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Sales Webinar | So You Think You Have a $500,000 Sales Forecast
 

Sales Webinar | So You Think You Have a $500,000 Sales Forecast

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Will Wiegler, CMO The TAS Group, discusses how to use automated intelligence in the sales cycle to increase deal win rate and average deal value, and shorten sales cycles.

Will Wiegler, CMO The TAS Group, discusses how to use automated intelligence in the sales cycle to increase deal win rate and average deal value, and shorten sales cycles.

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  • How do we know what success looks like?Think about Sales Velocity as dollars per day. How much revenue can you generate each day? Day after day.
  • Fear (and business turmoil) is risk management without analyticsSurprises are bad (particularly in sales forecasts)Intuition – while valuable – is inadequateAccurate data is ‘king’Predictive analytics is a powerful lever
  • Sales Cycles are getting shorter
  • Typical Sales Process / Buying Process
  • Typical Sales Process / Buying Process
  • Information is garnered from a network more than ever before – reference selling as we know it is broken
  • Typical Sales Process / Buying Process
  • To take control of the sales process you need to have incorporated best practice steps to manage the deal through the funnelSystems can help by learning about the normal behavior to calculate the close date and closure probabilityAnd it has to be configurable to map to the multiple buying process your buyers go through
  • To take control of the sales process you need to have incorporated best practice steps to manage the deal through the funnelSystems can help by learning about the normal behavior to calculate the close date and closure probabilityAnd it has to be configurable to map to the multiple buying process your buyers go throughThis helps with win rate – because you know what to do,And when you get control of the process, you don’t end up negotiating purely on price.
  • To take control of the sales process you need to have incorporated best practice steps to manage the deal through the funnelSystems can help by learning about the normal behavior to calculate the close date and closure probabilityAnd it has to be configurable to map to the multiple buying process your buyers go through
  • Dealmaker will help you by selecting deals that will closeAnd highlight large deals to manage risk
  • Dealmaker will help you by selecting deals that will closeAnd highlight large deals to manage risk
  • Even if the number of deals remained the same … 325 deals x 28% win rate = 91 won deals91 x avg = $3888840$3888840/126 days = 30864 = SVEAverage x win rate / days = 42270 x 28 /126 = DVF – the value of deals/day for one deal – just add deals
  • Even if the number of deals remained the same … 325 deals x 28% win rate = 91 won deals91 x avg = $3888840$3888840/126 days = 30864 = SVEAverage x win rate / days = 42270 x 28 /126 = DVF – the value of deals/day for one deal – just add deals
  • Even if the number of deals remained the same … 325 deals x 28% win rate = 91 won deals91 x avg = $3888840$3888840/126 days = 30864 = SVEAverage x win rate / days = 42270 x 28 /126 = DVF – the value of deals/day for one deal – just add deals
  • Even if the number of deals remained the same … 325 deals x 28% win rate = 91 won deals91 x avg = $3888840$3888840/126 days = 30864 = SVEAverage x win rate / days = 42270 x 28 /126 = DVF – the value of deals/day for one deal – just add deals
  • Dealmaker will help you by selecting deals that will closeAnd highlight large deals to manage risk