big data

General Data Protection Regulation: What You Should Know

May 24, 2018 by Daniel Laws Leave a Comment

If you’re in the digital marketing or analytics industry, you have probably been inundated by communication from vendors and partners regarding the General Data Protection Regulation, often referred to as (GDPR). Below, we’ve highlighted what GDPR is, why you should care, what impact it will have on your business, and what actions you need to take.

What is GDPR?

GDPR standardizes data protection law across all European Union (EU) countries and imposes strict rules on how personally identifiable information can be collected, stored, and used. The law goes into effect on May 25th, 2018, and all organizations working with the data of EU citizens must comply or face heavy fines. GDPR applies to every business that collects data from customers in the EU, regardless of the company size, location, or intentions.

Why should you care?

GDPR applies to all organizations that handle the personal data of EU residence. Many companies located outside the EU are unaware that the new EU data regulation applies to them. If an organization offers any products, services, or information to EU residents, it must meet all GDPR compliance requirements. Gartner predicted that up to 50% of American firms will not be compliant. Those organizations that do comply with the required transparency should help to build brand trust and equity among consumers.

How GDPR impacts your business?

Fines for noncompliance can be significant. A maximum fine of 4% of global revenues can be applied to companies that fail to gain user consent or violate core data security expectations. Lesser fines of 1-2% of revenues can be applied in situations where a company keeps incomplete records or implements insufficient data controls. GDPR requires organizations to appoint a Data Processing Officer (DPO) for EU government entities or public bodies or a company that either processes or monitors data subjects or sensitive information for citizens of the EU on a large scale.

What actions should your business take?

Below are a few steps that can help guide you for GDPR compliance:

Create Procedures for Breach Notifications
Determine if you’re a controller or a processor. The regulation breaks out responsibility for protecting data into two roles: controllers and processors.
Audit your data and know which technologies are being used on your website
Take the time to understand what data your business is collecting and why.
Review what consent and disclosure look like for your customers. Get the consumer’s blessing on data collection.
Evaluate exactly what third-party processors are collecting, where that data is going and how it’s being used.
Keep a document on data processing and create a process to refresh the documentation periodically
If a breach occurs, take action to inform regulators within 72 hours and be
ready to inform consumers as quickly as possible.

GDPR Impact on the United States

In our opinion, it’s a matter of time before the US government takes action on data collection. With Facebook data privacy being a “hot button” issue currently, antitrust questioning, data collection, and consumer privacy are on the radar of the US government and citizens who watched the Congressional hearings. You would think that the US government is closely watching and measuring the impact of the GDPR to see if it’s worth considering within the US.

Resources:

https://www.pandadoc.com/gdpr

https://www.observepoint.com/wp-content/uploads/2018/04/GDPR-ASAP-a-7-step-guide-to-prepare-for-the-general-data-protection-regulation.pdf

https://blog.pipedrive.com/2018/03/gdpr-compliance/

https://www.informationweek.com/strategic-cio/security-and-risk-strategy/7-steps-to-gdpr-for-us-companies/a/d-id/1329235?

Tips to Move Towards Big Data & Enterprise Solutions Part 2

September 19, 2012 by Daniel Laws Leave a Comment

Last week, I released my Tips to Move Toward Big Data & Enterprise Solutions that focused on your organization internally. This week’s 5 Tips to Move Towards Big Data & Enterprise Solutions are focuses on projects and customer outcomes from the data.

1. Think Data Quality & Security

In this day and age, it’s critical that you think of data quality and security for the long-term. What’s the point of having data if it’s not worth a damn? Work to implement data quality testing and regular data quality checks to ensure that you’re collecting as well as filtering to the necessary databases or solutions.

With all of the privacy issues and customer concerns, you’ll need to create data security policies and procedures. I would advise that you openly display your data collection polices on your website as well. The IAB is a great resource to help you self-regulate online behavioral advertising and how you use data.

2. Start small with a project

Rome wasn’t built in a day and Cesar didn’t build it by himself, so start with small projects. This will help get departments to collaborate and build relationships. It will also help to identify issues that would adversely impact larger projects so that you can develop a plan to solve the issues. Small projects will be the building blocks of long-term solutions for big data and enterprise solutions.

In my experience, if you can show proof of a successful small project, it will help the decision-maker to see the value and provide justification for universal data as well as the implementation of enterprise solutions. Tie the small project to brand or high-level strategic goals and objectives, and it will improve your level of internal support.

3. Focus on High Value & Good Customers

The small projects should focus on high value customers. It’s recommended that you look to answer questions about high value customers, such as who they are, how they interact with your brands, what marketing tactics are critical to conversions, etc. Again, align this information back to your organization’s goals & objectives to gain internal support.

4. Focus on Insights & Outcomes

The high value customers generally account for a large part of revenues, so focus on insight and outcomes that align with revenue generation. Think about what causes high value customers to complete an action or task. Sometime that data can help you develop hypotheses that can later be validated with surveys or focus groups. It’s recommended that you connect the quantitative and qualitative data but it needs to be simplified so everyone internally can understand the value of the data.

5. Don’t Measure Everything, Measure what Matters to the Project/Customers!

I’d heard many people say, “Measure everything,” and I understand the thorough process behind it. If you’re looking to move toward big data & enterprise solutions, I would recommend only measuring what matters for your specific project. How do you ensure that you’re capturing the data that matters? It starts with a measurement plan that aligns goals, objectives and KPIs for your project.

Conclusions

This list of tip should help to get your organization on the path toward “Big Data and Enterprise Solutions” but it’s not the end all, be all document. It should get your thinking about internal, external, and the politics that comes with navigation across business unit to develop value for marketing and your customers. Let us know what type of progress your organization is making and send us your recommendations to expand the list.

Tips to Move Toward Big Data & Enterprise Solutions Part 1

September 12, 2012 by Daniel Laws 1 Comment

With all of the talk about “Big Data”, I thought it was about time that I provide you with a few recommendations to get your organization moving to leveraging large amounts of data. The beauty of having big data is that you can be statistically confident when testing. Small businesses don’t always have the luxury of this when looking to get a large sample size.

After years of working for organizations such as Liberty Mutual, Sovereign Bank, Idearc Media, and numerous clients (Comcast, Merck, Helzberg Diamonds to name a few), I want to share what I’ve learned about Big Data. Below are my top 10 tips for big data or developing enterprise solutions that can make a difference:

1. Leadership & Way of Life

You’ll need leadership that’s focused on the facts, invested in people/technology, and constantly pushing for better customer value. At this time, leadership will need to put up or shut up every step of the way. Prove it to your customers and employees with actions based on big data that’s part of the organizational goals & objectives!

2. Integrate and Simplify Solution Platforms

Simplify and integrate solutions for optimum efficiency as well as consistency of terminology. Use solutions that are designed and configured to work together; otherwise you’ll spend time and money trying to connect the dots instead of analyzing the information. This shouldn’t be limited to digital information, but should include CRM, calls, web analytics, testing, advertising, etc.

3. Invest in Time & People

Spend the time to do the research on big data solutions, recommendations from the field, retailers, etc. Big Data is still young, so this will be a continuous process and the technology will evolve. You’ll need to educate people to evolve with the technology and methodology in order to analyze different types of data sources and integrate new technology. A statistician and developer will most likely be your number 1 priorities. The statistician is the numbers guru that will make sense of things, and the developer will help connect the information to solutions with APIs.

4. Consistency of Language & Terminology (classification) across the company

Everyone across the organization must use the same language regardless of their geographic location, and the definitions must be documented. You should think beyond metrics and include meta usage as well as tagging. If not, you’ll run into issues integrating the data and people understanding what reports or dashboards are showing.

5. Leverage Statistics

Leverage your statistician’s experience and expertise with testing that drives business success. In college, most of the business programs required statistics, and it’s time that you start using it!

Here are a few ideas that I would recommend:

Correlations can show you whether and how strongly pairs of variables are related.
Probability can be used to measure and predict when an expected event is likely to occur in the future (conversion).
ANOVA tests can be used to determine impact the changing a single or two factors has on a measured outcome (a headline has on the CTR).
Regressions analysis can be used when the focus is on the relationship between a dependent variable and one or more independent variables (marketing surveys)

Part 2 of the Top 10 Tips to Move Toward Big Data & Enterprise Solution will be available next Wednesday, September 19. For the most part, this first half focused on your organization internally. The next 5 tips will focus more on demonstrating the value. Stay tuned for the next part!