Monday, November 23, 2020

Real-Time Use Cases Enabled by the Database of Now

While we all know that real-time applications and analytics are constrained to respond in the order of microseconds, real-time systems have been difficult to justify and attain until recently. There is a whole new class of real-time analytics that are now open to more organizations and applications with the advent of “The Database of Now." This blog investigates some of the new and emerging uses and is meant to give the reader some real-world examples. Hopefully, this list of successful uses will inspire others to follow suit, mainly where real-time dashboards and analytics deliver significant benefits.

Real-Time was for Special Applications

Real-time computing started with operating systems and then only a handful of applications because of specialized software costs. The first implementations revolved around real-time networks and market-driven applications where results demanded no significant delays or instant results. Real-time was an excellent fit for physical systems that need instant responses like fly-by-wire or ABS brakes or single purpose-focused applications. These use cases required extreme correctness, deep concurrency, and durable stability while being distributed and sometimes autonomous. Real-time was a limited set of applications and systems until recently.

What Has Changed?

Business drivers require more speed. It used to be good enough for businesses to have dashboards that were relatively up to date. Now that kind of speed is not acceptable even if applications aren't hooked up to devices on the internet's edge (IoT).  Almost all the leaders of business-focused software organizations believe that speed is the new currency of business. We are in an era of extreme competition and dynamic adaptability. Those organizations that can handle emerging trends by sensing them, making rapid decisions, and implementing fast are the ones that will emerge as the winners as long as they consider the voice of the customer and other constituents. Savvy organizations will switch from reactive to proactive by planning alternatives, practicing them, and put in listening posts for an emergent change.


Technology enablers have been emerging to meet the need at a lower cost and broader use cases. It started with complex events processing's ability to sense signals, events, and patterns of interest and even respond in limited situations. And now, fast forward to today, and we see the accelerating trend of adapting to real-time applications with the mainstream use of streaming data. Ventana research states that more than 50% of enterprises will leverage real-time streaming data in their enterprise next year. It reaches full bloom now with databases that can handle various kinds of complex monster data in the cloud-managed as a single logical store rather than multiple special-purpose datastores, greatly simplifying and accelerating data delivery. Organizations simplify the complexity that revolves around data location, meaning, and transformation connected to the smart IoT, often embedded in Industry 4.0 solutions facilitated thus increased speed. 

Sample List of Successful New Real-Time Use Cases

They are listed in no particular order with common uses highlighted in bold text. All industries will have emergent situations that will cry out for real-time assists.

  • FinTech
    • Portfolio Management & Analytics
    • Fraud Detection
    • Algorithmic Trading, Crypto Exchange
    • Dashboards & APIs
  • Software & SaaS
    • Improved CX for Internet Services
    • Supply Chain Visibility  
    • Machine Learning Pipelines & Platforms
    • Dashboards & APIs
  • Media & Communications
    • Ad Optimization & Ad Serving
    • Streaming Media Quality Analytics
    • Video Game Telemetry Processing
    • Network Telemetry & Analytics
  • Energy 
    • IoT & Smart Meter Analytics
    • Predictive Maintenance
    • Geospatial Tracking & Calculations
    • Dashboards & APIs


Net; Net:

While there are many more industry examples not listed here, the evidence is clear that it is time to rethink real-time utilization. The Database of Now has lowered the hurdles keeping organizations from leveraging real-time implementations. This is especially true of dashboards, analytics, and other transparency rich situations. If you need to know about the status of work or outcomes on the spot and right now, you should be considering the real-time use cases that the Database of Now enables. Real-time is for everybody now, so start planning and preparing for new competitive implementations.


Additional Reading:

Corporate Performance in Real-Time

Database of Now

Monster Data

Ventana Source



Thursday, November 19, 2020

Customers; Let Your Voice Be Heard

We all know that customers are the lifeblood of organizations, so organizations should treat their relationship with the customer as extremely important. Applying intelligence to voice data, either through analytics or artificial intelligence (AI), is particularly useful to both the customer and the organization. Organizations can identify patterns to improve the relationship, and customers will, in turn, get a better experience. Typically organizations use crucial voice interactions to extract vital information from customer interactions to measure and improve performance, but there is much more potential in leveraging voice data. The power of voice data in the customer experience goes beyond organizational excellence to relational effectiveness. 

Using Voice Data for Organizational Performance

Organizations are always looking for efficiency while optimally managing their resources. Contact centers and agents need the utmost efficiency and performance so that voice data can be searched for desired and undesired behavior. Customer service usually means measuring call handling times to deal with call volume. Sometimes call center agents are just measured on time to complete without considering if the customers' outcomes were delivered or experienced frustration in getting their needs translated into corporate transactions. Measuring customer sentiment in real-time adds a differentiating factor to the overall call handling perspective. If a customer has to call multiple times to get something done while the organization/agents hit handle time goals, they may not be impressed and leave permanently.

Indeed, voice data helps improve agent script adherence and the actual scripts themselves. Voice is also helpful in detecting when competitors' names are mentioned for further evaluation. When fine-tuning agent training programs, voice data is invaluable, enabling first call resolution and even reduce average call handling times. Some "bigger picture" efforts such as payment compliance, including redaction for terms like "credit card number" or "social security number," also benefit from voice data and analytics. You can even fine-tune your marketing campaigns by picking up on themes and slogans.

Using Voice Data for Voice of the Customer

Voice data delivers significant opportunities for a better customer experience without the customer knowing it. An example would be finding the best call center agent for each customer on a real-time basis. AI can understand which agent is suited for the type of call because not every call needs your best agent. Understanding who is needed will reduce frustration, call transfers, and escalations to managers or higher-skilled agents. Another terrific use is AI & voice data would understand the customers’ emotions. This emotional understanding would allow a real-time sense of frustration, anger, or sweet satisfaction. Appropriate actions could be taken at the moment, and lessons learned could be recorded for future analysis. Instant adaptation is a much more reasonable approach to responding to the customers in a way that optimizes the customer's experience. 

Customer pain points are sensed with voice analysis and dealt with before becoming a sour customer growing negative reputations. This analysis will reduce customer churn and increase net promoter scores. Imagine learning what is causing customer churn and adjusting strategies on the fly. Customer analysis helps implement predictive speech analytics to deal with the customer at risk and act immediately. It might include a link to smart calling software for callbacks when an expert can reach out back to the customer. In turn, call center supervisors can implement strategies to prevent churn by improving building a knowledge base, better training, and improved scripts.

Even if caller emotions can’t be handled in a real-time fashion, there is an aggregate picture of the overall customer satisfaction by measuring and classifying caller emotions into buckets. Examples would likely include want, like, frustration, anger, annoyance, need, passion, and pleasure. Not only can sentiment be classified, so can call drivers, topics discovery, and brand health. Keywords can lead to emerging trends, and real-time dashboards focused on customer experience.

Using Voice Data for Voice of the Employee

Often forgotten in the shuffle is the actual employee voice data. Looking for comments from the agents that say things like "I wish we could do ….."  Employees are a great source of understanding your customers' journey even if the journey is outside your organization's purview that might encourage communicating or partnering with other organizations. Indeed, voice data should be analyzed for more knowledge for the agents, creating projects, and training curriculum adjustments. Lack of experience might lead to AI knowledge bots to adapt scripts in real-time instead of the batch script creation process.

Net; Net:

Analyzing voice data with analytics and AI will accelerate time-to-value for both the customer and organizations. It makes organizations more personal for both customers and employees while demonstrating the power of voice data plus AI rich analytics in the customer experience.


Additional Reading

Voice; Voice Baby               

Got Customer Excellence? 

Journey Maps  

Tuesday, November 3, 2020

Voice, Voice Baby

Voice-enabled devices are everywhere, and there is a high awareness of the potential for voice data on a personal level. Devices are in our living rooms and even in our bedrooms, but we are just scratching the surface of the use of data in organizations other than a simple search, understanding, and basic commerce. People talk to speech recognition like real people and say things like "please and thank you". Organizations need to up their game to take on smarter uses of voice over the coming decade. Organizations will have to gear up for “Big Voice Data” that goes beyond rudimentary search to analytic leverage and secure redaction of sensitive voice phrases.

Popular Uses Today

Voice search is prevalent and driven by the younger generations, but the deep usage is coming for the middle-aged wealth builders. Search is a critical participant in understanding what something is, how to leverage it, and the best way to go about it. Search is also a significant participant in simple commerce to find and buy specific products and services. It is particularly useful for lower-cost items like groceries, entertainment, and essential clothing. Voice is poised for explosive growth in the enterprise for large and complex voice sources. 

Needed Uses for Tomorrow

Because the voice influence cuts both ways, voice can influence commerce and help organizations to get better.  Organizations will have to ramp up their use of AI-powered voice analytics to gain an advantage. Savvy organizations are examining the critical moments of sales or service leveraging conversation analysis speed and accuracy at optimal cost levels. By understanding what was said and making the intent discoverable, new opportunities arise. This process allows organizations to analyze interactions and prescribe proper actions. The typical uses are for offers, complaints, first call resolution, compliments, outages, and escalation analysis.

On The Edge Uses

Organizations need to stop thinking about voice as just an interface or the outcome of a conversation. Voice data is a unique source of critical insights for the business. The leading organizations create the next generation of communication and collaboration with AI bots/agents to identify call drivers, trends, predict new directions, and design or optimize products and service bundles. This kind of smart voice leverage can apply to prospects or customers and all constituents involved with product/service creation, including employees and vendors. Voice analysis could cover the end to end supply or value chains. Voice analytics applies to both external and internal voice moments of truth, differentiating amongst the individuals' diversity at the same time.

Net; Net:

We all know that voice has much more value than any other means of communication because it expresses context, sentiment, intent, emotions, and action potential. Speech technology should be a vital part of any digital transformation as there are critical insights about product, service, and customers. Better accuracy, smarter implementations, and bulletproof security will allow more complex solutions while making it easier for users. It's time to up your game at getting more value out of the voice in your organization.