Speech Analytics Statistics 2024 – Everything You Need to Know

Are you looking to add Speech Analytics to your arsenal of tools? Maybe for your business or personal use only, whatever it is – it’s always a good idea to know more about the most important Speech Analytics statistics of 2024.

My team and I scanned the entire web and collected all the most useful Speech Analytics stats on this page. You don’t need to check any other resource on the web for any Speech Analytics statistics. All are here only 🙂

How much of an impact will Speech Analytics have on your day-to-day? or the day-to-day of your business? Should you invest in Speech Analytics? We will answer all your Speech Analytics related questions here.

Please read the page carefully and don’t miss any word. 🙂

Best Speech Analytics Statistics

☰ Use “CTRL+F” to quickly find statistics. There are total 78 Speech Analytics Statistics on this page 🙂

Speech Analytics Market Statistics

  • Speech analytics is estimated to be a $214 million market today. [0]
  • The speech analytics market is projected to grow by 20% in 2014 . [0]
  • According to reports, the market accounted for a value of $22.16 billion in 2020 and is expected to reach a value of around $42.95 billion in 2028, with speech and AI analytics as some of the main elements driving company growth. [1]
  • The speech analytics market was valued at USD 1649.34 million in 2020 and is expected to reach USD 5460.66 million by 2026 and grow at a CAGR of 22.14% over the forecast period. [2]
  • The large enterprises segment is estimated to hold a larger market share in 2021. [3]
  • The market is expected to grow at a compound annual growth rate of more than 20% during the forecast period from 2021. [4]
  • The field is one of the fastest growing segments in the call center management technology market as of 2018, according to market research firms. [5]

Speech Analytics Latest Statistics

  • 90% of all customer conversations are still happening on the phone despite changes in the digital world. [0]
  • Just 15% of call center agents report they’re able to easily track customers across multiple channels. [0]
  • 65% of businesses today use at least six channels to engage their customers. [0]
  • Nearly all (94%). [0]
  • Speaker separated audio in the cloud can lead to 45% more accuracy on speech recognition than using traditional call recording technologies. [0]
  • Nearly a quarter of organizations (24%) use speech analytics solutions . [0]
  • Between the years 2021 and 2026, the environment is expected to grow at a CAGR of around 22.14%. [1]
  • Organizations leveraging call analytics tools, from speech analytics systems to sentiment analysis tools, can reduce average handling time by around 40%. [1]
  • Analytics solutions can also improve selfservice containment rates by up to 20%. McKinsey & Company. [1]
  • 75% of customers say they expect companies to anticipate their needs and make relevant suggestions. [1]
  • – Zion Market Research 40% of companies say they rely on artificial intelligence to help with their CX strategy, and 71% find AI useful in personalizing the customer experience. [1]
  • Unfortunately, only around 37% of organisations feel they’re using analytics correctly to create value for their customers. [1]
  • According to experts, 90% of the world’s data has been created in the last two years, and we’re producing around 2.5 quintillion bytes per day. [1]
  • 82% of customers say agents must have access to the right resources to resolve their issues. [1]
  • 79% also say they want to be immediately routed to the agent most knowledgeable about their specific issue – this is something speech analytics solutions could help with. [1]
  • Asia Pacific Largest Market North America CAGR 22.14 % Market Overview. [2]
  • , an estimated 90 % of the workforce still worked in a traditional contact center environments, according to CallMiner. [2]
  • Also, according to CallMiner, call volumes in contact centers have dropped by about 25 % during COVID 19, which reflects the overall slowdown in the economy as a result of the coronavirus pandemic. [2]
  • Moreover, the total number of voice assistant devices is expected to reach 870 million in the U.S. by 2024, which is a 95% increase from a total of 450 million estimated in 2017. [2]
  • The Speech Analytics Market is growing at a CAGR of 22.14% over the next 5 years. [2]
  • 80% of fortune 2000 companies rely on our research to identify new revenue sources. [3]
  • About MarketsandMarketsâ„¢ MarketsandMarketsâ„¢ provides quantified B2B research on 30,000 high growth niche opportunities/threats which will impact 70% to 80% of worldwide companies’ revenues. [3]
  • Currently servicing 7500 customers worldwide including 80% of global Fortune 1000 companies as clients. [3]
  • Gathering and Analyzing Data for Product or Service Insights Call center voice analytics allow businesses to turn unstructured voice data into tagged, structured data across 100% customer interactions. [6]
  • One in four call centers in the U.S. have an employee turnover rate of 30% or more. [7]
  • One survey found that 94% of employees would stay at their current employer if they invested in their long term learning. [7]
  • According to an Oracle study, 9 out of 10 customers change their preferences because of a poor experience. [4]
  • The above plot shows the silence regions highlighted in red by using a threshold of 0.01% of the average short term energy of the speech signal. [8]
  • First, they follow random, manual call sampling methods, which capture less than 2 percent of all interactions, producing incomplete raw data sets. [9]
  • The results include cost savings of between 20 and 30 percent, customersatisfaction score improvements of 10 percent or more, and stronger sales as well. [9]
  • At another company, customers complained about needlessly long handle times more than 60 percent of calls included more than 20 seconds of continuous silence. [9]
  • A third firm’s average handle time was consistently 10 percent above target. [9]
  • These moves can accelerate traditional diagnostics time by nearly 400 percent, helping organizations implement recommendations much faster. [9]
  • One internal help desk provider defined ten use cases that helped it unlock 20 to 30 percent cost savings and a customer service improvement of more than 10 percent. [9]
  • The speech reception threshold is typically defined as the signalto noise ratio at which a subject scores 50% correct on a speech intelligibility test. [10]
  • An alternative is to measure the speech reception threshold of each subject, which is typically defined as the SNR at which the subject scores 50% correct. [10]
  • At the SRT, although the average word score is 50%, it is relatively uncommon to score near 50% for any particular sentence; instead some sentences receive scores near 100%, and a roughly equal number of sentences receive scores near 0%. [10]
  • A histogram of the sentence scores for Study One , with large spikes at values 0% and 100%, is shown in Fig 2. https//doi.org/10.1371/journal.pone.0132409.g002. [10]
  • Endpoints of the 95% confidence intervals are computed as the lower and upper 2.5% percentiles of the fitted proportions correct, at each covariate combination. [10]
  • The noise gender factor, however, was significant, with estimated marginal group means of SRT of 2.59 dB for male interferers, and 3.99 dB for female interferers. [10]
  • The fitted overall means of percent correct for each algorithm are shown in Fig 3, separately for both noise genders, together with confidence intervals constructed by parametric bootstrap. [10]
  • For all three algorithms, the male interferer provided significantly better speech intelligibility than the female, with the difference being larger for algorithms B and C. 95% confidence intervals were calculated using 500 parametric bootstrap samples. [10]
  • https//doi.org/10.1371/journal.pone.0132409.g003 95% confidence intervals were calculated using 500 parametric bootstrap samples. [10]
  • More specifically, the estimated means of SRT were 0.171 dB,. [10]
  • Fig 6 shows the fitted overall means of percent correct, i.e. the mean psychometric functions for the six algorithms. [10]
  • A horizontal line at 50% correct intercepts each psychometric function at an SNR equal to its SRT, illustrating the 4.6 dB SRT improvement of SpZ+3 over Beam, as found in the traditional approach. [10]
  • 95% confidence intervals were calculated using 500 parametric bootstrap samples. [10]
  • One limitation of a retrospective analysis of the data is that the adaptive rule used in these studies started with a high SNR, then adjusted the SNR towards the 50% correct point. [10]
  • This concentrates the observations near the 50% correct point, which is the most efficient placement for estimating the SRT [6] but yields relatively few observations at lower SNRs. [10]
  • One solution is to randomly interleave multiple adaptive tracks, each targeting different percent correct scores, e.g. 30% and 70% correct [6] [7]. [10]
  • Instead, the proposed approach allows the result to be better understood in a noisy situation, average scores improved from 25% correct with Beam to 62% with the best spatial noise reduction algorithm. [10]
  • – Workforce Manager, Healthcare New York Life reduced call volume by 400,000 calls a year, realized savings of 40% across quality assurance . [11]
  • The solution transcribes 100% of recorded calls to automatically discover and analyze words, phrases, categories, and themes. [11]
  • With Verint, you can accurately process voice with complete speaker separated transcription for 100% of customer interactions. [11]
  • This solution can search, transcribe, and analyze 100 percent of calls and surface those containing suspicious words or phrases. [11]
  • By leveraging speech recognition, Verint Speech Transcription provides accurate transcriptions of 100% of contact center calls. [11]
  • Given the ease of using voice relative to other forms of search , close to half of all consumer searches online is predicted to be originating from voice based searches by the end of 2020. [12]
  • A Gartner report indicates that the percentage of enterprise generated data is created and processed outside a traditional centralized data center or cloud will increase from 10% to 75% by 2024. [12]
  • Most call centers fail to improve their productivity because they hardly screen through 5 10% of the total calls made/received by them. [13]
  • With almost 90 95% of their data slipping through the cracks, such organizations find it challenging to detect customer issues and pain areas. [13]
  • Having such conversation intelligence tools will help you monitor and report 100% of the conversations within your contact center and help derive critical insights that would be almost impossible to gain otherwise. [13]
  • Industry experts have long estimated that 25 cents of every dollar spent by a call center goes toward fixing issues that weren’t properly addressed during the customer’s initial call. [14]
  • A recent study by the Yankee Group revealed that 66 percent of all contact center costs can be attributed to callbacks. [14]
  • The statistics are stunning a 1 percent gain in first call resolution translates into a 1 percent gain in customer satisfaction. [14]
  • Many companies that incorporated speech analytics as part of their FCR strategies have reported improvements of 8 to 10 percent simply by correcting how their agents respond. [14]
  • Prior to deployment, one organization’s customer callback rate was nearly 8 percent. [14]
  • Once agents knew that all their interactions were being monitored and evaluated through speech analytics, the rate dropped closer to 3 percent. [14]
  • Although no speech tool is 100 percent accurate, an automated approach will be far more accurate than any individual’s speculation or judgment. [14]
  • For example After spotting a pattern of customers calling to complain about their password not working, one organization was able to reduce call volume by 2 percent just by identifying and fixing issues with its password reset process. [14]
  • A retailer told me he was able to reduce the number of callers who wanted to speak with a receptionist by 5 percent by identifying why customers were calling, and then adding a new option in their auto attendant menu. [14]
  • Through valuable insights gained with speech analytics, one call center retrained their agents and decreased the percentage of repeat calls from 40 percent to 30 percent, with a 20 percent improvement in average handling time. [14]

I know you want to use Speech Analytics Software, thus we made this list of best Speech Analytics Software. We also wrote about how to learn Speech Analytics Software and how to install Speech Analytics Software. Recently we wrote how to uninstall Speech Analytics Software for newbie users. Don’t forgot to check latest Speech Analytics statistics of 2024.

Reference


  1. callminer – https://callminer.com/blog/13-things-didnt-know-speech-analytics.
  2. cxtoday – https://www.cxtoday.com/speech-analytics/speech-analytics-statistics-for-2024/.
  3. mordorintelligence – https://www.mordorintelligence.com/industry-reports/global-speech-analytics-market-industry.
  4. marketsandmarkets – https://www.marketsandmarkets.com/PressReleases/speech-analytics.asp.
  5. taiwannews – https://www.taiwannews.com.tw/en/news/4385008.
  6. techtarget – https://www.techtarget.com/searchcustomerexperience/definition/speech-analytics.
  7. voicebase – https://www.voicebase.com/roi-of-using-advanced-voice-analytics-in-your-call-center/.
  8. voiztrail – https://voiztrail.com/call-centers/.
  9. towardsdatascience – https://towardsdatascience.com/beginners-guide-to-speech-analysis-4690ca7a7c05.
  10. mckinsey – https://www.mckinsey.com/business-functions/operations/our-insights/from-speech-to-insights-the-value-of-the-human-voice.
  11. plos – https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132409.
  12. verint – https://www.verint.com/speech-analytics/.
  13. upenn – https://wca.wharton.upenn.edu/white-paper/voice-analytics-and-artificial-intelligence-future-directions-for-a-post-covid-world/.
  14. callhippo – https://callhippo.com/blog/coach/benefits-of-speech-analytics.
  15. maintrax – https://maintrax.com/speech-analytics-first-call-resolution/.

How Useful is Speech Analytics

One of the most significant advantages of speech analytics is its ability to provide real-time feedback on customer interactions. By analyzing the tone, language, and specific keywords used in conversations, businesses can quickly identify customer sentiment and address any issues before they escalate. This real-time feedback can help companies improve their customer service efforts, leading to higher satisfaction and loyalty rates.

Additionally, speech analytics can help organizations identify trends and patterns in customer interactions that may not be immediately apparent. By analyzing large volumes of calls, businesses can gain insights into customer preferences, common issues, and emerging trends. This information can then be used to tailor products, services, and marketing strategies to better meet the needs of customers.

Speech analytics can also be a valuable tool for sales and marketing teams. By analyzing customer interactions, businesses can identify potential leads and opportunities for upselling or cross-selling. Managers can also use speech analytics to track sales team performance, identify training needs, and ensure that their teams are providing the best possible customer experience.

Another benefit of speech analytics is its ability to monitor compliance with regulations and company policies. By analyzing customer interactions, businesses can ensure that employees are following guidelines and best practices. This can help prevent legal issues, improve customer trust, and ensure that businesses are operating ethically and within legal boundaries.

Overall, speech analytics is a powerful tool that can provide valuable insights into customer interactions and help businesses improve their operations. By analyzing customer conversations, companies can gain insights into sentiment, trends, and opportunities that can help drive growth and success.

While speech analytics can be incredibly useful, it is important for businesses to remember that it is just one tool in the toolbox. It should be used in conjunction with other data and feedback sources to provide a comprehensive view of customer interactions and experiences. Additionally, businesses should ensure that they are using speech analytics ethically and responsibly, respecting customer privacy and confidentiality at all times.

In conclusion, speech analytics is a valuable tool that can help businesses gain insights, improve customer service, and drive growth. By taking advantage of the benefits of speech analytics, companies can better understand their customers, identify opportunities for improvement, and drive success in an increasingly competitive business environment.

In Conclusion

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