Technology in call center automation – Today the mass adoption of smartphone, social media and mobile applications has dramatically changed clients expectations.

Long waiting times, rude service and customer un-satisfaction are not tolerated.

At the same time, cloud services and machine learning are facilitating artificial intelligence adoption inside call centers with the scope to optimize user experience, that is a priority in call centers’ executives’ strategy and is placed even before costs reduction.

Using chatbots for call center automation, does not only mean adopting an additional tool to communicate with customers, but also having data and analytics workflows to improve customer service, even conducting sentiment analysis using chatbots’ conversational workflows.

technology in call center automation: from switchboard to artificial intelligence

Technology in call center automation – The switchboard originally patented in 1891 by Almon Brown Strowger (and acquired by Bell in 1916), may be considered a primitive form of an artificial intelligence system implemented to automatically switch calls allowing people to contact each other with no need of switchboard operators.

The system ACD (Automatic call distributor), introduced in 1950 and used from major telecomm companies, has been the technology that mede it possible to filter and route calls to the right agent at the right time.

In 1970 Welsh Company British Gas inplemented an ACD system able to handle 20.000 calls per week, with multi-lingual function (Welsh and English).

Through 1970 and 1980, importance of call centers in business strategies, grew as well as associated technologies, such as:

  • Touch-tone dialing: touch-tone dialing phones were introduced in 1963 by Bell System, thanks to multi-frequency dual.tone technology. The first touch tone dialing phone was released in 1964, but this technology didn’t really saturate the market until the 1980s.
  • Toll-free numbers: in 1967, Roy Weber, scientist of AT&T, introduced the toll-free number 1-800, with the intent to simplify the routing system. In 1984 calls volume towards toll-free number of AT&T company reached 3 billions per year.
  • Interactive Voice Response (IVR): this technology was used for the first time in 1970 by bank tellers and it is currently still in use.  Initially, IVR systems were expensive and time-consuming to create, while in 1980s, personal computing made the development of more functional, more cost-effective IVR systems.
  • Predictive dialers have been introduced in 1980s. This technology pick ups numbers from a data base and connects operators to those that produce a positive answer, using statistical algorithms to minimize the time that agents spend waiting between conversations, while minimizing the occurrence of someone answering when no agent is available.
  • Short message systems (SMS): SMS have been introduced in 1992 and they changed the customer service model from reactive to proactive.
  • Speech Analytics: introduced in 2000 this technology goes beyond vocal recognition, interpreting not just the words a caller speaks but also the manner in which those words are spoken. 
  • Chatbots. First commercial bots were developed in the mid 1990s, and arose with the need of a 24/7 available customer service to preside web sites services as long as the Internet economy started growing. Today customer care chatbots are employed in customer’s requests and Q&A management, services booking, purchasing process assistance, pre-sales and lead generation activities.
    Chatbots in call center automation strategies allow to reduce workloads of recurring requests, shorten waiting times with a service always available, able to interact with and support in parallel live operators.

Smart call center thanks to artificial intelligence

Technology in call center automation – Artificial intelligence employment inside call centers is solicited by the high volume of calls and the need to reduce waiting times and chatbots represent the ideal solution.

ACD systems are base don rules and conditions, they are an intelligentsystem but not smart enough to be defined as “AI”.

Thanks to predictive analysis and machine learning we can today talk about call center automation. Customer care chatbots provide insights that can be used to anticipate results, take “data-based” decisions and provide a better customer service.

A market study from Callminer reports the following trends in call center industry:

  1. digital transformation is the emerging trend: 85% of companies is increasing the use of digital channels by 2025

2. Customer care startegy aim to automation systems to increase customer satisfaction

3. Artificial intelligence is the key ingredient in the call centers’ future market strategy.

Final say, customer experience is a competitive advantage and artificial intelligence is the critical factor to maximize it. This does not mean to minimize the importance of human relationship, but it means instead to improve the quality of operators’ service, thanks to recurring requests and ripetitive tasks automatization.

Source:

https://callminer.com/blog/comprehensive-history-ai-call-center-acds-predictive-analytics-beyond/

https://learning.callminer.com/c/whitepaper-future-contact-center-forecast?x=CFl8z6&lx=amFxJO&topic=Artificial%20Intelligence

https://www.forbes.com/sites/insights-ibmai/2020/06/26/chart-your-organizations-progress-with-ai/?sh=7a4fb92861cd

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