Que medidas você pode tomar para proteger a privacidade do cliente na análise de marketing?

Laws and regulations are often dense walls of text which are daunting to most marketers and analysts. They also refer to other laws an regulations on top of which they build, which makes it even harder. When starting out, you might want to focus on reading discussion forums where marketing experts and legal experts discuss these topics. This will help you understand the nuances and hopefully makes it more interesting to you. (One recommendation is the #data-protection-priv channel in Measure Slack (join.measure.chat).) If you want to further pursue this topic, you might consider getting IAPP certified, or at least read through the body of knowledge required for the relevant geolocation where you operate.

Technical marketers do not have time & resources to read through every lines of the laws. And they keep on changing. Its highly recommended to bring out the trackers anyone wants to build then consult with client’s legal team and let the trackers be the decision of the client only. Because anyone will not want any blame in the future (if anything goes wrong).

Specifically when marketing to existing customers, it’s important to have a contact governance in place that can act as a guiding tool to set frequency capping based on channels, product(s), type of messages, current satisfaction level, and exposure of the same message etc. Following such a governance also makes one smart in prioritising campaigns such that business priorities and honoring customer preferences are balanced. We mastered this way back in 2007, for HDFC Bank, through whom we introduced enterprise marketing automation to India.

Protecting customer privacy in marketing analytics involves anonymizing data, obtaining consent, securing storage, and adhering to regulations. It’s crucial to be transparent, minimize data collected, train staff, and regularly audit practices. Prioritizing privacy not only builds trust but also ensures compliance and ethical data usage.

Studies do show that consumers trust brands that prioritize data ethics. Building your marketing on a foundation of transparency can boost loyalty and engagement, especially in today's privacy conscious landscape.

Rather than targeting a particular set of population, it is more useful to create a 'persona' and then plan your marketing activity targeting people who fit that 'persona'. It not only helps in adhering to data privacy policies (which can vary based on different geographies) but also reduces the cost of marketing which can be really high if target group is very small & close.

Choose a tool adapted to the market your targeting. For instance if you have a website in EU, you should consider using cookieless tracking tools such as Piano Analytics, Piwik Pro or Matomo.

Incorporating peer review into the data collection process is crucial for producing high-quality, trustworthy data as it helps to ensure the quality and validity of the collected data. This process also helps to identify any potential biases or errors in the data collection process and ensures that the data is reliable and generalizable.

First, audit the current state and determine what data you want to collect from your users. Second, research what geographical areas are compatible with what data formats and types. Last, closely collaborate with your legal team and together with them enable the user consent for only essential data.

Data collection is the lifeblood of marketing, enabling us to make informed decisions and deliver personalized experiences. However, it's a double-edged sword. Data fuels us, it also poses risks. As strategists, our role is to evaluate what data we need, where we can get it, and how we INTEND to use it. We build a "best-case" scenario and collaborate with privacy experts to reign us back into reality... OVER collaboration with IT, legal, and other departments is crucial to ensure we protect customer privacy. It's about striking the right balance between building the best data-driven insights possible and totally safeguarding our customers' trust & info.

As a Marketing Leaders, we need to work in partnership with IT, Audit, Legal and Security departments to ensure that the data we are collecting from all of our sources is secure and well used. It doesn’t matter that it is a responsibility of someone else, if you are getting de data you need to push inside your organization to protect and to guarantee that information will be safe.

Data governance in marketing has always been a mess which most companies are trying to work out with more or less success. Still, it is very common to find u unclear ownership between departments or even agencies/consultants or fear based decisions. Given the risks that companies face when not ensuring a proper level of security, this leads to slow and risk averse decisions without allowing the company to develop the right security measures. Establish policies with the right enforcement and making key employees accountable for respecting internal policies is also key in ensuring following best practices that avoid losing consumer trust.

Security is critical, but it's crucial not to confuse Privacy and Security. The fact that you store and transfer data securely, although important, has almost no influence on privacy (regulation) whatsoever. Often, security measures (like hashing data in transit) are touted as privacy features. They're not. The privacy of the data subject is still at risk with the data processors and data controllers that are involved. So, security: yes please! But also: privacy yes please!

Lock it down: Strong access controls, encryption, and backups keep data safe, not in open forums. Minimize is maximize: Collect only what's needed, anonymize where possible. Less data means less vulnerability. Transparency matters: Be clear about data use, respect opt-outs, and build trust with every click. Educate, empower: Train teams on data security, and watch for any suspicious activity like a hawk. Adapt and evolve: Stay ahead of threats with ongoing audits and updates to your data fortress. Remember, secure data means happy customers and thriving campaigns. So lock it up, minimize it, and build trust – your analytics will thank you.

Securing customer privacy in marketing analytics is vital for trust and compliance. Here are steps with tool suggestions: Anonymize Data: Tool: Google Analytics, Adobe Analytics Action: Remove personally identifiable information (PII) to prevent individual identification Data Encryption: Tool: AWS Key Management Service, Azure Key Vault Action: Encrypt data during transmission and storage to prevent unauthorized access Data Masking: Tool: IBM Guardium, Oracle Data Masking Action: Mask sensitive information, revealing only essential data to users based on their access levels Regular Audits: Tool: Varonis, SolarWinds Action: Conduct periodic audits of data access to identify unauthorized activities. Stay informed about data protection

When we analyze past and potential customer data, this is one of the crucial steps we take. In most cases, quantitative analytics are already anonymized when we receive it from data sources. But qualitative data will always have personally identifiable trace backs to real customers. What we do is, we summarize such qualitative insights from customer data and assign a pseudonym to the customer persona and remove any personally identifiable data. We share such qualitative customer insights with content creators, partners and agencies, only after going through this step thoroughly.

An effective method to anonymize data involves aggregating it to a level where it remains valuable for generating customer-centric insights without compromising privacy. However, achieving this balance requires careful deployment, aligning with the principle of collecting only essential data. Organizations face crucial decisions when determining the granularity of data collection. Establishing robust data governance is pivotal, restricting access to only essential parties for viewing, processing, and aggregating the data. Post-aggregation, this data can be more widely shared across various analytics applications, harnessing the power of data analytics while upholding customer data privacy.

Anonymization or pseudonymization are great ways to ensure data science teams can work with customer data, extract insights or support decision making by using the latest solutions on segmentations, predictions, scoring and some others. You can apply those learnings in an aggregated manner as you cannot trace back the individual. However, when you want to leverage customer information for digital marketing, you need the ability to apply the learnings in an individual manner, for example to send them a personalized email or to include them in an audience for Meta Ads or Google Ads. Anonymization and in most of the cases pseudonymization will prevent you from benefit of the most value in using data for digital marketing

Optimizing digital marketing campaigns often doesn't necessitate user-level data. In such cases, consider employing data clean rooms, which enable the analysis of customer data without compromising individual identities. These clean rooms also provide stringent controls to prevent the cross-sharing of customer-level data between different entities. Also, keep updated on the latest developments in digital marketing and data privacy best practices. Engage in industry conferences, webinars, and training sessions to ensure the team remains up-to-date. Given the rapid industry shift towards privacy-centric regulations, a lot of solutions are emerging. Thus, staying relevant in this dynamic landscape is crucial.

Per my experience, anonymizing organizational data is a crucial step to protect privacy and comply with data protection regulations. The process starts from data inventory management and classification, define objectives of the anonymization process, understand the level of privacy needed for the specific use case and the regulatory requirements applicable. Now the data minimization and anonymization techniques to be implemented based on the data types and privacy requirements. Anonymization process to be documented followed by testing and validation. Last but not the least enforcing strict access controls is the key to ensure that only authorized personnel have access to both the original and anonymized datasets.

A general rule of thumb is to ask yourself this - Does your use of granular customer data, and subsequent actions, have the potential to ‘surprise’ the customer? Regardless of how pleasant you think this surprise might be, once you’ve crossed that line, you are basically giving your end customers full authority (and rightly so) to start questioning your intentions, prompting them to wonder if they should continue to let you use ‘their data’ to such intrusive levels.

When customer provides data to you, that means they trust that you are a partner who will take care of their data collection, analysis, and use. Avoid sharing with third party since this will increase your chances to lose control on collected data unless you are tied up with right agreement. Customer expect that you will be carful about his privacy. Your team needs to understand that this trust needs to be respected and it should not miss used.

As both a marketer and a consumer advocate, I strongly believe that customers do value personalization and that when it makes their lives easier, customers are willing to share their data. However, it's a delicate balance. If personalization isn't done correctly, it can come across as intrusive, making the efforts ineffective and worse, counterproductive. A strong foundational understanding of the customer and continual experimentation is key to finding the sweet spot. Consider variables like the customer's buying cycle stage, messaging, psychographic segments, and data points used for personalization to ensure a well-calibrated approach. An overarching guideline must be to be perceived as a helpful friend, not an unwanted intruder.

It may be old school, but the fundamental insight that "the customer is always right" should never be forgotten. Whatever the findings from analytics indicate, step carefully before acting against a customer preference or privilege. It takes only one negative experience to undo years of expensive brand building!

Data privacy regulations are not scaling back, if anything, they are rolling out in more countries and are being expanded upon. The days of wishful thinking and/or sticking your head in the sand are behind you. Marketing data never was fully accurate to begin with, and with consent in the mix, it will get even less accurate. These are the new rules, and they apply across the board. It's in your best interest to adapt your marketing practices to this new reality and learn how to work with imperfect data. You can try to continue to work in the grey zone, but in most cases, you'll probably lose more time/energy/money/lawyer fees doing that. Unless you're a billion-dollar advertiser, you're probably better off accepting this new reality.

Employing DMAIC (Define, Measure, Analyze, Improve, Control) from Lean methodology can enhance customer privacy in marketing analytics. Regularly review and refine data processes, identifying areas for improvement. Stay abreast of evolving trends and technologies, incorporating customer feedback and regulatory insights. Testing and measuring the impact of marketing analytics practices on customer satisfaction ensures continuous enhancement. By applying the DMAIC framework, organizations can systematically enhance strategies, fortifying customer privacy and fostering improved satisfaction, retention, and loyalty.

I'd like to add two more steps: offering granular control to users and moving beyond static to dynamic consent platforms. I generally recommend considering the "ACTED" framework, which is easy to remember: (A) Anonymization – Utilize techniques that dissociate information from user profiles, making it harder to identify individuals. (C) Consent – Obtaining consent from users implementing dynamic consent platforms where users can adjust their preferences and withdraw consent at any time. (T) Transparent Practices – Clearly communicate with users regarding how their data will be used for. (E) Empower Users – Offer granular controls over privacy settings. (D) Data Minimization – Collect and retain only the min necessary amount of data.

One thing that could be helpful is to have the Legal team do a yearly review of the privacy practices implemented by the organization. This way you could make sure that you're up to date with the latest regulations - which are almost impossible to follow by a regular marketer.

Los objetivos estratégicos de toda corporación debería ser medibles y aterrizados un cumplimiento real. Las grandes mentes del marketing tienen como objetivos atraer, pero, realmente estamos haciendo una gestión responsable y medible. El éxito de toda campaña es la medición de los resultados. En análisis de los mismos te garantizan obtener datos cuantitativos para poder categorizar los resultados y tomar decisiones basados en ellos. La analítica de datos ha centrado su base en entregar resultados positivos, pero también es válido cuando los datos arrojan resultados para tener un feedback y así poder implementar un correcto feedforward.

I have been in a position where I've had to work with legal for a whole quarter to review T&C's on data collection because we had not updated them in over three years. This is a very strenuous and monotonous process that can be saved if you're consistently monitoring what you your legal obligations are.

If you're a business that relies on customer data to monetize in any form, there must be a sound, air-tight consumer value exchange. In other words, for passing their personal information to you, how are you making your customers' lives easier or better? Make that value exchange abundantly obvious in your customer experience if you have to. Data businesses that are legally compliant but have a disingenuous (or nonexistent) value exchange with their consumers or brands will have a shorter runway than you.

It's also crucial for company leaders to champion data privacy and protection in marketing analytics. They should prioritize providing adequate training and resources across the entire organization. Emphasizing the significance of data protection encourages every employee to actively contribute to self-governance in this realm. Often in bigger companies, people don’t know what they don’t know. Tie it in with your company values and make it a point to remind people of the consequences of data breach.

In advertisement world collection of data represent the two way interaction between consumer and brands. Remarketing needs data to reach out and convert interest into purchase through showcase product list. Data in the form of NEP (name, email & phone) is not only a consumer identity in real or digital world its may be his/her key of finance and physical security so all marketer should take a oath to protect data from any breach.

Respecting the privacy regulations is a sign of respect to the customers. If you don't respect your customers, they'll never trust you, and they won't buy from you. Yes, it's tedious work to consider the privacy laws from each country where you are selling, but once implemented it brings only advantages.

C'est aussi très important pour une entreprise de s'assurer que ces collaborateurs externes respectent la vie privée de ses clients et traite les données éthiquement. Les responsabilités juridiques peuvent remonter jusqu'à vous en cas d'anomalies.