How TapClicks’ Google Cloud Migration Makes Life Easy for Marketers
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Editor’s note: In this blog post we learn how TapClicks migrated to Google Cloud to offer their marketing customers a unified platform for data management, operations, insights, and analysis.
TapClicks is a smart marketing cloud, powered by data, that unifies our customer’s marketing. By choosing to migrate our core applications last year to Google Cloud, we cut costs, solved data-sharing concerns for our customers, and opened our stack up to a new ecosystem of possibilities.
The core problem that we’re solving for our customers is how to manage their marketing infrastructures data and operations. Life isn’t easy for marketers now. There are 7,000 different vendors servicing this space today – creating much complexity between digital agencies, media, and brands. Marketers face challenges in navigating all of these systems, logging in and out, understanding pacing goals, and managing the flow of marketing data so they can analyze and report internally as well as to their clients at scale.
We unify omnichannel campaign data (250 API connectors and 6000 Smart Connectors ™ ) from a plethora of marketing sources on an automated data warehousing solution, creating simplicity for organizations. Over 4,000 agencies, media companies, and brands use our Marketing Operations and Data Management Platform, which imports data at scale and creates an automatic data warehouse on Google Cloud. Teams can also leverage TapClicks, like our world class Facebook connector, to import data directly into Google Data Studios. Beyond importing and storing, we also provide data exporting to other Google solutions like Google Data Studio and Google Sheets. We also create interactive dashboards that let stakeholders and clients analyze their data, as well as automated, multi-channel reports that go out to clients at specified times. So channel comparisons, optimizations, attribution, and calculations are easily performed. Some of our customers are able to generate hundreds of thousands of individual reports and dashboards for their clients.
Although we may be best known for our reporting and analytics, we also empower teams managing the marketing operations workflow from customers and internal stakeholders, especially at scale. Our user-friendly, configurable system helps manage their orders and campaigns. Through automation of this process, we deliver tremendous amounts of efficiency, time saving, cost savings, and reduction of errors. The combination of these solutions makes up our unified platform, with additional capabilities like marketing intelligence that offers competitive and brand-level analysis. This is a disruptive solution in use by all leading media companies, agencies and many brands.
Partnering for possibilities
We faced a few challenges with our original tech stack, which included a mix of the leader in web services revenue, leaders in high performance data warehousing, as well as vendors on bare metal servers.
- One challenge was around costs, which were growing.
- Second, many of our customers work with multiple brands, and are very hesitant to share their data with the leader in web services, who’s often viewed as their competitor.
- Third, these vendors are more focused on their own revenue rather than a true long term partnership that would enable their customers to enjoy similar success as they have experienced.
When looking at other cloud providers, Google Cloud emerged for us as the front runner. They were competitive on costs, and their native Kubernetes support was superior— a big selling point for our DevOps team. There’s also a movement in the marketing and advertising industry away from AWS toward Google Cloud because of the data-sharing concern. Finally, most of our customers are already using Google Cloud tools, so there’s brand recognition and familiarity there, and easier integrations with their own systems.
Migrating to Google Cloud
Our migration, which took about five months, involved moving a significant chunk of our infrastructure, including our core applications, using Google Kubernetes Engine (GKE). In our legacy architecture, each of our clients was assigned to one of our virtual machines (VMs), and there was a lot of unused capacity because we had to provision for the max usage. We appreciated GKE’s cloud native capabilities, especially autoscaling, a huge benefit for our web application. We have varying usage patterns during the day, and though our application is mostly used during business hours, there are also days in the month of higher usage, and autoscaling saves us time and costs. GKE also makes deployments much easier, and we anticipate a lot of benefits there for our developer environments. We’ve moved some of our microservices into GKE and plan to move more in the future. All in all, we were able to migrate our core products and the bulk of our AWS spend successfully to Google Cloud.
We also moved from our other vendors Relational Database Service (RDS) to running MySQL on our own VMs on Google Cloud, which gives us more flexibility in terms of settings and fine tuning. We’re still trying to find the best mix as we’re modernizing our infrastructure, and we took this opportunity to migrate from MySQL 5.7 to 8.0.
Our next stage is exploring more of the capabilities and services of Google Cloud, including BigQuery, which we’re considering for our own data warehouse. The fact that we could also run Snowflake on Google Cloud, if needed, was another selling point for our migration.
We’re especially interested in BigQuery ML’s machine learning and natural language processing capabilities, which enabled better predictive insights. Our customers want insights from their campaigns— which are working, which are paying off, where should they invest next? Using our platform, they’re looking not only to generate reporting, but also identify opportunities to improve campaign performance. We plan to use AI and ML to improve those capabilities, so that our customers can seamlessly unlock insight and intelligence from their marketing data and campaigns.
Double-clicking on Google Cloud
For us, being able to deeply leverage and partner with Google Cloud to deliver those solutions on a single stack is critical, and we think our customers will love it. We see TapClicks and Google Cloud partnering at a level beyond what you typically see in a cloud provider relationship. Already, fifty percent of our company is working with various Google Cloud solutions, and we envision TapClicks and Google Cloud as extensions of each other, providing a single, powerful platform solution.
Google Cloud understands the partnership concept, and their team was able to shine a light on their services and what they could bring to the table. Compared to our previous experiences, dealing with the Google Cloud team has been a true pleasure. Now that we’ve migrated, we’re ready to take our next steps into the services available to us in the Google Cloud ecosystem, and the problems we’ll continue to solve for our customers. Learn more about TapClicks and BigQuery ML.
New Visual Interface for Google Cloud’s Speech-to-Text API Makes API Easy to Use !
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At Google Cloud, we’re committed to making artificial intelligence (AI) accessible to everyone and easier to harness for new use cases. That’s why we’re excited to announce the general availability of our intuitive, new visual user interface for Google Cloud’s Speech-to-Text (STT) API, right in Google Cloud Console, which makes the API much simpler and easier for developers to use.
The STT API lets developers convert speech into text by leveraging Google’s years of research in automatic speech recognition and transcription technology. As advancements in AI continue to bring speech to new interfaces and devices, the STT API helps developers add speech functionality to their applications in order to better meet consumer demands.
The STT API covers a wide variety of use cases, from dictation and short commands, to captioning and subtitles. Getting the most of STT, however, can be a complicated process. To achieve the highest accuracy on any AI use case requires careful testing and tuning.
Previously, developers building on the STT API had to do this work manually by carefully experimenting with our API. Just to get started, developers needed familiarity with GCP integration concepts and had to either build their own tools or manage various scripts and API calls to fully understand the API documentation. These actions required cumbersome and time-consuming effort and made measuring, customizing, and improving models even more difficult.
Today’s announcement significantly simplifies the process, facilitating iteration and integration of models into developers’ applications by letting developers perform every API function from within the Google Cloud Console. These tools will make it easier for developers to integrate the STT API with their products or services. This update also gives developers the ability to manage and quickly iterate on their STT model customizations with Model Adaptation.
Model Adaptation allows developers to customize STT specifically for their domains or use cases. Developers can maintain lists of words and weights that will be applied to either every request or just single requests, depending on their needs. Model adaptations are reusable and composable, so once developers have seen good results in the STT Cloud Console, they can deploy to their entire solution.
The Speech-to-Text Cloud Console and Model Adaptation API is available now in all Google Cloud regions and languages and is accessible to all GCP users with no additional cost to that of the underlying API usage. The STT API supports over 70 languages in 120 different local variants. If you’re a developer looking for an easy to use, easy to integrate, and high-quality STT experience, sign up for our free trial and try our new interface on your own datasets today!
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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Introduction to Cloud Shell Editor
Watch the video to understand how Google’s Cloud Shell Editor and its powerful features-packed environment can streamline your development workflows.
Google Cloud Helps Northwell Health to Boost Caregiver Productivity and Access to Right Care Using AI
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Lung cancer is the leading cause of cancer death in the United States and like any cancer, early detection is crucial to survival. Screening at-risk populations is an important part of reducing mortality, and if concerning nodules are found on imaging, further testing may be required. Today, we’ll share how Northwell Health uses Google Cloud products such as Cloud Healthcare APIs and BigQuery to increase caregiver productivity and deliver better care for patients with findings that indicate potential development of lung cancer.
Northwell is New York’s largest healthcare provider
Northwell Health is New York’s largest healthcare provider with 23 hospitals and nearly 800 outpatient facilities. Northwell’s nearly 4,000 doctors care for millions of patients each year, and at this scale, there is an immense amount of healthcare data to manage. To better manage and leverage this data, Northwell Health partnered with Google Cloud starting in 2018.
Enabling caregivers to spend more time with patients
Nic Lorenzen, the lead developer of Northwell Emerging Technology and Innovation team, has a mission to put together data for caregivers in a way that makes sense. It is no secret that inefficient electronic health records systems have a negative impact on a physician’s ability to deliver quality care. Traditional EHRs have information distributed across many tabs, which forces caregivers to spend considerable time at the computer trying to find information. Moreover, speed of care matters. If care is delayed, patients may have to spend more time in the hospital and may suffer worse health outcomes.
To solve this problem, Nic’s team focused on giving caregivers the most relevant pieces of data at the right time by developing an intelligent clinician rounding app. The data needed to derive these insights can depend on the caregiver’s role–a nurse cares about different things than a cardiologist. This system aggregates multiple data sources, and provides patient-specific insights to caregivers.
This system would not have been possible before with traditional EHRs and data warehouses that have proprietary data models and rarely sync data in real time. Now with data easily accessible through Google Cloud’s Healthcare solutions, Nic’s team can deliver the right clinical information to the right people instantly. These days, Nic says, “instead of spending 75% of our time dealing with architecting the underlying platforms, we spend 75% of our time focused on higher value use cases for clinicians and patients. Google Cloud’s Healthcare solutions have greatly improved our developer productivity and time to value.”
Caregivers have found this new system to be a game changer.Before the implementation of this system, caregivers would spend, on average, seven to nine minutes finding the data needed to make medical decisions for one patient. Now, that aggregated information is delivered to a caregiver’s mobile device in less than a second.
Ensuring patients get the right care with the power of AI
There are a number of reasons why patients might not get the care that they need. For example, patients today can go to multiple hospitals and clinics settings, and coordinating care across multiple facilities is complex. Regional hospitals and clinics have their own siloed view of their data, so pertinent information gathered by one clinic might not be seen by another. These gaps in clinical data lead to gaps in patient care.
When a patient gets radiologic imaging, they may have findings unrelated to the reason they initially got the imaging. For example, a chest CT for a car accident might reveal an incidental lung nodule that could be cancerous. Unfortunately, research shows that a large portion of patients do not get follow up for these incidental findings because it isn’t the primary reason why the patient is seeing a doctor. Moreover, social determinants of health are a factor that affects which patients receive follow-up care. Identifying these patients and providing the necessary follow up care prevents adverse events related to delayed detection of cancer.
With Cloud Healthcare solutions, Northwell built an AI model to identify these patients so that oncologists can appropriately follow up with patients who have findings suspicious for lung cancer. The AI model detects incidental pulmonary nodules in radiology reports so that doctors can then contact the patients that need follow-up care. Nic says his team was able to build this system in a week: “Google Cloud did a lot of heavy-lifting for us and allowed us to get to the AI applications much faster. It allowed us to build a platform that just works.”
Healthcare systems can now rapidly generate healthcare insights with one end-to-end solution, Google Cloud Healthcare Data Engine. It builds on and extends the core capabilities of the Google Cloud Healthcare API to make healthcare data more immediately useful by enabling an interoperable, longitudinal record of patient data. Northwell Health uses Google Cloud as the core of their platform, enabling their developers to create solutions to the most pressing healthcare problems.
Special thanks to Kalyan Pamarthy, Product Management Lead on Cloud Healthcare and Natural Language APIs for contributing to this blog post.
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Video: How Pitney Bowes Leveraged Apigee to Create New Revenue Streams
Headquartered in Stamford, Connecticut, Pitney Bowes helps businesses navigate the complex world of commerce. They enable organizations to send parcels and packages across the globe. Pitney Bowes serves 90 percent of Fortune 500 companies, has 90 plus years of innovation, supports 1.5 million small businesses and has 15,000 employees globally.
The company leveraged the Apigee platform and was able to create a self-service model for both its internal and external customers. The monetization capability of Apigee empowered the organization to create new revenue streams.
“The monetization capability of Apigee has helped us create new revenue streams and business models for Pitney Bowes. Now we have tens and millions of dollars in revenue that we never had in 2016,” says Roger Pilc, Chief Innovation Officer, Pitney Bowes.
Watch the full video to get more insights on how Apigee helped Pitney Bowes boost its business.
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