“What prompts someone to make a purchase?”
It’s the ultimate sales and marketing question.
All our tools, plugins, integrations, analysis, and predictions, all concentrated in a multi-billion-dollar effort to answer this question. Every datasheet, every PowerPoint presentation, every metric – every effort marketers and sales professionals make serves to inch prospects closer to a tipping point.
We put the question to 207 sales and marketing professionals in a director position or above, and published our findings in a resulting study of 80+ individual data points and datapoint combinations. Get the full study here.
95% of all respondents find positive revenue gains when predictive indicators are present – and the most common benefit is higher conversion rates.
Over half of companies surveyed use data to formally score leads and accounts to assess fit, propensity to buy, or readiness to buy. Just 13% of respondents did not.
Overall, it’s clear that predictive data matters.
So 95% have been able to link growth to predictive indicators. The positive result with the highest correlation is most often higher conversion rates of prospect to qualified lead. Interestingly, though, no other positive result (e.g. shorter sales cycles, more wins, higher sales price, more demos) showed up in a majority of responses.
This points to a couple of critical key findings for sales teams.
- Many companies aren’t able to accurately track the impact of these predictive indicators all the way through the funnel – and technology is less than optimally effective at delivering these insights.
- Predictive indicators will get you a foot in the door – perhaps even allowing you to get there first – but they don’t do the selling for you. Just because a buyer looks like your best customer and is ready to buy a solution like yours doesn’t mean that they will ultimately choose you as their vendor – you still have to put your best foot forward every time.
Fit + Opportunity + Intent = Predictive indicators
As Peter Herbert, VP of Marketing at Terminus, describes so well in Adventures in Account-Based Marketing, “Fit refers to accounts that fit the Ideal Customer Profile (ICP) of who your company is trying to market and sell to.
“Think of ICP as the firmographic, technographic, geographic, etc. filters you apply to your data to narrow your accounts to your target market, plus an incredibly powerful machine that considers thousands of variables to see if those accounts are similar to your healthy customers, open opportunities, or whatever you decide is best for your business to build your model from.”
So, which data points predict a purchase? Grab a full copy of our study to find out.
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