Scott Belsky, co-founder of online portfolio platform Behance Inc said, “It is not about ideas, but it’s about making ideas happen.” Speech Analytics have become a mainstay industry solution since 2002 and has clocked a double digit growth trajectory. It is expected to be a $2.17 billion industry by 2022.

But it has to be noted that Speech Analytics is not a just plug-and-play solution. Organizations cannot expect immediate answers by installing analytics capabilities. The starting phase of deployment is extremely critical in fine-tuning and audit of Speech Analytics platform to create quality insights of business value. It involves creating a talent pool, process workflows, and product avenues to maximize Speech Analytics potential.

Blog 2 - Tips to Harness the Power of Speech Analytics During the Early Stage of Deployment

Tapping into Skills

Speech Analytics need skilled individuals who can effectively utilize all the opportunities. The Speech Analytics inner circle should have the business analysts and internal employees who understand the organizational goals and values. The business analyst can guide and train individuals to seamlessly integrate analytics capabilities and actionable insights into the daily business processes and programs. This inner circle should be able to achieve the short term business outcomes within the first six months of project implementation.

Technology Refinement

Tweaking the Speech Analytics engine is an important on-going activity for every business. Organizations need to create a comprehensive speech repository to analyze the real intention of the customer. This involves creating a work-in-progress audit timetable to capture all the customer phrases into relevant call categories. It requires extensive planning and understanding about the business customer.

Speech Analytics also brings to the table several features like Phonetic Indexing, Interaction Analysis, Automated Scoring, Geography Specific Accent Recognition and more. These need to be adopted with specific understanding of the business use cases to extract value. For example, interaction analytics solution can ensure 100% capture and analysis of customer interactions across a wide variety of channels, devices, and agents. This would enable businesses to totally monitor agent performances and gain a 360 degree visibility into customer needs.

Speech Analytics is a great way to ensure regulatory compliance. With the emergence of privacy laws like GDPR, key features like private data redaction gains prominence. Data redaction can identify sensitive phrases and words and replace them with generic terms thus ensuring fool proof privacy of customer information.

The above features are only few handful examples of how Speech Analytics features can be incrementally implemented based on business requirements. This requires continuous learning and refinement of business objectives and goals to perfect the Data-Insights-Action cycle.

Scalability and Integration

Organizations have multiple technology systems like IVR, CRM, Social Media monitoring tools and Web Analytics which work in isolation. Most of these systems do not speak to each other, thus reducing agent capability to gain an in-depth understanding about customer intentions. It is important to focus on integrating Speech Analytics with agent desktop tools and CRM software to maximize returns from Speech Analytics investments. This would bring in the question of scalability of the speech engine across diverse channels, devices, and platforms. It is imperative that business analysts and the subject matter experts sit together and fine-tune the speech engine scalability to meet organizational requirements.

Conclusion

Speech Analytics implementation can deliver definitive tactical and strategic advantages to businesses.  The proposed business outcomes can be discerned within the first six months of implementation through proper KPI setting and feature implementations. Experts have accepted that an ROI of 5X over the six month period is an indicator of a successful project implementation. Thus, the best use of Speech Analytics during the first quarter of implementation a critical goal outcome.

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