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