In my last post I introduced The Silo Connect Framework – a process to drive business success intentionally. At the base of the Framework is its most crucial element: good, clean customer data. A single source of truth that’s available to every part of the business in real time. If all departments within an organization can operate from this one point of clarity, connecting the silos becomes much easier.
While getting to this state of data nirvana is the true core of the Framework, there are other important reasons your company must look to create management approaches for your customer data. You should highly consider developing strategic policies around:
- Committing to Clean Data
- Entity Resolution
- Data Compliance
Committing to Clean Data
Data comes at us from everywhere. Adding to the never-ending data stream that comes through inbound sources, social media, marketing events, etc. is the user-generated data that employees enter into CRM systems. Did they bother to search to see if the customer already had an account, or did they just create (another!) duplicate record for that same customer?
Getting to clean data is the first step in establishing a single source of truth – the scrubbed, up-to-date version of each record within your CRM, marketing systems, etc. This initiative must be a company-wide commitment at the highest levels in the organization. The responsibility to properly handle customer data, wherever it’s used, is everyone’s responsibility – not just the IT Department.
Get your data clean and keep it that way! Build CRM hygiene standards that can be measured and enforced. Create management-level dashboards to quickly show your strengths and weakness, which can be measured down to the individual contributor level. Once these good habits are established, you can build on these principles to incorporate marketing and sales motions within your Lead-to-Cash process.
Start with Entity Resolution
Now that you’ve made the commitment to clean up your data, you might realize the challenging task you just signed up for. Don’t worry – help is readily available! The best place to begin is with an entity resolution solution that involves artificial intelligence and machine learning.
Have you ever tried to manually de-duplicate records in a spreadsheet? I have, and it’s an excruciating process. Combine that process with trying to understand if/how each record could be related, and you’ll soon reach for a bottle of aspirin.
So – what is entity resolution? Let’s start by defining entity: a unique object (company, person, etc.) that is described by particular traits. For example, your customer (the entity) is usually depicted in your systems with the characteristics of name, address, phone number, etc. Furthermore, a contact (person) is described in your systems similarly, but with items such as email address, job title, etc.
Now imagine your company’s customer data set. You could easily see several customer records in your CRM look like this:
- ABC Corporation
- ABC Corp
- A B C
- A.B.C. Inc
- ABC, Inc.
Are those all the same? Can you tell just by looking at the company names (the entities)? Why not let a real-time, AI-based entity resolution system do the heavy lifting for you? I recently used Senzing to help me clean up my data. It was quick, easy, and involved no coding at all. If you’re looking to get started with a solution like this, Miller Operations can help.
Many companies have industry-specific compliance guidelines, such as HIPAA for healthcare providers. PCI compliance is also well understood for accepting credit card payments online. But what about giving your customer access to the data you’re storing on their behalf? Are customers able, on a self-service basis, to come to your website and access their data? They should be in control of what you can keep and what it’s used for.
If you haven’t quite come around on customer-controlled data privacy yet, I recommend reading this article – How to Earn Customer Trust With Permission Marketing. Lauren Pope explains the difference between express-permission marketing, implied-permission marketing, and non-permission-based marketing. Think of how you want your data treated on the websites you do business with, then look for the best ways to build trust with your customers and grow that relationship from there.
Building on Your Single Source of Truth
We all want to grow our businesses, build strong customer relationships, and show meaningful business outcomes to our stakeholders. Remember, all of these things should be done intentionally, not by accident. As we embark on our journey together through The Silo Connect Framework, keep in mind that none of our future intentional success is possible without first creating that single source of truth within our data sets. Only then can we achieve Intentional Demand Generation and Superior Pipeline Management.
What issues do you currently have regarding data? Have you achieved a single source of truth with your customer data yet? Feel free to share your experiences in the comments below.