Latest news with #customerdata
Yahoo
14-07-2025
- Business
- Yahoo
Amperity Appoints Grigori Melnik as Chief Product Officer
Veteran technology leader brings decades of product innovation experience to accelerate Amperity's growth and platform strategy SEATTLE, July 14, 2025--(BUSINESS WIRE)--Amperity, the AI-powered customer data cloud, today announced the appointment of Dr. Grigori Melnik as chief product officer. A seasoned product executive with more than 25 years of experience leading platform innovation across high-growth startups and global enterprises, Dr. Melnik will lead Amperity's product strategy and execution during a period of rapid growth and industry transformation. "Grigori is an exceptional product leader who blends deep technical expertise with a clear vision for customer data," said Tony Owens, CEO of Amperity. "He knows how to build platforms that define categories — and he knows how to do it at enterprise scale. His arrival marks a new chapter for Amperity as we double down on innovation and continue helping the world's largest brands turn customer data into business growth." Dr. Melnik has held leadership roles at Microsoft, Splunk, MongoDB, Tricentis, and most recently Cribl, where he expanded the company's multi-product strategy and drove significant market growth. At Splunk, he helped grow the business to over $1 billion in annual revenue while building a robust developer ecosystem. Across all his roles, he has consistently driven product transformation, scaled teams, and delivered measurable impact. "I've spent my career building tools that empower technical teams to solve hard problems efficiently," said Dr. Grigori Melnik. "Amperity is doing exactly that — tackling one of the most complex challenges in the data space with the right mix of ambition, innovation, and customer obsession. I'm incredibly excited to join this talented team and help shape the next wave of product innovation for both our company and our valued customers." Dr. Melnik holds a Ph.D. in Computer Science from the University of Calgary and continues to contribute to academic research in software engineering and automation. He also serves as a board director and strategy advisor to startups and private equity firms including Insight Partners and Warburg Pincus. With this appointment, Amperity strengthens its executive bench to support an ambitious product roadmap and its continued leadership in the customer data platform market. About Amperity Amperity's Customer Data Cloud empowers brands to transform raw customer data into strategic business assets with unprecedented speed and accuracy. Through AI-powered identity resolution, customizable data models and intelligent automation, Amperity helps technologists eliminate data bottlenecks and accelerate business impact. More than 400 leading brands worldwide, including Alaska Airlines, DICK'S Sporting Goods, BECU and Wyndham Hotels & Resorts, rely on Amperity to drive customer insights and revenue growth. Founded in 2016, Amperity operates globally with offices in Seattle, New York City, London and Melbourne. For more information, visit or follow us on LinkedIn, X, Facebook and Instagram. View source version on Contacts Press ContactAndrea Mochermanpress@ +1 (206) 432-8302
Yahoo
10-07-2025
- Business
- Yahoo
KlariVis Recognized as a 2025 Tearsheet Data Award Winner for Best Customer Data Implementation
ROANOKE, Va., July 10, 2025--(BUSINESS WIRE)--KlariVis, a leading data analytics solution for financial institutions, today announced that it has received the 2025 Tearsheet Data Award for Best Customer Data Implementation — a recognition that reflects the company's growth, rapid client adoption, and commitment to delivering actionable insights to community banks. The award celebrates the creative implementation and presentation of customer data that provides clear value to the end user. KlariVis was recognized for transforming how community banks access and utilize their data. Since 2019, the company has empowered over 130 financial institutions through an interactive, cloud-based analytics platform designed specifically for the challenges and priorities of community banking. "This recognition is really about what our clients are achieving," said Kim Snyder, CEO and founder of KlariVis. "Banks using KlariVis are making smarter pricing decisions, identifying growth opportunities, and coaching teams in real time — not weeks after the fact. We're proud that our platform makes data analysis not only possible but practical for institutions with limited resources. And we'll continue building with and for our clients to ensure they stay ahead in a fast-changing industry." Built by former bankers, KlariVis consolidates critical operational and customer data from siloed systems into intuitive, role-based dashboards accessible across the organization. The platform requires no technical expertise and is fully integrated alongside KlariVis' award-winning implementation team in as little as 90 days, giving leadership and frontline teams the ability to act on data insights faster and with more confidence. The platform's consistent evolution is driven by client feedback and banker input received during KlariVis' Executive Data & Innovation Summits, ensuring the product roadmap stays aligned with real-world banking needs. KlariVis' proprietary Transactional Intelligence suite, developed in response to client requests, played a key role in the award selection. This new enhancement allows banks to turn their raw transaction data into enriched insights that help deepen customer relationships, detect wallet-share risks, and drive revenue growth. As community banks face increasing competition from both fintechs and large institutions, KlariVis delivers a scalable, efficient way to unify and activate the data they already have — driving meaningful outcomes without the heavy lift of traditional business intelligence tools. For more information, visit About KlariVis KlariVis® is the only data analytics platform built by former community bank executives to help financial institutions turn their data into actionable insights. By consolidating and simplifying data from across the bank into interactive dashboards and reports, KlariVis empowers teams to make informed decisions that drive growth, efficiency, and customer impact. Built on a modern technology stack, KlariVis eliminates the need for manual reporting, allowing banks to focus on strategy, performance, and innovation. To learn more, visit View source version on Contacts Media Contact Gracie GayWilliam Mills Agencygracie@ KlariVis Contact Erica StarrChief Marketing Officerericastarr@ Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
ABC News
09-07-2025
- Business
- ABC News
Qantas tells 5.7 million customers how much of their data is in criminal hands
Qantas chief executive Vanessa Hudson reveals nearly six million customers have had their data stolen, including names, email addresses, phone numbers, addresses, and even meal preferences.
Forbes
08-07-2025
- Business
- Forbes
Unlocking The Potential Of Advanced Analytics To Ignite Growth
Helping CMOs Aggregate, Organize and Monetize Knowledge In Marketing Actions, Conversations and Decisions Digital marketing has blessed modern marketers with a wealth of customer engagement data. This data pours out of web sites, digital media campaigns, Customer Data Platforms (CDPs), ecommerce channels, CRM systems and mobile devices. In theory, the current revolution in advanced analytics and AI should multiply the ability of marketing leaders to use this data to unlock more growth for their businesses. Data-driven marketing can improve the performance of marketing campaigns, personalize customer experiences, and multiply the return on brand, relationship and channel assets. But in practice, most marketing teams are far from realizing the potential of big marketing data to ignite growth. And many are not satisfied with efforts to maximize AI's value – despite the hype. For example, only 31% of marketers are fully satisfied with their ability to unify customer data sources, according to a survey of 5,000 marketers by Salesforce. Less than one third (32%) of marketers surveyed by Salesforce were completely satisfied with how they use customer data to create relevant experiences. And while almost every CMO surveyed by the Fuqua School of Business has invested in a wide variety of tools to manage and monetize this data, the majority of them are unsatisfied with the results they are getting from this technology. Over three quarters of growth leaders say they face talent gaps and operational constraints that limit their ability to effectively harness AI technology, according to a survey of 1,800 marketing and sales executives by The IBM Institute for Business Value. This begs the question: why are marketers struggling to unlock the full potential of advanced analytics to ignite Growth? Is it the data? Is it the way it is organized? Are the tools and techniques being used to analyze it inadequate? Or the skills of the analysts? Or is it the inherent risks of relying on big data that are holding them back? The answer is likely all of the above, according to Frank Findley, Executive Director of the Marketing Accountability Standards Board (MASB), who is actively studying the problem with a team of top academics in the field. 'There are no clear standards for the methods, tools and procedures that businesses use to collect, structure, analyze and monetize the wealth of 'marketing big data' that they generate,' says Findley, who is leading the MASB Big Data in Marketing Study. 'It is difficult for CMOs to know which analytical and statistical approaches still work in a world of big marketing data, and many have not yet figured out what what new AI enabled analytics methods they can rely upon to make better, faster and more reliable business decisions about their marketing actions and investments.' For example, tried and true traditional statistical based approaches like regression analysis and reporting tools and dashboards that have been proven to be reliable for analyzing customer data in the past. But these proven tools may not be fast or cost effective enough to support the large data sets and analytical needs of a modern marketing organization. Likewise, while many marketers are quick to experiment with new AI enabled analytics approaches, such as Natural Language Processing (NLP), Machine Learning, and Generative Artificial Intelligence (GAI) – their efficacy, trustworthiness, reliability, and integrity remain in question. In public forums, Marketers regularly tout the potential of advanced analytics to better segment audiences, plan media, forecast demand, optimize pricing, and allocate growth resources. For example, CMOs expect a full 44% of their work to be AI enabled in the next three years, according to the CMO Survey by the Fuqua School of Business. But behind closed doors they worry about whether AI will give them the wrong answers, introduce biases into their decision making, and create brand and compliance risks due to hallucinations and privacy breaches. In addition, the reliability, availability and cost advantages of these tools are not well understood. 'If marketers don't figure out the best ways to structure, analyze, and monetize their marketing big data, their role as the voice of the customer and the leader of customer insight will be called into question,' says Purush Papatla, a Professor of Marketing in the Sheldon B. Lubar School of Business who helped design the MASB Big Data in Marketing Study. Purush makes a prescient point. For the first time, fewer than half of CMOs report they have customer insights as one of their primary responsibilities in the latest CMO survey. If the marketing team does not own customer insights, which functional organization does? – and do they have the business acumen, analytical skills, and customer context to use those insights to improve go to market performance? Getting an answer to the questions MASB is asking is important. Why? Because today, the knowledge that resides in this customer big data can be the largest and most valuable financial asset in the business. When you consider that over 80% of the value of any B2B organization is made up of 'intangible assets' like intellectual property, innovations, 'know how', customer insights, and codified information, and brand equity - the knowledge in your customer database could be worth millions or billions of dollars, according to analysis in the book Capitalism without Capital. In that light, much of the value of marketing creates lies in their unique ability to capture, organize, and analyze all this customer engagement data to create useful information to support marketing decisions and actions. 'Our goal with the MASB Big Data Study is to help CMOs learn from the collective intelligence of other CMOs on how to best squeeze the most value out of investing in AI and how to avoid the roadblocks and landmines, so to speak, they will face along the way,' says Professor Papatla, who is also the Co-Director of the Northwestern Mutual Data Science Institute. For example, the best marketing organizations are creating value by connecting and consolidating their customer engagement data assets in ways that turn it into knowledge that can support marketing decisions and plans. There are many ways that marketers can use advanced analytics and AI agents to turn messy and disorganized marketing big data into valuable go-to-market knowledge that supports marketing actions and actions. They include: A bigger opportunity to create financial value from this data is to turn it into codified knowledge that can be monetized in marketing channels, selling situations, commerce transactions, and customer responses. Codified, or explicit knowledge, is defined as information that is captured and cataloged and converted into knowledge that is ready for people to use – ideally to make more money. It appears in documents, procedures, and databases. In contrast with tacit or implicit knowledge, explicit knowledge is codified and articulated. The most important aspect of codified knowledge is that it is acknowledged by the accounting profession as an asset with financial value. In accounting, a knowledge asset refers to the intellectual resources and expertise an organization possesses that can be used to create value and gain a competitive advantage. These assets can include things like patents, trade secrets, customer databases, employee skills, and company processes. In the context of revenue generation, codified knowledge assets are useable materials in a customer database or knowledgebase such as codified/explicit knowledge such as instructions, AI agents, algorithms, models, software that can be used sales and marketing to generate future revenues. There are many ways that marketers can use advanced analytics and AI agents to turn insights into codified knowledge that can be monetized in marketing, media, and sales channels, according to a Certification program for marketers by Revenue Operations Associates. The list includes: One problem is that in most organization, knowledge is spread around in many systems, brains and silos. Much of it lies in on average eight systems such as CDPs, marketing automation, CRM, digital media, content management, and first party web sites. Much of this knowledge still lives in adjacent systems like word processing, collaboration software, emails, SharePoint drives, or in spreadsheets. 'Marketers are tasked with analyzing a variety of first party data structures, that track behavior across web sites, mobile devices, commerce platforms and social media channels – but also increasingly unstructured data from audio recordings, video and images,' says Findley. Another problem is there is often no single function, or role with responsibility to organize and analyze that data. Often big customer data is managed by marketing, or sales, or a third party vendor, according to Findley. In some cases a center of excellence is put in place to coordinate and analyze data. This challenge is multiplied by the growing variety of people who are actively analyzing that data. For example, in any given organization analysts from marketing, sales or finance can be evaluating the same data sets, in a different context, with different purposes (e.g. targeting audiences, defining account coverage, forecasting cash flow). Different players will have different levels of skills and use different types of tools. For examples marketers may use path analysis to optimize resources and attribute revenues, cluster analysis to segment markets objectively, and computer vision to evaluate, categorize and personalize creative. 'Specific tools have specific usefulness, so having a wide variety of proven tools in your belt can be a real advantage,' says Findley. 'But marketers also need to understand the unique risks and deficiencies of the tools they are using. For example AI agents create a range of compliance, bias, and privacy risks which are not well understood – while other traditional BI and reporting tools may be too slow or labor intensive to manage the large data sets marketers have at their disposal.' By examining the current practices for collecting, managing and analyzing customer data across hundreds of businesses – and cross referencing the associated risk and financial implications of those approaches – his team hopes to provide CMOs a complete picture of how they need to organize their approach to big data.
Bloomberg
04-07-2025
- Business
- Bloomberg
Louis Vuitton Korea Suffers Cyberattack as Customer Data Leaked
Louis Vuitton Korea suffered a cyberattack that compromised some customer data, the second time in recent months that hackers have targeted the world's largest luxury group. The Korean unit of LVMH 's flagship brand said an 'unauthorized third party' accessed its systems on June 8 and some customer information was leaked. No financial data including credit card or bank account details were taken and the security breach has been contained, it said in a statement.
