When a foundation of quality data underpins your business initiatives it has the potential to positively transform your organization. However, a lack of trustworthy data can prevent your organization from maximizing the value of this asset. That’s why it’s essential to ensure that you have strong operational data quality at the foundation of your business. With the right processes and technology in place, you can achieve a trusted data source. If you are struggling to achieve the high-quality data you need, don’t fret! Here are our top 3 tips for maintaining data quality:
Last week, I had the privilege of attending the 2018 MIT CDOIQ Symposium in Cambridge, Mass. The event brings together data practitioners and business leaders from a variety of sector to advance the professional development of Chief Data Officers. Throughout the three days of workshops and classroom-style lectures, attendees were treated to a rich agenda with topics ranging from regulation to artificial intelligence. While I wish I could have attended all of the sessions, I wanted to share some common themes from the workshops I did attend.
This week, I attended the 2018 Tessitura Learning and Community Conference (TLCC) in Orlando, FL. For the first time, a Disney property was selected for this conference and at first, I was surprised by the size of this location. However, once I arrived I realized that while the venue seemed larger than ever before, the 1900 attendees filled it up quite well. So when the conference shared that this was the largest attendance of any previous Tessitura conference, it wasn’t hard to believe. This community is growing and is strong, and throughout the conference, I saw many positive trends.
Last week, myself and members of the Experian team attended the MDM and Data Governance Summit in Chicago. The main topics of this conference were MDM (Master Data Management) and DG (Data Governance), although at many times, it was difficult to tell the difference. MDM and DG are starting to meld together as one topic, with MDM being the data repository for all (or as much as possible) corporate data, and DG being the documentation and “GPS” for navigating the data (in this case, GPS means “Gain Perspective Simply”.
After running email campaigns, performance metrics start flowing in. There is a gratifying feeling in seeing open rates and click-through engagement. But there are other metrics that indicate the success, or even lack of success, of your email campaigns; yes, I am talking about bounce rates. High bounce rates are the bane of any email marketer’s existence, but they are very common.
So, how you can reduce bounce backs and see better ROI from your email marketing campaigns? The answer may be simpler than you think.
Pride is celebrated across the United States, and across the world, for the entire month of June. Here at Experian, we celebrate diversity and inclusion 365 days a year. Our promise to diversity and inclusion resonates beyond just a mission statement—it’s something we as an organization live out every day. Grace Jakubowski, an Account Manager at Experian, said: “Diversity and inclusion in the workplace is about creating an environment where a person can bring their whole self to work—Experian does that.” This June, we joined in on the celebrations, showing our pride at every one of our offices throughout the United States. All of our offices had different activities, gatherings, and networking opportunities to celebrate the month of Pride for members and supporters of the LGBTQ community.
Have you ever launched an email campaign only to find out that most of your emails never even made it to the intended target due to soft or hard bounces? Have you ever spent a large amount of your budget on syndicated content and then come to find out that your target audience is from a database that was collected from tradeshows and POS systems where a consumer’s email is captured with no verification? How can you determine if those email addresses were correctly captured? Whether the information was wrong at point of capture, or became outdated, these issues ultimately contribute to your company’s email reputation.
As mobile devices continue their rise to prominence, organizations in every industry are clamoring to find ways to optimize the mobile experience for their customers. At this point, a positive mobile experience has become virtually synonymous with a positive customer experience. Simply designing an app or making your website mobile responsive is a great place to start, but how do you continue to optimize the experience from there? A good mobile experience is all about making it as simple and frictionless as possible. And that’s where data quality can truly help.
Data is now at the heart of the digital transformations occurring across the economy and building an advanced data analytics team is one of the keys to competitive advantage. Whether you plan to simply disrupt your own industry or expand into an adjacent segment, data is the key to unlocking opportunity. Data has become a critical corporate asset, and business leaders want to capitalize on the information they hold. But its value is tied to how it’s analysed and by whom. One dataset may be of little value, while another may contain the key to launching a new product line or cracking a challenging marketing question. One might affect only a small percentage of a company’s revenue, while another could reveal an opportunity for significant future growth. How do firms find out? Analytics.
So you convinced your business leadership that investing in a data governance program is in the best interest of the company. Now what? While embarking on a data governance program is an exciting time for any enterprise data management team, it can also be a big undertaking. With little example to follow, those beginning a data governance program, and even those who have implemented one recently, would be wise to follow industry best practices and learn from some of the cautionary tales out there. Knowing what works, and what doesn’t will help you get your program stood up faster and with greater efficiency. Here are the data governance best practices that we saw throughout the 2018 Data Governance and Information Quality (DGIQ) conference: