RevOps Leaders

17 Tactical Tips from Data Ops Experts

The best thing about our Data Superheroes interviews is the opportunity to pick up tangible tips and tricks from the incredibly talented leaders within the Ops space. Now that we've grossed over 20 Data Superheroes interviews, we thought this would be a good time to reflect on some of our favorite tips from leading marketing, sales and revenue ops experts.

Do you know the difference between an amateur and an expert? 

One practices until they get it right. The other practices until they cannot get it wrong. Two very different approaches. Two very different data quality outcomes.

Which side you fall on can influence your entire data ops outlook. Whereas some people tend to focus on problems, or who caused them, it’s only the experts who focus on solutions. Really great operations people—like the dozens of Data Superheroes we’ve interviewed for our project—are very much the latter.

In this issue, we recap their best nitty-gritty tactical tips and best-loved analogies, like the infamous “data washing machine.” 

(See anything we’re missing? We’d love to hear about it on Twitter.)

1. Define before you fix

“When your data is a mess, start with a definition of one thing you want to fix. You might want to find all accounts that don’t have a website … identify all the places where accounts are created without websites and plug that hole. That way, you’re cleaning, but also improving processes in a lasting way.”

Grey Meyer, Data Quality Manager at Redis Labs

2. Publish a data dictionary

“A data dictionary is an invaluable asset for making sure people have a common understanding, even of simple things like pricing naming conventions or capitalization of records. It might seem basic, but they definitely can take on a life of their own if they’re not put in a common language.”

Toby Carrington, VP of Revenue Operations, Seismic

“Take the time to create a data dictionary, or to document your data flows. What does it look like? What are the data definitions? What’s that data governance model look like? How is the data going to flow through your systems and through your tech stack?”

Rosalyn Santa Elena, Head of Revenue Operations, Clari

3. Start with the customer journey and work back

“One of my favorite Steve Jobs quotes is, ‘You have to start with the customer experience and work back toward technology.’ So often, I see Revenue Operations professionals putting technology before people and process.”

Mollie Bodensteiner, Director of Revenue Operations, Granular

4. Stop and ask, “What am I putting a band-aid on now that’s going to scar?

“In RevOps, I find you have to continuously step back and re confirm what you’re trying to accomplish, otherwise you end up with short-term fixes that leave lasting damage. If you let something sit too long, it may become impossible to rip out.”

Mollie Bodensteiner, Director of Revenue Operations, Granular


5. Before you apply a fix, check with other departments

“One department decides they need to modernize and automate their client-oriented processes …. All well and good. Cut to another department—they also decide they need to modernize, so they too come up with a new approach for their needs. Pretty soon the company has 27 different approaches to client data.”

Thomas “The Data Doc” Redman, Consultant and Data Provocateur

6. For real success metrics, tie campaigns to actual finance data

“If you want to bring money into the equation, you’re either going to need a direct integration of SaaS applications with the financial system, or you have an analyst on the finance or marketing team download a spreadsheet with what we spent with Google last month, as an example, and tie that to a set of marketing metrics in yet another spreadsheet.”

Pete Perrone, CFO at AtScale

7. Small time-saving tools are force multipliers

“We recently implemented a calendaring and meeting booking software onto our website called Chili Piper. It reduces the time needed to book a meeting from 25 minutes down to just five. That’s efficiency. That’s time back in everyone’s day. Similarly, we just implemented a CPQ to shave 12-24 hours off our approvals process by being able to, among other things, substitute in pre-approved legal language. That’s days off the average cycle. Multiplied across the entire org, that’s significant.”

Michael Canty, Head of Global Revenue Operations, Tomorrow

8. Bring the data to sales meetings

“The biggest thing I can offer is insights. I bring the science to the art of sales, so to speak. There’s people here who’ve been selling for 20 years. My job is to come back to them and say, “Hey, I understand, but here’s what the data is telling me. If we look at the average stage tenancy of deals we win versus those we lose, and we match that up against our current pipeline, there’s inherent risk in a significant portion of it. We can’t ignore that.”

Michael Canty, Head of Global Revenue Operations, Tomorrow

9. MOPs should be in the room at the start of every campaign

“A MOPs (or Sales Ops / RevOps) person should be in the room from the beginning to thoroughly vet the initiative for operational, data management, and measurement processes. If marketing ops is not assisting in establishing performance targets alongside key executive stakeholders, there will inevitably be major gaps between planning and execution.”

Aubrey Morgan, Director of Demand Generation, Syncari

10. Set up scoring first—don’t put it off

“The best marketing operations professionals set processes up for scale from day one …. I’ll often see marketers who are solely focused on launching campaigns say, ‘How do I report on this?’ And I’ll be thinking, ‘Well, you didn’t set up any way to actually report on it. So you can’t.’ Then we have to finagle a way to work backward. That’s why I always advise clients to think about tracking and measuring success right from day one.”

Cristina Saunders, Co-Founder, CS2 Marketing

11. Insist on an organizational data strategy

“Build out an organizational data strategy instead of just a departmental data strategy. If everyone’s coming to the boardroom with different data sets, it causes huge problems for the business. Your team will waste time chasing down the right data, and you run the risk of leaders making bad decisions based on bad data. This is why you have to know where all your data points live and document their relationship to one another.”

Cristina Saunders, Co-Founder, CS2 Marketing

12. Set up a “data washing machine”

“Back when I worked as a consultant, we created what we called a “data washing machine,” which consisted of setting up three to five campaigns to normalize all lead data that entered a client’s system. Simple things like normalizing location data when a lead would fill out a form—for example, making sure “CA,” “Cali,” and “California” were all recognized as the same state, so marketers could effectively geo-target emails.”

Maneeza Aminy, CEO and Founder, Marvel Marketers

Bad data monster

13. Blacklist your competitors (aka a ‘sorry not sorry’ campaign)

“Blacklist competitors so they get removed from your lead lifecycle at the ‘front door’ of your marketing. It may sound basic, but you’d be surprised how often I’ve gotten emails from competitors trying to pitch their services.”

Maneeza Aminy, CEO and Founder, Marvel Marketers

14. Create “dopamine” success pop-ups for proper data entry

“If you can find ways to make [sales data entry] simple and enjoyable, you can vastly improve the quality of the contact data in your CRM. For example, we’ve just implemented a tool at Go Nimbly called Troops, which pushes activities from Salesforce to Slack in real-time. And it’s been super fun because if sales logs the right information in Salesforce when a deal closes, then we get a notification in Slack and everyone celebrates. Colorful emojis and gifs abound! If there’s a positive trigger for the human brain when processes are followed correctly, you can incentivize your team to do the right thing. That little hit of dopamine will reinforce their behavior, and these small moments add up to a major upgrade in the quality of your customer data.”

Lorena Morales, VP of Marketing, Go Nimbly

Lorena Morales Quote

15. If a small error arises, take the time to fix the root cause

“Bad data can often be more a symptom than a problem. Investigating the root cause of bad data—whether inefficient processes, internal misalignment on goals, or tech stack shortcomings—is often the key to eradicating it, and finding improvements in the process. Too often we fix the impact of problems without slowing down enough to really understand why they are happening.”

Amy Palmer, Head of Revenue, Autodesk

16. Increase form-fills with data appending

“Forms that are too long—when requesting information, keep the form really short and then look up the information you need on the backend. You don’t have to ask somebody what industry they work in. Just match them to the right account and look up what industry they’re in off their account.”

Jon Miller, CPO, Demandbase

17. HubSpot can’t see your SFDC campaigns? Add a hidden field

This one’s straight from the Syncari team: Add a hidden field to the form with the SFDC campaign ID. See more HubSpot tips.

As they say, amateurs practice until they get it right. Experts practice until they cannot get it wrong. Which are you, and how does that shape your data practice?


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