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Data Driven Sales Planning using Territory Models


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Data is the DNA of any organization and is critical to its success. Organizations with a strong data quality and governance framework enjoy the fruits of an intelligent sales territory planning process. Lack of good quality data leads to a very laborious territory planning cycle and could result in a sub-optimal mapping of sales representatives to manage customers. This could result in an over or under allocation of a sales person’s territory and can result in poor customer experience and even attrition. On the operational side, this could result in poor forecasting, inefficient revenue attribution, tedious reporting exercises due to lack of data modeling and a significantly delayed root cause analysis when financial goals are missed.

 

The following set of best practices are written with a lens of data that is housed in a CRM environment. The business model that the below strategy best aligns with is B2B direct subscription product sales. The scope of sales territory planning outlined below is limited to certain organizational groups - core and specialist sales teams, sales operations, corporate finance and any other teams that directly influence sales territory allocation and revenue measurement. While sales has a significant role to play in the curation of the company’s GTM strategy - it typically rests within the wheelhouse of sales operations. The revenue and HR organizations contribute heavily to the planning exercise.

 

The four most crucial elements of conducting territory segmentation at scale are:

  1. Identification of the fundamental data attributes that are reflective of the company’s go to market strategy

  2. Maximize completeness and correctness of these fundamental data attributes enough to ensure that the data is trusted across the organization

  3. Writing rules to segment customers into “cohorts”, on top of this trusted data

  4. Scalable automation i.e. IT support to codify these rules into the system (in this case, a CRM).

 

Let us look at each of the above elements in detail.

 

  1. Identification of the fundamental data attributes that are reflective of the company’s go to market strategy

 

Data Quality is a thankless task and a moving target. Data will never be 100% current and it will very rarely be 100% complete. However, the way one can optimize the completeness and correctness of data is by “scoping” out what’s important. Of the hundreds of data points that one could capture about their customer into the CRM, only a handful really matter! How about the 80-20 rule? Many a time, 20% of the data attributes directly drive 80% of the value.

 

Every B2B company has a system of record of its customers i.e. businesses. This exercise entails identifying the core data attributes or fields (in the CRM world) that are integral to the company’s GTM strategy. For example: a company that sells its product globally, across several industries could have the following attributes of its customer records as building blocks of segmentation:

 

  • Geographical

  • Vertical or Industry or Category of the customer

  • Materiality of the customer to the company - Employees (reflecting size), Seats/Licenses (in case of a subscription model), Revenue (reflecting business), Deal Pipeline (reflecting potential) 

  • Product adoption

 

These fundamental building blocks could be identified by a handful of leads from multiple groups coming together and forming a council. There could be 1-2 members from finance, 3-4 across the global sales teams, 2-3 sales operations team members and a few more. These exercises could be moderated by a data governance expert. The conclusion of these exercises is a thorough documentation of critically important fields i.e. a data dictionary.

 

  1. Maximize completeness and correctness of these fundamental data attributes enough to ensure that the data is trusted across the organization

 

Now that one has identified the critical attributes, it is important to install guardrails around these attributes. There are one or more best practices one can adopt to ensure correctness and completeness of the data.

  1. A small team of business development representatives, junior data analysts, or interns who can scrub the data and maintain accurate information. They could refer to third party trusted data sources to periodically look up and maintain freshness.

  2.  An investment to procure business firmographic data from trusted data vendors and conduct data cleansing at scale (1-2 times a year) prior to annual planning

  3. Tight access controls in place on a handful of critical roles that can edit these critical attributes in the CRM. Implement these access controls at an attribute level into the CRM with the help of IT.

  4. A robust intake process for data changes from the sales organization. Provide strict guidelines and detailed procedures to the data support team (BDRs, analysts) who are processing these requests - ask for a verified source of truth, or may be a business justification.

  5. Capturing history of every data change.

  6. Dummy fields to capture real time changes and having fixed fields that are updated only once a year to drive sales territory planning.

  7. A handful of attributes with some automation to compute a ‘Health’ score. Simple code that checks completeness of data, the last modified date on a field to reflect recency of an update are some of the ways. If 8 out of 10 critical attributes are populated, record a Completeness Health Score of 80 (scale or 1-100). If 5 out of the 8 attributes were updated in the last 6 months, record a Recency Health Score score of 62.5 (⅝) to reflect recency.

  1. Writing rules to segment customers into “cohorts”, on top of this trusted data

Doing this for the first time is the hardest! It requires numerous conversations and pilots across the sales organization to build trust that “data” can replace some element of “intuition” in territory segmentation. It requires various permutations and combinations of choosing the right attributes and choosing the right level

 

Examples: 

  1. One can stay high level by creating a cohort of a combination of country and revenue size (based on some sizing exercises). Eg: US-LargeEnterprises, UK-MidEnterprises, India-SMB

OR

  1. One can create many granular cohorts with a combination of country, state, employee count (based on some sizing exercises), vertical, sub-vertical and hero product adoption. Eg: Take a company with three distinct product lines - Pa, Pb, Pc. 

    1. CA-Quebec-SMB - A sales leader covering the Quebec province for all small businesses.

    2. US-OregonWashington-Large-ConsumerProducts-Food-Pa - A Pa specialist sales representative covering the large scale Pacific Northwest food industry.

 

It is very challenging to get this right in the first year and it is an iterative process for subsequent cycles. BUT it is one of the most efficient techniques that will reward the organization in the longer term and get you a step closer towards an efficient sales planning cycle.

 

  1. Scalable automation i.e. IT support to codify these rules into the system (in this case, a CRM)

 

Just as critical devising the GTM strategy of an organization is, so is the implementation. An IT organization serves as a backbone for sales planning. Primarily there are three facets of IT which shall serve to contribute to an organization’s operational excellence:

  • Product (Product Owners, Business Analysts) - This group is primarily responsible for acting as a conduit between engineering and sales operations. Every sophisticated automation essentially calls for constant enhancement, maintenance and support. In the aforementioned examples of territory models, US-LargeEnterprises calls for much simpler automation infrastructure and routing rules vs US-OregonWashington-Large-ConsumerProducts-Food-Pa which calls for advanced routing rules on multiple attributes on a customer record. Typically smaller businesses at a nascent stage with territory planning will opt for a simpler model and gradually mature to a more complex model. This transition requires a significant amount of interaction amongst IT, Sales Operations, Finance etc. The POs or BAs who have the functional knowledge of both worlds are perfectly positioned to steer these conversations.

  • Engineering (Data and Application, incl. Architects) - To manage the infrastructure, to help enhance the complexity and to help scale a growing company, a strong engineering organization is required.

  • Support (Sales Processes, Application and Data) - This is where an immediate ROI in terms of sales excellence shall be seen. Everytime you introduce data-driven territory planning, chances of “nuances” and “exceptions” only rise. To help maintain the sanity of the sales organization to sales territory mapping, constant maintenance and sales support is important. Such support can be handled in the form of tasks/cases. A team of sales support professionals can follow a standard set of protocols to maintain the mapping of sales to customers. These professionals can also support the sales operations organization with:

    • The correctness, completeness and freshness of data on the system of record - customer records, territory tables etc. Every time the sales operations team procures external data for cleansing, it could be this support team that implements those updates.

    • Processing account coverage updates due to employment changes - Promotions, Hiring, Attritions - Employees, Internal transfers, Leave of absence

    • Archival of records or hiding those from the active sales models i.e. attrited customers 

    • Sales coverage changes due to key changes happening to the customer - contract changes, industry change, customer up-size/down-size - all of these could entail a shuffling of the sales team managing that customer.

    • Senior leadership strategy - Often there are mid-year changes to a company’s strategy based on how the business is performing. During an economic crisis, companies often go into a reactive mode. When a product market fit gap is identified, companies could make acquisitions. All of these can have a significant impact on sales territory coverage. Processing all these changes will require numerous support professionals who maintain the best possible state of the system as the business demands.

    • And much more……

With all of the above, the primary focus of a Sales Operations team is to maintain simplicity and momentum for the sales organization. It is critical to keep the sales organizations shielded from any bottlenecks or operational overhead. The larger the company or the faster the company grows, the more convoluted the sales operations process is. Complexity can depend on the pricing and packaging model, breadth of product offerings, size of the sales organization, revenue recognition process, approval layers, reporting needs, forecasting needs and more. 

 

But everyone (literally everyone) needs to start somewhere, albeit small! Delivering small wins for sales and showcasing the power of a true data driven sales planning process in increments, will gradually bolster trust and pave the way for an organization to truly scale.


5 replies

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This is amazing @iyervenketesh, thank you for sharing, going to take this back to my team!

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Awesome piece, looking forward to meeting you and asking a ton of questions on the upcoming webinar you’re speaking on. RSVP if you haven’t already ops peeps! https://app.livestorm.co/adaptivops/scaling-your-operations

The four most crucial elements of conducting territory segmentation at scale are:

  1. Identification of the fundamental data attributes that are reflective of the company’s go to market strategy

  2. Maximize completeness and correctness of these fundamental data attributes enough to ensure that the data is trusted across the organization

  3. Writing rules to segment customers into “cohorts”, on top of this trusted data

  4. Scalable automation i.e. IT support to codify these rules into the system (in this case, a CRM).

Love how you broke this down so concisely!

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@iyervenketesh - great insights shared in your post. One important thing that is often a hurdle for ops folks that should be reflected here as well, is stakeholder buy-in! These strategies and structure are great, but unless there is buy-in, different components (like data quality, etc) will suffer. Overall I love the mindset that “Data is the DNA of any organization and is critical to its success. Organizations with a strong data quality and governance framework enjoy the fruits of an intelligent sales territory planning process.” Thanks for sharing!

-Adam

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Hi @adamjackowitz - Totally! None of the strategic investments shall move any further without stakeholder buy-in and some early wins based on a possible pilot.

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