The reputation of a business is an essential factor in its survival and a crucial component of its overall valuation. Executives know their companies’ reputations are important because firms with strong positive reputations are differentiated in highly competitive markets and they attract more people, which enables them to enjoy sustained earnings and future growth.
Moreover, in an economy where 70% to 80% of a company’s market value comes from hard-to-assess intangible assets, such as brand equity, intellectual capital, and goodwill, organizations are especially vulnerable to anything that damages their reputations.
Poor consumer service can negatively affect a business in a variety of ways. It can result in a loss of current and potential customers and cause negative word-of-mouth advertising, which can result in the loss of future customers. Furthermore, it can have a negative effect on small businesses, which rely on repeat business and positive word-of-mouth advertising.
Although companies are aware of the importance of a good reputation, they try to attract customers mostly by providing as much content as possible. Most of them believe any data is better than no data and that there is no such thing as bad data. But the problem is that data can be bad.
Bad or dirty data refers to information that is erroneous, misleading, and not formatted. Unfortunately, no industry, organization, or department is immune to it.
Businesses open, close, or relocate on a daily basis. It takes a lot of effort to obtain the most current geolocation information. Most users believe the data they find online is accurate. They trust data providers, and they don’t even think about the possibility that the data could be outdated and/or incorrect. In the past couple of years, users have discovered and reported a lot of missing and inaccurate geolocation data, such as missing national parks, misplaced businesses, and new airports. Another very common situation is the presence of inaccurate data, such as incorrect addresses or telephone numbers for hotels and restaurants. This might seem like a small mistake, but these mistakes have a negative effect on all parties included in the geolocation data life cycle:
- A poor end user experience will decrease customer satisfaction.
- Businesses will lose clients, which will have a negative effect on their revenue.
- Data providers will lose their good reputation since customer satisfaction and a company’s reputation go hand-in-hand.
- In the end, company that sell data will have to lower the price, and they will never be able to charge a premium for their data again.
Conclusion
Bad data matters to those who see it. It matters to end users, to businesses whose information is published, and to the companies providing the content. Inconsistent, inaccurate data results in a loss of customer trust and customer churn, and it highly damages companies’ reputations. Obtaining high-quality data is expensive. But it could cost you even more if your data turns bad. You’ll have to spend significantly more to clean up that data and repair the damage left in its wake.
