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Phase I: Develop Your Predictive Model

We believe data science is the most reliable way to predict revenue results.


Historically the data fueling analysis came from two primary sources, digital engagement and system captured human feedback. While these sources are still critically important, an untapped source has yet to be utilized at scale - human to human call interactions.

Yes, there are many tools boasting the capability to record and even summarize a call, but the value of the interaction has never been quantified at scale. With AI and machine learning tools reaching maturity, we now have an opportunity to evaluate and grade the phone interactions of sales teams bringing a new source data into predictive analytics.

Uncover why your sales conversations are winning and losing revenue.
Identify the business circumstances needed to develop a predictive model
Create a predictive model to grade your sales calls and prioritize opportunities

Opportunity Autopsy

Breaking new ground can be exciting and incredibly rewarding however, a new approach is not without risk. To mitigate this risk, we start with a focused proof of concept analysis. By gathering your sales call recordings and CRM data, we evaluate positive and negative outcomes to create the first version of a custom linguistics dictionary. This custom dictionary serves as the basis for your custom predictive model.

This analysis includes:

  • Creating quantitative signals from calls, text, and video including but not limited to sentiment, emotion, buyer committee dynamics, and specific topic & use case modeling
  • Contextualizing these signals through models of psychology, business, economics, and game theory.
  • Identifying verbal and visual styles and topics that are associated with wins and losses
  • Discovery Assessment

    To further ensure the partnership with Structure Digital creates accurate and impactful results for your organization, we execute a discovery assessment in parallel with the opportunity autopsy. The assessment evaluates key areas of your business across strategy, process, and technology to ensure we have the necessary context to develop a truly predictive model.

    Potential Areas of assessment include:

  • Market Research
  • Audience Research
  • Go-to-Market Approach
  • Messaging & Positioning
  • Journey Orchestration
  • Organizational Structure
  • Revenue Process
  • Data & Analytics Strategy
  • Data Architecture
  • Data Orchestration
  • System Implementation
  • Application & Research Recommendations​

    This exercise reveals the value of further research on the accuracy of the predictive model. Leveraging these key pieces of information, we will create a prioritized roadmap of the highest impact research to support the evolution of the predictive model.

    Recommendations Include:

    • Extended quantitative and qualitative research roadmap to improve predictive accuracy.
    • Testing opportunities including new sales approaches, talk tracks targeted at specific loss pathways, and messaging and positioning opportunities.

    Our buyer is highly technical so our sales cycles are longer than average. Having a rating for trust, value, and pain is super valuable as we’re investing a ton of time into pipeline. We can see a dashboard of where we’re making progress and where we’re wasting time.

    Want to work with us?

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