May 16, 2023
May 16, 2023
by
by
Minami Rojas
Minami Rojas
The Build vs. Buy Guide for Product-led Sales Tooling
Guide
Guide
A guide to outline the 4 key factors to consider of building vs. buying product-led sales tooling. Hint, the real question is do you need pipeline and revenue now or can you wait 10+ months?
As revenue goals loom and headcount is constrained, sales teams are leaning more than ever into tools, data, and systems to help uncover pipeline faster, improve pipeline performance, and increase rep productivity.
This is where the rise of product-led sales has stepped in.
Product-led sales is simply using product data as a core part of the sales strategy. Reps can use product data to better understand who they should target, build a compelling business case, and determine what message will be most effective. In the end, this helps reps generate more pipeline and close deals faster.
While it may sound simple, translating product data into actionable workflows for sales teams is a technical and operational hurdle, which is why we built Endgame. Oftentimes, internal options require complex pipelines, heavy resources to build, and long-term requirements to maintain.
The stack needed for product-led sales
In order to determine whether to build vs. buy, it’s important to understand the core components of the tech stack that is needed for product-led sales. The stack consists of:
Data Platform: Connect disparate data sources to attribute product usage to CRM constructs
Data Science and ML: Ongoing conversion analysis of opportunities, new logos, expansion, and churn to identify the right propensity signals to build the best dynamic score.
Rep UI: Simplified rep UI that prioritizes play to quickly action workflows and visualizes account usage and catalogs all product user and workspaces to build rep insight and trust
4 Key Factors in Determining Build vs. Buy
The TL;DR is that there are four key factors to consider when deciding whether to build or buy a product-led sales platform:
Team resources: Do you have the cross-functional resources and expertise to build a solution? Are there higher priority strategic projects they should be working on?
Ongoing maintenance: Do you have a dedicated team to own data observability and act as product managers? Can the team scale faster by partnering with a vendor to manage ongoing maintenance?
Strategic direction: Do you have requirements that warrant a customized in-house solution? Would your team benefit from partnering with a vendor that is building off best practices and insights from the wider market?
Time to revenue: Do you have the 6-12 months of pipeline coverage to hit quota while building internally? Is it worth the opportunity cost of revenue lost to build compared to the cost of buying a solution?
We’ll walk through the questions you should consider, as well as walk through common ways “build” options fail. So let’s get into the details!
1. Team Resources
One of the key factors to consider when building a tool is the amount of internal resources needed. With a product-led sales platform, the work touches many organizations across data, ops, and sales with many hands needed to support.
The initial build responsibilities will sit within RevOps, Data Science, Data Engineering, and Product. At a high level the jobs to be done include:
RevOps: Owning end-to-end strategy of tools and systems, helping operationalize and enable the GTM workflows, and acting as a product manager post launch to field new requests, track adoption, provide day-to-day maintenance, and monitor data pipelines
Data Science: Building ML models to identify key product signals that drive individual plays for the GTM motions like new logo, expansion, and churn
Data Engineering: Map product data to CRM data, incorporate streaming data from ML models, and build pipelines into the GTM systems
Product Management: Create and iterate on the core product, features, and UI based on feedback from reps
If partnering with a vendor, 95% of those responsibilities are reduced with the main resource requirements internally to be initial integration and then to act as a partner to help drive strategy forward.
Expertise Within the Team
Another factor to consider when building vs. buying is beyond the resources – does your existing team have the expertise you need to build the right tool?
The worst case scenario is your internal team invests time into building a solution and it ends up discarded because either it isn’t built for reps to easily incorporate into their workflow or it doesn’t produce the right insights to drive revenue impact.
When building a product-led sales platform, you want a team that understands best practices in approaching data, has experience with the challenges in solving the complexity combining product data with CRM data, and most importantly deeply understands the wants and needs of the end user: sales.
Team Resources: Questions to Ask Yourself
What's your team's current capacity?
Do you have alignment across all organizations needed to build this?
Do you have the expertise in house to take this project on?
What’s the opportunity cost of having your team building this vs. working on other strategic projects?
2. Ongoing Maintenance
Once the tool is built, the work doesn’t stop there. Another key factor to consider in build vs. buy is who will continue to maintain the solution in year 2 and year 3? Maintaining the tool long term comes in two forms of work; data observability to notify on call when things break, and managing feedback and improvement requests.
Data Reliability
A huge consideration in building vs buying is data. Who will take on the important responsibility to ensure data reliability from raw data, through pipelines, into rep workflows?
Within a product-led sales workflow, many things can impact your data reliability:
Data freshness: Data becomes outdated or stops syncing due to upstream integration and API changes
Data quality: Data could be missing from the pipeline that is more important in the rep workflow
Sales workflow changes: Changes in team roles and responsibilities, new hires, new territories, changes in segment definitions impact what’s important to the end user
Pricing and packaging: Changes in pricing and packaging, SKUs, and new products can change the core data and use case you are designing for
Building in-house not only requires a team to be on-call, but a team to be able to evaluate the quality of data and make changes as the business evolves.
On the other hand, a product-led sales platform is built to flex and grow with your business with data observability notifications and on-call set up, a data platform to automatically sync new data, and ML models that learn and adapt with sales and pricing and packaging changes.
What’s the impact of not maintaining data reliability? Unhappy reps and unhappy customers. Reps are using outdated information to target the wrong users for the wrong play. Best case scenario; a rep reaches out to an account to drive expansion but they aren’t adopted so don’t respond. Worse case scenario; a rep reaches out to an unhappy customer to drive expansion and the customer gets upset and churns. Worse worse case scenario; reps lose confidence in the tool altogether and it’s been a long and expensive journey to shelf-ware.
Managing Feedback and New Requests
Identifying who is responsible to “product manage” the tool is an added cost when building internally. Managing feedback and feature requests can come in multiple forms such as:
Request to pipe additional data into the system: Existing data that requires additional piping, existing data that requires transformation, and/or net new that need tracking
Questions around which data points to focus on: Clarifying questions around which data points are best to use, why they should be trusted, and which ones are most important to focus on
Requests to improve workflow and UI: Asks to change rep experience to drive better revenue impact through increased usage and adoption
Working with a vendor, you will have a partner whose #1 job is to help action data requests, address questions, and incorporate requests into future releases.
Most importantly, user feedback is the lifeblood of a vendor helping drive future roadmap vs. internally is added work and resourcing constraints for your internal team.
Ongoing Maintenance: Questions to Ask Yourself
Does your team have scope for added maintenance and support tickets?
What priority will your team have to fix any issues?
What else could your team be driving forward instead of maintaining this system?
How frequently are upstream factors changing that could cause downstream issues?
3. Strategic Direction
When deciding between building or buying a solution, thinking about how your needs will scale and how they will be supported in the future is an important consideration.
When building internally, you have the benefit of a custom-made solution for your own team. This means:
Custom-built for your data, team, and workflows
In-house ownership of the learnings, features, and improvements made
Evolving the solution based on internal company strategy and direction
When buying through a vendor, you have a partner that lives and breathes the ability to solve this problem. This means:
A partner who can ideate, take feedback, and share back best practices and learnings across revenue teams in the entire industry
A solution and roadmap purpose-built based on market research and deep understanding of how revenue workflows can be supported with product data, ML models, and plays
A source to crowd-source innovation with every other high growth b2b sales teams
Strategic Direction: Questions to Ask Yourself
Do you have unique requirements that warrant a custom build?
Would you want to benefit from insights and best practices from other revenue teams in the market?
4. Time to Revenue
The most important factor to consider in the build vs. buy conversation is time to revenue, the core reason behind this investment. On average, building in-house can mean 10-12 months before seeing revenue impact.
Building in-house takes time and for a solution that requires cross-functional alignment, resources, and enablement, no matter how big or small the team there is always a time element. Interestingly enough, the enemy of revenue or more specifically revenue goals is time. The longer it takes to find a deal, create an opportunity, and close a deal the further and further away the reality of achieving quota becomes.
Buying a solution can reduce time to revenue by 3x with your team seeing pipeline impact within 1-3 months and revenue within 4 months.
That’s why when determining build vs buy, it’s important to consider each phase and how much it adds to your time to revenue. The key phases are:
Alignment: Mapping strategy, getting alignment, aligning resources
Build: Actively building or integrating data pipelines, connecting product data to CRM data, operationalize in GTM systems
ML Models: Analyzing past performance, building models, QA’ing output
Enablement: Validating workflows, launching, tracking usage and adoption
Pipeline: Prospecting, generating pipeline, managing deals
Revenue: Closed deals and revenue
Time to Revenue: Questions to Ask Yourself
Do you have pipeline coverage to hit quota while this is being built?
With your sales cycle what is the earliest you’ll see pipeline impact vs revenue impact?
What budget do you have to buy and is it worth the potential revenue lost during time spent building?
The summary: what is the opportunity cost in pipeline and revenue worth?
At the end of the day, revenue goals aren’t going to be delayed. The decision comes down to a single equation; the total opportunity cost of resources and revenue to build a solution vs. the cost of buying a tool.
If you are still considering building in-house, review the guide to launching product-led sales to walk through each step you need to take to launch product-led sales for your revenue teams.
However, we believe strongly that partnering with a vendor is the best way to leverage your team’s time, open up internal focus for higher strategic objectives, and lean into a partner who can help scale based on the expertise and insights of the entire market.
Our team built Endgame after repeatedly building in-house solutions that were 20% effective and knowing that revenue teams deserved better. Interested in partnering with us? Contact us today—we’d love to chat!
A guide to outline the 4 key factors to consider of building vs. buying product-led sales tooling. Hint, the real question is do you need pipeline and revenue now or can you wait 10+ months?
As revenue goals loom and headcount is constrained, sales teams are leaning more than ever into tools, data, and systems to help uncover pipeline faster, improve pipeline performance, and increase rep productivity.
This is where the rise of product-led sales has stepped in.
Product-led sales is simply using product data as a core part of the sales strategy. Reps can use product data to better understand who they should target, build a compelling business case, and determine what message will be most effective. In the end, this helps reps generate more pipeline and close deals faster.
While it may sound simple, translating product data into actionable workflows for sales teams is a technical and operational hurdle, which is why we built Endgame. Oftentimes, internal options require complex pipelines, heavy resources to build, and long-term requirements to maintain.
The stack needed for product-led sales
In order to determine whether to build vs. buy, it’s important to understand the core components of the tech stack that is needed for product-led sales. The stack consists of:
Data Platform: Connect disparate data sources to attribute product usage to CRM constructs
Data Science and ML: Ongoing conversion analysis of opportunities, new logos, expansion, and churn to identify the right propensity signals to build the best dynamic score.
Rep UI: Simplified rep UI that prioritizes play to quickly action workflows and visualizes account usage and catalogs all product user and workspaces to build rep insight and trust
4 Key Factors in Determining Build vs. Buy
The TL;DR is that there are four key factors to consider when deciding whether to build or buy a product-led sales platform:
Team resources: Do you have the cross-functional resources and expertise to build a solution? Are there higher priority strategic projects they should be working on?
Ongoing maintenance: Do you have a dedicated team to own data observability and act as product managers? Can the team scale faster by partnering with a vendor to manage ongoing maintenance?
Strategic direction: Do you have requirements that warrant a customized in-house solution? Would your team benefit from partnering with a vendor that is building off best practices and insights from the wider market?
Time to revenue: Do you have the 6-12 months of pipeline coverage to hit quota while building internally? Is it worth the opportunity cost of revenue lost to build compared to the cost of buying a solution?
We’ll walk through the questions you should consider, as well as walk through common ways “build” options fail. So let’s get into the details!
1. Team Resources
One of the key factors to consider when building a tool is the amount of internal resources needed. With a product-led sales platform, the work touches many organizations across data, ops, and sales with many hands needed to support.
The initial build responsibilities will sit within RevOps, Data Science, Data Engineering, and Product. At a high level the jobs to be done include:
RevOps: Owning end-to-end strategy of tools and systems, helping operationalize and enable the GTM workflows, and acting as a product manager post launch to field new requests, track adoption, provide day-to-day maintenance, and monitor data pipelines
Data Science: Building ML models to identify key product signals that drive individual plays for the GTM motions like new logo, expansion, and churn
Data Engineering: Map product data to CRM data, incorporate streaming data from ML models, and build pipelines into the GTM systems
Product Management: Create and iterate on the core product, features, and UI based on feedback from reps
If partnering with a vendor, 95% of those responsibilities are reduced with the main resource requirements internally to be initial integration and then to act as a partner to help drive strategy forward.
Expertise Within the Team
Another factor to consider when building vs. buying is beyond the resources – does your existing team have the expertise you need to build the right tool?
The worst case scenario is your internal team invests time into building a solution and it ends up discarded because either it isn’t built for reps to easily incorporate into their workflow or it doesn’t produce the right insights to drive revenue impact.
When building a product-led sales platform, you want a team that understands best practices in approaching data, has experience with the challenges in solving the complexity combining product data with CRM data, and most importantly deeply understands the wants and needs of the end user: sales.
Team Resources: Questions to Ask Yourself
What's your team's current capacity?
Do you have alignment across all organizations needed to build this?
Do you have the expertise in house to take this project on?
What’s the opportunity cost of having your team building this vs. working on other strategic projects?
2. Ongoing Maintenance
Once the tool is built, the work doesn’t stop there. Another key factor to consider in build vs. buy is who will continue to maintain the solution in year 2 and year 3? Maintaining the tool long term comes in two forms of work; data observability to notify on call when things break, and managing feedback and improvement requests.
Data Reliability
A huge consideration in building vs buying is data. Who will take on the important responsibility to ensure data reliability from raw data, through pipelines, into rep workflows?
Within a product-led sales workflow, many things can impact your data reliability:
Data freshness: Data becomes outdated or stops syncing due to upstream integration and API changes
Data quality: Data could be missing from the pipeline that is more important in the rep workflow
Sales workflow changes: Changes in team roles and responsibilities, new hires, new territories, changes in segment definitions impact what’s important to the end user
Pricing and packaging: Changes in pricing and packaging, SKUs, and new products can change the core data and use case you are designing for
Building in-house not only requires a team to be on-call, but a team to be able to evaluate the quality of data and make changes as the business evolves.
On the other hand, a product-led sales platform is built to flex and grow with your business with data observability notifications and on-call set up, a data platform to automatically sync new data, and ML models that learn and adapt with sales and pricing and packaging changes.
What’s the impact of not maintaining data reliability? Unhappy reps and unhappy customers. Reps are using outdated information to target the wrong users for the wrong play. Best case scenario; a rep reaches out to an account to drive expansion but they aren’t adopted so don’t respond. Worse case scenario; a rep reaches out to an unhappy customer to drive expansion and the customer gets upset and churns. Worse worse case scenario; reps lose confidence in the tool altogether and it’s been a long and expensive journey to shelf-ware.
Managing Feedback and New Requests
Identifying who is responsible to “product manage” the tool is an added cost when building internally. Managing feedback and feature requests can come in multiple forms such as:
Request to pipe additional data into the system: Existing data that requires additional piping, existing data that requires transformation, and/or net new that need tracking
Questions around which data points to focus on: Clarifying questions around which data points are best to use, why they should be trusted, and which ones are most important to focus on
Requests to improve workflow and UI: Asks to change rep experience to drive better revenue impact through increased usage and adoption
Working with a vendor, you will have a partner whose #1 job is to help action data requests, address questions, and incorporate requests into future releases.
Most importantly, user feedback is the lifeblood of a vendor helping drive future roadmap vs. internally is added work and resourcing constraints for your internal team.
Ongoing Maintenance: Questions to Ask Yourself
Does your team have scope for added maintenance and support tickets?
What priority will your team have to fix any issues?
What else could your team be driving forward instead of maintaining this system?
How frequently are upstream factors changing that could cause downstream issues?
3. Strategic Direction
When deciding between building or buying a solution, thinking about how your needs will scale and how they will be supported in the future is an important consideration.
When building internally, you have the benefit of a custom-made solution for your own team. This means:
Custom-built for your data, team, and workflows
In-house ownership of the learnings, features, and improvements made
Evolving the solution based on internal company strategy and direction
When buying through a vendor, you have a partner that lives and breathes the ability to solve this problem. This means:
A partner who can ideate, take feedback, and share back best practices and learnings across revenue teams in the entire industry
A solution and roadmap purpose-built based on market research and deep understanding of how revenue workflows can be supported with product data, ML models, and plays
A source to crowd-source innovation with every other high growth b2b sales teams
Strategic Direction: Questions to Ask Yourself
Do you have unique requirements that warrant a custom build?
Would you want to benefit from insights and best practices from other revenue teams in the market?
4. Time to Revenue
The most important factor to consider in the build vs. buy conversation is time to revenue, the core reason behind this investment. On average, building in-house can mean 10-12 months before seeing revenue impact.
Building in-house takes time and for a solution that requires cross-functional alignment, resources, and enablement, no matter how big or small the team there is always a time element. Interestingly enough, the enemy of revenue or more specifically revenue goals is time. The longer it takes to find a deal, create an opportunity, and close a deal the further and further away the reality of achieving quota becomes.
Buying a solution can reduce time to revenue by 3x with your team seeing pipeline impact within 1-3 months and revenue within 4 months.
That’s why when determining build vs buy, it’s important to consider each phase and how much it adds to your time to revenue. The key phases are:
Alignment: Mapping strategy, getting alignment, aligning resources
Build: Actively building or integrating data pipelines, connecting product data to CRM data, operationalize in GTM systems
ML Models: Analyzing past performance, building models, QA’ing output
Enablement: Validating workflows, launching, tracking usage and adoption
Pipeline: Prospecting, generating pipeline, managing deals
Revenue: Closed deals and revenue
Time to Revenue: Questions to Ask Yourself
Do you have pipeline coverage to hit quota while this is being built?
With your sales cycle what is the earliest you’ll see pipeline impact vs revenue impact?
What budget do you have to buy and is it worth the potential revenue lost during time spent building?
The summary: what is the opportunity cost in pipeline and revenue worth?
At the end of the day, revenue goals aren’t going to be delayed. The decision comes down to a single equation; the total opportunity cost of resources and revenue to build a solution vs. the cost of buying a tool.
If you are still considering building in-house, review the guide to launching product-led sales to walk through each step you need to take to launch product-led sales for your revenue teams.
However, we believe strongly that partnering with a vendor is the best way to leverage your team’s time, open up internal focus for higher strategic objectives, and lean into a partner who can help scale based on the expertise and insights of the entire market.
Our team built Endgame after repeatedly building in-house solutions that were 20% effective and knowing that revenue teams deserved better. Interested in partnering with us? Contact us today—we’d love to chat!