SetSail Announces Revenue Acceleration Programs To Align Sales Behaviors With Specific Growth Objectives

Silicon Valley Startup Improves On Its Industry-leading Revenue Execution Platform With A Host Of New Ai And Workflow Enhancements

SetSail, the Revenue Execution platform for sales, has launched a library of machine learning powered Revenue Acceleration Programs that extend its intelligent signals engine. Combined, these two products form a complete solution for driving predictable revenue growth for B2B businesses and digitally transform their sales processes.

“Despite the maturity of the CRM space, running efficient sales programs has always been the Achilles heel of revenue organizations,” said Haggai Levi, the CEO of SetSail. “By introducing a new layer of program management on top of SetSail’s intelligent signals, we are making it easy for sales managers to guide their teams towards in-quarter goals. Just like ABM ushered us into the age of programmatic marketing, Revenue Acceleration Programs ensure teams can rally around specific growth objectives — with clear accountability and higher impact on key behaviors.”

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Turn Waste Into Value With Analytics

Trusting your data, telling stories about your success and knowing that every act, no matter how small, can help win the fight against waste was some of the advice shared by Queen of Raw and Topolytics, two gamechangers in waste management at the recent SAP Sustainability Summit panel discussion about orchestrating ecosystem innovation for impact.

“Zero waste can only be achieved with the help of data,” said Michael Groves, Founder and CEO of Topolytics, a data analytics business for waste managers. “Data shows public and private players exactly what is happening to their waste and will help them build better intervention options and create closed loops for recovery.”

Groves was one of the people on the boat hosting the Ocean Plastics Leadership Summit (OPLS) in 2019, a research expedition to better understand the scope of plastic pollution and to develop cross-industry solutions and partnerships to solve this global challenge over the next decade.

Seeing is believing

Whenever the ship approached clumps of sargassum seaweed, the participants would stop their meetings and jump into zodiac boats with their snorkeling gear. But they didn’t see any fish. And at first, they didn’t see much plastic either. That’s because it’s often not visible. Plastic in the ocean breaks down into small particles that are caught in seaweed and ingested by marine creatures.

“What you don’t see is the real problem,” says Groves, winner of the Circular Economy 2030 challenge sponsored by SAP and Google that year. A geographer who was appalled by the amount of plastic he encountered in South East Asia long before people began talking about the crisis, Groves believes waste is still not getting the attention it desperately needs.

While we may not actually see the damage, the data is irrefutable. An alarming 60 percent of waste produced in cities around the world gets dumped or leaked into the environment, and an equally alarming 61 percent of people globally don’t have access to proper waste management infrastructures. It’s a thorny problem because the waste value chain is very complex and opaque, with many private and public sector players and a significant informal sector around the world. To make matters worse, there is a huge mix of materials, each requiring different methods of recovery and recycling.

Realizing that money follows data, Groves developed a solution that uses analytics and machine learning to follow trash as it travels. Clear data and insights are fundamental to spurring investments in new infrastructure and innovation in the sector. With useful data available about what waste is where and in what quantity and quality, companies can then procure this waste much more effectively and bring the materials back into their production processes through platforms like SAP Ariba software.

Debunking myths

“Many companies think they know what’s going on with their waste, but they are usually surprised by the truth,” he says. “There is huge potential to unlock economic and social value that is currently just draining away!”

One person helping fashion retailers stop the drain is Stephanie Benedetto, co-Founder of Queen of Raw, a marketplace to buy and sell unused textiles, from organic cotton to some of the highest quality luxury deadstock fabrics that would otherwise be burned or buried.

Benedetto was inspired by her childhood experiences growing up in an immigrant family in the Garment District of New York. Her grandfather would collect unused clothes from the neighborhood and repurpose them into beautiful, fashionable items for local sale. It was a profitable, sustainable business that inspired her when she later became a corporate attorney on Wall Street, specializing in technology and sustainability. When the crash came in 2008, she decided to start her own company.

When Benedetto first started talking to brands and retailers about sustainability years ago, it was seen as nice to have. People responsible for sustainability were new in the position, and they did not have big budgets. Her first big challenge was debunking the myth that sustainability has to cost a lot of money.

She realized that retailers became paralyzed when faced with objectives such as becoming 100 percent sustainable by 2030. “You wouldn’t know where to start on day one if you heard that. It’s too much, too fast,” she says. “We go to the retailers and help them pinpoint the valuable waste in their supply chain. We look at their unused inventory and their deadstock. We help them sell it on the marketplace, and we provide tools to minimize waste going forward.”

Once the retailers are making money on their unused inventory, she explains, they can start putting their savings into doing other good work such as paying their workers better wages and using innovative technology and sustainable materials without increasing overall capex expenditure.

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How Staple is Helping to Power the First Mile of Data Processing

We talked to Ben Stein, CEO at Staple about converting documents into structured data and here is what he said about it.

First of all, how are you and your family doing in these COVID-19 times? 

Ben Stein: We are all doing well, thank you! Like most of the world, all team members have been involuntarily separated from friends and family. Our team is decentralized across Singapore, Vietnam, India and Sri Lanka. Our relationships have shifted online, and that is something we have grown accustomed to. Thankfully our team, our families and our friends are all doing well.

Tell us about you, your career, how you founded Staple.

Ben Stein: I previously worked with KPMG in Australia, Europe and North America for almost a decade, then in various corporate positions in London and Singapore. After working with clients in banking, energy, manufacturing and real estate, I noticed persistent inefficiencies in both enterprises and SMEs around data management. I left my CFO position at the time to explore how deep technology (“deep tech”) might present potential solutions to these inefficiencies. I joined EF (joinef.com), where I met my co-founder, Josh, a Ph.D. computer scientist. Together we met with more than 150 companies to understand their most pressing pain points, and we built Staple to address them. 

Staple’s solution can read, interpret, extract and reconcile data from semi-structured and unstructured documents, regardless of layout or language. Currently, we support more than 90 languages, and we are helping customers process data-heavy workflows in Thai, Vietnamese, Japanese and Indonesian. 

How does Staple innovate? 

Ben Stein: There is a lot of hype around big data, RPA, AI and analytics and their potential to rapidly accelerate the digitalization of business. What many don’t appreciate is that these technologies can’t function without a core ingredient: clean, structured data. RPA and bots are fantastic innovations, but they can only work with structured data. There is so much reliance on data, yet enterprises struggle to access, unlock and use it at scale because the data is not available in a standardized, accessible format. Without structured data, RPA bots cannot function, analytics tell an incomplete story, and information for decision making is either not timely, inaccurate, or not useful. 

Many businesses are unable to reap the benefits of automation technologies as they cannot cross the divide between structured system needs and the unstructured or semi-structured realities of business. It’s the classic adage of “garbage in, garbage out”: unless meaningful, accurate, standardized data is ingested from the outset, RPA and automation implementations will fail. It’s important that digitalization agendas have proper regard for the “first mile of data processing.” 

We dedicate a lot of effort to building software that employees actually enjoy using, as opposed to software that employees are forced to use. We don’t think there should be a distinction between software for SMEs or software for the enterprise; it should all just be software to be more productive. We also have a sharp focus on developing solutions that anybody – from the most junior employee to a highly technical CTO – can use. We’re working on tools that allow non-technical users to develop new AI models without touching a line of code. This introduces a level of flexibility that was previously out of reach for many users.

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project44 Acquires ClearMetal Inc.

project44 announced that it will acquire San Francisco-based ClearMetal, a market leader in international supply chain visibility and predictive analytics for enterprises. ClearMetal’s patented artificial intelligence (AI) enables organizations to optimize their supply chains and provides customers with easy access to trusted, live information about their orders and shipments. project44’s acquisition of ClearMetal is the latest growth milestone preceded by building on tremendous 135% YoY growth, crossing the $50M ARR mark, and being named a Leader in the latest Gartner Magic Quadrant. This acquisition places project44 on the cutting edge of logistics AI, enabling customers to improve agility, and resiliency across their global and multi-modal supply chains.

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Breinify announces $11M seed to bring data science to the marketing team

Breinify is a startup working to apply data science to personalization, and do it in a way that makes it accessible to nontechnical marketing employees to build more meaningful customer experiences. The company announced a funding round totaling $11 million.

The investment was led by Gutbrain Ventures and PBJ Capital with participation from Streamlined Ventures, CXO Fund, Amino Capital, Startup Capital Ventures and Sterling Road.

Breinify co-founder and CEO Diane Keng says that she and co-founder and CTO Philipp Meisen started the company to bring predictive personalization based on data science to marketers with the goal of helping them improve a customer’s experience by personalizing messages tailored to individual tastes.

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Pangaia introduces ‘digital passports’ in apparel

Apparel brand Pangaia has today partnered with traceability solutions provider Eon and will leverage its CircularID Protocol to introduce ‘digital passports’ in its garments.

With product-specific QR codes linked to a cloud-based platform, Pangaia customers will be able to scan items and access a digital archive of lifecycle data including carbon emissions output and water usage.

Natasha Franck, founder and CEO of Eon, said: “Through product digitisation, Pangaia is redefining the relationship between brands, products and customers – pioneering an entirely new model for sustainable commerce and taking a mission-critical step towards realising a fully circular business model.”

LiveEO Enters Strategic Partnership with Planet, Setting Preconditions for Rapid Expansion

Earth observation company LiveEO has today announced its partnership with Planet, the leading provider of global, daily satellite imagery and insights. The strategic move empowers LiveEO to massively scale its infrastructure monitoring operations around the globe, avoiding friction in the procurement of satellite imagery.

During the past 12 months, LiveEO has been able to quadruple its customer base by establishing more client relationships outside of Europe, especially in the United States and Australia. In order to accommodate its growing customer base, LiveEO doubled the size of its engineering team and significantly strengthened its infrastructure, with the new partnership being a central component of this effort.

Different from the traditional reseller model prevalent in the satellite data industry, as a part of the Powered by Planet program, LiveEO is able to purchase satellite imagery up front, with no predefined areas of interest (AOIs). Allowing the data usage to be freely and seamlessly adjusted to current customer needs.

“From day one we developed our tech stack with a clear focus on scalability”, says Daniel Seidel, Co-Founder and Co-CEO of LiveEO. Since every newly onboarded customer entails vast amounts of data to be acquired and processed, and with quick turnaround times being one of LiveEO value propositions, velocity is key. “To build scalable applications, we need great APIs to purchase data on a recurring basis without human interaction. In this regard, we consider Planet a role model for other satellite operators in the industry, which at times still handle the ordering process via email.” concludes Seidel.

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SetSail Leverages AI To Empower Sales & Increase Team Productivity

SetSail, an AI-powered sales tracking, motivation and empowerment platform, leverages AI to identify buying signals and provide recommendations for sales teams, and help them follow the best path of action to closing deals faster and building good selling habits.

 

Back-Of-The-Box Details

SetSail is designed to help sales teams automate their sales data and buying signals in their CRMs to improve sales team behavior, helping salespeople at every level of an organization improve their productivity and performance while closing deals. SetSail’s signal-based coaching app also uses these signals to help managers coach their reps to close deals and generate revenue more efficiently.

The signal-based platform offers three different solutions, including:

  • SetSail Collect, which integrates all sales data from disconnected sources into a single view in a CRM or any other platform, and allows salespeople to pull relevant information for specific buyer interactions;
  • SetSail Discover, a solution that analyzes customer interactions with salespeople and provides 370+ prescriptive buying signals to help them uncover what is driving the buyer’s deal and decide what actions to take; and
  • SetSail Accelerate, a custom program that uses real-time micro-incentives to increase sales team motivation, rewarding reps for the right actions throughout the customer relationship.

Who It’s For

SetSail is designed for everyone involved in the sales cycle, including CROs, sales managers, sales reps and more, at organizations of all sizes.

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Coca-Cola chooses Shippeo to provide real-time visibility for its road transport

The real-time visibility of Coca-Cola HBC’s transportation network provided by Shippeo will allow the company to further improve both internal and external logistics efficiency, by improving collaboration with its carriers.

The deployment of the technology aims to improve service levels, while at the same time reduce transportation costs, due to a reduction in waiting times, improved flexibility, and resources planning.

Valentin Radu, Logistics Technology & Automation Manager at Coca-Cola HBC said: “The scale and complexity of our operation creates a large administrative effort to coordinate with carriers, which makes handling exceptions time consuming. By implementing Shippeo’s real-time transportation visibility platform, we aim to streamline our logistics operations while further improving on-time deliveries to our customers.”

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Data prep platform Explorium raises $75M

Explorium, a startup developing an automated data and feature discovery platform, today closed a $75 million funding round led by Insight Partners with participation from existing investors. The capital, which brings the company’s total raised to $127 million to date, will be used to expand Explorium’s platform after a year in which it doubled its customer base and more than quadrupled revenue, according to CEO Maor Shlomo.

In machine learning, a feature is a property or characteristic of the phenomenon being observed. Features are usually numeric, but structural features such as strings and graphs can be used in pattern recognition. Feature engineering — the process of using domain knowledge to extract features from raw data via data-mining techniques — is often arduous. According to a Forbes survey, data scientists spend 80% of their time on data preparation, and 76% view it as the least enjoyable part of their work. It’s also expensive. Trifecta pegs the collective data prep cost for organizations at $450 billion.

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How Parcel Perform is reimagining the logistics experience for businesses and end-users

The logistics market in Southeast Asia is expected to reach $55.7 billion by 2025, at a CAGR of 5.5 percent. Some of the key catalysts in this market include the rapid growth of e-commerce, enhanced trade across the region, and accelerated infrastructure development. This does not come without challenges, however. Last-mile deliveries can be difficult due to complexities in geographical terrain, poor roadways, and transport systems like railways.

Technological innovations in logistics and freight management are meant to address these opportunities. In this TechNode Global Q&A with Dr. Arne Jeroschewski, the Founder and Chief Executive Officer of Parcel Perform, we learn how innovations in logistics are improving the user experience and ultimately enhancing value for both businesses and consumers.

A winner at the ORIGIN Innovation Awards — Startup Awards in Logistics and LMF, Parcel Perform is a carrier-independent delivery experience platform for e-commerce merchants and their end-customers covering 700+ logistics carriers worldwide. Established in 2016, the company has offices in Singapore (HQ), Vietnam, and Germany with a global team of 70+ experts in e-commerce and logistics management.

Before founding Parcel Perform, Dr. Jeroschewski was Vice President for Business Development at DHL eCommerce Asia Pacific, where he led the development of e-commerce logistics products tailored for online marketplaces and merchants as well as market entries for DHL eCommerce throughout Asia. Before that, he was Vice President at Singapore Post’s SP eCommerce, where he was responsible for the B2C e-commerce businesses including vPost and Omigo. In 2012, Arne was the founding CEO of ZALORA, South East Asia’s leading fashion e-commerce player across 8 markets.

Arne was a long-time management consultant at McKinsey & Company where he worked on technology projects in Europe, Africa, and Asia. Arne is a trained economist with a PhD in regulatory economics.

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Why Inclusive Entrepreneurship Could Mean More Time For Healthcare Employees To Save Lives

Throughout the pandemic, businesses and individuals have been reminded of the fragility of time and the notion that it can never be recovered. With pre-pandemic routines shifting, organizations and their employees are now questioning how to make more time for the things that matter most. Perhaps the industry hit hardest by this is one that is arguably the most in need of more time— healthcare.

Healthcare employees traditionally must complete lots of administrative work because of strict industry regulations. This has only amplified during the pandemic. Additionally, healthcare professionals often waste time doing indirect patient care like searching for medical supplies or time reporting for regulatory and billing use. Unfortunately, this pattern hinders care efficiency and takes focus away from the patient.

High-intensity and unsafe work environments have quickly revealed the pivotal role healthcare organizations play in decision-making that protects the needs of frontline employees. With 42% of physicians experiencing burnout, Kishau Rogers launched healthcare startup Time Study already knowing the solution must not just improve operational efficiency, but it must enhance the lives of the people treating the patients.

Valuing the Time of Healthcare Employees

Time Study is a system of time management that focuses on the heartbeat of the healthcare industry: humans. The cloud solution uses intelligent time tracking to monitor how physicians and other healthcare employees spend their time at work. This equips hospitals with data insights to make human-centered business decisions that improve the employee and patient experience.

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Omnichannel Insights for Marketing Decision Support

An old adage goes like this: 50% of the money spent on marketing programs is wasted. But which 50%?

That question can finally be answered in the new era of advanced analytics – and by Adverity Marketing Data Analytics Platform. No more tedious number crunching on spreadsheets for marketing teams, thanks to this popular solution on SAP Store. Now, data-driven marketers can take advantage of fully automated data integration for a single source of truth on the performance of their programs and move past “point-in-time” performance monitoring toward insights that lead to tangible actions.

I spoke with Sven Woeltjen, partner manager with Adverity GmbH, to find out more about the solution’s impact on the life of a marketer.

“From every source – paid search, social media, direct demand-generation campaigns, events – you get different data in different formats,” Woeltjen said. “Everyone is asking for ROI, and no one has the answer. Many marketing teams work in silos. Harmonizing and cleansing the data from all the different sources is a labor-intensive process that’s prone to mistakes, and typically takes many days. As a result, marketers spend more time wrangling data than they do interpreting it, meaning they miss out on opportunities to optimize performance and improve ROI. They don’t have current info and can’t produce timely reports. Those are the problems Adverity solves.”

Reporting in Near Real Time

With the Adverity solution, marketers can create omnichannel overviews in near real time. Integration with SAP ERP and SAP Marketing Cloud allows them to enrich their insights by pulling in data from finance or HR or whatever interests them, Woeltjen continued. The ability to build ad-hoc reports on their own enables them to explain to the business the impact of what they’re doing whenever they’re asked. Report templates and data visualization tools make that even easier. “With tangible results based on real data, they can turn their attention to the next program or campaign rather than the next report,” he added. “By better understanding what works and what doesn’t, they can make decisions from a strategic standpoint.”

In fact, Woeltjen speaks from experience after spending his career in marketing, including tenure with an agency where he was using the Adverity solution himself. He ended up approaching the company about potential partner opportunities and, not long after, joined the firm and worked with its most important partner, SAP.

Understanding Marketing Challenges – as Marketers

I asked Woeltjen to tell me more about the company, which was established in 2015. Like him, the founders themselves were working in the marketing field, experiencing the data challenges , and saw an opportunity. The company has grown steadily since then, largely by building relationships, understanding customers’ needs, and building new features accordingly – as all good marketers do. For example, an augmented analytics module uses machine learning to analyze large amounts of data, identify trends and anomalies, and deliver suggestions for improvements that enable marketers to proactively address issues affecting performance.

Teamwork is a crucial factor for Adverity. The implementation team sits next to the developers to promote collaboration. Even as they have transitioned to working from home, the relationships are in place. Now with about 250 employees, based largely in Austria, the U.S., and the UK, the company plans to double in size this year. With offices in London and New York City already, Adverity plans to establish a presence on the West Coast of the U.S. and in the Asia-Pacific-Japan region. As a digital company with most employees working remotely, not just during the pandemic, he commented, “We can hire the best people.”

And speaking of the pandemic, Adverity has been in the position to cushion some of the fallout for customers suddenly making the transition to online marketing. “Here in Germany, for example, many stores have been closed for a full year,” Woeltjen remarked. “People have had to get used to buying more online, causing many smaller businesses – distilleries, for example – to sell directly to consumers and use their marketing budgets to acquire customers online. We can help them with our tool.”

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DataRobot’s Zepl acquisition bridges the AI divide

DataRobot revealed yesterday during an online AI Experience Worldwide conference that it has acquired Zepl as part of a larger effort to enable data scientists to customize AI models developed on its platform. Zepl created an open source Apache Zepyl notebook that enables data scientists to collaboratively develop and analyze code written in Python, R, or Scala.

DataRobot also unveiled a slew of updates, including an ability to clone, edit, and reconfigure machine learning blueprints created using the AutoML framework at the core of its platform for constructing AI models. That Composable ML feature enables organizations to integrate their own custom training code with the AutoML framework employed by DataRobot, senior VP Nenshad Bardoliwalla said. “Data scientists can now tweak our AI models,” he added.

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