 Microsoft said that they use customer service as a factor in deciding whether or not to do business with a company; 58% said they'll switch companies because of poor customer service.

But Patel notes that Neuron7 can power self-service portals for both customers and employees beyond the customer service division. That's one differentiator, in his mind — the other being Neuron7's algorithmic innovations. Investors were evidently won over by the pitch, with Battery Ventures and Nexus Venture Partners co-leading Neuron7's $10 million Series A (which closed today).

Drawing on existing systems like Salesforce Service Cloud, ServiceNow, Microsoft Dynamics 365, Neuron7 attempts to understand the context of a question to find an answer from within a body of customer service documents. To inform future recommendations, the platform also tries to capture how technicians diagnose and solve issues, in part by monitoring data streams from relevant connected devices.

“We believe it’s important for AI to go way beyond analytics and high-level AI predictions. We don't want to just give a report card that shows how service organization is doing — we want to help change the report card by impacting the most crucial service metrics,” Patel said. “Customer service data is often siloed across geographic locations, product areas, and even within different customer service departments and systems. Neuron7 solves an expensive problem for IT, by putting it to work without developing custom search applications or funding expensive data integration and curation projects .. The beauty of AI is that it continuously improves with each outcome — nothing ever gets stale.”

Patel didn't reveal the number of customers Neuron7 is currently servicing, but named Sofftek, an IT and business process consultancy, as one of them. He said that the proceeds from the Series A will go toward client acquisition efforts as well as expanding Neuron7's 20-person workforce, with a focus on the go-to-market and product teams.

“The pandemic hit customer service organizations very hard by increasing employee turnover, and with each departure, years of expertise leave the team. It also forced companies to not roll trucks and send field service engineers on site, unless absolutely necessary,” Patel said. “These situations make customer service productivity and collective intelligence building tools like Neuron7 extremely valuable due its ability to make new employees as productive as experts and to increase customer service KPIs across all tiers of service. Unless customer service productivity and profitability go out of style, Neuron7 will be fine.”

Neuron7 has raised a total of $14.7 million to date inclusive of the Series A.

The advantages of software that automates everyday workflows don't have to be spelled out. In theory, it's a major labor saver — not to mention wallet-friendly. But perhaps because automating back-office tasks is low-hanging fruit, the market for workflow automation software has become overcrowded in recent years. UiPath, one of the largest automation vendors, saw its market cap drop from $35 billion to $15 million within the span of a year. And a number of smaller players, including Signavio, Intellibot MyInvenio, Clear Software, and Servicetrace, were snatched up by larger tech firms.

Pascal Weinberger, the CEO of Bardeen, believes the software automation industry has two main challenges to overcome: ease of use and discovery of automation. Currently, to implement automation, companies buy tools and then typically hire large consulting firms to actually implement automation with the tools, Weinberger asserts. Post-implementation, companies find that these tools are tough to use, particularly when it comes to discovering which processes to automate — a step known as process mining. 

“This leads to a lot of friction and makes it hard for the end-users to actually automate their work,” Weinberger told TechCrunch via email. “Existing tools are too hard to use for the end-users who actually do the processes which need to be automated.”

Weinberger has a dog in this fight; Bardeen is an automation vendor. But while he acknowledges that the market is nearing the saturation point, he argues that Bardeen is positioned for success because it solves many of the problems with process automation platforms today.

“Bardeen is working to bring … automation to the masses. We do so by making it very easy for our users to build and customize their unique workflow automations across their software-as-a-service tools,” Weinberger said. “Bardeen [can] enable … IT departments to focus on what matters, while end users are enabled to identify, automate, and maintain their own automation for their unique workflows.”

Weinberger co-founded Bardeen in 2020 alongside Artem Harutyunyan, with whom he shares a curious work history. Weinberger previously studied neural anatomy as an intern at the Max Planck Institute for Brain Research before co-launching Gaia Solutions, a startup monitoring crop conditions through satellite imagery and soil sensors. Harutyunyan was a senior fellow at CERN, focusing on software, and later a senior director of product and engineering at Mesosphere.

The inspiration for Bardeen came from Weinberger's and Harutyunyan's personal experiences running engineering organizations, according to Weinberger, where they had to complete many “mundane” development tasks every day. With Bardeen, users download a browser extension and select from a range of automations the tasks they want to automate, like scraping data from the web and copying it to a spreadsheet or reminding participants about an upcoming meeting. They can also create custom automation workflows or modify prebuilt ones to fit their needs.

“Bardeen has a huge advantage … here because the system operates inside the user’s browser. All the data processing and storage is done on the edge — i.e., inside the user’s browser,” Weinberger explained. “We don’t actually see, store, or access any user’s data directly. This approach is quite unique and none of the competitors do that — they all use traditional cloud-first model. We essentially built a platform for automating workloads in a privacy-preserving way.”

Weinberger sees AI modules for things like text-to-speech and optical character recognition and Smart Suggestions, which recommends automations to users based on the current context, as another key differentiator. He says that the goal is to evolve Smart Suggestions over time so that it learns and suggests “any automation that can help save time.”

Ease of use is certainly important when it comes to automation. According to a recent survey from Creatio, despite the fact that automation is becoming more common within companies, more than one-third of business technology workers say that slow or no adoption of automation from their coworkers is a top challenge in their line of work.

“We make it really easy not only to create an automation, but also to share it and make it accessible to the team members and people you work with every day. We built more integrations with the most commonly used software-as-a-service platforms on the market, for example Slack, Zoom, Google Sheets, Airtable, Notion, and ClickUp,” Weinberger added. “We’re working towards making it feel like magic … [the goal is] automating the automations such that non-technical users can, without any effort or prior knowledge, identify, build and share their workflow automations.”

Since the public launch of Bardeen in February, Weinberger says that the platform has grown to more than 25,000 users. He declined to share revenue, emphasizing that Bardeen is focused on expansion.

While Bardeen might face a challenge from Magical, which takes a similar edge, browser-based approach to automation, Weinberger didn't express concerns. No doubt boosting his confidence is the $15.3 million Series A that Bardeen closed today, which was led by Insight Partners with participation from existing investors 468 Capital and FirstMark Capital. It brings the company's total raised to $18.8 million.

Weinberger expects Bardeen will hire on the engineering, AI, and growth side of its 11-person team in the next year. 

“Our main competitors are software-as-a-service automation tools like Zapier, as well as incumbent … tools like UiPath, Automation Anywhere, etc.,” he said. “Bardeen is well-positioned to help its users to increase their efficiency at work and can therefore benefit from the increasing need for more automation and digitalization due to the pandemic and other pressure factors at this current time,” he said.