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Why Contact Centers Of The Future Need Machine Learning

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Why Contact Centers Of The Future Need Machine Learning


The involvement of machine learning in CRM makes customer grievance handling more streamlined and, above everything else, quicker.

Businesses must leverage the technology to make the experience of dealing with contact centers less tedious for already aggrieved customers.

The success of contact centers is measured on the basis of, more or less, two key performance indicators — the average call handling time (AHT) and customer satisfaction ratings. This means that each call made by a customer not only has to be completed quickly but also with the caller’s grievance resolved for good (preferably with no need for callbacks or escalation). That is a tall task during the best of times but becomes especially hard to accomplish during a difficult phase such as a pandemic. Machine learning and cognitive automation can be useful to resolve such problems and make contact centers faster and more effective in terms of customer grievance handling and query resolution. The implementation of AI in CRM can positively transform contact centers of the future. Here’s how:

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Reduction of Call Handling Time

If there’s one thing customers hate doing when they call a contact center, it is waiting on the line for an extended period. Long waiting times are incredibly frustrating for callers, and several customers may feel that organizations are simply disrespecting their valuable time for the sake of it. To return the favor, customers may cease using the products or services of an organization just because they’ve had to wait a long time before getting to hear a customer service executive’s voice.  According to a study, long waiting times are the reason why Americans consistently incur collective losses of about US$100 billion annually. From a business perspective, that translates into productivity losses of about US$900 per employee for organizations. 

The deployment of voice chatbots and text chatbots helps businesses resolve this problem to a great extent. For example, voice chatbots can immediately engage with customers, cutting the waiting time of a given call right from the onset. Voice chatbots use NLP to “understand” customer problems. In contact centers of the future, such applications will also be able to resolve calls involving simple customer grievances or demands—such as adding a hold bag or correcting a duplication error in one of the travelers’ names in a booked flight reservation. For complex queries, grievances or requirements, the system can simply redirect calls to appropriate Subject Matter Experts (SME) for resolution with minimal delay. This represents a massive upgrade over the same situation playing out in an AI-less environment wherein callers will end up wasting several hours trying to explain their situation to a customer service agent before even getting to speak to an SME.

Improvement of Customer Experience

Several organizations have their contact centers located in offshore regions. Customer service agents in those countries may find it challenging to understand international customers’ accents and other linguistic intricacies during a conversation, making it impossible to have a call completed and query resolved quickly. NLP enables voice chatbots to comprehend what a customer is saying, regardless of their language or accent.

Customers generally find it highly irritating when they’re made to repeat themselves over and over again during a call. The involvement of AI in CRM enables callers to have their queries understood and resolved in double-quick time, thereby raising the overall customer satisfaction index.

It is safe to say that contact centers of the future can add several layers of effectiveness and speed by including AI in CRM-related communication.



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TECHNOLOGY

SaaS pricing inflation growing 4x faster than market inflation

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Cloud Computing News


Inflation has dominated the financial news landscape in 2022. In many markets, the consumer price index (CPI), has reached its highest point in a generation. This growth in the cost of ‘things’ also applies to software.

Almost every organisation has come to rely on SaaS to conduct business, from communications tools like Slack and Zoom to productivity suites like Microsoft 365 and Google Workspace, as well as department-specific platforms like Atlassian, Workday, NetSuite or Salesforce.

This is according to a report into SaaS inflation pricing from Vertice, a SaaS purchasing and spend management platform.

Spending on SaaS products grew more than tenfold between 2010 and 2020, from $13b to $157b annually. Investment accelerated even faster at the onset of the coronavirus pandemic, as companies raced to support remote working. SaaS spending increased by 26% in the months following the initial lockdown in 2020 and has only continued to grow in the years since.

Unlike many other significant overheads, like payroll and rent, the selection, management and renewal of SaaS are decentralised in nearly every organisation. This is for a variety of reasons, but buying power plays the most important role. Buying power typically sits across several individuals and departments, with finance leaders managing budget requirements, IT teams assessing systems and compliance considerations, and department heads selecting based on functionality. It’s a complex web of decision making and, even with the best intentions, it can be a struggle to gain a single view of all of the SaaS products a company uses.

This ‘wild west’ of a cost centre is a significant problem when the share of the total cost is considered. A growing percentage of all expenditures for businesses goes to SaaS, with around 12.7% of total spending now used on software investments. That means $1 in every $8 that modern organisations spend is now dedicated to SaaS. To translate that into dollars — as of 2022, companies spend around $3,112 per employee each year on SaaS. This figure rises to $4,552 for technology companies, who spend more than firms in any other category.

It has taken only five years for average SaaS spending to double. Based on the economic inflation rate over the same period, it would take 18 years for the cost of SaaS to double. This growth has far outpaced the rate of general economic inflation, even after factoring in recent periods of an uncharacteristically high CPI.

Clearly, the impact of SaaS in terms of productivity, collaboration and inclusion has been significant – but the accompanying cost has also been quietly spiralling upwards.

Analysis of more than 10,000 SaaS contracts shows that 74% of vendors have increased their list pricing since 2019. Among the quarter of vendors that have not, almost all have reduced the size of the average discount afforded to customers – effectively raising the spend without touching the list price.

A comparison of regional inflation rates with the SaaS inflation rate by geography reveals that over the past five years the cost of SaaS for US organisations has grown 3.5x faster than the general inflation rate – even after accounting for an exceptionally high national inflation rate in 2022.

SaaS inflation has outstripped general inflation rates even more rapidly elsewhere; spending at British and Australian firms has risen at a rate five times greater than regional economic inflation.

Joel Windels, VP of marketing at Vertice, said: “It’s become clear that not only is SaaS critical to modern businesses, but also that it represents a growing cost centre that can rapidly spiral out of control without strategic management. Even without investing in new tools or added licences, the data shows that spending on SaaS is exploding. With an uncertain economic outlook for 2023, finance leaders absolutely have to start taking a more considered approach to SaaS spending if they are to maintain growth and streamline their operations” 

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