Why transform?

Market challenges

Unpredictable and changing market conditions make forecasting demand increasingly challenging

  • Post pandemic job migrations (aka the “Great Reshuffle”) and rise of remote/hybrid work

  • Technical disruption: Cloud computing, Quantum computing, Crypto, AI/ChatGPT

  • Recession, inflation, interest rates hikes, and rising oil prices have slowed spending

  • Banking crisis exacerbates the climate of uncertainty, layoffs, and budget cuts

Operational challenges

Traditional sales process is unable to meet market challenges

  • Average tenures are getting shorter making long ramp times more costly

  • Forecasting and other insights rely on sales history and poor quality CRM data

  • Buying patterns more complex (eg, larger buying teams) and with higher expectations

  • Volume based selling less and less effective (eg, declining win rates, lower ACV, etc.) 

  • Poor collaboration leads to missed revenue and 17% buyer satisfaction in won opps

Productivity challenge

Sellers operate at ~30% productivity rates

  • No time to train: 82% of buyers think sellers are unprepared

  • Time spent on non-revenue producing tasks such as CRM data input and forecasting

  • Time spent on internal meetings to uncover risks and surprises

  • 3x pipeline coverage leads to missed opportunities

  • Declining sales effectiveness combined with budget freezes requires more efficiency