AI-Driven GTM Strategy Relaunch Doubles Speed of Tech Giant’s Sales Cycle


A U.S.-based digital communications technology giant had a fast-growing $3 billion services-based business unit. While leadership was aligned on the high-level direction, the team was slow to implement its strategy. It needed to accelerate go-to-market (GTM) execution to meet goals.

Evalueserve took a scientific approach to relaunching the GTM strategy from the ground up. Solutions improved margins through value-based pricing, used propensity modeling to identify the most attractive customer segments, and built a recommendation engine for cross-sell and upsell campaigns. The client relied on Evalueserve as a strategic execution partner, which shortened the sales cycle by 50% and increased sales productivity by 70-80%.

The Challenge

A major technology company that was historically product-focused was expanding its service offerings. One of their new services units hit $3 billion and was on a high growth trajectory.

Leadership invested in a GTM strategy, setting the high-level direction and goals for the business unit. They identified key investments to make and calculated the expected return on investment (RoI). The director of product management, commercial lead, and customer success lead needed to execute the strategy.

Quickly, they realized they were missing key components to achieving success. They needed a substantial amount of reporting, research, and analytics based on what was happening on the ground to set realistic KPIs and timelines.

GTM Strategy Doubles Speed of Sales Cycle

Our Solution

Evalueserve relaunched the GTM strategy for the tech giant from the ground up, prioritizing price optimization and customer expansion recommendations.

Our experts tackled value-based pricing first due to its high impact on margins and profitability. As a price setter, the tech company did not have much data on competitor pricing, so we combined traditional modeling techniques with extensive intel gathering. This included everything from price elasticity curves to choice-based conjoint analysis to understand customer value perceptions. We conducted over 80 interviews to gather competitor intel.

We synthesized all this data into a pricing simulator, where sales users can find:

  • Ideal product bundles
  • Predictions for customers’ willingness to pay
  • Price changes’ impact on purchase probability
  • Competitor pricing
  • Scenarios to maximize revenue and profit


The next high-impact way to accelerate the growth strategy was enhancing their cross-sell and upsell campaigns. Evalueserve combined AI-driven propensity modeling with external benchmarks for value-add to build a recommendation engine for the sales team. The product was built on a microservices architecture and used APIs to pull from key customer data sources such as Customer Relationship Management (CRM) and Customer Data Platform (CDP).

The sales recommendation engine showed:

  • Total addressable market (TAM) so that sales reps can filter by key audience traits like owner, region, vertical, propensity level (bucketed into low, medium, or high), and attractiveness score
  • Customer segments based on customer data (transaction, services used, touchpoints), firmographics, and external intelligence (industry trends, white space, and share of wallet), allowing sales to see who the champions are and who is most likely to churn
  • Top opportunities for cross-selling and upselling per account


Together, the pricing simulation and recommendation engine gave sales the tools to execute the GTM strategy. The data-driven approach boosted the sales team’s ability to hit their KPIs and revenue targets.

Business Impact

Evalueserve’s GTM strategic guidance paid off, resulting in a 100% increase in sales cycle speed and a 70-80% increase in sales productivity (as measured by proposals per month). With our cross-sell and upsell recommendations, Evalueserve projected an incremental total addressable market (TAM) of $1 billion, which the sales team expects to meet.


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