With today’s online capabilities enabling information to spread like wildfire, one minor slip-up can cause extreme reputational damage. For corporations and organizations, maintaining a clean and professional reputation is essential to conducting successful business operations.
Marketing teams strive to achieve positive brand awareness, and corporations of higher stature are more likely to land partnerships. Security and reputational risks can always pose threats.
For these reasons, organizations may turn to reputation and performance insight technology to improve their operational efficiency and protect their reputations. These tools enable business leaders and decision-makers to understand the status, changes, and trends of their reputation and business performance.
While there are various software solutions available on the market for managing reputational risks and performance, Signal AI’s tool utilizes a unique approach for maintaining security and managing reputation’s impact on business performance. The global decision augmentation company harnesses AI technology with metrics that enable users to run high-level analyses and aggregations.
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In addition, Signal AI’s technology is built on knowledge graph principles for mapping reputational data and showing shifts over time. Its new API suite supports topic mapping for enhanced analysis of organizational reputation and risk data. This solution provides users with access to new quantifiable reputation risk data for better insights and informed decision-making.
CIO Insight interviewed David Bengison, CEO of Signal AI, to discuss the company’s software, its influence on business operations, the future of reputational software technology, and more.
Performance insight and its effect on operations
CIO Insight: Why do you believe collecting and analyzing data is valuable to the success of an organization? How have current events or recent business trends influenced the importance of reputation analysis for businesses and organizations?
Benigson: Even before the pandemic, the global business environment was quietly evolving in the face of two key forces. The first was a huge boom in business intelligence and the need for comprehensive, data-driven decision-making. And the other was the rise of ESG as a serious factor in corporate strategy and success.
This fact is evidenced by our recent research that showed that a whopping 72 percent of business leaders see reputation as a stronger driver of business performance than the margin in the next five years. And the fact is that without sophisticated data and an equally advanced means of analyzing it, organizations stand virtually no chance of successfully tracking and maintaining their reputations in a way that will keep them in the best reputational light.
Enter AI. Through advances in AI and next-gen data science, it is now possible for organizations, their comms teams, and agency partners to not just monitor reputation in real-time but proactively identify possible risks, avoid them and then recalibrate.
Moreover, organizations can now set reputation goals such as “we want to be known as the most innovative financial services brand by 2030” and have metrics to measure how well they perform against these stated objectives. This is a far cry from the reactive world many brands live in today and allows organizations to finally take control of their reputations in a way they simply haven’t been able to before.
CIO Insight: What is the main mistake businesses and organizations make today regarding their performance and reputation management?
Benigson: Data is the lifeblood of every decision a business makes…that is, except when it comes to their comms and reputation management operations. All too often today, while the rest of an organization is speeding toward a new data-driven future, comms teams are stuck in yesteryear using outdated methodologies and guesswork to try to deliver communications success.
The result? Instead of being in a position to dictate their own future, businesses are constantly on the backfoot and waiting for issues to arise. This is largely due to many organizations not realizing that the tools are now available for them to become more progressive in their reputation management, or decision-makers don’t see the value of data and thus decide to “stick with what they know.” Either way, this state of play needs to change if organizations have any chance of finding reputation success today.
Businesses trends and reputational management
CIO Insight: How have current events or recent business trends influenced the importance of reputation analysis for companies and organizations? Can you think of a specific use case where organizations could improve their reputation with revised data analysis methods?
Benigson: Because of how long static and reactive reputation management has prevailed in the business world, there really isn’t a business arm or industry that can’t benefit from the switch to a real-time approach.
For example, before launching a new ESG initiative, organizations can use real-time tools to scientifically assess media sentiment and key trend areas to identify opportunities where they might be able to deliver the most impact instead of banking on rudimentary analysis.
Furthermore, organizations can use real-time data to understand the media sentiment or proximity to topics around their organizations better ahead of key events—such as annual meetings or earnings announcements—and take proactive steps to position themselves as best as possible instead of relying on guesswork.
New methods for gaining insights on organizational performance
CIO Insight: In what ways do Signal AI’s new methods for analyzing reputation risk data differ from that of other decision augmentation solutions?
Benigson: Our decision augmentation solution provides a new kind of external intelligence fit for the modern world business leaders now have to navigate. We are constantly thinking about how we can deliver insights to power an entire organization, not just one specific business function or another. And to deliver that, we believe that you have to go beyond just simple media monitoring and dig into what is underneath.
For example, to truly understand an organization’s place in the market and its opportunities and hurdles, you need to be able to easily synthesize a myriad of factors. These include which topics the organization is most associated with, how prevalent it is in the public consciousness, how it stacks up to competitors, what risks a company faces as a result of a breaking trend in a far-off part of the world, and much, much more.
These capabilities—alongside our endless organizational push to create a hub for all of the insights a company needs—separate our platform from the rest in this space.
CIO Insight: How do Signal AI’s reputation scoring methodologies help business leaders make better decisions?
Benigson: Our AI-powered knowledge graph can track an organization’s proximity to a topic in the media and see how this shifts over time, from established topics the company is known for to new topics that they may want to be known for.
At Signal AI, we work with business and comms leaders to establish scoring methodologies that sit alongside company goals. For example, an ESG framework can measure real-time pillars and topics the company wants to be known for and is also actively working on.
We have standard measurement frameworks, but what is most valuable to our customers is the work we do in supporting them to index business priorities. The index can be used in reporting, but also as a live litmus as to where external narratives are headed. It forms an external intelligence radar.
CIO Insight: How often do you believe a company should analyze this data to develop insights?
Benigson: Given how interconnected the business world is today, enterprise brands really cannot afford to not have their fingers on the pulse of what is happening at every moment of the day. Therefore, they need access to the insights around not just their own branded terms, but also around any topics that relate to both their brand and those of their competitors.
Moreover, since the business world is perennially speeding up, and conditions around a company’s ecosystem are constantly evolving, businesses simply can’t rely on periodically updated data anymore. There is a strong chance that insights from that morning have changed by that evening, so real-time data has become a prerequisite for business success today.
Reputation and performance tools and services
CIO Insight: What challenges that corporate businesses face could be alleviated by Signal AI’s technology? What reputation threats does Signal AI’s analysis identify and protect against?
Benigson: Brands are largely aware of the importance of key terms related to their company or competitors, as well as known-unknowns. However, they still almost universally struggle to monitor for unknown-unknowns—items that they had no idea would potentially impact their reputation—and thus are routinely left with unwelcome surprises.
A good example of this would be detecting anomalies. All too often, companies may see a spike in coverage around a particular event—a labor strike within a particular industry in another country, for example. But because they don’t see an obvious direct correlation between the incident and their organization, they may not take any proactive action until it comes back to bite them later.
This is just one example of how the Signal AI platform can help organizations keep tabs on evolving areas of risk and opportunity and connect the dots between how those areas could potentially impact their reputation and business performance.
CIO Insight: In what ways can an organization’s operations improve through this method of data analysis? What industries do you believe would benefit most from these revised practices of reputational analysis and why?
Benigson: Many companies have a good grasp on their internal data and are already making confident decisions based on that data. For example, commercial teams use Salesforce data to spot risks and opportunities or trends, and talent teams use eNPS data to spot areas of improvement for employee engagement. Internal data has been driving strategic decision-making for some time.
What organizations don’t understand as well is their external intelligence—the things happening outside their company that can have dire effects on the fortunes of the company, or indeed contain potent opportunities.
With the emergence of ESG and related reputational issues that have a direct impact on company performance, having a decision-making “sat nav” for these external factors is going to impact many industries, from fund management to insurance to tax and regulation. Having a way to make sense of the external data that will affect your industry is key.
The future of performance and reputation technology
CIO Insight: What are your future predictions for AI technology to maintain business reputations? Do you believe there will be an increase in technological development for this intent?
Benigson: Prior to the mass digital transformation efforts that gripped the business world during the COVID-19 pandemic, there were definitely industries that saw the value in being as data-driven as possible. However, because of the COVID-19 pandemic, virtually every industry has now seen the virtues of having data as another core tenet in their business intelligence and decision-making. This includes reputation management.
That said, many businesses are still in the early stages of adopting AI for reputation management. They are just beginning to see the value of top-level benefits like having real-time monitoring capabilities. But, as AI becomes more synonymous with reputation measurement and management, we will see a push among businesses for tools to deliver more intuitive insights.
Thus, the biggest priority for the AI industry over the next few years needs to find ways to innovate and push their tech capabilities even further to keep up with market expectations.
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About David Benigson
David Benigson is Chief Executive Officer and founder of decision augmentation company Signal AI. He, Miguel Martinez, and Wesley Hall founded Signal AI in 2013 to use automated intelligence to augment the process of accessing and analyzing business-related news.
Signal AI has become one of the world’s fastest-growing applied AI companies, conducting business with multiple Global Fortune 1000 businesses and offices in London, New York, and Hong Kong. So far, the company has seen much support, and they have gained a current total funding amount of $101,600,000.
Note: This interview has been edited for length and clarity.