The average sales rep spends 24 percent of his time preparing for sales calls. Rather than feeling empowered by all this data, the rep is overwhelmed. Reps are struggling to find the information they need to close deals. CSO Insights found that 82 percent of sales reps are challenged by the amount of information available and the amount of time it takes to look through it all. The study found that reps were searching as many as 15 different data sources in the course of their research. The data deluge is real. The key to sales productivity is not delivering more data to sales reps. It is providing the insights that allow them to focus on their best opportunities.
The way most sales organizations operate is obsolete. And the results prove it:
-Ninety-four percent of all "marketing qualified leads" will never close.
-The average sales rep spends 68 percent of his time on administration, research, and preparation, not talking to customers.
-Fifty-two percent of sales reps in the U.S. do not achieve their sales quota.
In most social, information, and collaboration systems the complex activity of agents generates rapidly evolving time-varying networks. Temporal changes in the network structure and the dynamical processes occurring on its fabric are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset describing the activity of millions of individuals and investigate the temporal evolution of their egocentric networks. We empirically observe a simple statistical law characterizing the memory of agents that quantitatively signals how much interactions are more likely to happen again on already established connections. We encode the observed dynamics in a reinforcement process defining a generative computational network model with time-varying connectivity patterns. This activity-driven network model spontaneously generates the basic dynamic process for the differentiation between strong and weak ties. The model is used to study the effect of time-varying heterogeneous interactions on the spreading of information on social networks. We observe that the presence of strong ties may severely inhibit the large scale spreading of information by confining the process among agents with recurrent communication patterns. Our results provide the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks.
The emergence and role of strong ties in time-varying communication networks
Márton Karsai, Nicola Perra, Alessandro Vespignani
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