New research suggests that Marketing organizations need to do a better job at breaking down the internal “silos” that separate functions and data. One of the reasons why this issue has emerged is that people like to keep a tight control their slice of the data “pie.” I thought it might be helpful to share some suggestions on what can be done to overcome this challenge to help unlock greater efficiency and performance with how Marketing teams operate – a win-win for all!
Data silos can be found in many places. Within a digital campaign, it might include contact information, such as name, title, employer, email address, and phone number. Event sponsorships might include a list of attendees; website visitors represent another source of contact information.
Over time, it can be difficult to keep track of all this information while ensuring the data is accessible and current. Further, with the changing data privacy laws and the fact that these records include Personally Identifiable Information (PII), it is now increasingly critical to know exactly where all this data resides.
The Evolving Requirements of Data Privacy
Those who practice marketing in Europe are already well aware of the General Data Protection Regulation (GDPR) law. The purpose of this regulation is to give individuals better control over how their personal data is captured, stored and used.
The United States is now following suit. As one example, the California Consumer Privacy Act (CCPA) will have a similar purpose and is set to go in place on January 1, 2020.
A key provision of each act is that consumers can contact any company and demand that their PII be removed from all records and systems. Those not in compliance will face severe penalties and the potential for brand degradation. This could be an onerous task if customer information is scattered across your organization.
The transformation of the data privacy environment is now forcing every company to rethink its data collection and storage strategy. Large organizations likely have a distinct advantage over smaller ones, at least those that have already implemented a comprehensive CRM / marketing automation solution. This approach provides a centralized customer and prospect data file, which lets you better adhere to these elevated regulatory burdens.
Quality vs. Quantity
Unlike a fine wine that gets better over time, the value of data typically follows in the opposite direction. The more time that passes by, the more out-of-date it becomes.
To put some perspective on this, think about how many times your job responsibilities change, you move, or you start working for a new company. Even a new boss could alter your future buying habits. Every time something changes, the value to a marketer of this information declines.
Actively nurturing and maintaining a current, high-quality database takes time and effort. Even if you had an army of people just responsible for doing updates, the data would continue to trend out of date.
A Common Data Model
The perfect scenario is one that aggregates all disparate data sources into a single repository – one that is mutually owned by all parties interacting with your company’s customers and prospects. Then, with a shared interest in managing and maintaining this highly valuable asset, the likelihood it stays accurate increases substantially.
Here is an opportunity where sales could work closely with marketing to improve each other’s productivity. Every marketing campaign could include a feedback loop as part of the process. As obsolete contact data is discovered, it could immediately be replaced with updated information that is made available to the sales team. Think of this as a continuous process improvement methodology – but applied to data.
Similarly, every time the sales team finds out something new about an employee working for an existing customer or prospect firm, they could update this information in a shared, common data repository. This process improvement would improve the value of this critical asset.
The scope of implementation for this data strategy extends well beyond marketing or sales. Those involved in providing customer support could incorporate into their routine a question to confirm if all contact information is accurate. This could be asked at the start of every service engagement. The same could be done when customers call about bill questions or other issues.
Overcoming the Challenge of Web Inquiries
In each of the above examples, a human was involved – a key component to ensuring this data accuracy strategy works. With web inquiries, however, we face a different challenge. Web inquiries are best run as an automated process. Inaccurate data could be input when prospects or customers want to download a brochure or research paper. We certainly wouldn’t want to add new “bad” data into the system.
A new strategy is needed to overcome this data accuracy challenge.
One option that could work is if a login process was required before gaining access to any website-based materials. As part of the login process, users would be prompted to identify themselves as belonging to a customer account, or getting set up as a new account. This could occur by choosing their company name from a drop-down list. Requiring the use of a company email address is another option – those that don’t provide an accurate email address don’t gain access to the content (the download link is then emailed to the address shared).
I realize none of these options are perfect. But, any additional information that could be collected and matched to other customer account activity would be a welcome addition to your database and provide new insights that might help future customer behavior. This information could then be shared back with the sales team as a follow-up action.
By sharing the stewardship of a single customer and prospect database, every employee has a vested interest and a common focus in keeping it current. The resulting benefits can then enjoyed by all, ultimately resulting in an organization that operates with greater efficiency, delivers a superior customer experience, and enables companies to better adhere to data privacy regulations.
Maybe there is enough of the data pie to share and go around – even while being consumed by all!