Lice Clinics of America, a network of over 300 clinics in 35 countries, was looking for a way to better understand how their national advertising campaigns were impacting their lead flows. They wanted to know which campaigns were driving the most calls and to which locations. They were also facing challenges with their existing provider for sending out text messages through their booking platform with clients. The messages were experiencing significant delays, which was a problem as their clients needed immediate responses.

Genesys, a company that sells customer experience and contact center technology, was facing challenges in managing its sales process. The sales managers were operating in a world of “guessing and speculating” about where to spend their time and effort for maximum efficiency. They were scaling rapidly, yet struggling to onboard efficiently. The process of preparing for a call was time-consuming and did not scale. Sales managers were heavily involved in every deal, which spread them thin and did not allow them to deep dive into each deal. The process was more about “following fields in the company’s CRM” and then using one-on-one meetings to “add color” to better understand each deal.

Workato, an Enterprise Automation platform, was in a phase of hypergrowth and was relying heavily on anecdotal data for tracking demand generation. This approach was restricting their visibility into the full sales funnel. The sales team was growing rapidly and was looking for a way to scale the team consistently while providing top-notch training and guidance. The uncertainty of relying on anecdotal data was not sitting well with Bhaskar Roy, Head of Growth and Marketing at Workato, whose marketing team is driven by the number of opportunities it generates. The team was ready for a change and was looking for a solution that could provide them with accurate and reliable data.

Sendoso, a rapidly growing company, was struggling to analyze its retention data. The Customer Success team wanted to understand what was causing churn and what was driving positive retention numbers. The company's annual contracts meant that a customer lifecycle was long, making it difficult to track what happened during that span that led to a renewal or churn. The reasons for sales and churn had also changed over the years due to the company's rapid growth and scaling. The team was also struggling with inefficient and redundant handoffs from the Account Executive (AE) to the Customer Success (CS) team.

Appen’s Customer Success team was struggling with managing their communication with customers. The team was often engaged in the “fun” game of Telephone, which turned out to be frustrating, inefficient, and often a huge waste of time and effort. There was no way to go back and validate what was actually said in the call. This ended up being a huge pain point for the CSM team. Moreover, the onboarding process for a new CSM was painfully long, taking up to six months. The first three months were reserved for just learning about AI, learning about data labeling, learning about machine learning, and really getting up to speed with the industry. The next three months were spent learning the different use cases on the platform.

Drift, a conversational marketing platform, was experiencing hypergrowth. With the expansion of its team, product, and customer base, the potential for redundancies and inefficiencies increased. The leadership team was spending countless hours on phone calls with sales reps and prospects, trying to understand what was and was not working. There was no consistency around pitches or coaching new reps. The lack of clarity was not limited to the Sales Team. Drift’s Product Marketing Manager, Daphne Funston, would hear different issues from the customer when they spoke with the CSM and the product team. The Drift team needed a solution quickly.

With the impact of COVID-19, simPRO needed a way to strengthen and develop their new remote sales process. The company was initially structured along geographic lines, with offices operating as independent units. However, they decided to restructure their business units along functional lines, bringing together colleagues from around the world—regardless of location. The pandemic forced them to put these plans on hold. When the lockdowns persisted, they decided to move forward with the reorganisation and invest in their future. They wanted insight into the remote sales process, including intel about their customers’ needs and their reps’ performance.

EdgePetrol, a UK-based software company that specialises in fuel price optimisation, was facing challenges in meeting their pipeline goals. Their prospect base was so used to the status quo, they didn’t recognize their situation as problematic, or see a need for a solution. With a global pandemic and an off-kilter economy, EdgePetrol needed new ways to build a highly qualified pipeline and communicate its product’s value so it could close big deals. The company was also transitioning from a field sales team to an inside sales team due to the pandemic, which presented its own set of challenges.

Demandbase, a marketing technology company, was aware of the vast marketplace opportunities available but lacked a reliable method to uncover them. They needed a solution grounded in reality that could identify areas for improvement and growth to generate more revenue. The company was also facing the challenge of integrating the functionality of three new companies it had recently absorbed. This required a collaborative approach and the identification of data that could help increase their Average Contract Value (ACV).

Filtered, a UK-based learning technology and content company, was seeking ways to grow its revenue and better coach its sales reps. As the company grew, the need for a Revenue Intelligence tool became apparent. The company wanted to focus on its most important accounts and make the most of its pipeline. In early 2020, the Filtered sales team spent a lot of time sharpening its sales skills and methodologies. They implemented a more deliberate and structured sales framework, began running more internal demos, and started a sales book club. However, they needed something more to take their efforts to the next level.

Mintel, a global leader in market research, was facing a challenge in improving their efficiency. With a large portfolio of over 6,000 clients worldwide, it was difficult for them to detect patterns in calls, which delayed improvements to customer service processes. They needed a single tool that could provide guidance based on data from feedback in client calls. The company was also struggling with getting internal teams up to speed with new initiatives, which often resulted in lost or stalled deals. The lack of a tool to review calls meant that the knowledge gap was not being closed quickly enough.

Corporate Traveler’s customer success (CS) team wanted to invest in efficiency as a way to boost its customer adoption and retention rates. During the pandemic, they started using Gong, and have seen their adoption and retention rates improve dramatically. By streamlining their handover system and focusing on an accurate, trackable voice of the customer, Corporate Traveler has leveled up their CS game.

Rapid7, a cybersecurity firm, was struggling to understand the voice of its customers to win more deals. The majority of its customer interactions were conducted via phone and web meetings, and the leadership team spent a significant amount of time gathering information from these calls to make critical business decisions. However, the information they received was anecdotal and often distorted as it was passed from person to person. This, along with a limited subset of customer interactions, made it nearly impossible to make sound decisions about where to focus their efforts and how to address the market's needs.

Iron Mountain, a Boston-based enterprise information management firm, had to adjust to a fully remote work environment due to the pandemic. This sudden shift posed several challenges, including onboarding new reps, managing people remotely, and keeping teams aligned. They also needed to understand what was happening in sales calls and which actions to take based on their conversational data. Before implementing Gong, Iron Mountain’s new reps participated in “physical ride-alongs,” sitting beside a seasoned rep, headphones on. In a working-from-home world, this wasn’t possible. Additionally, trying to find the right call to listen to had always been a hit or miss exercise. As a result, they couldn’t target specific behaviors, and that was something they wanted to correct.

Wärtsilä, a global leader in smart technologies and complete lifecycle solutions for the marine and energy markets, was facing a communication bottleneck due to its global operations. The company's sales cycles could run up to five years, and the rapid changes in the marine and energy sectors due to factors like climate change and regulatory requirements made it crucial for the sales teams to stay updated. However, the company's traditional learning management system (LMS) was unable to deliver mobile, instant accessibility, which was necessary for the sales teams to keep up with the industry changes.

PriceLabs, a leading revenue management platform for vacation and short-term rentals, was seeking a solution to record customer calls. The aim was to uncover customers’ sentiment and gain insight into their needs. The product team felt that there were new solutions that weren’t being adequately pitched. Recorded calls would help PriceLabs share feedback with the product team and also help identify where the team was missing the mark on explaining its product. This was particularly important as PriceLabs had doubled its team in the previous six months, and planned to double the team again in the following six months.

Menemsha Group started as a traditional sales training company, hosting live workshops and webinars for its client base of IT recruiting companies. Clients loved the content, but had no way to measure results of the training over time. Beyond the half-, full-, or multi-day session, there was no method for quantifying or certifying knowledge. Additionally, Dan Fisher, Menemsha Group’s founder, needed to re-evaluate his content delivery methods with the goal of being able to scale his business and take on new clients without the drastic additional headcount required for in-person training. He also needed a way to deliver a quantifiable service so that clients engage with him on an ongoing basis, rather than one-and-done training sessions. Menemsha Group reached a point where it was only generating revenue when Fisher and his team were out in front of customers, working around the clock—and burnout was setting in. In an effort to scale the business without increasing work hours, they experimented with different learning management systems (LMS), all of which they found to simply serve as content repositories.

Intuit, Inc. sought to delight its customers by building digital engagement into a larger strategy to improve the customer experience. Later, the company consolidated live chat operations and began using transcription and text analytics to optimize the customer experience. As a result, Intuit has achieved a 20 percent improvement in customer satisfaction scores for certain product lines and as much as a 25 percent improvement in conversion rates. The company projects significant additional benefits with the recent deployment of predictive targeting for high-value customers.

Harvard Business Services, a leading provider of business formation services for Delaware corporations and LLCs, faced several challenges. The company wanted to extend its culture of personalized service to an online channel, increase sales by engaging with customers at moments of confusion, and provide a comfortable channel to assist international customers for whom English is a second language. The company had previously used AOL Instant Messaging as a channel for quick answers to questions that came up during the signup process, but found it was not convenient for clients to connect with them, and the interface wasn’t always user friendly.

Shortcuts, a software provider for the hair, beauty, and spa industries, wanted to increase sales and provide a non-intrusive way for potential customers to have their questions answered. The company decided to deploy a live chat engagement channel to provide 24-hour sales support from three locations worldwide. The goal was to field an average of 15 to 20 live chat conversations daily, with the hope of generating qualified leads and sales. The challenge was to find a suitable live chat solution and integrate it into their existing system.

Exodus, a tour operator that offers small group expeditions led by expert local guides, was facing a challenge with its online customer engagement. The company sells high-end adventure holidays that require a high level of commitment from customers, resulting in low conversion rates on its website. Exodus needed a solution to support and engage with online customers who required extra guidance when booking their adventure holidays. The company was looking for a way to drive sales, improve customer service, and collect valuable data for future promotional activity.

TOOLSTOP, a UK-based online retailer of professional hand and power tools, was looking to enhance its customers' online shopping experiences. While the company had various channels for customer engagement, including email, Facebook, and a blog, it recognized the potential of real-time interaction with product experts to address customer queries about pricing, shipping, and technical details. TOOLSTOP had already implemented LivePerson’s LP Chat for Small Business solution on its website, which significantly increased sales conversions. However, the company wanted to further optimize their chat initiative without a significant investment in time and resources.

Cenovus Energy, a Canadian oil company, was facing the challenge of collecting, aggregating, and reporting emissions and energy consumption data across more than 1,000 facilities spread across a vast geographic area. The process was complex and difficult due to the use of numerous spreadsheets and systems to compile emissions data and reports. It was an onerous and labor-intensive process, involving collection and aggregation of data from multiple sources for a very large number of facilities. Much of the data would require additional pre-calculation or other conditioning to be suitable for emissions calculation and compliance report compilation. Cenovus envisioned a single, automated integrated enterprise-wide solution to manage air environmental reporting.

Tikkurila, a paint manufacturing company, has been providing consumers and professionals with user-friendly, sustainable paint solutions for over 150 years. The company prides itself on product safety and quality, which are among the cornerstones of its operations. Tikkurila's product labeling must meet customer needs and expectations as well as regulatory requirements. The company works hard to systematically determine the health, safety, and environmental impact of the raw materials used in its paints. Product teams must develop material safety data sheets (SDS) and labels in up to 15 languages as it markets more than 2,000 products. However, Tikkurila’s facilities across 11 countries used different methods to create safety data sheets and labels, including outsourcing for translation. They realized that they needed a more efficient way to create their SDSs if they were going to continue to grow.

Uprise, an ad-tech company, uses a 'continuous delivery' approach for its software development, pushing around 20 new software releases into production each day. Each new release can affect the platform’s performance, making it crucial to monitor results in a timely fashion to determine if the new release should be kept in production or rolled back. The ad tech environment itself has many moving parts, each of which is a potential point of failure. These can include server issues, changes at the ad affiliates, introduction of ad blocking software, or even fraud. Whenever a problem occurs, isolating the source can require complex, time-consuming analysis. Identifying issues in the first place is also tricky, since network traffic behaves seasonally. With the traffic naturally reaching various peaks and valleys throughout the day, noticing a 20% loss or gain at any given point is next to impossible.

Penske Media Corporation (PMC) was facing significant delays in discovering important incidents in their active, online business. The company was using Google Analytics’ alerting function to track business incidents but found it inadequate due to the millions of users across dozens of household-name and professional publications. The initial use case for PMC was to start using Anodot to track its Google Analytics activity, for example, to identify anomalous behavior in impressions or click-through rates for advertising units.

The company, an affiliate network with over 200,000 members, was struggling to monitor business and technical incidents that were impacting their bottom line. The dynamic nature of their marketplace and the extensive metrics they had to track made it difficult to monitor changes in real-time. Factors such as changes in search engine algorithms and third-party trends, as well as changes in affiliate accounts, could significantly impact their business. The tools they were using required them to set thresholds manually, which allowed time for incidents to escalate.

As a real-time trading company, eToro must provide users with reliable market rates as quickly as possible, necessitating close monitoring of the quality of the connection from both the client and server side. eToro had been using open-source tools to monitor the metrics from their Price Streams service that sends price quotes to their users. However, the company quickly realized that it needed to expand the number of metrics being monitored and faced resource challenges adapting their traditional monitoring tools to meet the new demands. With stringent regulations in Cyprus and the UK, eToro treats any trading error or problem as critical.

Magnite, the world’s largest independent sell-side advertising platform, processes trillions of transactions each month in real-time auctions that each occur within 40 milliseconds. The company's internal teams and existing tools could not scale to handle the growing volume and velocity of data. They needed real-time insight into incidents that were being detected too late, such as anomalies in normal transaction volume from a large buyer. Their manual alerting system with static thresholds also created costly alert noise and false positives. Magnite works with many demand-side platforms (DSPs) across its global data centers in different time zones. Along the bid stream, there are many potential areas for communication or technical breakdown, which would prevent the bid from going into the auction, and negatively affect overall bid health.

Companies are generating more data than ever before, and traditional dashboards are unable to keep up with the volume and complexity of the vital business data collected. This is particularly true for companies using a Snowflake warehouse. The businesses served by Anodot have millions of customers across the globe and must manage millions of daily business metrics involving product usage, application performance, APIs, log-ins, and payment gateways, among others. Traditional manual business monitoring solutions cause significant delays of at least 24 hours or longer in detecting and resolving critical incidents, which threaten to impact customer satisfaction, brand equity, and the company’s bottom line. Transactional and customer experience data is too volatile for static monitoring. Since business data is complex and dynamic, AI/ML-based autonomous solutions are critical for achieving business outcomes and avoiding blind spots. Static monitoring approaches based on dashboards, and manual thresholds aren’t sensitive, robust, or agile enough to withstand this challenge. AI-based early detection of revenue issues and business system failures is nonnegotiable.