AlphaSense Uses the Power of Qualified to Generate Attributed Pipeline and Revenue and Achieve 4,109% ROI

公司规模
Large Corporate
地区
- America
国家
- United States
产品
- Qualified
- Qualified Conversations
- Qualified for Outreach
技术栈
- Salesforce
- Marketo
- Outreach
- Clearbit
- Slack
实施规模
- Enterprise-wide Deployment
影响指标
- Revenue Growth
- Customer Satisfaction
- Productivity Improvements
技术
- 平台即服务 (PaaS) - 连接平台
- 应用基础设施与中间件 - API 集成与管理
适用功能
- 销售与市场营销
- 商业运营
用例
- 补货预测
服务
- 系统集成
- 软件设计与工程服务
关于客户
AlphaSense, headquartered in New York City, is a leading market intelligence and search platform trusted by thousands of top-tier corporations and financial institutions, including a majority of the S&P 500. Founded in 2011, AlphaSense empowers research professionals to make informed business decisions by providing key insights from a vast array of private and public content, such as equity research, trade journals, expert interview transcripts, news, and company filings. The company operates in the IT services and consulting industry and is renowned for its AI-based technology that helps businesses quickly find the right answers. AlphaSense's platform is designed to assist the world's largest corporations in making smarter, faster, and more confident decisions by delivering valuable insights from a comprehensive universe of public and private content.
挑战
AlphaSense was experiencing significant web traffic through various marketing channels, but their website was not effectively converting this traffic into a demand generation machine for pipeline. Prospects who reached the website were not engaged at critical moments of high intent, leading to missed opportunities for sales development representatives (SDRs) to interact with prospects and drive pipeline. Mike Werch, Director of Marketing Operations at AlphaSense, had previously implemented other conversational solutions but was dissatisfied with their customer support, high costs, and lack of integration capabilities. He sought a new conversational solution partner that could seamlessly integrate with AlphaSense's existing tech stack, provide superior support, and deliver tangible results.
解决方案
AlphaSense partnered with Qualified to transform their website into a powerful engagement tool and drive pipeline while creating memorable buyer interactions. Qualified helps B2B companies generate pipeline faster by identifying valuable visitors, initiating sales conversations, shaping sales and marketing campaigns, and uncovering buying intent signals. AlphaSense received strong support from their dedicated Salesforce-certified implementation consultant, Anna, who helped develop a blueprint for success. This included segmenting website traffic to focus on high-priority visitors, using Salesforce data to automatically route visitors to their assigned reps, personalizing experiences on high-intent pages, and instantly routing prospects from Outreach emails to the website with tailored greetings. The implementation of Qualified allowed AlphaSense's SDRs to monitor important buyers, categorize visitors into buyer segments, and engage with them using every known data point. The integration with Salesforce ensured that visitors were automatically routed to their assigned reps upon landing on the website. Additionally, the Qualified Video feature enabled SDRs to humanize interactions and book meetings more effectively. The sales team also utilized Qualified for Outreach to send personalized emails referencing accounts' website engagement and third-party research behavior, delivering a seamless buying experience across channels.
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Procter & Gamble Implements Terra Technology's Demand Sensing for Improved Forecast Accuracy
Procter & Gamble (P&G) faced significant challenges in accurately forecasting short-term demand for their consumer products. Their existing 24-month forecast provided a good overview for monthly or weekly production, but it was insufficient for the immediate needs of supply chain planning and manufacturing teams. These teams required a short-term forecast to plan production effectively and avoid 'fire-fighting' practices. P&G needed a solution that could provide accurate short-term demand forecasts to ensure agility and flexibility in manufacturing, especially for products with very short production and order lead times. The company explored various solutions but found that most big software companies lacked the agility to meet their specific demand sensing needs. Terra Technology's Real-Time Forecasting, later known as Demand Sensing (DS), emerged as a promising solution due to its specialized focus on consumer packaged goods (CPG) demand planning and forecasting.
Case Study
Blue Bottle Coffee Enhances Ordering Accuracy and Reduces Waste with ML-Driven Demand Forecasting
Blue Bottle Coffee (BBC), a global coffee roaster and retailer, faced a significant challenge in managing the supply of pastries across its international network of cafes. The company was using a manual ordering system, where cafe leaders estimated the required quantity of pastries based on historical sales data, current inventory, and growth projections. This system was effective when BBC had a few cafes, but with over 70 cafes worldwide, it became inefficient and inaccurate. The inaccuracies led to either under-ordering, causing sell-outs and customer dissatisfaction, or over-ordering, resulting in food waste and profit loss. The suboptimal utilization of pastries was also affecting BBC's bottom line. Therefore, BBC needed a scalable, precise, and predictive ordering solution to improve pastry ordering accuracy, reduce food waste, and meet its sustainability goals.
Case Study
Designing an intuitive UI for effective product demand forecasting in retail
The client, a leading luxury store chain operating in over 100 countries, was facing challenges with their product demand forecasting process. The process involved a significant amount of manual work, with all sales-related data being kept in Excel tables and calculated manually. The client's merchandising and planning experts used a demand forecasting web application to make estimations of customer demand over a specific period of time. The solution calculated historical data and other analytical information to produce the most accurate predictions. However, the client wanted to improve the efficiency and effectiveness of this process, making it faster, more accurate, and less complicated for their employees. They sought to unify all processes under an intuitive UI.
Case Study
YAZAKI Europe Limited: Ensuring rapid, cost-efficient order fulfillment and quicker insights into business performance
YAZAKI Europe, a leading automotive supplier specializing in the production of customized wiring harnesses for car manufacturers, was facing challenges in meeting the automotive industry’s demand for same-day delivery. The company's continuous growth was impacting its ability to analyze performance and complete its end-of-month consolidation and reporting processes for its headquarters in Japan. The company needed to eliminate delays and manual processing in its logistics to ensure extremely efficient operations. The company also needed to boost its data analytics capabilities for its finance and controlling departments to accelerate the delivery of complex financial reports.
Case Study
How the Philadelphia 76ers Win Off the Court Using Machine Learning from DataRobot
The Philadelphia 76ers, a professional basketball team in the NBA, is part of a new wave of sports franchises that are leveraging data analytics to optimize both their on-court performance and business operations. The organization has a strong focus on using data to inform decision-making processes across all levels. One of the key challenges faced by the 76ers' Analytics Team was improving the efficiency of their season ticket renewal process. The team had been using data science and simple modeling techniques, but lacked a dynamic machine learning tool that could adapt and learn as more data was collected. This meant that the team had to do a lot of work in the offseason to produce a static model. The goal was to transform the renewal process from a once-a-year event into a year-round retention process.
Case Study
Business services company saves approx. 80% of projected deployment costs with Acumatica
Caystone Solutions Ltd., a small but ambitious company, aimed to provide a variety of services to entrepreneurs and individuals globally. To achieve this, Caystone needed to operate with extraordinary efficiency and be able to easily manage growth. The company required an accounting system that could support its own business requirements as well as its clients’. The system needed to be customizable, support multiple currencies, and unlimited users. It also needed to provide both Caystone and its clients anytime, anywhere access from any web browser. Caystone required a system that wouldn’t necessitate a big—and costly—hardware infrastructure. And Bahamas-based Caystone needed the comfort of knowing its client data was stored locally.