Organizations need to take every advantage that their data mesh affords. A truly underutilized data source is digitized speech turned into actions based on reusable and leveraged voice data. Savvy organizations are learning to rely on machine learning (ML) combined with natural language processing (NLP) to quickly and accurately take advantage of voice transcriptions for organizational leverage and business advantage. What are the major benefit streams for organizations to tap? What are some essential functions to look for in a voice-based vendor?
It is
essential to understand what your customer is saying and keep their goals in
mind while serving them within your organization’s interactions and goals.
Striking a balance requires your organization to quantify your customers'
sentiment to understand and respond to the customer's authentic voice. This
balance means that you need help to analyze that sentiment in real-time and
predict the sensed sentiment's likely outcomes. Once the possible outcome is
determined, organizations can coach customer service representatives to take
actions on behalf of the customer and meet their organizational goals. While
this helps any interaction, organizations can gather data for reputation and
competitive analysis in the background.
Lower Compliance
Risk
It is
imperative to improve an organization's compliance by automatically scrubbing
sensitive data such as credit cards to protect your customers' data.
Organizations often employ automatic detection and redaction of credit card
numbers and other sensitive information. Automated redaction of call center
recordings and transcripts scrubs payment information, social security numbers,
and other sensitive data so others can’t use it for illegal or immoral
activities. The minimum here is to enable payment protection.
Optimize
Sales Activities
It is often
hard to teach your people to sell, upsell or cross-sell for increased revenue. Sales
will be helped significantly by discovering via voice discovery, analysis, and
optimization. The best techniques can be replicated across your organization’s
teams to increase conversions. Machine learning algorithms can be fine-tuned to
measure emotion, keywords, and sales signals. Teams can optimize techniques,
spot weaknesses, and bring in more revenue. Using voice, organizations can
identify approaches that overcome sales objections and use that knowledge to
arm others. Also, failed sales attempts can be analyzed for keywords and topics
to improve the entire sales process.
Essential
Voice Data Functions
What
critical functions help provide fast and accurate voice transcriptions to
sense, decide, and take actions upon voice data?
Transcription allows you to read, search, edit and click-to-play all of
your transcripts. Good transcription usually provides transcripts in TXT, Word,
RTP, or SRT format.
Stereo Speaker ID locates each voice in stereo recorded content to enable
speaker ID, while improving accuracy and filtering keywords by a speaker.
Custom Vocabulary allows you to add unique words such as pronouns,
company names, product names, or acronyms specific to your industry to improve
accuracy.
Number Formatting transcribes numbers to digits giving you the option to
properly format currency, addresses, and phone numbers formatted for
click-to-call.
Video
Captioning generates
subtitles or closed captions for your video project and retrieves your audio or
video file transcript.
Voicemail Transcription automatically transcribes voicemails with a number
formatting and callback capabilities, delivered to you via email or
SMS.
Net;
Net:
While
it might seem mundane, digitizing voice data is essential for downstream
advantage. There are significant benefits in gathering, aggregating, analyzing,
and leveraging appropriate actions from voice data. There are obvious benefits
in customer service, sales management, and compliance. Voice data is an equal
tributary in the growing data mesh that organizations are dealing with for now
and the future. We are only at the beginning of leveraging voice data, so
expect a big push in brand monitoring next.
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