Effective Online Reputation Management During Covid
The unprecedented outbreak of the COVID-19 pandemic has caused many businesses globally to scramble to connect with customers digitally. Many deeply introspected their individual approaches toward novel and adaptable forms of Customer Experience (CX) Management.
If there’s any silver lining, it’d be that this crisis has led the future of technological innovation to be preempted sooner than ever expected. For many institutions and brands, analyzing digital interaction and assessing the ratio of digital dependency for daily sustenance became the essential first step.
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The main challenges
At Locobuzz, our clients faced volumes of customer concerns that were treated as critical and logistical pain points for the brand managers. Hence, our first step was to use this large influx of data to our advantage and strengthen our Artificial Intelligence to build seamlessly accurate sentiment models.
If we apply Machine Learning (ML) daily, people-centric businesses, we’ve to consider a constant change. Whether evolving markets or customer preferences, CXM becomes highly dependent on the ability of AI technology to deeply understand different customers’ intentions.
In ML terms, it becomes important to train AI also sometimes known as chatbots to understand the difference between two responses that carry the same words but can mean totally different things. For instance, someone enquires with a bank for a loan:
User: Hey, I need a loan!
Let’s say that the AI has been fed with two responses for the word “Loan”:
- Sorry, we are not providing any kind of loan at the moment
- Can you help us with which kind of loan product you want?
Assume, that based on the query “loan”, the AI can elicit any one of the above responses which can result in two entirely different circumstances!
Enter: smart replies
The Smart Reply functionality is Locobuzz’s one of million ways to reduce an ORM agent’s biggest woe: TAT reduction. However, it also helps segregate responses into different categories. It starts with the AI being fed responses that are bifurcated by the query. Smart Reply not only helps by providing quick responses but uses Sentiment Analytics and ML to efficiently increase the accuracy of the responses.
What’s interesting is that the feature recommends responses based on predicted queries based on “intent”. Why intent? Because, oftentimes, users don’t know how to ask for help.
If a user asks, “I don’t know. Which loan will help?” can elicit a response such as “Would you like to share your contact details with us for further assistance?” This function of machine learning helps the feature analyze a query based on keyword sentiment and populates a suggested response for the query.
Locobuzz has noticed a commendable improvement in TAT after the in-house team started using the ‘Smart Replies’ functionality. While working with Locobuzz, a BFSI brand observed their FLR TAT had reduced from the initial 41 minutes in May 2020 to a whopping 17 minutes in June 2020!
Additionally, ‘Smart Replies’ in essence prevent the brand from sounding monotonous or impersonal. While personal touch is the key to client retention, we must remember that AI technology is much like a child: it identifies and makes sense of patterned behavior. Imagine if a series of patterns are observed acutely, compartmentalized, analyzed, understood, internalized, formulated, and revealed. That’s what the process of “accuracy” looks like. AI technology and sentiment analytics, with the help of machine learning, will teach itself to evolve, but human intervention will always be the point of evolutionary-based learning.
Single smart response engine (SSRE) by locobuzz
At Locobuzz, we deploy our Single Smart Response Engine (SSRE) designed to leverage a higher standard of AI and respond to users quickly without compromising quality. It enables companies to cut costs and reduce turnaround times while improving CX.
Online Reputation Management (ORM) is about adding value to a company. Better ORM builds a positive reputation, enhances trust, and contributes to success. AI technology currently gathers and analyzes user queries and designates them as tickets that need to be responded to by a manual agent.
Conclusion
Of course, AI is constantly improving, and Locobuzz tirelessly works towards perfecting its approach for sentient AI, smart reply, contextual word clouds, and many more recommendation and computer vision technologies.
With an accomplishment of even one of these mechanisms, Locobuzz will set high industry standards leveling higher than the standard analytics tool geared to provide brands what is required to overcome the challenge of any crisis.
