Nothing matters more to brands than their reputation. This invaluable asset determines brand preference, customer loyalty, brand awareness and contributes over 60 percent to a company’s market value. When we talk about the health of a brand, we aren’t just thinking about whether or not people think favorably of a company. Brand health consists of how key audiences and stakeholders think of your brand. This isn’t limited to products and services — it’s all-encompassing, from a company’s sustainability to its innovation and use of corporate assets.

Enterprises want to measure every aspect of their brand and the impact individual traits have on their overall reputation. This is a proven challenge. What traits or qualities are associated with your brand? What traits are more valuable than others? How can you measure how much traits like innovation affects your brand reputation? Why is your company known for innovation?

In the past, companies relied on expensive, time-consuming, manual activities such as phone surveys, focus groups and hand coded quantitative analyses to gain insights into how key audiences viewed their brand. Today’s rich digital environment makes measuring brand reputation and its individual components a far easier proposition. Innovative companies are using machine learning to calculate message pull-through metrics to measure how key audiences talk about their brand. Here’s how these types of metrics can measure your brand reputation against key brand attributes.

Brand + Attribute

Just knowing that your brand was mentioned 12,000 times over the past week means very little. What provides far more value is understanding the context of each of those mentions. Machine learning can search through articles and identify the words your brand is associated with. For example, IBM likely wants a strong brand reputation for its artificial intelligence, Watson and big data capabilities. To measure this, the tech giant would want to know the number of times their brand is referenced in the same sentence as the phrases “Watson,” “artificial intelligence” and “machine learning.” Using this information, the company can work out what audiences most closely associate their brand with and alter marketing and communications campaigns based off of this information.

Market Leadership References

Everyone wants to be the market leader in their space – but as the old saying goes, wishing doesn’t make it so. Accurately measuring a brand’s reputation helps the company learn if they can truly claim the mantle of market leader – or if they have some work to do before they get there.

Machine learning can help unearth these useful markers. For example, it’s not just enough to earn a mention in The Wall Street Journal – it’s also the context around your brand. Are you mentioned with words like “leading,” “innovation,” “pioneer,” for example? Augmented intelligence can surface these. Likewise, looking at where your brand is mentioned in a piece is also important; the headline is worth so much more than the closing paragraph, for instance. Those same metrics can be used as a yardstick against competitors, allowing you to rank the perception of your brand against the competition.

Media metrics have come a long way from just mentions and shares. When used correctly, this dataset can provide crucial information on the health of your brand and provide key information on how competitors position themselves in the market.

 

Learn more about these modern media metrics by downloading our white paper: The Modern Media Metrics That (Should) Matter To Businesses And Brands.