Analytics

The introduction of a digital product is not the conclusion of a project. It is often the opening of a journey. At Honeyconecorp, our Analytics team works with product owners to set and extent keys and endlessly monitor user feedback in order to twist the perceptions back into the design team.
From product visualisation to implementation originating insights for constant improvement
• Classify retention, transformation and assigna metrics
• Predictive and unbending analytics using AI/ML
Analytics is an essential part of the product life cycle. Our analytics team helps inventiveness in using data through the product development and implementation process. Our analytics services include
User Behaviour Analytics
That helps to describe product objectives and creating a reliable user feedback twist to confirm constant product improvements
Personalization & Recommendation
Originating business visions that can assist enterprises suggest a modified and pleasant user experience

CORE FINANCE ANALYTICS

Common finance analytics challenges:

• Reduced quality data due to the absence of an combined analytics platform
• Poor user experience results in low output and business agility
• Inadequate diagnostic abilities with zero prominence of data
• Limited practical analytics and development capabilities

Commercial analytics

Using analytical models and data conception, we help pharmaceutical companies enhance their commercial spend across marketing, sales, reductions.

Bringing data into focus

Analyzing sales presentation and competitor and customer behavior was hard.
The absolute volume and variable quality of data was also tough to accomplish. Creating reports and sharing timely visions with result makers and sales teams on how to increase sales was time consuming.
In fact, analysts were spending their time removing and cleaning data for reporting, leaving little time to turn this data into visions. Even when analysts could appeal insights, they often have faith on manual spreadsheets, which led to mistakenness. This made distrust in data, particularly among sales teams.
Our client desired to mechanise data processing and cleansing, speed up vision discovery, and built self-serve analytics solutions to direct strategic decision-creating across its commercial business

Analytics through an experience lens

The company set out to convert its analytics abilities. We beganwith a week assessment, interviewing executives, analysts, and commercial sales representatives to realise user requirements.
From these interviews, we were able to categorise the reasons behind mistakenness, late decisions, limited prominence, and lost business opportunities.
By merging years of industry and digital expertise with results from user research, we driven with our client to visualise an ideal future state. This comprises automatic, user-friendly analytics solutions that put the requirements of the business and its employees major.
To carry this vision to life, we considered a roadmap and used agile delivery principles to speed up the path from resistant of concept to solution delivery.

Self-service analytics

To improve the user experience, we developed self-service analytics for our client’s commercial team so that they can generate their own insights on day-to-day activities.
More sales representatives can admit reports through the presentation management systems. They can track sales targets and discover ways to advance their performance.
Analysts have lessen time spent on data management from allowing them to concentrate their efforts on discovery actionable business visions

A refreshed commercial business

With improved analytics abilities, the commercial teams prepared the tools they wanted to improve presentation across all areas of its business.
Analysis exposes a relationship between how often sales representatives evaluate the performance management system and their general performance.

Insurance analytics

Using a constant scoring framework that activates algorithm scoring began and then again when new information on a claim becomes accessible
Removing intelligent data (internal and external) to associate and collect data from various dissimilar
data sources and formats
Using text analytics to build additional indicators from unstructured data such as claim notes and investigation reports Using advanced claims analytics to run all suspicious claims through one or more supervised and/or unsupervised machine learning models
Using link/network analysis to provide investigators with additional leads, analysis, and insights from claims data to capture organized fraud
Deploying triage analysts to review and analyze the data and refer cases with the highest-risk score to the SIU team
Using scored but rejected claims to recalibrate models to improve efficiency and accuracy
Using a case management suite to help investigators keep track of their assigned claims
Using a visualization suite to enable SIU managers to track model as well as SIU unit performance

Consumer analytics

Consumer analytics
We help initiatives attract new customers, increase marketing ROI, and improve sales efficiency. Our analytics-driven solutions expose and extent the entire customer journey from awareness to advocacy.
The bank's management knew that to create customers happier, it needed a full understanding of their favourites and pain points in order to advance planned and operational decision making. The bank had advanced in some new technologies, such as voice-to-text, but it hadn't recognised any benefits. Only a few people had the training to use these tools and the firm hadn't calm any analytics to determine if the technologies were working well.

AI- and analytics-led transformation for inbound customer service processes

Improve a data-driven method of calculating customer experience that crossed all interaction channels agent, interactive voice response, e-service, chat, and social media
Quick notice sub-agent performance and best-practice distribution openings to increase service proficiency and recognise cross-sell opportunities
Use the current voic
e-to-text technology platform to precisely capture customer complaints and uncover the reasons behind their frustrations Offer practical and suggest support for projects, extent post-roll out performance, and acclaim timely solutions by co-operating across client teams
The assignment was wide, but we design to the challenge, concentrating on the following three key areas

Customer experience management

We take out, and rationalize structured and unstructured customer interaction data. then planned customer behavior through channels and functions. Relating to a predictive customer satisfaction model, we studied customers' conversations. Then our proprietary analytics algorithm stated the customer experience through multiple touch points and collected the results into a customer effort score. In doing so, we exposed that web crossovers and repeat calls were the leading problems. So we gave agents added preparation to increase first call resolution and decrease call handling times. As a outcome, satisfaction scores improved in just four months

Agent performance optimization

We integrated all digital agent performance management platform. We then used our AI-powered automatic call quality assessment tool to make the Agent Performance Index — a single metric openly connected to cost savings and revenue development opportunities. By ranking agents within and across sites, products, and teams, we recognised targeted training needs.

Advanced speech analytics

We used text mining to revise call transcripts. We also used speech tuning and automated capture and organisation to sort grievances. Based on what we educated, we gave representatives training to actively hold customer anxieties. Customer satisfaction totals enhanced