The Growing Role of Brand Tracking
Brand awareness is a top priority for companies in 2024 (Figure 1), but how can you systematically measure and track something as intangible as "awareness"? This comprehensive guide covers essential techniques and best practices for conducting brand awareness surveys – one of the most effective methods for gauging brand perception.
Figure 1. Marketers state building brand awareness as their top priority.
As Figure 1 shows, organizations are investing more into brand tracking than ever before. Google search interest in "brand awareness" has rapidly grown globally over the past five years:
Figure 2. Global Google search interest in "brand awareness" has nearly tripled since 2020, highlighting its increasingly strategic role.
Industry surveys also find 90% of companies now monitoring brand KPIs consistently versus just 63% in 2016. Clearly, brands recognize consumer sentiment and associations as key growth drivers alongside product and pricing factors.
This guide will cover what‘s driving adoption plus best practices to leverage brand tracking – especially awareness surveys – within your organization.
Defining Brand Awareness Surveys
Brand awareness refers to how easily prospective customers can recall or recognize your brand. It‘s the first step of brand perception and a prerequisite for further brand building (Figure 3).
Figure 3. Brand awareness drives customer journey stages.
Brand awareness surveys specifically gauge current perceptions by questioning a sample customer audience. They reveal:
- Familiarity: How easily can respondents recall or recognize your brand? What perceptions exist?
- Associations: What attributes, feelings, and associations surround your brand image?
- Touchpoints: Where and how often are audiences engaging with brand messaging?
Unlike vague marketing KPIs, brand awareness survey data is rooted in direct customer feedback. This makes surveys invaluable for accurately tracking awareness over time.
Surveys also have unique advantages over other common brand tracking methods:
| Method | Pros | Cons |
|---|---|---|
| Surveys | Direct customer feedback | Manual analysis needed |
| Web Analytics | Automated data | Indirect awareness signal |
| Search Volume | Broad signal | No context on perceptions |
| Social Listening | Real-time feedback | Can lack representation |
We‘ll revisit integrating surveys with these complementary awareness metrics later in this guide.
Quantitative vs. Qualitative Analysis
Effective brand awareness surveys use both closed-ended quantitative questions and open-ended qualitative questioning.
Quantitative questions gauge hard metrics like familiarity and purchasing rates on a numeric scale. These metrics allow precise awareness tracking against business growth metrics.
Examples:
- On a 1-10 scale, how familiar are you with Acme Co. products?
- Have you purchased from Acme Co. in the past year?
In contrast, qualitative open-ended questions reveal detailed audience sentiments that quantitative data misses. Common text analysis approaches include:
- Word frequency analysis
- Sentiment categorization
- Topic clustering to find shared opinions
Examples:
- What words or feelings come to mind when you see Acme Co.?
- How could Acme Co. better address your pain points?
Later sections will demonstrate advanced analytics to draw deeper insights from qualitative data at scale.
Sentiment Analysis
One especially useful brand awareness analysis is sentiment analysis on open-ended survey feedback.
This uses machine learning models to categorize each response as positive, negative or neutral based solely on written content. The overall breakdown shows current brand sentiment and helps identify growing issues.
Our guide covers Sentiment Analysis Benefits more in-depth, including top use cases.
For example, Acme Co. noticed declining purchase intent scores in their surveys. Sentiment analysis revealed a sharp increase in negative complaints about shipping delays:
Figure 4. Sentiment analysis on open survey responses revealed shipping delays were hurting brand perceptions.
Addressing this operational issue helped reverse falling metrics. This demonstrates the power of connecting qualitative feedback to quantitative KPIs.
Advanced Analytics Methods
While essential, basic survey analysis only hints at the insights possible from direct customer data. Advanced analytics help surface hidden patterns driving consumer decisions:
Predictive Modeling uses machine learning algorithms to identify likely behaviors based on survey profiles. For example, brands can predict purchase intent likelihood for new subscribers based on feedback data. These models guide highly targeted, highly effective campaigns.
Text Analytics reveal deeper semantic insights within written feedback beyond basic sentiment. Topic modeling uncovers overlapping themes across all comments to learn shared opinions. Keyword analysis tracks evolving brand associations and pain point trends.
Interactive Visualizations connect survey metrics to business performance automatically. Dashboards relate response patterns to website traffic, revenue, return frequency and 300+ other metrics through drag-and-drop. This enables faster root cause analysis and better data-backed decisions.
Later in the guide we‘ll demonstrate survey analytics through real brand case studies. But first, let‘s cover common methodological pitfalls in data collection.
Survey Bias and Representativeness
Garbage in, garbage out – biased samples produce misleading results. Unfortunately, subtle sampling biases can easily creep in:
Participant Biases
- Self-selection bias if respondents opt-in or take incentives
- Social biases like wanting to look knowledgeable
Access Biases
- WEbsite pop-up survey misses mobile users
- Email survey misses non-subscribed customers
Analysis Biases
- Leading questions anchor responses
- Confirmation bias in interpreting results
The best defense is simple awareness coupled with best practices, including:
- General population panels over open recruitment
- Standardized questions tested for neutrality
- Multiple question phrasing and contexts
- Random sampling within target segment
- Checking results against behavioral data signals
Later we‘ll cover multi-mode data collection and integrated dashboards to cross-verify survey findings. But first, let‘s explore top considerations when initially drafting your brand tracking survey.
Crafting Brand Awareness Questions
We‘ve stressed using both qualitative and quantitative questions – but great survey design is still essential. Keep these tips in mind when building a questionnaire:
Familiarity Questions
- When did you first become aware of our brand?
- How often do you encounter our brand messaging?
- How familiar are you with our products and services?
Perception Questions
- What words or feelings come to mind when you see our brand?
- How strongly do you associate our brand with __ attribute?
- How well does our brand address your pain points?
Message Testing
- What channels and messaging grab your attention, positively or negatively?
- How effective have you found our recent ___ campaign?
Demographic Questions
- Optional location, age, gender, etc. questions for audience segmentation
Keep questions clear, specific and concise. Balance open and closed-ended types to encourage detailed feedback.
Integrating Surveys with Other Brand Data
While powerful independently, surveys truly excel when integrated with external awareness metrics. This provides validation, alternate perspectives, and a bigger picture view.
Web Analytics reveal traffic drivers and on-site behaviors indicating awareness strength:
- New vs returning visitors
- Referral sources
- Site search queries
- Landing/exit pages
Search Volume taps into broad consumer interest beyond your existing audience:
- Monthly search volumes
- Click-through rates
- Competitor benchmarking
Social Listening is real-time, open qualitative feedback from both customers and prospects:
- Brand handle mentions
- Sentiment trends
- Demographic variations
Integrated dashboards relate survey findings to these datasets for richer insights:
Figure 5. An integrated dashboard ties survey results to web, search and social data in one view.
Look for validating trends as well as gaps suggesting survey sampling issues or segment differences. Our 40+ Integrated Dashboard Examples article explores top use cases more in-depth.
Next let‘s connect the dots from survey results all the way to guiding business growth through advanced analytics.
Relating Surveys to Business Impact
Listening to customer voices is table stakes – but it‘s still important to connect feedback to the bottom line.
Quantitatively track awareness metrics against business KPIs like:
- Web traffic
- Ad recall lift
- Purchase intent
- Revenue
The goal is to find leading indicators from surveys that precede tangible results. Declines in familiarity or message resonance often manifest in hard KPIs months later, creating an early warning system.
Figure 6. Correlation analysis reveals leading survey indicators with 3-6 month priors to business impacts.
In Figure 6, message awareness lift leads eventual web traffic bumps by three months. Purchase intent correlates with revenue, but also likely indicates retention risk six months out.
These insights help optimize resource allocation across acquisition, conversion and retention initiatives. Our guide to Marketing Mix Modeling covers this advanced analytics concept more.
Building Customer Relationships
Beyond numbers, brand awareness surveys build customer relationships and goodwill. They signal to audiences that their voice and feedback matter.
Pay special attention to the pain points and suggestions within open-ended responses. Addressing these directly through site updates, new content or feature tweaks goes a long way to strengthening customer bonds.
For example, Acme Co. noticed a sharp uptick in complaints about limited shipping options:
"I love Acme Co. products but really wish there were faster shipping upgrades. I can‘t always plan ahead 2+ weeks and pay exorbitant rush fees when I unexpectedly need something sooner."
Acme Co. responded by testing a new Premier Delivery program with free 5-day shipping and free returns. They announced this directly to complaining survey participants.
The positive, grateful reactions created brand advocates – driving more value than any single order. This demonstrates the power of closing the loop with customers through surveys.
Attracting New Customers
While current customers offer useful perception data, brand awareness surveys also provide a window into untapped segments.
Ask both existing purchasers and cold prospects about your outreach channels and messaging. Look carefully at gaps in channel usage and themes in negative feedback.
These reveal opportunities to tailor content and exposure to demographics you currently miss. New personalized messaging helps convert more prospects most open to your brand‘s unique value.
For example, Acme Co. noticed very low awareness and favorability within college-aged survey respondents. Further brand association analysis revealed perceptions of being antiquated and boring.
Acme launched an integrated "New Perspective" campaign showcasing fresh styles and young brand reps. Early results show much higher consideration and click-through rates among university publications and forums.
Our detailed guide on Buyer Persona Development explores ideal customer profiling to inform targeted outreach.
Distribution and Sampling
You need diverse, representative participants for insightful brand awareness results across all audiences.
Cost-Effective Channels
- Email existing customer lists
- Website banners or pop-ups
- Social posts and ads
Third-Party Audience Access
- Survey panel providers like AIMultiple
- Targeted social ad buys
- Rewarded channel partnerships
Adopt best practices like personalized invitations and mobile optimization. Expect a ~10% response rate for cold outreach up to 30% for existing buyers.
Follow our guide covering Online Survey Research from start to finish for more distribution and sampling tips.
Key Takeaways
Brand awareness surveys provide uniquely valuable data on current brand perceptions and changing audience sentiments over time. This guides messaging and growth opportunities in a way marketing KPIs alone can‘t match.
Conduct periodic brand tracking surveys across diverse audiences while employing both quantitative and qualitative analyses for a multi-dimensional view. Look to correlate feedback themes with business impact and address pain points through improved customer relationships.
Integrate survey results with web, search and social data for validation and blind spot checks. Treat text responses not as one-off anecdotes but as strategic listening posts via advanced analytics.
Most importantly, close the loop with customers by directly addressing suggestions and complaints. This builds brand advocates likely to drive even greater lifetime value than a single transaction.
Now learn more about turning insights into action via AIMultiple‘s managed analytics services. Our data experts help implement best practices around surveys, dashboards and advanced analytics tailored to your growth goals.