The Benefits of a Sales Tech Stack


  • A strategically designed Sales Technology stack replaces ad hoc and piecemeal systems with a holistic portfolio that achieves greater salesforce utilization, drives the most important revenue goals, maximizes investments and future-proofs technology investments.
  • A smartly designed sales tech stack creates a competitive advantage as it defines an overarching architecture that blueprints the apps needed to directly acquire, grow and retain more customers.
  • It's not about acquiring more of the latest technology that determines your success. It's about acquiring the apps that create synergy and drive achievement of your most important objectives. And it can be done in a 3-step process, shown below.
Johnny Grow Revenue Growth Consulting

Selecting the right sales software is essential to process automation, information reporting and revenue outcomes. It's also an underlying requirement for efficient and scalable revenue growth.

But that doesn't make it easy.

The sales technology landscape is complex, and the volume of applications can quickly make it feel overwhelming.

Sales leaders struggle to align limited budgets with what looks like a sea of unlimited solutions. And unless they demonstrate clear payback or measurable ROI from their investments, they put those budgets at risk.

What's needed to escape this confusion is an approach that separates technology hype from reality, directly aligns technology with measurable outcomes and creates a simplified roadmap for technology planning, procurement and payback.

A 3 Step Approach to a Sales Tech Stack


Start with Technology Strategy

Sales technology research (link to sales technology success factors) shows that the Best-in-Class sales leaders started with a technology strategy 4.5X more frequently than their lower performing peers. That's a substantial difference that should not go unnoticed.

Sales Technology Strategy

The goal for a Sales Technology Strategy is to identify the most effective sales technologies that drive the most important business outcomes. And because it's not realistic to acquire every helpful solution at once, the strategy should be designed as a roadmap to be navigated over a multi-year period.

That roadmap will plot the specific apps and tools that build upon each other and drive slated revenue objectives with evidence-based best practices.

Those best practices may include things like automated lead scoring to feed the funnel, opportunity win plans to increase conversions, manager coaching for improved quota attainment, automated processes for higher staff productivity, push-based recommendations for guided selling, or real-time alert notifications to quickly intervene when forecasted opportunities stall or regress.

For the strategy to be effective, it's critical that these best practices be directly linked to the most important business outcomes. Those outcomes generally include increasing customer acquisitions, customer share and customer retention.

Without a selling technology strategy, most companies acquire piecemeal solutions to solve an urgent problem. That may help with the problem of the day, but quite often contributes to software sprawl, data siloes, lack of integration and temporary results. It also fails to contribute to a more strategic application portfolio that aligns with the company's priorities.

A Sales Tech Stack Design Approach

Starting with strategy may seem like common sense. But it's not commonplace for business leaders unsure of what a technology strategy should include, how it should accelerate execution and what measurable benefits it should deliver.

Adopting a proven framework can help. One we routinely use with clients is called PACE.

PACE is a technology strategy that aligns business goals with technology capabilities.

More specifically, the PACE model aligns the methods revenue leaders use to create competitive advantages, described in terms of common ideas, different ideas and new ideas, with a technology portfolio that segments the Sales Tech stack into layers called Systems of Record, Systems of Differentiation and Systems of Innovation.

PACE Technology Strategy

PACE is not limited to sales technologies but is particularly well suited to them. An illustration with selling examples might look like the following.

PACE Technology Strategy Sales

The benefit of the PACE model is that it allocates more investment to the capabilities that drive the most business value and less investment toward capabilities that don't deliver differentiation or competitive business advantages.

Many people believe PACE was created by Gartner. It wasn't although Gartner's promotion of this technology strategy has made it very popular.

One last point when defining your Sales Tech stack. The research found that most salespeople use a small fraction of their CRM software or Sales Force Automation (SFA) application and other selling apps. Start your technology strategy by assessing what you have and how much of it is being used. Using more of what you already have will accelerate time to value, reduce the volume of apps needed and decrease costs.


Sales Solution Architecture

Once the technology strategy identifies the software apps that drive the most important revenue outcomes, it's time to organize those apps and show how they can fit together to better empower the salesforce.

That starts with a Solution Blueprint, or what some call a Sales Solution Architecture. Its purpose is to show how apps work together to create synergy and lower total cost of ownership (TCO). The illustration below is an example.

Sales Tech Solution Blueprint

Solution Blueprints vary by company size and sophistication, technology maturity and industry. For example, selling software such as Configure-Price-Quote (CPQ) and Partner Relationship Management (PRM) will be important for manufacturers that sell highly configured goods and sell through indirect channels. Internet of Things (IoT) and Field Services Management (FSM) will be important for manufacturers of equipment pursuing high margin revenue growth through additional reactive and preventative services.

Once you have a holistic technology strategy that shows how selling software works collectively to achieve revenue goals you can better plan the timing and procurement for each component.

But there's one more thing to consider in your planning. And that is how to best leverage platform and best of breed applications.

Platform Solutions

A good Sales Tech stack is built on a solid foundation that starts with a Platform solution.

The three most important platform solutions are the Customer Relationship Management (CRM) platform, the Sales Force Automation (SFA) platform and the Customer Data Platform (CDP).

The goal here is to use platform solutions that provide the most capabilities from a single application. That results in fewer apps that do more and facilitates end to end process automation, decreases system integration and consolidates data siloes for easier and more effective reporting.

And because platform solutions generally have ecosystems of integrated third-party apps, they facilitate extensibility which helps future proof your salestech stack investment. Salesforce's AppExchange and Microsoft's AppSource are the two largest platform ecosystems.

While a single platform solution can replace dozens of standalone piecemeal apps, they often can't do it all. A smart selection of best of breed apps may be needed to fill the gaps and accelerate certain objectives.

Point Solutions

The goal here is to selectively curate best of breed selling technologies that deliver distinct capabilities needed to achieve unique goals.

Most point solutions solve a single, particularly difficult and often very important challenge. For example, an ABM MarTech Stack or similar account-based marketing apps enable salespeople to drive new qualified leads. Integrated sale methodologies increase win rates. Integrated sales playbooks facilitate guided selling and the adoption of best practices. And artificial intelligence (AI) aids the salesforce with process automation and highly intelligent recommendations.

Many point solutions deliver capabilities not available in the CRM or other platform solution. But they may be part of a platform ecosystem which generally means they will offer a consistent user interface (UI) and packaged integration to the CRM software. That makes them quick to deploy and relatively easy to maintain.

The tradeoff with these best of breed solutions is often risk and impact. Because they are generally delivered by small innovative startups, they come with a much higher risk. Because they solve big problems, they deliver a big impact.

When considering the risk and impact, many evaluators come down to a decision of added value with the point solution versus good enough functionality with a more generic capability built into the CRM or SFA system they already have.

The diagram below shares positioning and characteristics of platform and best of breed applications.

Sales Tech Stack

Lastly, recognize that over time the CRM publishers build or acquire point solutions which means many of the innovative startups have relatively short life spans.


Data and Analytics

The final step is to identify the best technologies to convert raw data into actionable insights and route those insights to the people that can use them to engage a customer, remedy a variance, implement a course correction, make a more timely and informed decision, or take some other informed action.

Data and analytics make the salesforce smarter. They advise which buyers will buy, which opportunities will close, which selling actions will influence the sale probability, and how sellers can better allocate their scarce time to produce better results.

But for data to improve selling activities, engagement, conversions and decisions you need processes and tools to harvest, convert and forward data to the person or place it can be applied.

This part of the Sales Tech stack needs four things.

  1. Data Transformation Tools
    Data is an asset. But to yield value, it must be converted from a raw material to a finished product of information or insight. That's best done with a data transformation process, or what is sometimes called a data transformation pipeline.
Sales Data Transformation

Much of the data will reside in the CRM system. But data will also come from additional sources such as the social sphere, data enrichment providers and other company systems such as the Marketing Automation Platform (MAP) and ERP system.

The most successful leaders are defined by their ability to collect and curate the right data, use data to create the most impactful actions and apply data analytics to make insights actionable to sellers at every customer interaction.

  1. Performance Dashboards
    Good sales dashboards deliver the right information to the right seller at the right time. They focus on the most essential key performance indicators and prioritize information based on what's most important to each user.

They show what should be done, in a sequenced order, to aid time management, create a work rhythm cadence and maximize productivity.

But most CRM packaged dashboards display what is easy instead of what is important.

To a first-time observer these dashboards looks good. But if good looks were the factors for success my first marriage would have made it, and sales dashboards would get much more utilization.

Sales analytics research shows that dashboards achieve up to 30 percent utilization immediately following an implementation go-live. But within 3 weeks that utilization falls to 9 percent. Over time it falls further. The decline is due to dashboards not providing real help to sellers.

The key to analytics is to translate selling activities into business outcomes and measure what matters. Defining the right metrics to track progress and prompt real-time corrective action is an essential best practice for achieving dashboard success. If your dashboards are not continuously suggesting, adjusting or reprioritizing actions for your sale opportunities, they are not working.

Sales Dashboard
  1. Predictive Analytics
    Analytics convert data into trends, patterns and anomalies that support sales objectives and revenue impact.

Predictive analytics shift information reporting from hindsight to foresight.

For example, they use Ideal Customer Profile (ICP) characteristics to identify the highest fit prospects and calculate lead scores to prioritize sales-ready leads.

They apply propensity models to show the combination of selling actions, offers and strategies that will optimize pipeline growth and conversions.

The best analytics show how selling activities directly impact revenue outcomes.

The below Predictive Pyramid is a Johnny Grow predictive model that shows how lower levels of selling execution drive to pipeline and revenue growth. And it's not just predictive, it's interactive to support dynamic modeling and What-If scenarios.

Revenue Growth Predictive Analytics

The pyramid is helpful because no selling program operates in a vacuum. Each has cascading effects that impact other areas and those impacts must be considered when making tradeoffs. This visualization is helpful in determining where to invest your limited time to achieve the biggest financial uplift.

  1. Artificial Intelligence
    Sales AI use cases include things like predictive prospecting, calculated lead and opportunity scores, guided selling, intelligent forecasting, and improvements to workflow processes that save salespeople time.

AI is embedded in the most common CRM systems, such as Salesforce Sales Cloud, Microsoft Dynamics 365 and SAP CRM. Adopters are well past their pilot projects and AI is now in the mainstream for process automation and decision support.

AI detects sources of revenue leakage that have historically been hidden, such as lead leakage, stalled opportunities or customers at risk of churn.

The question for sales leaders standing on the sidelines is not if AI will impact their salesforce, but how and when.

Data is the fuel, AI is the engine, and selling insights are the destination.

Every person, process, information system and decision in your company is improved with more relevant data.

When properly harvested and fully yielded, your data is more valuable than your products.

But to realize the value of data and analytics you need one more thing – a data driven culture. That is a corporate culture that discourages intuitive, gut-based, trial and error, and subjective customer engagement or decision making and instead rewards data-driven, fact-based and objective engagement and decision making.

About 100 years ago, a smart guy named William Edwards Deming advised his management team, "In God we trust, all others must bring data." That statement perfectly describes a data driven operating culture.

See the 3-step approach to define your sales tech stack and the technologies that drive the most important revenue outcomes.

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The Point is This

A Sales Tech stack is designed to aid the most important revenue objectives and solve the most vexing problems.

It's an evolutionary approach that replaces individual software procurements with a holistic and planned approach designed to achieve strategic benefits. It's also helpful in cutting through the clutter of a confusing software landscape.

Designing the best Sales Tech stack is not just about software. It's about the alignment of technology with business outcomes.

That means identifying how solutions work together to aid sales strategies, tactics and productivity so sellers win more deals. It means enabling the salesforce with process automation so they reduce manual activities and reallocate more time to selling. If the salestech stack doesn't do these things, the synergy is missed, the effort is futile, and the investment will disappoint.