where to start onboarding a new CRM system

One of the most frequent initial recommendations we’ve made to clients over the years is to invest in a proper Customer Relationship Management (CRM) system.

Maybe not the sexiest of recommendations, but building sales and marketing success is near impossible without it, and a surprising number of businesses are still logging leads in some archaic combination of Excel spreadsheets, Outlook, notebooks and drawers filled with business cards and other assorted items that will never see the light of day.

Previously on this blog, we’ve discussed why you need a CRM system and offered tips for how you can use CRM software to maintain sales intake best practices. Today, we’ll be looking specifically at where you should start once you’ve onboarded with a new CRM system.

Clean up Your List

Before you upload your company’s entire contact database that dates back to 2003, take a moment to consider whether this is a good idea — and then decide that this is NOT a good idea.

Unless your team has been methodically maintaining and pruning your contacts over the years, there’s some work to do before you upload.

Purge the Oldies and Not-So-Goodies

For starters, you need to figure out who stays and who goes. Here are the main factors you’ll want to consider:

  • How long ago was the contact created?
  • Where did it come from?
  • When was the last time the contact engaged with anyone at your company?
  • Has an email sent their way ever resulted in an unsubscribe or a hard bounce?

If a contact is so old that you don’t know where they came from and no one on your team remembers communicating with them, get rid of them. Same thing goes for those that have resulted in hard bounces or unsubscribes.

Organize and Cleanse Your Contacts

With the outdated contacts removed, it’s time to organize and clean up your remaining data.

You might be tempted to cut corners here or skip this step all together because who wants to clean up data? Depending on how big your list is, this can be very time-consuming, mind-numbing work, but research shows it’s time well spent.

According to estimates from IBM, bad data cost U.S. businesses $3.1 trillion in 2016 alone.

So, what does cleaning up your data entail? To begin with, you want to create consistency among:

  • Contact name formatting and case issues (Charlie vs charlie)
  • Phone number format (555-555-5555 vs (555) 555-5555)
  • Email address format (cnadler@simplemachines.com vs cnadler at simplemachines)
  • Job title format (COO vs Chief Operating Officer)
  • Industry format (nonprofit vs NPO)

Once those issues are addressed, you can move on to the really fun stuff, like:

  • Removing unwanted characters from old uploads (Ã, ¢, â, ê)
  • Fixing extra/missing white space issues
  • Associating contacts with companies
  • Removing duplicates
  • Fixing mailing address formatting issues (partial zip codes, missing street addresses etc.)

Verify Your Email Addresses

Next, make sure the remaining email addresses are still active. People change employers, employees get married and change names, companies rebrand and get acquired and humans occasionally enter email addresses incorrectly.

All of these things result in the same thing: dead emails that take up space in your CRM and result in bloated, misleading data and poor email deliverability.

To find and purge these before importing to your CRM, consider using an email verification service to save you some time, especially if you’re dealing with a big list — the cost will be worth it.

“Do I Need a Data Scientist to Do This Stuff?”

For this type of work, no. Data scientists more often work with larger and enterprise companies because they need a minimum of tens of thousands — if not hundreds of thousands or millions — of data points to build useful, statistically sound models. Startups and small businesses rarely have this kind of data.

They’re also not cheap.

According to Glassdoor, the average base pay for a data scientist in the United States as of April 30, 2019 is $117,345 per year. This is in part because the work they do usually encompasses more advanced data segmentation and modeling than what’s included above.

Bottom line: using a data scientist for basic cleanup before a CRM import is not a financially wise investment. A better option is to find an intern who’s good with spreadsheets.

Set up Your Customer Lifecycle Stages

Set up customer lifecycle stages

Once you’ve cleaned up your contacts and imported them into your new CRM, one of the most beneficial things you can do is to set up your customer lifecycle stages.

The customer lifecycle refers to the various stages a customer goes through in your marketing and sales process. The terminology and definition of these stages can vary by company and CRM platforms used, but for a frame of reference, below are HubSpot’s default lifecycle stages, which tend to be relevant for most clients we work with:

  • Subscriber: Contacts who know of your business and have opted in to hear more from your team. This are likely visitors that have signed up for your blog or newsletter.
  • Lead: Contacts who have shown sales readiness beyond being a subscriber. An example of a lead is a contact who signs up for a content offer from your business.
  • Marketing Qualified Lead: Contacts who have engaged with the team’s marketing efforts but are still not ready to receive a sales call. An example of an MQL is a contact who responds to a specific form in a marketing campaign.
  • Sales Qualified Lead: Contacts who have indicated through their actions that they are ready for a direct sales follow up. An example of a SQL is a contact who submits a question about your product through a contact form.
  • Opportunity: Contacts who are real sales opportunities.
  • Customer: Contacts with closed deals.
  • Evangelist: Customers who advocate for your business and whose networks may be leveraged for further leads.
  • Other: A wildcard stage that can be used when a contact does not fit any of the above stages.

Why is going through this beneficial? By categorizing contacts in your CRM based on their lifecycle stage, you create a framework to understand how leads are becoming customers, where they can be handed off from marketing to sales and where they might be falling off or failing to convert.

Think of it this way: if you only know that 30% of all leads become customers, that’s a pretty general insight to work from if you’re trying to improve your conversion rate.

Are the leads unqualified, which would indicate you may need to revisit your marketing message and/or targeting? Are you getting qualified leads who need more nurturing before they’re ready to buy? Is the sales team letting hot leads slip through the cracks?

Without lifecycle stages, it’s a guessing game. With them in place, you can take a more surgical approach to improving your conversion rate because you know where to troubleshoot.

Taking the First Steps

Once you’ve onboarded your new CRM system, your options are nearly endless in terms of additional segmentation, reporting and analysis you can do with your contacts.

In our experience, it’s best to walk before you run. By taking the first steps and starting with clean contacts and defined lifecycle stages, you’re setting yourself up to successfully leverage your software.

Feeling overwhelmed? There are plenty of agencies and consultants out there ready to help you onboard. At Simple Machines, we’ve helped a number of clients with various CRMs — and as a HubSpot agency partner with HubSpot certified trainers on staff, we’re especially equipped to help if this is your platform of choice.

Learn more about our CRM training and workshops here.