Branding

Brand Perception: What It Is, Why It Matters and How to Measure It

When was the last time you really thought about your perception of a product brand or service? Sure, we might use online brands every day in our work or at play, but do you think about how you perceive a brand? You should.

Brand perception is important. It's the sum of our feelings, attitudes, and experiences with a product or service. Brand perception is what moves the needle for companies, taking a common product and giving it elements that evoke emotional feelings. Every car ad during football season is appealing to a viewer's emotions about the brand. Every skincare ad seeks to sway a consumer's emotions into creating a favorable brand perception.

Ultimately, the customer is the one who decides their perception of your brand. Whether you're marketing a consumer commodity like clothing, or a high-level B2B web application, how consumers view the brand can make or break a product.

Let's break down exactly what brand perception is, why it matters and how you can measure its impact in your daily work.

What Is Brand Perception?

Put simply, brand perception is the sum of feelings a consumer has about a brand. These thoughts and feelings happen when a consumer is aware of the brand, and what follows when that consumer hears, sees, or interacts with the brand and its product.

Brand perception incorporates a multitude of areas that touch upon the brand's customer interactions. From product development and packaging to public relations and social engagement, brand perception is a top-level measuring stick of a product's visual presence, goodwill, and emotional character. All of these can play into the product's success.

Think about Facebook, for example. Last year Facebook's brand perception fell out of favor with many because of privacy issues and the platform being found to be the conduit of false or misleading news stories. Brand perceptions of Facebook were significantly changed in 2018, which is why the company is now making moves to make public opinion of its brand more positive.

Even for small companies, brand perception is one part of a larger marketing equation. How does your product or service resonate with its target audience, why does it matter, how do consumers feel about your brand, and how can you measure this?

Why It Matters

Brand perception is important because it reflects what consumers think about a company's culture. We've mentioned Facebook, but this affects even emerging online brands such as Fashion Nova and Everlane.

You might see a branded TV spot, read a review, or catch a pre-roll YouTube ad. These brief interactions can quickly change a consumer's perception of a company from negative to neutral, or from neutral to positive. That's the power of brand perception, and that's why it matters.

Once consumers formulate a perception in their minds, whether positive, negative, or neutral, it's hard to change their beliefs. That's why companies are trying hard to measure brand perception on their own.

Measuring Brand Perception

How can companies measure brand perception? There are agencies that would be glad to charge $5,000 to $25,000 a month for the privilege, but your own team can scout the web to get a fairly reliable reflection of consumers' perceptions of your brand. Some ways your research and marketing teams can do this might include:

●       Setting up Google alerts to track online mentions.

●       Reading online reviews. (This is critical for all brands. Efficient customer response can also help with brand reception.)

●       Social listening, which means monitoring social media comments, hashtags, and other mentions.

●       Measuring metrics for pay-per-click brand search and dwell time.

Overall, companies need to work hard to measure brand perception. A brand owner must measure the brand from the outside to truly understand how people view it. To do so, companies can try a variety of methods to gauge brand perception:

●       Track metrics in your target audience around your brand.

●       Use custom research among primary and secondary target audiences.

●       Conduct a brand audit on your company's brand perception against that of your leading competitors'.

●       Track customer sentiment through each stage of the purchase cycle, including information search, product evaluation, comparison research, buying decision, and post-buying feelings.

Brand perception is a critical part of your company’s marketing effectiveness. Getting a handle on it and putting your resources into knowing how to use it will help your company better plan its marketing campaigns.

How Can Machine Learning Boost Your Brand? Check Out These Key Ideas

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Artificial intelligence is now playing a greater role in capturing and developing relationships with consumers, and machine learning is one field of AI that has marketing potential to harness. To truly understand machine learning's potential, deeper insight is required to fully execute its impressive applications.

Building Trust and Improving Experiences With Chatbots

Conversational interfaces continue to improve consumer relations, which ultimately opens the door for marketers to use chatbots in an array of applications. An intuitive form of conversational AI, chatbots are used across sales and customer support to provide customers with 24/7 self-service on their own terms. Not only does this machine learning technology align with the millennial mindset, but it's also hailed by industry research firms as a dominant force amongst decision makers in the purchase process.

Chatbots extract and sift through data quicker than humans can. The result? Better delivery of more personalized consumer experiences. This is especially true for customers desiring self-service. As such, the need to fulfill a task independently now outweighs the need for another person when technology is the desired choice. Instead of being instructed to "press three to speak with a representative," chatbots are quick to extract details to direct prospective customers without delay. This allows users to naturally communicate based on personal preference. 

Brands can effectively implement chatbots to serve as the first point of contact for engagement. What better way to drive up interactions and generate leads to funnel into the appropriate channels? Moreover, it's a definitive resource with which to operate more efficiently, add value, and build brand loyalty.

Prioritizing Personalized Care

Top brands are adopting machine learning practices to identify, predict, and take action on trends affecting product or service development. With more insight into leveraging machine learning, brands are better equipped to improve upon existing products and services.

Savvy brands use machine learning to launch innovative strategies for better customer experiences. It's the orchestrated efforts to attract, sell, and serve that win out when enhancing customer satisfaction. Another competitive strategy for market leadership hinges on customer intimacy — provide unique methods to personalize service and customize products to meet differing needs. AI is better at learning what's effective for prospects and consumers.

Improving Targeting Accuracy

As with any marketing strategy, there's always room for improvement. An investment in machine learning allows marketers to create targeted advertising effortlessly and effectively. The value of doing so (besides giving marketers valuable data on consumer behavior) is that advertising decisions are carried out in real time. With an AI-based model in place, the decision on when to display targeted ads is entirely up to you.

There's a heavy reliance on data, but as it increases, so does the challenge to manage data effectively. Machine learning streamlines the processes of data analysis in advertising. AI is the go-to process when brands want to target potential customers with precision. For example, Facebook Business Manager is an important advertising tool. When a target audience is created based on interests, machine learning enhances the strategy. The targeted interests are all generated via machine learning, which is the same algorithm that analyzes data users voluntarily input into their profiles.

Optimization of Pricing

For brands struggling to set appropriate prices, machine learning can help. Since consumers have a wealth of options with which to compare prices, brands must factor in specific competitor criteria to accurately set prices. Machine learning's algorithms generate data to better detect emerging trends or new demands. Brands benefit most from predictive models to best price products and services.

Next to autonomy and speed, the biggest advantage of using machine learning to optimize prices is globalization. Imagine manually inputting pricing parameters into multiple channels. Then there's price changing, which can impact product sales in other areas. Machine learning crunches the numbers more accurately. It even anticipates market trends when brands need to make appropriate decisions to adjust prices.

Lastly, when competitive pricing strategies are paramount to success, it is possible to use machine learning to crawl the web and social platforms to collect essential information about competitor prices for identical or similar products. You can also analyze customer feedback, popular deals, and pricing history over a period of days or weeks. An intelligent system like this will constantly learn the digital landscape to give brands more leverage over the competition, which leads to wiser pricing decisions.

Determining Incentives and Sale Offers

Brands can further optimize marketing efforts by defining which sale offers, promotions, and incentives to present to prospective customers. This is accomplished through the use of multiple channels, which is yet another machine learning strategy that's transforming marketing.

Specialized sale offers are created through contextual information, offers, and incentives. Each is systematically structured using machine learning. In turn, AI regularly predicts the best possible combinations of marketing elements to generate an upsell, cross-sell, or new sale entirely.

As brands work vigorously to ensure products are exposed to the right consumers, advances in AI continue to emerge to help reach marketing goals. With proper planning and execution, machine learning has the potential to have an exponential impact on advertising.