How Recommendation AI Helps Retailers Optimize Click-through and Conversion Rates

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Time to go outside again, I guess. I’ll need a sun hat. Sunscreen. Maybe some new sandals? What else?
With the Recommendations AI service, I might be reminded to grab a reusable water bottle and a swimsuit. Or some after-sun aloe lotion. Good thing, cause I’ll need it.

Recommendations AI is a solution that uses machine learning to bring product recommendations to their shoppers across any catalog or client list. This service is part of our full suite of Retail solutions. When you integrate with the Retail API, you get the benefit of Google’s Product Discovery. Integrating once to reap the benefits over and over. Recommendations is the starting point, and you can easily extend into Retail Search and Vision Product Search in the upcoming future.
The Recommendations solution is fully managed, global-scale and powered by deep learning, so you can focus on a great shopping experience and let someone else worry about the infrastructure.
Compared to baseline recommendation systems used by customers, Recommendations AI showed double digit uplift in conversion and clickthrough rates in A/B experiments controlled by the customers. You can optimize for click-through, conversion or session revenue, and fine tune the models to make sure you omit out-of-stock items or duplicates, for example.

So how does it work, and how do you get started? Read on, and we’ll walk you through the pipeline, starting with the data you already have to placement in your online store.
Formula: Data -> Model -> Placement
You start with your catalog, the list of all the things (postcards, movies, pie recipes) that you want to show your customers. Then you ingest your PII-redacted user events -this is the historic event data like home page views, add to cart events and more along with real time user events. This user event is joined with the product catalog and items that allows us to construct the sequence of shoppers’ activity, thus being able to predict what the shopper has a high propensity to purchase next. The user events can come from both online activity across devices or offline store purchases
The recommendation model will return a list of products, which are the recommendations. The brains of the operation, if you will. This model is trained using all the data that you ingest, using the latest neural network models and techniques that Google has built expertise over the years in flagship products like Youtube and News, that allows us to uncover shopper intent, so it can best predict the right recommendations to show to the right people.
Every model outputs a list of product identifiers, but where do they go? They go into placements, the spots, panels, carousels on your customer’s journey interacting with your brand that you’ve set aside to highlight recommendations. A model can send recommendations to one or more placements, but each placement only receives information from one recommendation model. Your pages will then need to render the products with the right images, text or other metadata, using the product ID that is returned by the model.
What do recommendations look like?
Let’s start by browsing our postcard-selling website, where I’ve been buying some vintage California postcards already. The recommendations algorithm has caught on to my interest, showing me other potential cards to purchase based on my history:

Put your data to work
To get started we need to bring your data into the recommendation model, so it can understand your customers, your inventory, and your sales patterns.
The model takes in the product catalog you use, and metadata about those products to better understand nuances in assortment, pricing and variables like size and style. You might already have this data stored in BigQuery or Merchant Center, and hence we provide easy integrations that you can leverage to get started even faster.
As for the user events, don’t worry if you already have systems in place to capture web and mobile activity. We make it easy to bring in your real time event logs by providing seamless integrations with Google Tag Manager, Javascript pixel, or even historic events from Cloud Storage, BigQuery or using inline API or JSON, so you can immediately train the models on this imported data. All this allows you to kickstart integrating with Recommendations AI in a matter of days.
The models then construct a sequence of activities that the user went through and joins with the products that the user engaged with. Once your data is ready to go, it takes a few days to train the model. Next onto making the data work for you.
Quickly customize your model
Setting up your own recommendations project in the console gives you the ability to choose what sort of model to train (based on what recommendations you want to generate) and your objective. Are you optimizing for click-through rate–more people click on the recommendation links or products–or for conversion rate–more people choose or buy what was suggested or revenue ?
Different models can be optimized for different optimization goals.; the GCP console explains what each one can do and how you can choose to optimize it.

Let’s unpack some of this terminology real quick.
We’ve got three model types:
- Recommended for you – Means we think these are items you’ll want to buy, based on your history; this is usually used on a home page to showcase items.
- Others you may like – Means if you’re browsing the page of a water bottle, we will recommend alternative brands of water bottles that you may like as well as a backpack, based on your engagement history.
- Frequently bought together – Means that when anyone buys sunscreen, we notice that they often also buy aloe lotion, so we will surface those items when someone adds any one of them to their cart.
And then we have three business objectives that the models optimize for:
- Click-through rate – How frequently did somebody click on a recommended item?
- Conversion rate– How frequently did somebody add a recommended item to their cart?
- Revenue per session – How much money did the recommendations generate for you?
Deliver anywhere along the journey
Now that you’re all set up in the Retail AI console, you can test out the recommendations in the console, even before you deploy to production.

You can integrate Recommendations into your frontend by calling the Predict APIt. The placements of recommendations will report data back into the dashboard and you can analyze and measure success for future iterations.
On top of that you can use the recommendations for other parts of your customer’s journey. Email promotions, storefront kiosks, display ads or follow-up notifications can include recommendations based on past activity and cart contents. The model gives you useful product recommendations for a wide variety of touchpoints and steps in the purchasing process.
More best practices, and guides, are available inside our documentation.
How to get started
Training your own models can be tedious, time-consuming, and expensive. On top of that it requires deeper data science expertise to set up. Let us do it instead!
You can see how IKEA Retail uses Recommendations AI in this recent talk and blog from the Google Cloud Retail Summit..
To get started today you’ll need to make a Cloud project and enable the Retail API, which then allows you to access all the recommendation tools in one menu. Bring in your catalog and purchasing data, define a placement or two, and you can start putting recommendations on your site in a matter of days.
Cart.com to Transform e-Commerce for Brands Globally

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The ecommerce playing field has been hard to navigate for most retailers, and Cart.com is on a mission to change that. Traditionally, retailers needing to run their online store, order fulfillment, customer service, marketing, and other essential activities have had to cobble together systems to get the capabilities they need – much less having access to analytics across these functions. The result is costly, siloed ecommerce operations that are difficult to manage and scale.
It’s clearly not a formula for success, yet that’s the reality facing most retailers. Cart.com, in contrast, has set out to democratize ecommerce by giving brands of all sizes the full capabilities they need to take on the world’s largest online retailers. Our end-to-end environment empowers retailers to keep more of their revenue, set up proven strategies for managing all aspects of their business, and act on valuable insights from customer data every step of the way.
Together with our talented team, we’re building a unified ecommerce platform that already provides value to many leading or up and coming brands including Whataburger, GUESS, Dr. Scholl’s, Rowing Blazers, and Howler Bros.
We’re excited about the opportunity ahead as we reimagine traditional approaches to online sales, fulfillment, marketing, accessing growth capital, providing a unified view of all ecommerce and marketing analytics, and other activities. Expectations for Cart.com are high, and we are building a company that can scale to $100B in revenue and beyond. Supported by the Startup Program by Google Cloud and Google Cloud solutions, we’re establishing a technology platform to transform all aspects of ecommerce for brands worldwide.
Partner in disruption
At Cart.com, we’re currently targeting an underserved market. Our ideal customer is beyond demonstrating product-market-fit and is now at an inflection point seeking a growth opportunity. Typically, those companies are generating between $1M and $100M in annual revenue. We’ve seen an enthusiastic response from brands and retailers as well as investors, with backing from investors in just over a year totaling $143 million in three funding rounds.
Our strategy is to build an integrated ecommerce model that combines best-of-breed solutions, many of which we gain through acquisitions and then build upon to provide a streamlined and fully integrated experience for our brands. We’ve made seven acquisitions so far to round out our online store, order fulfillment, marketing services, customer service, and we have launched some integral partnerships including easy access to growth capital through our relationship with Clearco and product protection for customers on every purchase with Extend. Instead of acquiring a data company, we’re building our data platform on Google Cloud, across each operating function for a single-view for brands to harness actionable data. We see Google Cloud as the leader for data management, analytics, machine learning (ML) and artificial intelligence (AI).
Other reasons why we’re building our business on Google Cloud include scalability, excellence, security, reach, and data analytics that are far superior to other environments.
We also feel a cultural and mission alignment with Google Cloud and envision leaning into a long-term partnership of marketing, selling, and disrupting the disruptors together. Equally important to us are the investments Google Cloud is willing to make in early-stage companies like ours. The support through the Google Cloud for Startups program has been outstanding.
Built on Google Cloud
A wide range of Google Cloud solutions provide the foundation for our platform. For instance, Cloud Pub/Sub keeps our services communicating with one another. We rely on fully managed relational databases, like Cloud SQL and Cloud Spanner, to securely handle the huge volume of brand and shopper data generated every day.
Cloud Run allowed us to develop inside of containers before our Kubernetes infrastructure was ready to go. Now, we are taking advantage of all the capabilities in Google Kubernetes Engine. BigQuery integrates with all Google Cloud solutions and offers true data streaming natively out of the box, along with Dataflow for advanced analytics. We also use Container Registry to store and manage our Docker container images. Right now, we’re testing Cloud Composer to evaluate using it for data workflow orchestration instead of Apache Airflow.
The openness of the Google Cloud environment is further enabled by Anthos, which we may deploy soon to perform data integrations quickly as we acquire more companies over the next year. For example, if we acquire a company using Azure, we can easily align it with our Google Cloud ecosystem.
Enabling ecommerce 2.0
Recently, our team has been experimenting with Google Cloud Vertex AI and the fully managed services of AI deployment and ML operations. The capabilities would save us substantial time in the management of the ML lifecycle which allows us to focus more on developing proprietary AI that will transform commerce at scale.
Because Google Cloud is so far ahead in data science, our teams benefit from deep Google Cloud expertise as we look to provide brands with unmatched insights into customers to improve services and revenue. We’re also planning to test Recommendations AI among other tools to deploy customer product recommendations and personalization as turnkey productized offerings. Moving forward, we will likely use Bigtable to aid in serving machine learning to hundreds of thousands of brands due to its low latency and scalability.
Fanatical about brand success
We know that our work with Google Cloud for Startups and use of Google Cloud solutions for best-in-class data management, analytics, ML, and AI will enable us to offer even more transformative services to brands.
We also see the opportunity to use our platform and customer insights to break down barriers between brands, enabling retailers to share information and work better together when it’s in their best interests. What we’re building today on Google Cloud is fundamentally changing what’s possible for retailers of any size everywhere.
As a startup, when recruiting talent or working with prospective customers, it helps to share our success with Google Cloud. We view them as an extension of the Cart.com team. It also validates our business as we continue building a more integrated, holistic approach to commerce that opens new opportunities and drives growth for brands worldwide.
For more details about Cart.com’s vision for unified ecommerce, check out our video.
If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.
Reactive Programming on Google Maps Platform: Watch Video to Learn

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The Google Maps Platform Android SDK supports extensions for reactive programming, which helps you write code to handle asynchronous operations.
Write reactive and responsive mapping applications with Google Maps Platform
In mobile apps, asynchronous events can happen at any point in time: user touch events, waiting for network calls to complete, or receiving push notifications, to name a few. As an app developer, accounting for these events and composing them with other asynchronous events can be challenging. Reactive programming is an alternative to passing callbacks for different events and helps simplify the process of working with asynchronous events. In reactive programming, events are modeled as a stream, emitting items over time.
https://youtube.com/watch?v=1TmJvOZfBVQ%3Fenablejsapi%3D1%26
There are two libraries you can use to write reactive code: Kotlin Flows and RxJava. The next two videos show you how to use each one.
Writing reactive and responsive mapping applications using Kotlin
If you’re a Kotlin developer looking to use Coroutines and Flows, the KTX library allows you to use Kotlin Flows to receive events. The Maps KTX library includes extension functions that return Kotlin Flow objects, so you can listen to events in a reactive manner. Unlike suspending functions, which return a single value, Kotlin Flows can return several values over time. For example, you can use a Flow to receive camera event changes over time. To get started using Kotlin Flows in your app, include the Maps KTX library in the dependencies section in your build.gradle file.
https://youtube.com/watch?v=Cotx1ZmEYg8%3Fenablejsapi%3D1%26
Creating reactive maps on Android with RxJava
Integrate Google Maps Platform SDKs with popular Android library RxJava. RxJava is the Java implementation of Reactive Extensions, which is a library for composing asynchronous and event-based programs using observable sequences. One thing RxJava does is allows you to convert callback-based asynchronous code into a chain of transformations. Learn how this works and the other ways you can use RxJava in the third video in this series.
https://youtube.com/watch?v=AgGE7fAMrdA%3Fenablejsapi%3D1%26
We hope you learn more about reactive programming concepts to help you build responsive and reactive mobile apps in this three-part YouTube series. Have ideas for helpful videos you’d like to see on our channel? Leave a comment on any of our videos. And don’t forget to subscribe to our YouTube channel for the latest updates, tutorials, customer stories, and more.
For more information on Google Maps Platform, visit our website.
How Google Meet Keeps Your Video Conferences Secure

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All over the world, businesses, schools and users depend on G Suite to help them stay connected and get work done. Google designs, builds, and operates our products on a secure foundation, aimed at thwarting attacks and providing the protections needed to keep you safe. G Suite and Google Meet are no exception.
Google Meet’s security controls are turned on by default, so that in most cases, organizations and users won’t have to do a thing to ensure the right protections are in place. Here, we’ll summarize the key capabilities of Google Meet that help protect you.
Proactive protections to combat abuse and block hijacking attempts
Google Meet employs an array of counter-abuse protections to keep your meetings safe. These include anti-hijacking measures for both web meetings and dial-ins.
Google Meet makes it difficult to programatically brute force meeting IDs (this is when a malicious individual attempts to guess the ID of a meeting and make an unauthorized attempt to join it) by using codes that are 10 characters long, with 25 characters in the set. We limit the ability of external participants to join a meeting more than 15 minutes in advance, reducing the window in which a brute force attack can even be attempted. External participants cannot join meetings unless they’re on the calendar invite or have been invited by in-domain participants. Otherwise, they must request to join the meeting, and their request must be accepted by a member of the host organization.
In addition, we’re rolling out several features to help schools keep meetings safe and improve the remote learning experiences for teachers and students, including:
- Only meeting creators and calendar owners can mute or remove other participants. This ensures that instructors can’t be removed or muted by student participants.
- Only meeting creators and calendar owners can approve requests to join made by external participants. This means that students can’t allow external participants to join via video, and that external participants can’t join before the instructor.
- Meeting participants can’t rejoin nicknamed meetings once the final participant has left. This means if the instructor is the last person to leave a nicknamed meeting, students can’t join later without the instructor present.

Secure deployment and access controls for admins and end-users
To limit the attack surface and eliminate the need to push out frequent security patches, Google Meet works entirely in your browser. This means we do not require or ask for any plugins or software to be installed if you use Chrome, Firefox, Safari, or Microsoft Edge. On mobile, we recommend that you install the Google Meet app.
To help ensure that only authorized users administer and access Meet services, we support multiple 2-Step Verification options for accounts that are secure and convenient. These include hardware and phone-based security keys and Google prompt. Additionally, Google Meet users can enroll their account in our Advanced Protection Program (APP), which provides our strongest protections available against phishing and account hijacking and is specifically designed for the highest-risk accounts.
For G Suite Enterprise and G Suite for Education customers, we offer Access Transparency, which logs any Google access to Google Meet recordings stored in Drive, along with the reason for the access (support team actions that you might have requested, for example). Customers can also use data regions functionality to store select/covered data of Google Meet recordings in specific regions (i.e. US or Europe).
Secure, compliant, and reliable meeting infrastructure
In Google Meet, all data is encrypted in transit by default between the client and Google for video meetings on a web browser, on the Android and iOS apps, and in meeting rooms with Google meeting room hardware. Meet adheres to IETF security standards for Datagram Transport Layer Security (DTLS) and Secure Real-time Transport Protocol (SRTP). For every person and for every meeting, Meet generates a unique encryption key, which only lives as long as the meeting, is never stored to disk, and is transmitted in an encrypted and secured RPC (remote procedure call) during the meeting setup.
Security is an integral part of all our operations at Google. Our team of full-time security and privacy professionals supports our software engineering and operations to ensure that security is always a part of how we build and run our services. All of our Google Cloud and G Suite customers benefit from these capabilities, including:
- Secure-by-design infrastructure: Google Meet benefits from Google Cloud’s defense-in-depth approach to security, which utilizes the built-in protections and global-private network that Google uses to secure your information and safeguard your privacy.
- Compliance certifications: Our Google Cloud products, including Google Meet, regularly undergo independent verification of their security, privacy, and compliance controls, including validation against standards such as SOC, ISO/IEC 27001/17/18, HITRUST, and FedRAMP. We support your compliance requirements around regulations such as GDPR and HIPAA, as well as COPPA and FERPA for education.
- Incident management: We have a rigorous process for managing data and security incidents that specifies actions, escalations, mitigation, resolution, and notification of any potential incidents impacting customer data.
- Reliability: Google’s network is engineered to accommodate peak demand and handle future growth. Our network is resilient and engineered to accommodate the increased activity we’ve seen on Google Meet.
- Transparency: At Google Cloud, we’re clear about our commitments regarding customer data: we process customer data according to your instructions; we never use customer data for advertising purposes; and we publish the locations of our Google data centers, which are highly available, resilient, and secure.
During COVID-19 and beyond, we will continue to protect Google Meet users and their data, and keep innovating with new features to make our tools helpful, secure, and safe.
How Did DTDC Express Speed Up Decision-making and Collaboration by 10x—While Cutting Costs?

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Among Indian courier and logistics businesses, DTDC has expanded rapidly since its foundation in 1990. Starting with seed capital of less than US$2,000, DTDC has grown to a US$175 million business with operations across the country and internationally.
The business is second only to the government-owned India Post in the courier and logistics sector with 522 offices, more than 10,700 franchisees, and a 5,000 employee-strong workforce.
It handles 450,000 shipments—primarily small to medium parcels—per day, has a direct presence in 12 countries, a presence through associates in 22 countries, and operates 16 gateway hubs.
DTDC’s mission is to become India’s preferred express parcel provider with a focus on the consumer and the company aims to be valued at INR 5,000 crore (about US$778 million) by 2020.
However, like all businesses in the courier and logistics sector, DTDC is facing greater competition. Most of the large ecommerce businesses in the country have created their own express delivery arms and these are contributing to heightened customer expectations.
“Businesses and consumers want information and answers now rather than later today or tomorrow,” Mrinal Chakraborty, Executive Vice President, Technology and Innovation, DTDC, says.
“For example, customers are looking for direct API integration between their systems and our tracking tools, rather than a mundane, old-style MIS-driven approach.
“The express delivery businesses themselves are eager to embrace trends such as increased predictability of delivery, greater capacity utilization, and how vehicles can be run in the most efficient way possible.”
External-facing Technology Policies
DTDC had operated a traditional technology operation including in-house infrastructure located in a mid-sized data centre at its Bangalore headquarters. This in-house data centre housed a completely virtualised server-storage environment and connected to all 522 offices by MPLS link or internet-based VPN services. The business also operated a small disaster recovery facility in another city in India.
However, DTDC realised its technology operation could not deliver the agility, flexibility, and performance needed for the business to thrive in a highly disrupted industry.
Its technology leaders started reviewing their options and in early 2017 adopted a policy that embraced external models such as public cloud services. The business moved its SAP HANA relational database management into the cloud and now is considering using Google Cloud Platform to host its core enterprise resource planning system.
Google Cloud Platform also gives DTDC the ability to analyse data in order to improve the efficiency and predictability of its services.
An Opportunity for Change
While the business had implemented cloud-based office productivity applications in 2016, these applications were not meeting its needs, Chakraborty says.
“What we observed after three years, despite a considerable cost, these applications were only being used for email rather than as a full suite of collaboration tools,” he says.
“For example, if a simple presentation file needed to be delivered for decision-making, it had to be sent to about 20 stakeholders,” he adds. “We would then have to collect feedback from each and aggregate it into a final draft. This approach compromised productivity and decision-making, and meant multiple versions of data were circulating within the organisation.”
DTDC also wanted to extend mobility from a small group within the business to the wider organisation as part of a broader project to improve collaboration, productivity, and decision-making. In addition, the business intended to improve the usability and relevance of its intranets to its employees.
Furthermore, Chakraborty and his team planned to help improve collaboration within and the performance of DTDC’s more than 10,700 franchisees in responding to customer needs.
G Suite Targeted to Increase Collaboration
Based on his previous experience with G Suite, Chakraborty recommended the cloud-based suite of intelligent applications to DTDC’s senior management team. He also provided a comprehensive cost-effort-benefit analysis to back up his recommendation.
DTDC had started with a three-week proof of concept exercise spanning 20 users across the business. Having determined that G Suite met its business requirements, the courier and logistics provider had chosen a ‘big bang’ implementation across about 5,000 users.
DTDC switched over to G Suite on 23 June 2017 and undertook an extensive user acceptance and training program—called Project Liberty—over the following two weeks with the assistance of a 24-hours-per-day, seven-days-per-week helpdesk.
“We made hundreds of calls to our employees to explain the move, created and distributed an FAQ, and provided extensive training at regional office and branch office levels,” Chakraborty says. The business also displayed posters and banners at all DTDC offices, sent teaser messages to users, and provided daily G Suite usage tips over a three-week period.
“We completed that part of the move in about six days and by 1 July 2017 we had migrated all databases and all old emails to G Suite. Two weeks later, we had signed off the job,” Chakraborty says.
Considerable Cost Savings
DTDC has reaped several rewards from its move to G Suite. The amount the business spends on video conferencing has fallen from about US$5,000 per month to nearly zero as it takes advantage of the voice and video capabilities of Google Hangouts Meet.
“Largely because the volume of email attachments has fallen dramatically since we moved to Gmail—despite the fact our business has grown significantly—we have not had to upgrade any of our links over the last year or so,” Chakraborty says.
“Team members are increasingly sending links through Google Drive instead.” The ability to store files in the cloud through Google Drive has also enabled DTDC to eliminate the need to perform local backups of users’ files.
Meanwhile, team members are also increasingly using Google Calendar to make appointments and check the availability of colleagues and superiors for meetings.
Supporting Mobilisation with G Suite
Deploying G Suite has also enabled DTDC to increase the number of workers with access to email on their mobile devices from 150 users to more than 4,000 users.
“At our National Franchisee Meeting in Delhi in February 2018, our Chairman explicitly explained in an open forum how significantly his performance had improved since we deployed G Suite and implemented mobility,” Chakraborty says.
With sharing of spreadsheets and documents rising through the use of Google Sheets and Google Docs respectively, DTDC’s employees are collaborating more effectively and making decisions faster and more easily. Several departments within the business are using Google Sites to create intranets to host commonly-accessed documents and provide knowledge bases, including FAQ documents to help employees solve problems themselves.
“Thanks to G Suite, we have experienced a 10-fold increase in the speed of collaboration, decision-making, and supporting systems,” Chakraborty says. “The activities of our management team are more transparent and cohesive while as an organisation we are making decisions in hours and minutes rather than days.”
DTDC has also completed the migration of more than 10,700 franchisees across to G Suite. “Thus DTDC has become one of the few organisations where its Chairman and Managing Director and a small franchisee in a town in India would use the same intelligent applications,” Chakraborty says. “This makes the organisation much flatter, more collaborative operation in nature.
“Furthermore, franchisees who are using G Suite have started telling us that the ease of collaboration and access to information is enabling them to resolve customer queries faster and more effectively.”
Delivering a Bright Future with Google
DTDC plans to continue developing its intranets on Google Sites and encourage further use of Google Docs and Sheets.
“We are continuing to go back to our internal teams to highlight the benefits of these products and drive takeup to create more awareness and enthusiasm,” says Chakraborty.
DTDC has also started evaluating Google’s big data and analytics platform for its internal MIS and dashboard practices. “More broadly, we see Google as key to our ability to realise our business objectives and remain competitive in the dynamic, fast-changing courier and logistics industry,” Chakraborty concludes
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Are You Suffering from Spreadsheet Paralysis?
Today, within the four walls of your office there’s just one concern everyone has: What do the numbers say?
The answer to that question almost always rests with you. If they get it wrong, everybody gets it wrong. But does it have to be so hard to get it right?
Wading in the waters of endless spreadsheets, trying to figure formulas to slice data in every possible permutation and combination, and still keeping your sanity is a herculean task.
That’s probably why today’s business leaders are most likely suffering from what’s being termed as spreadsheet paralysis. The symptoms include confusion, anxiety and a desire to throw away your computer in the garbage.
It doesn’t have to be that bad. With Explore in Google Sheets,
Watch this video to find out how.
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