Leading CRM platforms like Salesforce, Dynamics, Zoho and HubSpot are introducing new AI features for autonomous chats, automatic campaign launches, product suggestions and sentiment analysis. That’s great and exciting. But there’s one thing in the way: our data.
Ultimately, all the technology in the world isn’t worth the investment if the data it relies on is poor. The reality is that my clients’ databases aren’t great. They’ll admit that.
The systems they use to manage customers, fill their pipelines and generate new revenues are often outdated, incorrect and missing information. They see the potential of AI to automate processes and enhance productivity but are cautious about using it with unreliable data. Can you blame them?
Maybe your systems are in a similar spot. You’re not alone. The good news is you’ve got a little time. AI is still nascent. Tech firms will roll out more reliable and tested capabilities over the next year. In the meantime, it’s a good idea to use this period to do what’s needed to clean up your databases so you’re ready to leverage these new tools. Here’s how to do it.
Assign an administrator
For starters, assign an administrator to your database. It doesn’t have to be a tech person or a database expert. It does have to be a power user of your system or someone supporting the group utilizing the software. This person is the go-to person for any data entering or exiting the database.
Like an accountant preparing financial statements, they are responsible for the completeness and accuracy of the data in your system. It’s not their fault if anything’s wrong, but they are responsible for fixing data errors and implementing controls so these problems don’t happen again.
The administrator should be trained by the software vendor and receive whatever support they need from your management team.
Dig deeper: The data disconnect: Why understanding your data landscape matters more than ever
Make priorities
Next, look at your data and determine what’s essential. Too many of my clients want to accumulate too much data about too many of their prospects and customers.
Keep it simple. Focus on the fields necessary to sell and service them. There’s a difference between nice-to-have and need-to-have, and the first step here is determining what’s need-to-have data and getting that right.
Lock up your system
Once that’s done, nail down which fields and screens are essential. Re-configure your database to make them required for data entry, and don’t allow any user to move on without populating those fields.
Create lookup lists for each field with specific choices so users aren’t tempted to enter nonsensical data. You should have related fields so that, depending on what’s entered in one field, another field’s lookups only show what’s related (i.e., you choose “car” in one field and a related field’s lookup list now only shows car manufacturers like Ford or Toyota).
If it’s important to have the most current data in a field, then set an alert for that field (most mainstream CRM and other systems can do this) so you’re getting a regular report of which fields haven’t been updated in a set time. Act on that.
Dig deeper: Why clean data is key to organizational success
Enrich your data
Consider signing on with a database service that allows you to “enrich” a contact’s data from public information automatically with a simple click. Many mainstream CRM systems provide this functionality. Other services you can investigate include Versium, Apollo.io and People Data.
Break it down and delegate
After all that is done, get your people involved. The best approach to any big problem is to break it down into smaller problems. This is the same with your information.
Break down your data into segments (territory, region, salesperson, industry, etc.) and assign responsibility to sales and customer service reps to review each of these records and update by a certain time. Make sure they remove all duplicate data.
Dig deeper: How clean, organized and actionable is your data?
Any good sales and marketing professional will tell you their jobs depend on great data. It’s the core of a successful business because it contributes so much to the company’s value.
Creating and maintaining a reliable database takes time, resources and an ongoing investment. But without that data, any automation you hope to accomplish by using all the AI tools your software vendors are rolling out will be muted. Take your data seriously and it’ll pay back awesome returns.
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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
