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Guide to Five Brand Metrics that Matter

Posted by Margot Sinclair Savell on February 08, 2018

Brand-centric metrics have an elevated role in media analytics in 2018, because many organizations are losing interest in vanity metrics such as followers and fans, and instead are seeking brand insights to inform future strategy. My last blog post provided information about brand metrics. Now, let’s look at specific ways to pull and parse data for five brand metrics that matter.

First, the best practice is to choose brand metrics that align with your business and communications goals. But don’t cast the net too widely by using dozens of metrics. Choose a handful of specific metrics to provide an understanding about the words and phrases that your audiences associate with your 1) brand attributes and reputation; 2) products and services; 3) industry topics; and 4) competitors. As well, don’t forget to keep an eye out for words that might indicate a pending crisis.

Search Queries to Pull Brand-Centric Data

Your analytics tool should have powerful Boolean search features that return relevant results because you can laser-target specific keywords and phrases. These tools also enable you to slice and dice data with Word Clouds and other charts that display sentiment, brand messages, competitive share of voice, prominent topics and more.

Of note, many online documents are available to show you how to set up Boolean queries and their operators (such as AND, OR, and NOT). These operators, along with qualifiers and filters, reduce the number of irrelevant mentions.

For example, if your brand attributes or messages are part of the boilerplate of your press releases, you will likely receive results from thousands of online distribution sites that don’t contribute to valuable knowledge about brand perception. You can exclude this information from your results by using the NOT operator for the phrases that are in the opening sentence or two of your boilerplate.

By sorting and visualizing this data in different ways, you can find trends and insights to guide your communications and business decisions. 

Five Brand Metrics that Matter

Here is a guide to set up the five metrics listed in my previous blog post, so you can pull and parse data to find out your key audiences’ impressions of your brand.

1. Brand Message Pull-through

This metric helps you understand the stories and conversations that contain your brand messages to make sure they resonate with your audiences. If needed, this will also help you decide how to revise your messages to reach a wider or more targeted audience.

Steps to Take: Create a complex search string for each of your key messages. (In other words, if you have five messages, create five separate queries.) Start with your company and brand names; stock ticker symbol; and Twitter handles and hashtags. If your company and brand names have nicknames, abbreviations, initials or variations on the spelling, be sure to add them as well. Then, complete the string by adding keywords and phrases from one of your messages. Repeat these steps for each message. After you pull the data, parse it into a Mentions chart for each search string, so you can review and analyze the conversations for individual messages.

2. Brand Attributes

This metric gives you insight into the words and phrases that people associate with your brand, such as confidence, trust, innovation, integrity, leadership, sustainability, satisfaction, loyalty, customer service or other brand attributes. Determining why these words are used is crucial to your analytics program.

Steps to Take: In this case, set up one simple search string with your company and brand names; nicknames; abbreviations; initials; Twitter handles and hashtags; and stock ticker symbol. Once the data is gathered, create a Word Cloud to visualize the words that are being used the most frequently to describe your brand, and then evaluate the results. If there are too many irrelevant words in the Word Cloud, revise your search string – limit it to words that describe your brand attributes plus the words that caught your attention in the initial query. (Note: You can also use these steps to examine purchase interest and awareness of your products, services and specialties, such as mobility, Cloud services or big data.)

3. Brand Reputation and Perception

The combination of word associations and sentiment provides a powerful metric to analyze brand reputation and perception. This dual metric will help you learn what drives positive and negative coverage; during a crisis, this information can help craft your strategic reaction to it.

Steps to Take: Again, set up one simple search string with your company and brand names; nicknames; abbreviations; initials; Twitter handles and hashtags; and stock ticker symbol. Next, add positive and negative words (such as best, worst, love, hate, superior, inferior, etc.) to the query. After the data is retrieved, create a Word or Emoji Cloud, so you can evaluate the volume and context of positive and negative words associated with your brand.

4. Brand Preference and Recommendations

This dual metric forms the cornerstone of positive brand recognition and reputation, unveiling a preference for your brand over your competitors. Learning when and why people state that your brand is best, and/or recommend it to others, helps generate buzz, and can be used in advocacy programs.

Steps to Take: Take the same steps as for the Brand Reputation and Perception metric, but add only positive words such as best, prefer, superior, endorse, advocate, commend or recommend. (Do not include negative words for this metric.) Study these endorsements over time to see what is being said about your brand and by whom. If you are being recommended by influencers, cultivate them for your outreach program.

5. Competitive Intelligence

This metric determines who has the largest voice among competitors on key topics for your brand and industry. Gathering such knowledge can uncover competitive tactics, messaging and positioning.

Steps to Take: First, create an overarching search string that includes the important words used in all your queries listed above. Next, craft a separate search string for each competitor that mirrors your string. But, of course, list the competitor’s nicknames; abbreviations; initials; Twitter handles and hashtags; and stock ticker symbol instead of yours. After the data is pulled, create a Share of Voice chart and also sort it by topics that are important to your brand. Mine the results to find out which competitor has the largest overall share of voice and the largest SOV by topic, and why. For example, perhaps their messages, positioning and/or activities contributed to generating the largest voice; learning this intelligence could lead to tweaks to your tactics.

After you have developed all your search strings, create a weekly reminder to clean, validate and optimize the data by adding exclusionary words, as needed, to clear any new clutter.

Summary

The foundation for meaningful analytics is built by choosing specific metrics that matter to your brand, and carefully constructing search strings with operators, qualifiers and filters that help eliminate noise. The results can give you reasons, backed by data, to fuel your brand’s positioning strategy and drive your future business decisions.

My next blog post will look at how companies can start to apply these metrics and practices in their everyday workflows and reporting activities.
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Margot Sinclair Savell is an award-winning writer who has decades of experience crafting and editing content. During 15 years at agencies such as Hill+Knowlton Strategies and Weber Shandwick, she specialized in strategic counsel for measurement, insights and analytics. In 2016, she was inducted into the PR Measurement Hall of Fame.

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