What Swiggy and You Can Learn From This Company’s Use of ML to Engage Customers
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The app economy has enabled a huge range of unique business models to flourish. One such model is online food ordering and delivery services, in which apps leverage geo-location data to aggregate local food choices and offer personalized options to consumers.
A leading company in this space is Just Eat. Launched in the UK in 2001 with a vision of ‘serving the world’s greatest menu. Brilliantly.’ The company has capitalized on the popularity of online food delivery and grown its presence across 12 markets.
Just Eat acts as an intermediary between take-out food outlets and hungry customers, giving local restaurants access to a broader base of potential diners, while providing consumers with an easy and secure way to order and pay for food from their favourite restaurants.
Today the company helps 27 million customers find food from more than 112,000 restaurants—everything from homemade Italian pasta, to Chinese noodle bowls, to fish-and-chips.
Data is the fuel of Just Eat’s rapid growth, but it wasn’t always looked at that way. In its early days, Just Eat struggled with the deluge of information and faced fragmentation across its systems. In fact, the company realized its legacy data vendor wasn’t capable of ingesting 90 percent of the data produced by its food platform. This was incredibly frustrating for Just Eat’s analysts and data scientists, who had to waste time cleaning up sources instead of leveraging the data to create a better user experience.
Just Eat turned to Google Cloud, and now uses machine learning (ML) to power sophisticated consumer recommendations on both its app and website. It also makes heavy use of features offered by Google Cloud Platform, including BigQuery for running analytics on its customer data set and Cloud Pub/Sub for messaging app users with relevant offers in real-time.
Having all of Just Eat’s data in one platform has translated into real value for its customers. With Google Cloud tools, Just Eat has created its own proprietary Customer Ontology framework, which today contains 5.5 billion features that better understand consumers’ behavior and food habits, and provides insights into previous visits.
Just Eat recently created an “Adventurous Index” to map its customers according to their ordering habits, enabling them to tailor their marketing and user experiences. For example, mid-adventurous customers are shown a choice of restaurants that serve their most ordered cuisine, while adventurous customers can choose from restaurants that serve a wider variety. This not only has prompted consumers to be more adventurous with their choices, but also has led to more business at a more diverse set of restaurants.
Matt Cresswell, Director of Customer Platforms at Just Eat said that Google Cloud has become integral to its product delivery: “Consumer food choice is a hugely nuanced topic. We know that individuals have their own unique journeys when they use Just Eat. We’ve sought to create a truly one-to-one relationship with every customer. The changes we’ve made to the platform mean they can access the dishes they enjoy at the touch of a fingertip, and find inspiration to discover new dishes they’ll love. We’re grateful to Google Cloud for helping us support our customers on their culinary explorations.”
The Real Drivers of Efficiency, Growth, and Customer Experience
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The increasing adoption of technologies like connected devices, augmented reality, and machine learning has changed the way we shop, and retailers are evolving how they do business to meet the needs of their customers.
Retailers say it’s no longer enough to keep pace with shoppers’ growing expectations—they must get ahead of them. That’s why more and more are turning to the cloud. They’re using it to eliminate data silos and take advantage of cloud-based analytics. They’re tapping into machine learning to improve all aspects of the value chain. And they’re making use of reliable and secure cloud infrastructure to scale their businesses.
Although every retail customer is different, many of them share similar objectives. Here are three major ways retailers take advantage of the cloud.
Storing and Analyzing Data in the Cloud
Data presents both a challenge and an opportunity for retailers. Which is why Ulta Beauty, the largest beauty retailer in the US, is moving to Google Cloud Platform (GCP). Now, with the help of BigQuery, Ulta Beauty will be able to more efficiently predict and analyze outcomes and develop more meaningful data insights that can be leveraged to deliver a more personalized, relevant guest journey.
They are not alone. DSW has also chosen to use GCP to help relaunch their DSW VIP loyalty program for the first time in over 10 years. With more than 90% of transactions running through their loyalty program, DSW needed a flexible and scalable solution to deliver a real-time loyalty program for 26 million active members. They’ve already seen a 9% uptick in new customers and have improved their already strong retention rate.
Improving Customer Experiences with AI and Machine Learning
Once retailers are able to access these insights, they are turning to AI to help personalize the overall shopping experience. At first, retail companies leveraged AI tools such as machine learning for product recommendations.
Now, more retailers use AI to forecast trends, predict inventory needs and prevent
Just look at METRO AG, one of the largest B2B wholesalers globally. They’re using AI and machine learning to better serve their customers. For example, many of their customers are restaurant owners. With Google Cloud AI capabilities, they can create tools that identify when a restaurant is out of a particular ingredient and automatically order more.
Ocado is another great example. The world’s largest online-only grocery retailer drove a 3.5% increase in contact center efficiency by using Google Cloud machine learning technology to respond to customer emails four times faster.
To help businesses further accelerate their AI solutions, Google has developed the Advanced Solutions Lab (ASL), which gives businesses the opportunity to work side-by-side with Google’s AI and ML experts to solve high impact challenges.
Fast Retailing, the Japanese retailer behind Uniqlo, is working with Google Cloud and ASL to help them better analyze customer data to forecast demand and deeply understand what their customers want.
Carrefour, one of the world’s leading retailers, also announced last year that its engineers will be working side-by-side with our AI experts to co-create new consumer experiences. This is in addition to deploying G Suite to their employees to support the company’s digital transformation.
Scaling Infrastructure to Meet Demand
Of course, none of this innovation is possible without a reliable infrastructure that can scale instantly to meet surges in traffic.
And many have found the reliability and security they need with the cloud. That’s why global cosmetics brand Lush chose Google Cloud. They migrated their e-commerce platform to GCP to handle increased traffic without compromising stability.
This move that ultimately reduced infrastructure hosting costs by 40 percent.
L.L.Bean also modernized its IT infrastructure by moving capabilities from its on-premises systems to GCP, improving customer satisfaction and IT efficiency across multiple sales channels.
Apigee and Vision API: ICICI Prudential Life Insurance’s Journey of Speeding Document Processing
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Google Cloud results
- Helps enable instant document approval with optical character recognition by Vision API
- Processes 100,000 documents in 20 minutes with automated document processing product Recognic, powered by Vision API and Apigee
- Helps increase the number of applications processed by 30% within the same timeframe
The insurance landscape in India has seen significant changes in recent years with the adoption of new technology. As one of the major insurance providers in the country, ICICI Prudential Life Insurance has aimed to lead in this transformation journey. “There has been a data explosion across India over the past few years, together with a high mobile penetration rate. Today, about 60% of our customers approach us via mobile, for example, which was certainly not the case before,” says Alpesh Karnik, SVP, IT, at ICICI Life Insurance.
Consumer expectations have also evolved, with easier access to information and online services. “Consumers today are more informed on the importance of investing in insurance products, so there’s much more of a pull factor when it comes to sales, but they also want to be able to get these products quickly and easily,” adds Alpesh. To meet the demands of these consumers, ICICI Prudential Life Insurance realized it needed to make its processes even faster and more efficient. Looking to upgrade its infrastructure, the company turned to Google Cloud.
“The biggest benefit of using Recognic and Vision API is that it eliminates the initial waiting time, which can result in drop-offs. Now customers can know immediately whether their documents are sufficient, or if they need to revise or submit any others.”—Alpesh Karnik, SVP, IT, ICICI Prudential Life Insurance
Serving customers better by speeding up processes with Google Cloud
ICICI Prudential Life Insurance’s distributors were already using tablets to input customer data faster and more efficiently, but many of the company’s solutions still required a team at the back end to manually sift through documents for approval. This meant that customers needed to wait five or six hours, or sometimes until the next working day, to know if their documents were approved or needed revision.
That all changed after partnering with Google Cloud Premier Partner Searce to take advantage of its AI/ML powered automated document processing product Recognic, which is built on Google Cloud. Developed using the optical character recognition (OCR) capabilities of Cloud Vision, Recognic reads, understands, and validates documents at scale, enabling organizations that handle massive amounts of paperwork to digitize these documents and then accurately store and index them.
“Google Cloud has cut down the middle- and back-office work, leading to a 30% increase in the number of applications we can process in the same time span without the need for additional resources.”—Alpesh Karnik, SVP, IT, ICICI Prudential Life Insurance
“In the case of ICICI Prudential, the biggest benefit of using Recognic and Vision API is that it eliminates the initial waiting time, which can result in drop-offs. Now customers can know immediately whether their documents are sufficient, or if they need to revise or submit any others,” Alpesh adds.
Alpesh explains that if the details on the application form match the documents provided, the case doesn’t need to go to the underwriter for further checks and can go directly to policy issuance. “Google Cloud has cut down the middle- and back-office work, leading to a 30% increase in the number of applications we can process in the same time span without the need for additional resources.”
ICICI Prudential Life Insurance is also working with Searce to build deep learning models into Recognic so that it can overcome template barriers and input data from a variety of forms. This is particularly helpful for financial and medical documents underwriting because unlike a passport or driving license, financial documents have a higher structural complexity.
As customer data becomes more important in the work of ICICI Prudential Life Insurance, so does protecting it, and the company is taking every measure to safeguard the security and privacy of its customers’ information. “Details of customers’ contactability are automatically removed by Google Cloud after processing is complete. This step in the workflow gives us the confidence that data is not stored at any level of the optical character recognition process,” says Alpesh.
Partnering with the right teams for dedicated support
In achieving the best solution for its business goals, ICICI Prudential Life Insurance recognizes the importance of its decision to work with partners that truly understand the insurance business. “There are many intricacies involved in this business, and it’s clear that both Google Cloud and Searce really took the time to understand our underwriting processes before coming up with a solution,” says Alpesh. He adds that during the implementation process, all findings were well documented and queries were responded to quickly.
“We didn’t want to take any shortcuts deploying Recognic, but at the same time, we didn’t want to draw out the implementation process. The excellent support from both Google Cloud and Searce throughout the journey was reassuring for us as they were always thinking ahead.”
Future-proofing the organization through machine learning and AI
In the coming years, Alpesh foresees the insurance industry to be even more agile than it is today. “I doubt elaborate processes such as underwriting or operations checks will need to be done manually in the future. Everything will be done through machine learning and AI.” In light of this, ICICI Prudential Life Insurance is doing everything it can to prepare, as customers’ expectations are set to keep evolving. “We have to be prepared for the future, and I believe that with Google Cloud, we can do it.”
About ICICI Prudential Life Insurance
ICICI Prudential Life Insurance aims to lead the Indian insurance field through quality products and a hassle-free claim settlement experience. A customer-centric company, it offers long-term savings and protection plans to meet customers’ needs at every stage of life.Industries: Financial Services & InsuranceLocation: India
About Searce
Searce is a niche cloud consulting business with futuristic tech in its DNA, focused on “realizing the Next in the Now” for its clients. Specializing in cloud data engineering, AI/ML, and ad
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Signal Generation in the Investment Management Industry
Machine learning is seeing a lot of use cases in the financial sector. One of them is leverage AI to sift signal from noise and create insights or predictions that can give financial planners an edge.
In this video, David Li, Head of Advanced Analytics, BlackRock and Colman Madden, Customer Engineer, Google Cloud, present on how BlackRock leverages NLP on Google Cloud to search for signals in the investment management industry.
“We analyze large volumes of textual news via NLP to classify text into sentiment scores as well as other metrics such as news volume and emotions in these articles,” says David Li.
He also discusses some of the challenges they faced, and the solutions they found, and why they selected Google Cloud to run this project.
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AI has the power to revolutionize every industry—from retail to agriculture, and education to healthcare. Yet many businesses still haven’t begun to adopt AI.
There are a number of factors, including the need for specialized talent and hardware, the right types and quantities of data for training and refining machine learning models, and of course, the broader complexities of introducing a new way of working inside an organization.
But above all, AI can be challenging to apply to very specific business needs.
Google wants to change that, which is why it’s introducing a number of AI solutions aimed at making it easier for businesses to use AI to address many of these specific use cases.
Google’s AI solutions fall into two categories. The first is a set of pre-packaged AI solutions that can be easily integrated into existing workflows. To make these solutions as easy to implement as possible, Google works with popular, trusted enterprise partners who have deep-domain expertise in these workflows.
The majority of Google’s pre-packaged solutions will be delivered through these partners, although it will be offering some
The second category of AI solutions is comprised of reference architectures that businesses can use to create highly-custom AI tools. These require more development work than Google’s pre-packaged
Additionally, businesses can build on these architectures and deploy them to market more quickly, helping your business take advantage of AI, faster.
Learn more about all Google’s AI solutions. Download the whitepaper now!
Pindrop and Google Cloud Get Together to Make Way for Next Wave, Voice-first Interfaces!
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If you’ve ever used only your voice to authenticate a payment, place an order, or check an account over the phone, there is a good chance that Pindrop’s technology made it possible.
Founded in Atlanta in 2011, Pindrop provides software and technology that uses machine learning, voice recognition, and behavioral analytics to help detect and prevent fraud in voice channels like AI-powered call centers and solve the long standing identity problem commonly encountered in customer care and contact center experiences. Demand for Pindrop’s technology has grown considerably over the past decade, as more organizations and people adopt voice as an interface for customer service, transactions, entertainment and more. As that demand has grown, safeguarding these voice interactions from fraud or authentication loops continues to be a unique challenge.
Now, with frictionless voice-driven customer experiences at an all-time high, cybersecurity is more critical than ever. In fact, research shows that fraudsters are able to accurately answer knowledge-based authentication questions 92% of the time, as opposed to only 46% for actual customers. To address this, Pindrop is bringing its products and technology to Google Cloud in order to scale and develop new capabilities that will help enable the next wave of voice-first interfaces and call centers.
The new partnership will enable Pindrop’s teams to accelerate their development of new capabilities to address an ever-shifting landscape – like detecting deep fakes and robocalls, helping banks authenticate transactions, providing retailers with AI-powered call center support, and helping IoT makers optimize for security, speed and simplicity.
More specifically, the partnership will help Pindrop scale its own businesses, and meet ever-growing customer needs in several ways.
First, Pindrop is bringing its SaaS platform to Google Cloud, enabling customers to deploy it at global scale, on secure, sustainable, and highly performant cloud infrastructure. Not only does this give Pindrop the ability to deliver secure voice interactions with low-latency, it also aligns with its mission to enable customer choice when selecting and implementing security technology. And for customers already operating on Google Cloud, getting started with Pindrop can be done directly within their cloud environment, now that the company is making its solutions available on Google Cloud Marketplace.
Second, Pindrop plans to offer its voice secure technology with Google Cloud’s Contact Center AI (CCAI) capabilities to develop new solutions that will enhance call center experiences. CCAI capabilities in understanding, augmenting, and ML-processing conversations allows companies to deliver interactions that are helpful and keep costs low. These capabilities alongside Pindrop’s authentication and anti-fraud solutions will enable the company with the tools and technologies needed to create the next evolution of frictionless experiences in a secure way.
Finally, building on top of Google Cloud will equip Pindrop with multicloud capabilities that will offer new channels to increase revenues through. Using technologies like Google Kubernetes Engine, frequently chosen by startups and tech companies, to quickly launch and scale new ML applications up or down will also support Pindrop’s growth as it adds to its suite of technologies.
Supporting innovative startups and digital native businesses like Pindrop is in Google’s DNA, and we’re delighted to support Pindrops’ growth, and the success of their customers, with Google Cloud infrastructure, Contact Center AI, and go to market expertise.
You can learn more about Pindrop on Google Cloud here, and Google Cloud’s Contact Center AI solution here.
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