As we move closer to the end of third-party cookies, many marketers are looking for answers on how we can continue to deliver smart, segmented creative and behavior-based messaging.
Many experts recommend that organizations look inward, focusing on cleansing existing customer data and leveraging tactics that fill the pipeline with new first-party data.
In tandem with this shift, changes also pushed many businesses into a new, digital-first world that includes more touch points, new technologies and users who are demanding an omnichannel experience.
For teams ready to jump head-first into creating a comprehensive, 360-degree view of their customers — with the goal of enhancing and automating experiences — understanding where to start could be overwhelming.
This can be especially true for businesses with complex processes and legacy systems that do not play well with others. So where can you start?
Make a CRM system your single source of truth
For most organizations, an enterprise customer relationship management (CRM) system is going to be the best solution for creating that single, comprehensive view of your customers. The goal is to create a golden record that teams throughout the organization can access, providing everyone with the same information to engage with and build upon in real time.
And as teams and data get in sync, this single source of customer information should diminish the risk of data discrepancies or corruption. It also should increase your ability to create lasting relationships with customers through this omnichannel view.
It is important to note that departments across your organization should receive training on proper data hygiene and expectations to keep records updated.
Inputs might not always funnel directly into your CRM system. For example, customer service representatives should work to validate information during customer interactions, manually updating details like phone number or email in real time. Every touch point should be seen as a time to collect and/or validate data — from phone calls and email exchanges to new purchases.
Sync up departments
Once the organization aligns on using your CRM as the single source of truth, the next step is gaining alignment from cross-functional teams in partnership with data scientists. Whether you are just getting started with a CRM or have a mature system, agreeing on system goals, integration needs, field naming, record inputs/outputs, data usage and processes around entry and maintenance should all be a part of your road map.
As these discussions progress, consider the needs of each department and recognize the value of data points that range from demographic to transactional to personal interactions.
The ideal system will give everyone who engages with customers — including marketing, sales, customer service and others like finance, human resources and accounting — the same profile and interaction history to work from.
By moving to a unified CRM that doesn’t prioritize the needs of one team over another or silo customer data, you’ll also be able to better support the integration of new data points and systems as they arise.
Data unification and identity resolution
Data silos and inconsistencies often exist because departments were using specific tools to service their unique needs. These systems often are not designed to integrate with one another and might not even use the same language.
Breaking down these silos and stitching records together might be a manual process, but brands can explore identity resolution providers to make this step easier.
Identity resolution software uses probability and scoring algorithms to attempt to solve these discrepancies and stitch together a unified record in a more efficient way. This can be worth the investment if you’re working with many data sources and/or large quantities of records.
Segmentation, automation and beyond
Your CRM system is just a tool, not necessarily your end vision. Now that you have department and data alignment, the real value will come from how you activate strategies like lead scoring, personalization, automation and even machine learning.