Today’s marketing leaders strive to collect, process, and activate large amounts of data in an effort to improve data-driven decision-making, execute personalization at scale and activate a myriad of use cases.
The power of data and analytics is well documented and cannot be overemphasized. Highly data-driven organizations are three times more likely to report improvement in their decision-making, according to PwC research. However, too many marketers are focused on the quantity, rather than the quality, of the data they are working with. Companies will not reap the maximum benefit of data if they are working from a foundation of inaccurate information—or, worse, they will do more harm than good by making choices based on faulty intel. The problem becomes more severe when bad data is used to train machine learning models, since the resulting models are only as good as the data used to train them; without a good dataset, predictive analytics becomes merely calculated randomness.
The mere term “big data” illustrates the prevailing emphasis on quantity. That is going to have to change. Evolving data privacy regulations, coupled with consumers’ increased understanding of how their data is used, or misused, will force companies to revisit their data sources, scrutinizing accuracy alongside ethics and sustainability. Data collection processes also matter to a company’s consumers and partners. According to Pew Research Center, 81% of Americans feel they have very little or no control over the data that companies collect about them, and 79% are very or somewhat concerned about how companies are using this information. Likewise, our regular studies into consumer trust have repeatedly revealed that — while financial institutions and market research firms garner the most trust — there is considerable need for social, search, and media companies to improve consumer trust in their data practices. After all, privacy is a basic human right, and marketers need plans for obtaining data in a way that respects and protects people.
By focusing on data collection processes and the authenticity of data, companies will drive better business outcomes, remain in compliance with privacy regulations, and prove to consumers that they respect their privacy.
The need for transparent data processes
When marketers purchase data, they often fail to ask data providers about the data source and collection processes. This can lead to significant repercussions down the line, particularly if data was not sourced in a sustainable way that is respectful of user choice. After all, legislation continues to move rightfully in favor of consumer protections, with GDPR and CCPA being the most prominent examples. While compliance with today’s standards should be a baseline to avoid legal, financial, or reputational ramifications, companies would be better served in the long term by partnering only with the data providers who make their processes transparent to clients and consumers alike.
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Beyond following the law, maintaining ethical data practices is simply the right thing to do. How effective consumer privacy regulations will be remains to be seen, but giving people agency over their own data is a step in the right direction. It is also critical to the longevity of data-driven marketing. As an industry, we can only sustain a sharing economy — in which people willingly pass on their data in exchange for something of value — if people trust the process and feel empowered by choice.
The ripple effect of faulty data
Although the industry has made strides in its efforts to curb fraudulent traffic, bots are still booming. According to some estimates, more than half of all internet traffic is nonhuman. Bot traffic can skew data and cause marketers to make inaccurate decisions or waste their budget.
Every marketer proceeds on the assumption that their data is reliable, but most marketers are not putting in the work to verify it. If the data is not of high quality, it will negatively impact business decisions and marketing efforts. This will also have a ripple effect, causing the marketer to make inaccurate conclusions about their strategy, and therefore, ill-inform future decisions. So, when obtaining data, ask for details about the data collection process and whether it was obtained from humans and with their permission. If the data provider cannot answer these questions, or shares misinformation, it is a huge red flag. If a vendor is not transparent with you, it is likely they are not transparent with the people sharing their information either.
It’s also important to ask about how recently the data was obtained. In most cases, data value diminishes with time, especially if you are trying to adapt based on real-world user behavior. For example, an automotive dealership looking to drive foot traffic won’t achieve results by seeking to understand or appeal to people who were in-market for a car last year. Instead, they need to tune in to people currently exhibiting measurable behavioral indicators of purchase intention. This requires fresh, accurate, and rich data based on both consumer attitudes and behaviors.
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As marketers become more discerning about their data, they will find they have less meaningless data to sift through, yet discover more actionable insights. In return for their focus on data quality over data quantity, they will get a clearer view of how to best appeal to their audiences, whether in the products they make or the campaigns they launch. Above all, by raising the bar for data providers and advocating for fair and sustainable processes, they will foster consumer trust, building healthier relationships with the people who choose to share their opinions and behaviors.