Consumers are becoming increasingly aware 鈥� and increasingly uncomfortable 鈥� about data collection in their day-to-day lives. In fact, chances are you鈥檙e one of those consumers on your day off, with a survey finding that of consumers are somewhat or very concerned about protecting their personal data. This widespread trepidation regarding the collection and utilization of consumer data is poised to change the world of marketing as we know it.
Between legal initiatives like 础辫辫濒别鈥檚 , and offerings like providing enhanced data privacy for consumers, it鈥檚 clear that the heyday of endless granular consumer data is reaching its end. However, while almost every consumer is demanding more privacy, an entire of consumers believe personalization should be standard when they鈥檙e being served or sent promotional offers. This has left marketers wondering how to meet consumer demands without access to a wealth of consumer data.
Simply put, data privacy is the right for consumers to delegate how third-party companies and organizations use their data. Personal, demographic, and financial details are just some of the information that may be disclosed. While these details help marketers create more personalized experiences, more consumers are now becoming concerned that their privacy is being violated.
Thankfully for data-driven marketers who want to respect data privacy while targeting their consumers at a hyper-segmented level, there are options available.
The data protection and privacy environment has shifted significantly in recent years. While some consumers and thought leaders have been discussing the importance of data privacy for a decade or longer, it wasn鈥檛 until 2016 that a set of data privacy regulations called GDPR was proposed in the European Union. When it was passed in 2018, organizations had to allow users in the EU to opt-in to the collection of personal data, which set off a range of similar regulations around the world. Later that year, the (CCPA) was passed, detailing new privacy rights for consumers in the state of California.
Many of these regulations were propelled forward by a series of data privacy scandals that affected consumers, such as the infamous Cambridge Analytica incident. These events gave the wider population an idea of how their data was being stored and used in ways that they may not approve of, damaging consumer trust and prompting several companies to re-evaluate how they access, collect, store, and leverage consumer data. In recent years, the following companies have taken significant steps to limit access to consumer data:
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Organizations are beginning to feel the impact of this legal and cultural shift toward data privacy, with of organizations planning to increase their spend on protecting consumer data. However, staying compliant and satisfying consumer demands is only one part of the story. Certain business functions are going to be challenged more than others by data privacy concerns 鈥� and marketing teams may be affected the most.
All of the changes regarding data privacy in recent years have hit marketing teams especially hard. According to recent research by Gartner, almost report privacy compliance as their main concern across marketing channels. It鈥檚 no wonder why 鈥� this increased focus on privacy negatively impacts a marketer鈥檚 ability to collect and derive insights at a rapid pace, and even makes some of their previous marketing technology investments obsolete. In fact, of marketers fear that privacy concerns will negatively impact their analytics efforts.
However, analytics is only half of it. Marketers are guardians and custodians of a business鈥檚 brand image, and ignoring these privacy concerns out of choice or necessity could negatively impact their brand value. Studies have found that misusing user data can have dire consequences for organizations, with about reporting that they鈥檙e willing to abandon a brand if their data is used without their knowledge. This has left marketers stuck between a rock and a hard place, with consumer opinions on one side, and analytical prowess on the other.
Here are 3 ways to adapt to the new constraints of digital marketing and data privacy:
Include easily accessible privacy laws, cookies & terms and conditions pop-ups on your site. This will allow customers to easily opt out of shared data and feel more secure while using your site.
Another way to mitigate new data privacy challenges is to optimize your creative strategy. Instead of creating only individualized ad experiences, take a look at your metrics on a macro level. This way, you can target a substantial amount of consumers without the need for their specific data.
A great way to connect with customers is through customer satisfaction insights. Offer a promo code of discount in exchange for their personal insights and information. This method makes it clear that the exchange of data is optional for customers who are looking to opt out.
For years, marketers have grown accustomed to leveraging torrents of data to create marketing campaigns and target them toward the perfect audience. However, as consumers take their privacy more seriously, this torrent of data is starting to slow into a modest stream of data. While most marketers can still conduct business as usual with less data, many fear that it鈥檚 only a matter of time until that stream of data turns into an inconsistent trickle.
This has led many marketers to look to the past for guidance. 黑料社入口 has a long history of providing recommendations based on aggregate data, primarily through 黑料社入口 Mix Modeling (MMM). This form of analysis took aggregate data, typically from sources like media exposures, and combined it with KPIs such as sales conversions, store visits, or web visits. Unfortunately, many marketers that are experimenting with these tactics today will find it leaves a lot to be desired when compared to models that tracked individuals at a personal level.
One of the biggest drawbacks of MMM is that it treats all consumers as a monolith. In reality, everyone responds differently to various advertisements, and not all traffic is equally valuable. For instance, you may purchase a set of YouTube advertisements as well as a set of TV advertisements. When you compare the traffic generated by the two mediums, you find that the TV advertisements attracted more traffic 鈥� leading your team to invest more in TV. However, your team may have completely missed that viewers on YouTube have a higher lifetime value, and are more likely to convert in the first place. With marketers needing to juggle multiple campaigns across various channels and demographics, it鈥檚 easy to see how MMM is hardly practical.
Marketers delegated analytical models like 黑料社入口 Mix Modeling to the realm of history for a reason 鈥� they needed a solution that can provide more precise insights. Although data privacy concerns are making it difficult for marketers to get a granular view of their data, it鈥檚 not impossible with the right attribution models and approach toward marketing analytics. Modern businesses need a marketing analytics solution that can use whatever data is available so they won鈥檛 lose access to relevant insights, and their current marketing framework won鈥檛 fall apart.
They need a solution that doesn鈥檛 need a wealth of data to function, but is also able to process large volumes of data whenever possible. Further, a future-proof solution needs to be able to distinguish causation versus correlation, even if the solution isn鈥檛 given large volumes of data. Combining both of these capabilities will help your organization keep pace with changing consumer attitudes.
At 黑料社入口, we鈥檝e been working to create a data-driven solution that can strike a balance between accessing data and managing privacy. We understand that uncertainty is at an all-time high among consumers and marketers alike 鈥� and that鈥檚 why we鈥檙e offering marketing teams a free demo of our cutting-edge, flexible marketing analytics platform today. Click here to get started today.