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Uncover the risks of bad data for brand equity. Discover how inaccuracies, poor targeting, and misleading insights erode trust, hinder growth, and damage reputation.
The equity of a business brand is an essential aspect that plays a significant role in the success of a business. On most occasions, business stakeholders find it difficult to create a balance between short-term revenue investments and the long-term building of brand equity.
The invention of marketing analytics and big data has increased business stakeholders' challenges in their day-to-day operations. Given that the amount of data generated by companies is increasing every day, the challenges imposed on the decision-makers also increase.
What you need to keep in mind is the fact that bad data has a huge negative impact on the success of businesses. Data innovations and technologies play a significant role in helping business owners predict some of the strategies that customers can find appealing and what can solve their needs.
Data analysts understand the art of analyzing large data sets and extracting critical information that can help them figure out the best way moving forward. They can easily identify the customer's buying patterns and some transaction histories that can help them better understand their customers.
This article discusses what you need to know about brand equity and the bad data impact on brand equity.
What is brand equity?
When analyzing the customers' purchasing behavior, you need to understand that customers will only buy products from companies they trust and recognize. Brand equity refers to the perception that a given company adds to its products or services across its target market. Good brand equity automatically reciprocates an increase in the number of revenues and profits recorded.
Data scientists who know more about promotional analytics understand that brand equity is the most important aspect that makes them stand out. Regardless of the power of brand equity, you need to accompany it with the right data that communicates directly to your consumers.
Data visualization created with the help of different tools like, Powert BI, Tableau, ChartExpo, etc helps business stakeholders to bring brand equity to life, enabling them to make the right decisions.
Data has become more granular and is applied in almost every department to enhance business development. The quality of data you use to facilitate your daily operations will determine the milestones you will make going forward. The data you use should reciprocate the achievements you intend to make in the long run. This is why bad data will always have an impact on the brand equity of your business.
Effects of bad data on brand equity
When it comes to a data visualization scenario, data analysts always work with an adage that states that garbage in, garbage out. The quality and accuracy of your data input will determine the accuracy and quality of the data output. If the data insights you collect are inaccurate, they will automatically affect the reputation of your business. This is why you need to shed light on some of the impacts of bad data on your brand equity, as outlined below.
Affects the customer experience
When a given brand is associated with any ups and downs, the customer experience is automatically ruined. Remember that the customer experience is one of the major components that make your brand stand out from your competitors.
When you note a bad customer experience, it means that approximately 71% of your data is incorrect. If you are dealing with misleading data sets, it will automatically affect the decisions you make and how you serve your customers.
The customer profiles that are created from the demographics data are specifically used for advertisement purposes. They are also used to enhance growth initiatives and contribute to the continued development of the business. In addition, the data is also applied to create better inbound customer experiences.
When you look at these aspects closely, you will realize that bad data will send away potential customers who could have played a significant role in promoting business development.
The exciting fact is that you can restore orders and high-quality customer services if you cleanse the data and ensure that you are dealing with accurate values. The solution only lies in investing and accurate information that can play a fundamental role in decision-making and serving your customers appropriately.
Results in slow brand transformation capabilities
Data is an essential investment for companies that use innovative approaches to transform their daily activities. You will need high-quality data sets to enhance the brand transformation capabilities and create a data-driven business environment. The transformation of your brand will only be successful if you invest in quality data sets that communicate clear insects.
When bad data gets access into the brand transformation route, it blocks the transformation process that's blocking the company from reaching its full potential. Such instances are likely to retard the transformation process limiting the company from increasing its revenue streams and recording more profits. The success of a given product is mainly limited when a brand's reputation is altered from time to time.
High-quality data can help you recognize the essential changes you need to make to enhance your brand transformation. The slowdown in brand equity optimization affects the continued growth of a given company, limiting the chances for the business growing bigger.
Companies are always on the lookout for new opportunities that can benefit them in the long run, which bad data cannot offer.
Generates glitches in programmatic advertising
In the past, brand-building strategies were mainly formed based on instincts and intuition. The invention of data analytic strategies has dramatically changed how things were done in the past. Currently, most activities are automated in nature to increase production and efficiency across the business industry. The majority of customer data is used to generate insights that are valuable during the decision-making process.
The advertising department within the business setting is supplied with data generated from different channels to help them make better decisions. When this department is supplied with bad data, it affects the kind of decisions that are made, resulting in glitches. In addition, a company is likely to make significant losses when advertising decisions are made based on bad data.
Business automation requires you to have reliable data sets that can offer valuable insights to the respective department.
When your data is unreliable, it becomes challenging to make accurate decisions and investments that can benefit the business. This is one of the major challenges that business stakeholders tend to face when supplied with bad data.
Excessive promotional analytics
Promotional marketing is an important part of transforming business performance. It helps to enhance brand awareness and create a better environment for your customers. However, promotional analytics requires reliable data to help the marketing strategist invest in accurate decisions.
This mode of marketing generates income for the business in the form of dividends after a given period. Most developed companies use the strategy to enhance their continued growth and attract more customers.
Even though investing in this strategy can have a long-term impact on business success, using bad data is likely to cause redundancies in your strategies. Bad data will not be able to tell the marketing strategist anything that can help them make the right decisions. Remember that the role of data, in this case, is to tell more information about consumer logic and create accurate promotional strategies.
Creating promotional strategies from bad data will only generate sales for a shorter duration. At some point, the strategies generated cannot work, thus driving the company into losses.
Results in overspending
Even though the digitization process requires you to have a unique budget to facilitate the process, you are likely to overspend if you do not have a good strategy to use. This is one of the major challenges that most companies are facing when it comes to using modern technologies. For instance, digital ad spending requires you to use different programmatic channels that rely on data to work effectively.
Utilizing bad data can easily result in poor spending with limited results. You will reach a point and realize that you are spending more than you are getting. Companies tend to make major losses due to overspending on strategies that do not generate any yields in the end. When using digital advertisements, you need to ensure that ads are targeted to the right consumers in order to get good results.
The targeting requires you to utilize accurate data that can help in targeting your respective audiences. Bad data is ineffective when it comes to helping you channel your efforts to the right market in order to generate results. This reaches a point and drives your business in the wrong direction without making any returns.
Real-life example of a brand loosing brand equity because of bad data
Heineken began utilizing the slogan "sometimes, lighter is better" when advertising its light beer.
The 30-second TV commercial featured a barman passing a beer through three black people to a woman with lighter skin, despite the fact that the phrase is neutral on its own.
Naturally, the TV commercial was labeled racist by many, with Chance the Rapper leading the fight and tweeting to his more than 7 million followers about how "terribly racist" the advertisement was. One of the quickest ways for your brand to come under pressure is to have a well-known voice reinforce criticism of your marketing campaign in this way.
2. Dolce & Gabbana's chopsticks ad
Dolce & Gabbana, a high-end fashion label, may have avoided charges of using blackface, but a racist backlash followed an ad campaign that extensively included ethnic stereotypes.
The advertisements featured a Chinese model attempting—and failing—to use chopsticks to eat various Italian cuisine. The idea that Chinese people lacked sophistication and a knowledge of other cultures infuriated many.
Customers criticized the company by boycotting it and charging it with bigotry. In spite of their regrets, Domenico Dolce and Stefano Gabbana were forced to postpone their Shanghai fashion show, which cost the company millions of dollars.
3. Department of education
Education must not simply teach work - it must teach life. – W.E.B. DeBois pic.twitter.com/Re4cWkPSFA
— U.S. Department of Education (@usedgov) February 12, 2017
Typos happen, especially when tweeting on a specific day or occasion. Therefore it's usually a manageable problem. When you work for the American Department of Education, though, it is a significant thing.
The DoE tweeted a W.E.B. Du Bois remark in February 2017 but misspelled his name. The subsequent apology had 'apology' spelled incorrectly. Perhaps the third time is the charm?
Betsy DeVos, the controversial secretary of education, didn't do much better after this gaffe. This was definitely a social media flop that generated some heat for the department, especially since DeVos had already received repeated criticism for her lack of qualifications for the position.
Although novice errors may not be as harmful as some of the ones we've highlighted above, they can quickly erode performance.
Every company is doing everything possible to preserve its brand equity. What most business stakeholders fail to understand is that bad data can easily affect their brand equity, causing them to lose customers.
It is always important to ensure that your business brand has an impeccable reputation across the target market. This will help you to attract customers from different localities and gain their trust.
By understanding the impacts of bad data on brand equity, it is high time that every company should invest in high-quality data for better results. The quality of your data will determine the returns you get and the success of your business. Investing in data visualization technologies can greatly help you ensure that the data you are dealing with is high quality and accurate.
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