There is one word that haunts the dreams of marketers: alternatives. Alternatives are the foundation on which our whole modern, capitalist economic system is built. They are the paragon for competition and choice.

Alternatives can help a marketer brand a newly launched product as a substitute for an already existing one – in which case it’s the marketer’s sweetest dream. In the same way, they can disrupt the market completely for already established products and provide new fierce competition – in which case it’s a marketer’s worst nightmare.

Today, having no alternatives to a product is an extremely unlikely scenario. More likely, there are already at least a few players in the industry, and a marketer’s job is to convince the customers to choose their products, services or offerings.

Personalized digital experience

And so, the greatest show of all times begins: a marketer’s journey to provide a personalized digital experience for every user entering the platform.

We live in a hyperconnected world, where people provide a plethora of data to indicate their interests, needs, and desires. Companies now have to fill in the blanks and target their customers based on accurate data and deliver a personalized experience.

This means that companies have to focus on the customer, not just on their products or services. And data becomes the ‘spokesperson’ for every client.

This is one of the reasons the analytics industry thrives. A/B testing, data collection, data integrity, personalization, warehousing or data security are just a few of the services we, as analysts, engineers or marketers provide in the vast world of analytics.

Companies are hungry for more data. They want the full story behind their users, they want to know them better, so they can target more accurately and efficiently.

A recent Frost & Sullivan study showed that by 2020, customer experience is projected to overtake price and product as a key brand differentiator.
Clients are already used to being ‘wooed’ by companies with personalized experiences. They became so accustomed to being known and to instantly find what they need that they can discard a brand easily if it fails to provide just that.

It’s also a lot easier for customers to allow brands to have data about them. It saves a lot of time and effort and it provides a more immersive experience on the platforms.

For example, many times when you go shopping online, you don’t even need to go through the whole process of searching the item you want. It’s often displayed right on the homepage, via careful targeting, similar to the way programmatic advertising is being served.

A few years ago, programmatic advertising became the hottest trend among marketers and advertisers. By leveraging advanced machine learning algorithms, advertisers can now identify potential customers by demographics, interests, time of day, device, weather, geography, on top of location, age, and gender. This helps companies target their clients with a lot more precision, by pinpointing them using a lot more coordinated than before.

Similar machine learning algorithms are used for powerful suggestion engines, such as the ones on Netflix or Spotify. This can significantly improve a user’s experience on a website or platform, but it can also pose a serious risk when it comes to data privacy.

Whenever someone opts-in for something on a website, or chooses to share their data, they agree to be tracked – to some degree – by the company. Most of the time, this process is harmless, and it’s actually beneficial since it greatly enhances their experience.

However, companies can also sometimes misuse data.

Cambridge Analytica

Facebook’s Cambridge Analytica scandal represents one of the most vivid representations of such threats.

A small digital company specialized in profiling potential voters for candidates managed to be the epicenter of the biggest scandal in Facebook’s recent history. CA harvested data from the private Facebook profiles of around 50 million users without their consent.

Empowered by the data they’ve collected, Cambridge Analytica was able to exploit the private social media activity of millions of people, data that could be used in any way you can imagine.  

As analysts, we have a duty to both safeguard the data we collect, and to use it properly, legally, for the reasons that the users trusted us with.

It is easy to get hyped when you’re facing endless rows of data, some more precious than gold, but, to quote a Marvel classic, always remember: with great power, comes great responsibility.

Data is currently the world’s most precious commodity, and companies and individuals across the globe are trying hard to find ways to both harvest more of it and to protect it.

Data Privacy and GDPR

Europe’s reaction to the growing data-security crisis is the Data Protection law – GDPR (General Data Protection Regulation), which will force any company handing data to walk the extra mile to safeguard their client’s data.

The aim of the GDPR is to protect all EU citizens from privacy and data breaches in today’s data-driven world.

Even if the regulation only applies to EU citizens, US-based companies and organizations from all across the globe must get their platforms compliant if they want access to one of the biggest markets. Even if your website is hosted in the US, if someone from the EU access it, it falls under GDPR.

This forced companies from all over the world to start strengthening their data security and privacy.

With GDPR, the EU also introduced a new legal requirement: privacy by design. At its core, privacy by design calls for the inclusion of data protection from the onset of the designing of systems, rather than an addition.

Also, the conditions for consent have been strengthened, and companies are no longer able to use long illegible terms and conditions full of legalese.

“The request for consent must be given in an intelligible and easily accessible form, with the purpose for data processing attached to that consent. Consent must be clear and distinguishable from other matters and provided in an intelligible and easily accessible form, using clear and plain language. It must be as easy to withdraw consent as it is to give it”, according to the GDPR’s principles.

GDPR also introduced data portability – the right for a data subject to receive the personal data concerning them – which they have previously provided in a ‘commonly use and machine-readable format’ and have the right to transmit that data to another controller.

What can analysts and marketers do?

GDPR reshaped the way organizations across the region approach data privacy and the harsh sanctions for companies which fail to comply (up to 4% of the firm’s worldwide turnover) will be a reminder for anyone trying to meddle with data.

But regulators will not be able to verify how every company is handling data, and news agencies won’t always break the story.

Safeguarding a user’s privacy should also be the main concern and the mission of any business allowing third party-firms to operate on their sites.

It falls to us, the analytics community, to educate, to protect and to ensure that user data and their privacy is safeguarded.

“The main reason companies collect data is to be able to deliver an ideal experience for their customers. Many of the big company’s decisions are data-driven. Having a good product is no longer enough by itself, and it does not automatically mean that customers will embrace it. You have to target their individual needs and desires, to make sure you touch the pain points and tell them a personalized story convincing enough to convert them.

By being such a valuable asset, companies should try to ensure the highest level of data security. This means that not only that data collection must be thoroughly executed (so that data is accurate), but also that there’s where data security starts. Messy data is as bad as no data. No company can use non-qualitative data or inexact data.

When it comes to access to data and confidentiality, companies should aim for the highest level of security. Data is the most important asset a company possesses, so only certain people should be allowed to manipulate and handle data”, said Alex Holhos, analytics engineer at Cognetik.

Lately, data governance has been one of the top priorities of managers. With the growing volume of data and privacy scandals, the topic of who handles data within a company emerged.

As a definition, data governance encompasses the people, processes, and technology required to create consistent and proper handling of an organization’s data across the business enterprise.

Cognetik, as a company, helps companies implement Data Governance policies to establish fundamental processes for your organization in key areas, such as data collection, quality assurance, security, accessibility, and analysis.

Clearly defined procedures will drastically reduce the timeframe from ideation to implementation and analysis, and will decisively drive your business toward data-driven decision making. Strong Data Governance practices will highlight personal data protection as one of your company’s top priorities and will demonstrate your commitment to safeguarding your customers’ valuable data assets.

There are also other benefits of using data governance, such as increasing consistency and confidence in decision making, decreasing the risk of regulatory fines, improving data security, maximizing the income generation potential of data, optimize staff effectiveness, establish process performance baselines to enable improvement efforts and many others.

“While concerns regarding data privacy have skyrocketed in the past months, most consumers still want personalization to drive better digital experiences. These two concepts can avoid being antagonists, but for that, businesses need to take three major steps:

1. Rely on better data rather than big data. Organizations should start asking critical questions about all data elements that they are collecting, rather than turning their data warehouses into digital Pandora’s boxes.

2. Don’t focus on third-party data vendors. Not only do third-party data from different vendors have a higher percentage of inaccuracies (because of the way they are often aggregated from different sources), they also present a trust and legal risk as they are coming from an entity external of the business – client relationship.

3. Transparency and control. Consumers expect to have full visibility and control over what data your business owns and the possibility of easily controlling what and how their data is used”, said Robert Petrescu, Analytics Manager at Cognetik.

About the author

Sebastian Stan

Sebastian is a journalist and digital strategist with years of experience in the news industry, social media, content creation and management, and digital analytics.

eBook: Understand Your Customers

Cognetik eBook: Guide to User Journey Analysis


Related Articles