A well-structured media monitoring program empowers companies to make decisions with the latest facts and figures and enables them to take action and control brand reputation. Since information spreads fast through social media, companies need to identify them in real-time to monitor and predict their growth. However, performing media monitoring on the web and social web is both time consuming and effort-intensive. This is why today’s digital world is a tough place for providers of media monitoring and insight services.
Often, an unattended comment on a social media platform from a consumer can spiral into creating negative sentiment and impacting business performance. The key challenges faced by these service providers are measuring impact, proving value and demonstrating return on investment (ROI). This requires real-time monitoring software, expertise and dynamic visualization, which may be cost-intensive and affect ROI. Further, this gets compounded due to intense market competition with a crowded space of service providers operating at lower margins and where barriers to switching are even lesser. It does not help that service providers also have to contend with a fragmented landscape of different systems, often legacy processes and teams, which may be a result of several acquisitions across different geographies.
Media monitoring providers need to address these challenges with a fresh, more integrated approach to technology as well as operations. One that adopts smart technologies, ideally a single platform and new higher-value services without hurting the bottom line, while making sure that the local culture and language nuances are taken care of.
This requires a factory model for delivery that consolidates country centric operations into relatively more centralized operations. Doing this along with process standardization for common processes with accommodation of local nuances will help simplify the operations. These operations will be supported by teams organized by language and function, rather than by geography, which allows better cross-skilling and brings in more scalability. This frees up the remaining in-country teams to focus on customer support and sales, ensuring better ROI.
It is critical that the operations are supported by a common platform that have hyper automations built in with advanced analytics. A single integration layer will allow the ingestion of content from across all channels, making it easily available to current and future downstream services. Content augmentation through tagging, summarization and sentiment analysis is automated through a combination of a Boolean rules based engine together with cognitive and Natural Language Processing (NLP) methods. In the case of quantitative analysis, we see the potential for almost 100% automation, while the more qualitative work will continue to require some level of human intervention, although much reduced and likely to be further impacted as cognitive and NLP engines develop.
With the creation of a virtualized workforce of software robots to enable seamless automation for routine reporting and workflow activities, design thinking led AI enablement and simplification of processes to eliminate redundancies, companies can expect realizable savings of over 40% in addition to the increase in operational agility. Furthermore, a transformation like this will place media monitoring companies ahead of their competition to deliver high quality insights fast and at a significantly lower cost. Given the challenging business landscape, unpredictable demands and falling profitability, this is something surely worth considering.