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Brand analytics

How can brand analytics improve people, teams, or organisational effectiveness?

AccessibleOperationalTeam2 min read

Contents

Brand analytics seeks to determine the strength of your brand compared to your competitors.

Brand analytics measures how customers and other audiences perceive a brand, how that perception changes and how it compares with alternatives. A brand is more than its name, logo or visual identity: it is the accumulated meaning, expectation and experience associated with the company and its products.

When to use it

Monitor brand perception continuously rather than waiting for a periodic crisis or research project. Digital conversations make observation faster, although they represent only the people and channels visible in the data.

Gatorade illustrates real-time monitoring. Since 2010, its Chicago “Mission Control” centre has tracked brand, competitor, athlete and sports-nutrition conversations, analysed topics around campaigns and launches, and identified where discussion is accelerating. The aim is an ongoing view of how people talk about the company and its products.

Use brand analytics to answer:

What meanings, experiences and emotions do customers associate with the brand?

How are those perceptions changing?

How does discussion of the brand differ from discussion of competitors?

Origins

Brand analytics grew from earlier disciplines of brand tracking, consumer research and brand-equity measurement. During the late 1980s and early 1990s, scholars including David Aaker and Kevin Lane Keller formalised ways to measure awareness, associations, perceived quality and loyalty. The expansion of web search, online reviews and social platforms in the 2000s added continuous behavioural and text data, while natural-language processing made large-scale sentiment and topic analysis practical.

What it is

The intended brand is what management wants to communicate; the experienced brand is what customers and other stakeholders actually perceive. Search engines and platforms influence which evidence becomes visible, but they do not define the brand by themselves. Brand analytics should:

establish current market position and external associations;

measure the internal understanding held by managers and employees;

identify and close consequential gaps between intended identity and delivered experience.

Why it matters

Perception influences consideration, choice, willingness to pay, loyalty and recommendation. Even when a product is temporarily fashionable, management needs to understand the meaning customers buy beyond functional performance. Does the brand signal youth, innovation and creativity, or security, strength and trust? The answer shapes positioning, communication and commercial performance.

How to use it

Collect evidence wherever customers and prospects discuss or experience the brand: service and sales conversations, forums, blogs, reviews, search behaviour and social media. Google Alerts can flag new public mentions. Define the population and source bias before treating this evidence as representative.

Apply Sentiment Analysis to text or transcribed voice data to estimate positive, negative or neutral tone, then examine the topics and experiences driving it.

Practical example

Suppose you own a local chain of gyms and fitness centres. An earlier consultant-led study used Focus Groups, Quantitative Surveys, Qualitative Surveys and in-depth Interviews, producing valuable but expensive, slow evidence.

For the next cycle, begin with existing data. Search the brand, review result pages and gather relevant comments from review sites and public discussion. Use Sentiment Analysis to estimate overall tone and Text Analytics to identify recurring themes. Online material is recent and often candid, but it can overrepresent unusually delighted or dissatisfied customers, so combine it with representative research where important decisions depend on the result.

Top practical tip

Build a repeatable listening taxonomy covering the brand, products, competitors and key experience themes. Pair volume and sentiment trends with representative customer research and route actionable issues to owners quickly.

Top pitfall

Do not confuse available conversation with the whole market. Bots, channel demographics, selection bias, sarcasm and duplicated posts can distort results. Analyse only the evidence needed for a decision and validate automated sentiment before acting.