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Tag Archives: Million

Soci raises $80 million to power data-driven localized marketing for enterprises

January 22, 2021   Big Data

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Soci, a platform that helps brick-and-mortar businesses deploy localized marketing campaigns, has raised $ 80 million in a series D round of funding led by JMI Equity.

The raise comes at a crucial time for businesses, with retailers across the spectrum having to rapidly embrace ecommerce due to the pandemic. However, businesses with local brick-and-mortar stores will still be around in a post-pandemic world. By focusing on their “local” presence, including offering local pages (e.g. Facebook) and reviews (e.g. Google and Yelp), businesses can lure customers away from Amazon and its ilk. This is where Soci comes into play.

Founded in 2012, San Diego-based Soci claims hundreds of enterprise-scale clients, such as Hertz and Ace Hardware, which use the Soci platform to manage local search, reviews, and content across their individual business locations. It’s all about ensuring that companies maintain accurate and consistent location-specific information, which can be particularly challenging for businesses with thousands of outlets.

“For multi-location enterprises, the ability to connect with local audiences across the most influential marketing networks like Google, Yelp, and Facebook was critical to keeping their local businesses afloat through the pandemic,” Soci cofounder and CEO Afif Khoury told VentureBeat.

Moreover, Soci offers analytics that can help determine which locations are performing best in terms of social reach and engagement, integrating with all the usual touchpoints where businesses typically connect to customers, such as Facebook, Yelp, and Google.

“Soci is now housing and analyzing all of the most critical marketing data from every significant local marketing channel, such as search, social, reviews, and ads,” Khoury continued.

Above: Soci: Local marketing data

Soci had previously raised around $ 35 million, and with its latest cash injection the company plans to double down on sales and M&A activity. Its lead investor hints at the direction Soci is taking, given that JMI Equity is largely focused on enterprise software companies like financial planning platform Adaptive Insights, which Workday acquired a few years ago for more than $ 1.5 billion.

Looking to the future, Soci said it plans to enhance its data integrations, spanning all the common business tools used by enterprises, to build a more complete picture that meshes data from the physical and virtual worlds.

“As Soci continues to integrate with other important ecosystems and technologies such as CRM, point-of-sale, and rewards programs, it will begin to effectively combine online and offline data and deliver an extremely robust customer profile that will enrich the insights we provide and enable much more effective marketing and customer service strategies,” Khoury said.

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Equifax will pay $640 million for Kount’s AI-driven identity and fraud prevention tools

January 9, 2021   Big Data
 Equifax will pay $640 million for Kount’s AI driven identity and fraud prevention tools

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Equifax announced today that it would pay $ 640 million to acquire Kount, a company that uses artificial intelligence to drive its fraud prevention and digital identity services. In a press release, Equifax executives said the deal would allow the company to further expand into these markets.

Kount uses AI to analyze 32 billion transactions across 17 billion devices. As the system builds its intelligence, it is shifting from just analysis to predictive modes with the goal of helping companies prevent digital fraud.

“As digital migration accelerates, managing authentication and online fraud while optimizing the consumer’s experience has become one of our customers’ top challenges,” said Equifax CEO Mark Begor in a statement. “Our data and technology cloud investments allow us to quickly and aggressively integrate new data and analytics assets like Kount into our global capabilities and bring new market-leading products and solutions to our customers.”

Kount, founded in 2007, is representative of the hopes enterprises have that AI and machine learning can be used to help scale defenses to meet the rising challenges and resources behind cyberattacks.

In this case, Kount’s AI determines the trustworthiness of any identity used to create an account, attempt to login a, or make a payment. By allowing businesses to fine-tune the level of trust they want in their systems, they can decide on the percentage of transactions that are blocked and transferred to customer service.

The goal is to lower that percentage, which accelerates the rate of transactions approved, while still minimizing fraud and chargebacks. Equifax said Kount products would eventually become part of its own Luminate fraud platform.

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Starburst raises $100 million to take on data lake rivals

January 8, 2021   Big Data
 Starburst raises $100 million to take on data lake rivals

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Starburst Data has raised $ 100 million as the data analytics company continues to ride the surge in data lakes. Andreessen Horowitz led the round, which included Index Partners, Coatue, and Salesforce’s venture capital arm.

The funding comes just six months after Starburst raised $ 42 million, bringing its total to $ 164 million for a valuation of $ 1.2 billion. And the latest announcement came on the same day another data lake company, Dremio, announced it had raised $ 100 million.

So what’s this arms race all about? As companies grapple with growing amounts of information, data lakes allow them to pool structured and unstructured data in one spot, which then facilitates the movement and processing of that data.

“We believe we are solving the biggest problem that the big data era couldn’t: offering fast access to data, regardless of where it lives,” Starburst CEO Justin Borgman wrote in a blog post.

In the case of Starburst, it’s built on Presto, an open source project developed at Facebook. Indeed, three of Starbursts’ cofounders are from Facebook, where they worked on the project.

Starburst began life as Hadapt, a startup founded by Borgman. Teradata acquired Hadapt in 2014 but spun Starburst off in 2017. Along the way, Hadapt-Starburst shifted its focus from Hadoop to Presto.

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Graphcore raises $222 million to scale up AI chip production

December 29, 2020   Big Data

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Graphcore, a Bristol, U.K.-based startup developing chips and systems to accelerate AI workloads, today announced it has raised $ 222 million in a series E funding round led by the Ontario Teachers’ Pension Plan Board. The investment, which values the company at $ 2.77 billion post-money and brings its total raised to date to $ 710 million, will be used to support continued global expansion and further accelerate future silicon, systems, and software development, a spokesperson told VentureBeat.

The AI accelerators Graphcore is developing — which the company calls Intelligence Processing Units (IPUs) — are a type of specialized hardware designed to speed up AI applications, particularly neural networks, deep learning, and machine learning. They’re multicore in design and focus on low-precision arithmetic or in-memory computing, both of which can boost the performance of large AI algorithms and lead to state-of-the-art results in natural language processing, computer vision, and other domains.

Graphcore, which was founded in 2016 by Simon Knowles and Nigel Toon, released its first commercial product in a 16-nanometer PCI Express card — C2 — that became available in 2018. It’s this package that launched on Microsoft Azure in November 2019 for customers “focused on pushing the boundaries of [natural language processing]” and “developing new breakthroughs in machine intelligence.” Microsoft is also using Graphcore’s products internally for various AI initiatives.

 Graphcore raises $222 million to scale up AI chip production

Earlier this year, Graphcore announced the availability of the DSS8440 IPU Server, in partnership with Dell, and launched Cirrascale IPU-Bare Metal Cloud, an IPU-based managed service offering from cloud provider Cirrascale. More recently, the company revealed some of its other early customers — among them Citadel Securities, Carmot Capital, the University of Oxford, J.P. Morgan, Lawrence Berkeley National Laboratory, and European search engine company Qwant — and open-sourced its libraries on GitHub for building and executing apps on IPUs.

In July, Graphcore unveiled the second generation of its IPUs, which will soon be made available in the company’s M2000 IPU Machine. (Graphcore says its M2000 IPU products are now shipping in “production volume” to customers.) The company claims this new GC200 chip will enable the M2000 to achieve a petaflop of processing power in a 1U datacenter blade enclosure that measures the width and length of a pizza box.

The M2000 is powered by four of the new 7-nanometer GC200 chips, each of which packs 1,472 processor cores (running 8,832 threads) and 59.4 billion transistors on a single die, and it delivers more than 8 times the processing performance of Graphcore’s existing IPU products. In benchmark tests, the company claims the four-GC200 M2000 ran an image classification model — Google’s EfficientNet B4 with 88 million parameters — more than 32 times faster than an Nvidia V100-based system and over 16 times faster than the latest 7-nanometer graphics card. A single GC200 can deliver up to 250 TFLOPS, or 1 trillion floating-point-operations per second.

 Graphcore raises $222 million to scale up AI chip production

Beyond the M2000, Graphcore says customers will be able to connect as many as 64,000 GC200 chips for up to 16 exaflops of computing power and petabytes of memory, supporting AI models with theoretically trillions of parameters. That’s made possible by Graphcore’s IPU-POD and IP-Fabric interconnection technology, which supports low-latency data transfers up to rates of 2.8Tbps and directly connects with IPU-based systems (or via Ethernet switches).

The GC200 and M2000 are designed to work with Graphcore’s bespoke Poplar, a graph toolchain optimized for AI and machine learning. It integrates with Google’s TensorFlow framework and the Open Neural Network Exchange (an ecosystem for interchangeable AI models), in the latter case providing a full training runtime. Preliminary compatibility with Facebook’s PyTorch arrived in Q4 2019, with full feature support following in early 2020. The newest version of Poplar introduced exchange memory management features intended to take advantage of the GC200’s unique hardware and architectural design with respect to memory and data access.

Graphcore might have momentum on its side, but it has competition in a market that’s anticipated to reach $ 91.18 billion by 2025. In March, Hailo, a startup developing hardware designed to speed up AI inferencing at the edge, nabbed $ 60 million in venture capital. California-based Mythic has raised $ 85.2 million to develop custom in-memory architecture. Mountain View-based Flex Logix in April launched an inference coprocessor it claims delivers up to 10 times the throughput of existing silicon. And last November, Esperanto Technologies secured $ 58 million for its 7-nanometer AI chip technology.

Beyond the Ontario Teachers’ Pension Plan Board, Graphcore’s series E saw participation from funds managed by Fidelity International and Schroders. They joined existing backers Baillie Gifford, Draper Esprit, and others.

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Cargo.One raises $42 million to algorithmically match cargo with air routes

December 18, 2020   Big Data

Cargo.One, a real-time booking engine for the air cargo industry, today announced it has raised $ 42 million. The Berlin-based company says the funds will be put toward product R&D as it looks to expand internationally, particularly in North America and Asia, and triples its headcount to 70 employees.

This funding is especially timely as the air cargo industry mounts a response to the distribution requirements for COVID-19 vaccines. Cargo.One says its digital platform will help by addressing “structural inefficiencies” to streamline operations and by providing options for shipping temperature-sensitive products. Two leading vaccines — Pfizer’s and Moderna’s — must be kept at minus 20 Celsius or below while in transit.

Cargo.One’s booking platform gives users access to real-time prices and the available capacities of multiple airlines. Shipping customers can directly book into airlines’ systems or request quotes for shipments of different sizes, from 1 kilogram (around 2.2 pounds) up to 10 tons. They receive an overview of all bookable capacities of multiple airlines and real-time prices directly from the airline, just as on the phone. On the airline side, Cargo.One can make booking offers automatically available when shippers search for capacity on air routes.

 Cargo.One raises $42 million to algorithmically match cargo with air routes

When dynamic pricing is enabled, it takes into account factors like time to departure, capacity fill rates, and customers to work out appropriate shipping price points. The Cargo.One platform also provides access to structured, real-time demand and market data to better price products and serve shipping customers. It also gives airlines aggregated information on the entire market beyond inbound existing customer behavior, with the goal of replacing the often arduous process of calling and emailing to agree upon shipping rates and prices.

In Q4 2019, an estimated $ 17.5 billion worth of cargo — 35% of all global trade by value — was being moved via airfreight daily. Cargo.One, which was founded in 2017, says that a number of major shippers now rely on its platform. As of early December, over 1,500 freight forwarding offices used Cargo.One in their operations. Among its airline customers are Lufthansa, All Nippon Airways, Finnair, Etihad, AirBridgeCargo, and TAP Air Portugal, and the platform covers over 1.1 million air freight offices per month across more than 120 countries and 300 airports globally.

Bessemer Venture Partners led the series B round announced today, which brings the startup’s total raised to over $ 60 million. Previous investors include Next47, Creandum, Lufthansa Cargo, and Point Nine Capital.

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Zoomin has raised $21 million to unify enterprise product content

December 16, 2020   Big Data

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Zoomin, a “knowledge orchestration” platform that helps users extract answers from enterprise documentation, today revealed it has raised $ 21 million. Investors include Salesforce Ventures, Bessemer Venture Partners, and Viola Growth, and the investment, which had been undisclosed before today, came in the form of several tranches starting in 2018.

Zoomin was founded in 2015 and has hubs in New York and Tel Aviv. The company aims to help businesses make their vast pools of technical content easier to find and more usable. Companies may have many thousands of manuals, guides, training paraphernalia, online community discussions, and more, but all this disparate content is typically created and managed by different teams, people, and systems and often exists in silos. Zoomin “unifies” this content and delivers it in a more “intuitive and personalized way,” according to CEO and cofounder Gal Oron.

White label

Zoomin’s product can perhaps be crudely described as a white label search engine for enterprise product content, though Oron argues traditional federated search solutions focus on indexing content and taking users from their point of search to whatever external channel contains the results. Zoomin, on the other hand, can bring answers to the user wherever they conduct the search from.

“This means they don’t need to navigate across different sites and experience the fragmentation and drop-off that naturally accompanies this kind of ‘context switching,’” Oron told VentureBeat.

How Zoomin is used largely depends on what the customer needs from it. It could be a standalone technical resource center, perhaps something akin to a companywide intranet or even a public portal, transforming disparate static content into a dynamic search interface replete with filters, auto-suggestions, recommendations, and more. Or it could be a widget that offers content relevant to the context of a given situation, baked into the customer’s own applications, such as a customer relationship management (CRM) tool.

“In some cases, customers replace their existing portals with Zoomin, in other cases they keep their portal but use Zoomin to create an enhanced, intuitive, personalized experience,” Oron added.

Above: Zoomin “in-product”

Zoomin ships with various integration options, including REST APIs, JavaScript APIs, and command line interfaces (CLIs). It also offers prebuilt apps that can be downloaded, customized, and integrated with Salesforce or ServiceNow.

Above: Zoomin integrated into Salesforce

Under the hood, Zoomin says it uses both supervised and unsupervised machine learning (ML) models, developed and trained in-house, alongside off-the-shelf ML services.

“Zoomin’s knowledge graph ties together enterprise content, users, and interactions, powering the platform’s text analysis and classification, dynamic ranking, content recommendations, and predictive insights,” Oron explained.

Analytics also play a sizable role in Zoomin’s offering, including “traffic insights” that detail where traffic is coming from (including the referring domain and location); “content insights” that surface which topics and publications receive the most engagement; and “search insights” that give companies search pattern data that can be used to tweak the UX.

“These insights are designed to help our customers understand what users are searching for, learn which search terms are yielding no results, analyze the usage of search filters, and more,” Oron added.

Above: Zoomin: Content freshness analytics

Although Zoomin has operated fairly under the radar, it has amassed a number of notable clients, including now Adobe-owned Workfront, Chinese hospitality giant Shiji, and cybersecurity veteran Imperva.

Zoomin was entirely bootstrapped up until Bessemer’s inaugural investment in 2018, which was followed by Salesforce Ventures’ investment in 2019. Both VC firms reinvested in the startup this year, alongside Israel’s Viola Growth.

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Tive raises $12 million to track freight shipments with sensors and algorithms

December 15, 2020   Big Data

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Tive, a startup whose platform captures real-world data to inform supply chain decisions, today raised $ 12 million in a venture equity deal. Tive says it’ll invest the funds in product R&D as it looks to expand geographically and hire on new workers.

The pandemic and corresponding rise in online shopping threaten to push supply chains to the breaking point. Early in the COVID-19 crisis, Amazon was forced to restrict the amount of inventory suppliers could send to its warehouses. Ecommerce order volume has increased by 50% compared with 2019, and shipment times for products like furniture more than doubled in March. Moreover, overall U.S. digital sales have jumped by 30%, expediting the online shopping transition by as much as two years.

Tive provides customers across industries like consumer packaged goods, logistics, produce, and retail real-time visibility into the shipment process, including location data and metrics like temperature, shock, light exposure, and humidity. The company’s 5G-ready, non-lithium battery-powered trackers and cloud-based software provide visibility into a shipment’s condition, allowing shippers to create profiles, set custom alerts, configure geofences, and use an API to pull data into existing record-keeping systems.

 Tive raises $12 million to track freight shipments with sensors and algorithms

The Tive platform analyzes shipments’ data and turns it into actionable, real-time insights. It delivers alerts, reports, and tools to help customers understand and optimize supply chains.

Tive’s customers include Alpine Fresh, Crane Worldwide Logistics, Fastly, Aviagen, Hellmann Logistics, and BOA Logistics. One of the world’s largest logistics companies uses the platform to track pharmaceutical shipments across the globe, which Tive notes has taken on newfound importance with COVID-19 vaccine shipping underway, due to the temperature and shelf-life considerations for the front-running vaccines. Two vaccines — from Moderna and Pfizer — must be kept at temperatures below minus 20 degrees Celsius.

“Given the growing demand for Tive’s full line of tracking solutions, it was obvious that now was the time to dramatically expand our ability to meet industry demand,” CEO Krenar Komoni, who cofounded Tive in 2015 with Rob Stevens, said. “Gaining the support of RRE Ventures and Two Sigma Ventures, as well as our current valued investors, means we can leverage their expertise and focus on growing our customer-centric platform. The infusion of growth capital means bringing products to market faster, enhancing our sales and marketing efforts, adding key leadership, and growing our international presence.”

RRE Ventures and Two Sigma Ventures led the series A round announced today, with participation from existing investors NextView Ventures, Hyperplane Ventures, One Way Ventures, Fathom Ventures, and others. It brings Tive’s total raised to date to over $ 16 million.

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Bionic raises $17 million for tech that automates app analytics

December 10, 2020   Big Data
 Bionic raises $17 million for tech that automates app analytics

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App analytics startup Bionic today emerged from stealth with $ 17 million, a combination of series A and seed funding. The Palo Alto, California-based company plans to put the funds toward investing in R&D as it expands its client base internationally.

MarketandMarkets forecasts that the app analytics market will grow from $ 1.05 billion in 2018 to $ 2.85 billion by 2023. Among the factors driving growth are the demand for apps and an influx of mobile advertising. Because ads are a critical source of mobile app revenue, it’s increasingly important that bugs don’t interfere with their placement. In 2019, there were more than 204 billion app downloads, a roughly 6% increase on the year before. And by one estimate, mobile advertising represented 72% of all U.S. digital ad spending in 2019.

Bionic was cofounded by CEO Idan Ninyo and CTO Eyal Mamo, who spent over five years in Unit 8200, the Israeli Intelligence Corps unit of the Israel Defense Forces responsible for collecting intelligence and code decryption. Ninyo’s plans to relocate to the U.S. were disrupted by the pandemic, forcing him and Mamo to conduct Bionic’s series A round remotely.

Bionic’s platform reverse-engineers apps to create architectural and data flow breakdowns. It monitors core changes in production, enabling developers to define guardrails that prevent app updates and upgrades from negatively impacting performance. Bionic is agentless and ostensibly works across environments, locations, and infrastructures, from on-premises apps to hosted cloud-native microservices. (Microservice architectures arrange apps as collections of related services.) Moreover, the process is automated and can be deployed in what Bionic claims amounts to minutes.

“We are using many of the reverse engineering techniques we leveraged in Unit 8200 to deliver an automated and comprehensive inventory of customers’ applications: where they are deployed, configurations, APIs, data sources, changes, and more,” Ninyo told VentureBeat via email. “In minutes, we are delivering what used to take hundreds, even thousands of hours to compile across systems, spreadsheets, and other manual collection methods. We are able to show the full applicative dependency and dataflow map of the production environment, how different services consume APIs, what data is flowing between services, and data sources.”

Bionic competes with a number of app analytics startups, among them Apptopia and Adjust. But the company says its tools have experienced a rapid uptake in adoption and are already being used by IT, operations, and security teams at pharmaceutical, financial service, and technology companies.

“The pandemic accelerated digital transformation efforts across almost all organizations, especially since employees are working from home and enterprises are becoming more reliant on their digital offerings,” Ninyo continued. “That has made the issue of application chaos ever more acute for enterprise IT teams. All these organizations realize that they must maintain compliance, reduce risk, and improve resiliency without slowing down the rate of development.”

Bionic’s series A round was led by Battery Ventures investors Dharmesh Thakker and René Bonvanie. Additional investors include former Goldman Sachs CTO Don Duet, former Barclays CIO Sameer Jain, and Ariel Maislos. The company currently has 20 employees.

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Shippit raises $22 million to automate ecommerce shipping tasks

December 8, 2020   Big Data

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Sydney-based shipping logistics platform Shippit today nabbed AU$ 30 million (approximately $ 22 million), bringing its total raised to date to over $ 31 million. The company says the proceeds will be put toward supporting Shippit’s expansion in Southeast Asia as well as  growing the team of engineers based out of the startup’s Sydney development hub.

The pandemic and corresponding rise in online shopping threatens to push supply chains to the breaking point. Early during the COVID-19 crisis, Amazon was forced to restrict the amount of inventory suppliers could send to its warehouses. Ecommerce order volume has increased by 50% compared with 2019, and shipment times for products like furniture more than doubled in March. Moreover, overall U.S. digital sales have jumped by 30%, expediting the online shopping transition by as much as two years.

Shippit works with retailers to support multiple delivery options at checkout and to automate fulfillment and returns. The company’s software, which integrates with platforms like Shopify and eBay, gives customers access to carriers and provides tracking that starts from the time an order is placed until it’s delivered. Shippit offers transit protection to let customers cover goods against loss or damage, and beyond this, it recommends ways to pack orders and finds carriers for jobs, automatically generating things like packing slips.

 Shippit raises $22 million to automate ecommerce shipping tasks

Where shipment tracking is concerned, Shippit’s platform sends notifications via email and text and leverages “delay avoidance technology” to detect and correct issues that might cause delivery holdups. Using Shippit, returns can be configured to process automatically such that some are preapproved. And for each retailer,  Shippit shows a breakdown of everything that’s been sent and how much is being spent on deliveries — as well as how deliveries are performing.

Shippit says it’s focused on the enterprise market at the present time, handling over 5 million deliveries in Australia alone for thousands of retailers including Sephora, Uniqlo, Temple & Webster, Harvey Norman among others. In the near term, the company plans to invest in its technology that limits the environmental impact of discount deliveries by measuring how much carbon is generated by courier partners to inform purchases of carbon offsets.

Tiger Global and Jason Lenga led the series B investment in Shippit announced today.

Shippit might have a sizeable customer base, but it faces competition from rivals in the ecommerce shipping space. There’s Shippo, a platform that makes it easier for ecommerce companies to integrate shipping into their services, and smaller outfits like ShipBob. One of the largest is Flexe, an on-demand warehousing and technology platform used by retailers like Walmart.

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Glue raises $8 million to automate customer loyalty programs

November 26, 2020   Big Data

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Loyalty automation platform Glue today raked in $ 8 million in series A funding from private investors led by Unicorn Technologies. The startup says that the proceeds will be put toward nudging local businesses to adopt loyalty programs.

Retail has taken a major hit during the pandemic. Total sales are expected to hit 5.7% from 2019, nearly 12% below eMarketer’s pre-pandemic estimate of $ 26 trillion. Some data suggests that loyalty programs could help lessen future blows. According to Accenture, loyalty program membership in the U.S. grew at a rate of 26.7% from 2012 to 2014. And one recent survey found that 50% of consumers say their primary reason for joining a loyalty program is to earn rewards on purchases.

Glue offers a platform that attempts to gauge loyalty and facilitate the development of daily, weekly, and monthly engagement plans. It self-runs rewards, coupons, and points systems and provides tools for loyalty and sales growth analysis and reporting. Glue offers purchase and behavior tracking for customer targeting and tailors reward tiers to individual businesses; it can import data from existing customer relationship management software and enable customers to register for loyalty programs on their smartphones.

“Glue started as an app creator called Bobile. At the time, we thought every business needs an app, but after a while, we understood what’s really important to the business owners we spoke with is the ability to keep their customers coming back,” Glue CEO Ira Nachtigal, who cofounded Glue with Jacob Tenenboim and Dany Gal, told VentureBeat via email. “But, they are busy.  Most local businesses don’t have the time, the knowledge, or the resources to manage it.  Loyalty, when done right, is complex, so we decided not to create yet another loyalty tool, but rather to do the work for them.”

Glue supports loyalty strategies such as points-earning systems, coupons, loyalty cards, subscriptions, prepaid multi-passes, and play-to-win games. Customers can use it to schedule holiday and special occasions greetings, launch Google Ads growth campaigns, or encourage walk-ins with geofencing campaigns.

 Glue raises $8 million to automate customer loyalty programs

After completing a 15-minute onboarding questionnaire on Glue’s website, business owners receive a branded members club and a projection of savings. Glue claims its programs are customized by leveraging businesses’ customer data and pairing them with data points from 100,000 organizations, resulting in what the company calls an average savings of between $ 15,000 to $ 20,000 per small business and significant revenue growth.

“Glue collects the data from thousands of businesses around the world, analyzes the consumer behavior and optimizes the loyalty strategy that is built for every business,” Nachtigal explained. “For example, let’s say you own a coffee house in Boston. Glue already has a lot of information and accumulated knowledge about coffee shops and their consumers in the east coast. Using AI Glue knows what is most likely to work for your coffee house and your customers and given your specific price range, will be able to tailor a successful loyalty strategy for your coffee house.”

Glue has a number of competitors in the space. There’s AppCard, a mobile-first loyalty marketing program for small and medium-size retailers, as well as Punchh, a startup leveraging machine learning and omnichannel integrations to create customer journeys. Just last year, Drop, a coalition customer loyalty company headquartered in Toronto, raised $ 44 million. That’s all to say that 15-employee Glue will have to differentiate itself from the rest of the pack, but this latest funding round — and its growing number of coffee shop, cosmetic, pet store, service provider, and car repair shop customers — suggests that it’s had success in that respect.

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