Businesses rely on intelligence from media sources as a foundation for critical decision-making, as reflected in the 2018 AMEC Global Insights Study, where more than half of companies em-phasised insight over evaluation in media reporting.
At the same time, one in four media-measurement companies reported an increase in demand for fully automated solutions. Can machine-driven solutions deliver the insight that companies need, or are organisations falling for flashy dashboards delivering titillating, but largely useless, data? Let’s look at why it is important to strike a balance between automation and curation in media intelligence.
Technology has changed the face of the media industry, producing an explosion of online, social and digital channels that create and share content by the second. Similarly, it has boosted our capacity to quickly and cost-efficiently collect, process and display vast quantities of data faster than the human brain.
But speed and quantity doesn’t necessarily deliver quality. The key is to understand the limitations of technology, the parameters of the media that matters, and the context of how the information will be used within your business.
Computers operate best on the heavy lifting of data analytics to accurately monitor and measure anything that is tagged or categorised. Companies operating in formal settings, such as legal environments or national news channels, where communication tends to remain within searchable parameters of terminology and format, may find that automation alone delivers strong results.
"Data can be crunched but true insight – telling us what we don’t know that will make us do something differently – requires a human mind"
But if yours is one of the majority of companies today that communicates through a mix of earned, owned, shared and paid media and generates a broad variation of data – from text and video to images, emojis and GIFs – computer-based monitoring and measurement alone will not provide accuracy or insight, and rarely justifies the investment without an element of human validation, enrichment and insight.
Different generations, communities, nationalities, social groups and even individuals personalise their own forms of expression and communication at such pace and complexity that computer science struggles to keep up. Furthermore, sentiment, nuance such as sarcasm and humour, and even punctuation can dramatically influence interpretation, yet fail to be registered by machine-based analytics. Data can be crunched but true insight – telling us what we don’t know that will make us do something differently – requires a human mind.
Without question, automation has advanced over the years, but to date even the best monitoring and computer-based sentiment analysis programmes peak at 70 per cent accuracy, which means more than one in every three articles is likely to be wrongly reported in an auto-only scenario. Can solid strategic business decisions be made on data at this level of accuracy? And while auto-generated charts tend to count lots of stuff, ask yourself this: are they measuring the things that matter to your organisation?
Undoubtedly automation will continue to improve, and this should prompt more demand for qualitative and strategic insight. The two components go hand-in-hand. But the key to successful media monitoring and measurement is defining a blended approach of machine and mind – automation and curation – that delivers the right quality and reliability of actionable insight, so that your business decisions are based on the information that really matters.
Richard Bagnall is chief executive of Europe and the Americas for CARMA International, and Chairman of AMEC