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One of the world’s largest and fastest growing data analytics firms, LatentView is helping companies drive digital transformation and use data to gain competitive advantage. We catch up with Gopi Koteeswaran, CEO, who is driving the organisation to deliver customer centric processes. Koteeswaran gives us an insight into the analytics products and solutions by the company and how is it enabling enterprises to predict new revenue streams, improve customer retention and optimise investment decisions.
Analytics India Magazine: How is LatentView helping customers stay relevant in the fast evolving digital era with its innovative solutions?
Gopi Koteeswaran: The world is being transformed by new technologies such as artificial intelligence and machine learning, which are being used to create new models, thereby improving the process. LatentView Analytics is one of the fastest growing data analytics firms delivering solutions that help companies drive digital transformation and use data to gain competitive advantage.
With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities and support AI initiatives, LatentView Analytics enables global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimise investment decisions and turn unstructured data into a valuable business asset. We have clients such as PepsiCo Inc., Microsoft, Whirlpool, PayPal, and Expedia, among others.
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AIM: Please tell us about the various analytics solutions provided by the company.
GK: We have over 20 prebuilt analytic assets/solutions which fall under the service lines such as customer analytics, marketing analytics, finance, supply chain, sales analytics and others. Some of the prebuilt solutions include:
- AMPLIFYR, a simple, easy-to-use code free analytics platform that aids citizen data scientists to quickly discover insights from large datasets.
- PANEL MINER, a cloud-based automated data engineering and analytics solution that provides a comprehensive view of customer experience on digital properties.
- TURFVIEW, a fully automated, scalable, cloud-based solution that helps gather competitive intelligence at granular levels for digital marketing, and
- DIGIVIEW, a real-time digital marketing analytics dashboard designed to deliver a 360-degree view of a company’s digital marketing performance, across all its brand portfolios and channels including web and social analytics.
AIM: How have your clients been benefitted by the analytics solutions provided by the company? Please highlight few use cases.
GK: We provide advanced analytics solutions across different market segments and verticals such as banking & financial services, insurance, CPG, retail, e-commerce, technology, and others. Some of the interesting use cases that we have delivered are:
1| Recommendation system to increase share of wallet
- Business Challenge: In an industry where customer acquisition is fairly expensive, this company’s repeat orders were at a low 4 percent.
- Solution: Build an innovative recommendation engine that combined customer segmentation, user-based collaborative filtering and market basket analysis
- Result: 20 percent increase in value of new orders from existing customers. Higher customer satisfaction due to precise recommendations.
2| Risk identification by modelling customer behavioural patterns
- Business Challenge: Costs incurred due to warranty claims had a negative impact of almost 2.5 percent on the bottom line.
- Solution: Driving styles were identified based on vehicle usage and historical warranty claims which were then used to accurately predict future claims for each driving style.
- Results: Warranty costs reduced by 35 percent for the “long pause and short trips” driving style due to proactive ‘drive right’ messaging communicated to at-risk drivers.
AIM: How is LatentView helping organisations overcome some of the challenges faced by them?
GK: Some of the key challenges that we help organisations overcome are:
- Risk of Over-Engineering: LatentView Analytics’ data & architecture strategy is driven by business requirements rather than by technology needs which ensures that the solution provides the best-fit to functional needs.
- Rigid Data Models: A rigid data model might require significant changes to handle changes to business requirements resulting in higher total cost of ownership. LatentView typically utilises a “Schema on Read” and “Metadata Driven Architecture” which can accommodate changes gracefully.
- Poor Data Quality: LatentView Analytics’ data engineering practice incorporates comprehensive data profiling & cleansing techniques in all projects which ensures that correct data is used for all analytical initiatives.
- Data Duplication: LatentView Analytics incorporates strong data governance practices in all its engagements with data lineage at the core to ensure that clients don’t end up with a “Garbage In, Garbage Out” scenario
- Incorrect Quantitative Techniques: LatentView Analytics’ experienced Machine Learning & Predictive Analytics practitioners are well versed in all techniques and brings in the right approach to the problem at hand.
AIM: How big is your analytics team? What are the various skill sets you look for while hiring for your analytics team?
GK: The biggest asset of LatentView Analytics is its talented workforce. The workforce consists of some of the brightest technical and business minds from the top universities. They go beyond being analytics professionals and are rooted in a strong sense of social consciousness, with an environment that challenges them intellectually and empowers them to make a positive difference in the world around them. LatentView Analytics has more than 600 employees in offices in Princeton, N.J., San Jose, Calif., London, Singapore and Chennai, India. We also constantly empower our employees to imbibe the culture of innovation through initiatives such as self-learn platforms, internal job postings, social engagement and others.
AIM: What are the various applications that can run on your solutions at LatentView?
GK: The applications that can run on our analytical solutions can be categorised into:
- Data Visualisation Platforms: Tableau, Qlikview, Power BI, Kibana
- Machine Learning Platforms: Python, R, SAS, Azure ML, H2O.ai
- Web-based Platforms: Angular JS, Node JS, Bootstrap, D3
- Big Data Platforms: Apache Spark, Databricks, Hadoop
- Cloud Platforms: Amazon AWS, Microsoft Azure, Google Cloud
AIM: How LatentView uses analytics internally?
GK: LatentView uses analytics internally to:
- Streamline operations through advanced analytics to ensure service delivery excellence across the organisation
- Combination of process automation and advanced analytics to help resourcing and recruitment as well as sales intelligence
- LatentView utilises its proprietary “SmartInsights” platform to identify AI / ML trends in the marketplace to precisely focus its marketing & sales efforts
- LatentView uses chatbots in its support departments like Administration, Immigration, Human Resources to provide better employee experience
AIM: What are some of the contemporary trends in analytics you see emerging?
GK: Some of the key AI prediction that will be game changers in the way AI and ML would be used in the coming years are:
- Human Directed Machines: AI systems can now outperform humans at playing chess and Go, recognising faces, and driving safely. When it comes to AI, the trend points in the Man + Machine direction, to tap the full value.
- Organisations Will Identify Narrowly Scoped Areas To Build AI Success Stories: When it comes to narrow AI, algorithms are set in place to optimise a particular task. Instead of a one-size-fits-all approach, the algorithms will be more customised to suit a specific business needs. As AI techniques continue to evolve rapidly, the key will be to use unstructured data, which provides more granularity, to solve business challenges and drive value.
- Intelligent Ecosystem Reaches A Tipping Point: With the explosion of intelligent things, it is but natural to expect a paradigm shift from intelligent things working independently, to working together (harnessing the power of IoT data) to create an intelligent ecosystem, multiple devices will work together, with or without human input.
- How Humans Interact With Digital World: Conversational platforms are steering the ways in which humans will interact with the digital world. Simply put, there will be a tilt shift which will move from human to computer. Here, the system takes a command in the user’s natural language and responds by executing the function and also asks for additional information, if required.
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