With a view to what can happen in the coming months, or to an unforeseen event that does not have to be a pandemic, it is clear that the company that does not jump and take its commercial communications to a system based on the Internet and Cloud technologies, it is probable that it will not withstand another similar crisis. And, conversely, those that are prepared can take advantage of the opportunities that arise at the most critical moments. The client wants you to call him, and it is better to do it quickly Other interesting data presented in the Convertia report indicate that, especially, consumers of services in sectors such as telecommunications, public services or finance are the most impatient, at the same time that they are the ones most affected by the uncertainty of the situation.
For this reason, they demand greater agility to satisfy their needs and the probability of contacting one of them decreases by 90% if they do not do so within 10 minutes from the moment mobile number list they requested it. Therefore, a control of these leads through a solvent CRM connected to a virtual switchboard , are revealed as essential tools today. The company that does not prepare will not resist another crisis In summary, those who had been farsighted and had a communication system that inside and outside the office.
Without this being a problem for maintaining sales or customer service activity, not only have they not been affected in this 2020 coronavirus crisis, they have gained even more. And the truth is that the cost is minimal and the time required, just a few minutes to set up an IP telephony system that allows us to have a virtual switchboard, extensions and combine it with a CRM, both through an API and our own. .Speech recognition. What is it for and how does it work? 2.09.2020 speech recognition The new voice recognition function is available within the free virtual switchboard. Now you can convert all conversations in text format for the purpose of further analysis. What is voice recognition? With the help of neural networks and sound models that take into account the structure of different languages, recorded speech is converted (ie transcribed) into text. This technology has been studied for decades, however in recent years much progress has been made in the field by connecting neural networks.