The world of sales is not one-size-fits-all. Each expert has their own tools and practices that allow them to succeed and thrive in even the most competitive environment. We interviewed a variety of experts to get insights on what has made them successful.

In this interview, we sat down with Joe Brucker who recently co-founded a non-profit organization called Police Accountability Lab with MIT — a group working to reduce global police misconduct issues with data-driven policy analysis.

Joe Brucker previously led the data science practice at Oracle within NetSuite. He helped build the sales operations practice from the ground up from an analytical perspective. During his time at Oracle, he was also highlighted as 1 of 3 top operational leaders as part of the "Leadership Circle" and increased sales prospecting by 49%.

Listen or read our conversation with Joe below:




What are your current favorite books, podcasts, blogs for keeping up the sales ops industry news?


I think there's actually, unfortunately, kind of a vacuum in this space, so it's great that you guys are doing this. Sales has a ton of documentation out there, a ton of blogs who are talking about it, but sales ops is a huge industry and huge constituency that doesn't have a lot of information. The information that I have seen is from Harvard Business Review, but it's great that you guys are kind of hitting this nail on the head.


When you were at Oracle, what was one piece of tech that your team couldn’t live without and how did you use it on a daily basis?


We were really hyper-dependent on living within our CRM. NetSuite has its own CRM, so we'd use that. We would also really aggressively use DNB* and other kinds of abstractions of that, to really know who our customers are, where they are in our sales cycles, and how often we are talking to them. Unfortunately, a lot of these solutions kind of fell short in terms of being able to provide deeper insights into what kind of companies they were and how well we were penetrating them.

We had a sales enablement and sales productivity practice whose task was to go out and find new emerging technologies that helped improve our sales team's performance, our penetration and our management's visibility into how well we were selling and how well we were keeping up with the sales that we were in.

While I was there, we worked on a handful of technologies. LinkedIn Sales Nav is a huge staple for a lot of sales organizations. We used DNB and specifically DNB data to provide information to our sales organization. Although there were some points where maybe that wasn't up to date, so we had to try to fill those things out ourselves. We also used tools like HG Focus, HG Data, but basically all tools around the theme of trying to find more information about those specific customers. So to kind of reprise, LinkedIn Sales Nav, NetSuite CRM, DNB and HG Focus, HG Data.


As far as your day to day, you talked about the tech that your team uses, but what did you do day to day?


What was really exciting about the work that I was doing was I got to work with a variety of folks, where I was working with the marketing organization, sales leadership, operations in our back office and our planning organization. So on a day-to-day basis, it's kind of trying to balance those counterparties and seeing what their demands are, what their needs are. Because sales operations is the engine that really drives sales, which is what obviously moves the company.

So it could be meetings with marketing to understand their initiatives and put that into the sales channel, understanding sales leadership and processing their feedback, working with the planning organization, looking at analysis and forecasts to see what we could do to optimize behaviors and making sure that all those people are happy.


How specifically did you work with marketing and do you think they provided high quality leads?


We worked with the marketing team as close as we possibly could, because we understood their value in having a team that's centrally focused on building our story and our narrative in our sales processes and getting more leads that fit that. What's interesting about marketing as an organization is there's all these different tools and technologies available to them and all of these different sources of data that are available to them, in terms of intent, geolocation, hiring. All of these pieces of information that really drive the quality of a different company, in terms of how it fit NetSuite as a company, as our ideal customer profile.

But it wasn't hyper-centralized, we didn't have everything that we needed in every step of the process, so it wasn't as unified as well as it could have been. There were some contentious conversations, frankly, between marketing and sales in some ways, where marketing wants to deliver more and they feel that they're doing as much as they can, and sales is always going to be hungry and always going to be asking for more leads. I'm sure that's not a unique story.

What's great about sales operations, as a central focus within that, is you can kind of be an objective third party and try to bring the best of those things together. We did try to start programs that had marketing objectives and systemized those in a way that fulfilled lead generation needs.


What are your thoughts on CRM and data integrity? Specifically, if you use integrations, whether you think that they help or hurt? What is the best way to keep the data clean between different systems?


This is a contentious issue, since we actually sold the CRM. But to speak frankly, CRMs are built to essentially present information, but they're not always so great at collecting data from a large variety of sources or managing data that's up-to-date. The data that's in CRM is a huge, huge problem. The data's either not up-to-date, it's not assigned to the right person, it's incorrect or it's simply just not there.

So when you add all of those problems together, I think the last estimation that we had at NetSuite that I think someone quoted was that maybe 10% of the data that we were working with was up-to-date and functional. We have a great sales team who worked really, really hard within those measures, but it's also you have these competing pressures, where if you have a really high performing sales person, you don't want to ask them to spend more time doing data entry. So what are you left with, a CRM without your best sales people's data.

And it compounds over time because you have to deal with duplicate customer records, you have to deal with more subjective opinions as your company changes. What are the verticals you're selling into? How are you defining the market that you're pursuing? These issues compound over time and make for a really messy CRM.

One thing that we employed that I think was really effective was the practice of essentially gamification. So we would run these sales contests, which were hyper-effective in terms of drumming up volume and they were great for morale. But as one of the requisites for our phone call to count all of the information associated with that phone call had to be populated. That way we weren't being punitive and getting in the way of people's jobs, because at the end of the day, it's a voluntary sales contest. But we did see that our accuracy jumped really significantly after we employed those practices.

As a result of this, we saw stats as far as essentially an 80% improvement over a month in terms of our prospecting volume. So yeah, sales folks, super competitive, and when you turn that on, you definitely see the results.


Speaking of reporting and CRM, how did you create accurate forecasts for your team?


Sales operations is certainly in charge of sales forecasting. Sales forecasting is also kind of a joint effort, where we had our salespeople forecast their numbers and then through various tiers of management who maybe had a more discriminating eye, maybe say, "We're not sure about this deal, we think that this deal's going to close later." Then we ended up getting that to a round number at the end of it. Sales ops' job was to kind of maintain that, keep people honest and then roll that up to our final forecast, up through senior management.

Forecast accuracy is always going to be a point of contention, point of conversation within sales operations and within sales, where essentially senior managers, a big part of what they're judged on is their forecast accuracy. Which is fair, because it shows they know their sales.

But to say that the accuracy was always there, would definitely be an overestimation. It's a really hard game to play, it's much more of an art than a science for a lot of folks. When we tried to turn it into science, it was really difficult for us, because trying to make predictions algorithmically using machine learning off of bad CRM data was basically impossible.


How did you set up your comp structure to help encourage better data behavior and how did this align generally with your overall sales goals and strategies?


Comp structure is something that sales management should absolutely take advantage of, in terms of driving strategic goals. Our comp structure was set up, I think probably the way that most SAAS companies are, where we had our reps with a salary, but also compensation in line with how much they brought in terms of the deal that they brought in from the customer.

But we also had compensation ideas around bonuses oriented around strategic products that we were trying to orient around, strategic market positioning, strategic marketing initiatives. So attending certain events, etc. Then we could also tie that in with gamification again and use that as an additional compensation method and use that too inside of CRM. So if you're not tracking things the right way, it's hard for us to compensate for it. That's a great way to convince sales reps to enter their things correctly.


Do you ever award spiffs for the one-off little promotions you were doing?


So that actually somewhat varied. It varied by team, where teams that maybe had more senior workforce, they would respond better to more direct terms of compensation, like gift cards or a bonus cash check or a free dinner. Whereas our more millennial workforce really, really responded well to experience kinds of prizes.

So we had a sales contest where we sent our best performers to The World Series, and that was a huge, huge boon. If you just look at the cost of sending somebody to kind of an experience-oriented event versus the cash that you would bring in from such a drive in sales, then it ends up really being worth it. But people really responded to the experiences.



I see sales ops and enablement becoming increasingly kind of an intelligence engine. The more rote tasks that are associated with sales ops, processing commissions or transactions, those things are probably going to slowly get increasingly automated. So sales ops and enablement are going to be increasingly in a position of doing market intelligence, doing business intelligence and trying to turn it into more of an advisory role to their counterparties within sales and marketing.


Top Takeaways


  • Due to sales operations central focus within the company, it can act as a great, objective third party between sales and marketing. During his time at Oracle, Joe helped create specific marketing objectives and systemized those in a way that fulfilled lead generation needs.

  • Improve your CRM data quality with gamification. Oracle would run sales contests with cash or event based prices, which were hyper-effective in terms of drumming up prospecting volume. One of the requisites for the phone call to count was that all of the information associated with that phone call had to be populated in CRM.

  • Sales ops and enablement are becoming increasingly an intelligence engine. The more rote tasks that are associated with sales ops, processing commissions or transactions, those things are probably going to slowly get increasingly automated.

Appendix


DNB* - Dun & Bradsreet