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At this year’s Dreamforce we participated in a roundtable session focused on how Sales Operations teams use data and data-dependent initiatives to impact the business and, of course, revenue. It was an excellent session, and one of the highlights of my personal Dreamforce experience. I had the chance to share what Box is doing to overcome obstacles, more strategically align and manage territories, and ultimately arm Sales with the leads and information they need to sell. Then we had a chance to discuss these topics and hear what challenges other Sales Ops pros are dealing with, and how they’re innovating.
To start, we cleared the air and discussed some of the core Sales Ops data challenges Box faced prior to 2015. These included: duplicate records, various inputs for company data, stagnant and out-of-date information, and a lack of clear data and ownership policy. I pointed out that a reliance on manually updating records and the lack of Data Governance contributed to these issues, which were manageable when we were a small start up, but prevented us from scaling effectively as we grew.
This was our most animated discussion, and many of Box's data issues seemed to resonate with members of the audience. Many others had issues with duplicate records that were then owned by different users. They also struggled with records owned by inactive users and a lack of clarity around duplicate prevention and removal. Some participants talked about the struggles of data acquisitions: how to handle absorbing new instances from acquired or merging companies or business units. A few people mentioned the problems with list uploads from different sources and problem of filling the gaps where data is missing. Another big issue, probably more for large and global companies, is the difficulty sourcing data for EMEA and APAC regions and then keeping it up-to-date. For those who target smaller companies, their main concern was getting reliable data on companies that are constantly changing, are private, and don’t necessarily want information like revenue to be known. We talked about some of the solutions available in the Salesforce ecosystem, including the native Data.com features, and many offered their experience and ideas of how to overcome the challenges.
After establishing a baseline of clean data, Box was able to plan and align territories much more effectively. While some data challenges remained, the major issues had been resolved allowing us to focus on streamlining policy across Sales and Sales Operations, and programming those agreed upon rules into a Territory object in Salesforce.
Here are some key takeaways from our territory planning efforts:
1. Solve "clean" problem first - We implemented the Data.com Clean tool, and also hired contractors to manual review and clean records more deeply. Start with Account data like size, address, and industry as a baseline. From there, create aggregate fields and rules. Perform analysis off of those fields.
2. Policy first, infrastructure to follow - Territories and Territory Assignment Rules in Salesforce came out of our policy and rules of engagement meetings with stakeholders. At the same time we worked to develop a plan for modeling data and disseminating information. Our Modeling object became our Territory object when we launched the new Fiscal Year.
Data issues were still top of mind for this round of discussions, which is appropriate since we established it is nearly impossible to effectively territory plan without the prerequisite of clean data. Many warned that mistrust of territories based on data issues can unhinge the planning process. One of the remaining data issues and territory questions/comments involved ZIP code issues. We came to the conclusion that, yes, you do need to put them all in the system. Others had experience issues with verticals/industries and struggled with the right mix of territory assignments given a vertical-focused, or in some cases mixed, sales strategy. We discussed how "territory" doesn't mean "geo," so there needs to be a hierarchy for assignment rules (i.e. first segment, then vertical, then geo).
Clean data and territories in Salesforce (instead of "conceptual" territories that live in spreadsheets or outside tools) allow you to build additional workflows and gain efficiency. For Box, we were able to transition conversion of inbound leads that had been qualified by our Sales Development team away from Sales Operations. Sales Ops used to have to clean leads and verify ownership using complex routing rules. But the combination of the Data.com Clean API for appending company information, and the programming of the routing rules into our territory object, allowed us to build a workflow that maintains data integrity and ensures correct routing with much less manual intervention.
Ultimately, Sales Ops has a responsibility to make sure leads are clean before they’re converted to sales opportunities. Because assignment happens at the time of conversion we needed the Data.com API to apply "Clean" functionality for account data to leads. We were also focused on preventing duplicate record creation, so we made sure the lead cleaning was followed up by workflows to check for existing accounts that the lead might be appended to. Then, referencing the territory object, all leads are assigned to an owner based on their information upon conversion. Complex routing rules were programmed so Sales Ops and Sales could trust the correctness of routing opportunities in new accounts.
While most people took this last opportunity to network and resolve to keep in touch, there were some discussions that went on until they kicked us out. One group talked about permissions and the idea of locking down access to record creation outside of a designated workflow. While there is some pain associated with this, most agreed it’s necessary to maintain good data. A great suggestion and good example of governance came from someone whose company relies heavily on leads: they have a clear definition of what a lead needs in order to be converted into an account or contact and opportunity, and if it’s not there it doesn’t fly.
Start with policy and an understanding of the desired state, particularly pertaining to definitions around clean data. Then turn conceptual territory ideas in spreadsheets and napkin drawings into an object in Salesforce. Again, policy first, then infrastructure. Finally, see what additional functionality you can build on top of the foundation of clean data + territories.
I had a great time engaging with everyone during this session. I’d love to continue the dialogue, and look forward to many more Sales Ops information-sharing opportunities at future Dreamforce events.
About the Author
Greg Myer is a Sales Operations Manager at Box, where he has worked for two years. His team is primarily responsible for Data Governance, especially pertaining to account/company data and revenue-related information. You can connect with Greg on LinkedIn here ».
