Two Ad Agencies Leverage BigQuery to Support Next-gen Ad Campaigns

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Advertising agencies are faced with the challenge of providing the precision data that marketers require to make better decisions at a time when customers’ digital footprints are rapidly changing. They need to transform customer information and real-time data into actionable insights to inform clients what to execute to ensure the highest campaign performance.
In this post, we’ll explore how two of our advertising agency customers are turning to Google BigQuery to innovate, succeed, and meet the next generation of digital advertising head on.
Net Conversion eliminated legacy toil to reach new heights
Paid marketing and comprehensive analytics agency Net Conversion has made a name for itself with its relentless attitude and data-driven mindset. But like many agencies, Net Conversion felt limited by traditional data management and reporting practices.
A few years ago, Net Conversion was still using legacy data servers to mine and process data across the organization, and analysts relied heavily on Microsoft Excel spreadsheets to generate reports. The process was lengthy, fragmented, and slow—especially when spreadsheets exceeded the million-row limit.
To transform, Net Conversion built Conversionomics, a serverless platform that leverages BigQuery, Google Cloud’s enterprise data warehouse, to centralize all of its data and handle all of its data transformation and ETL processes. BigQuery was selected for its serverless architecture, high scalability, and integration with tools that analysts were already using daily, such as Google Ads, Google Analytics, and Data Hub. After moving to BigQuery, Net Conversion discovered surprising benefits that streamlined reporting processes beyond initial expectations. For instance, many analysts had started using Google Sheets for reports, and BigQuery’s native integration with Connected Sheets gave them the power to analyze billions of rows of data and generate visualizations right where they were already working.If you’re still sending Excel files that are larger than 1MB, you should explore Google Cloud.
Kenneth Eisinger
Manager of Paid Media Analytics at Net Conversion
Since modernizing their data analytics stack, Net Conversion has saved countless hours of time that can now be spent on taking insights to the next level. Plus, BigQuery’s advanced data analytics capabilities and robust integrations have opened up new roads to offer more dynamic insights that help clients better understand their audience.
For instance, Net Conversion recently helped a large grocery retailer launch a more targeted campaign that significantly increased downloads of their mobile application. The agency was able to better understand and predict their customers’ needs by analyzing buyer behavior across the website, mobile application, and their purchase history. Net Conversion analyzed website data in real-time with BigQuery, ran analytics on their mobile app data through the Firebase’s integration with BigQuery, and enriched these insights with sales information from the grocery retailer’s CRM to generate propensity behavior models that accurately predicted which customers would most likely install their mobile app.
WITHIN helped companies weather the COVID storm
WITHIN is a performance branding company, focused on helping brands maximize growth by fusing marketing and business goals together in a single funnel. During the COVID-19 health crisis, WITHIN became an innovator in the ad agency world by sharing real-time trends and insights with customers through its Marketing Pulse Dashboard. This dashboard was part of the company’s path to adopting BigQuery for data analytics transformation.
Prior to using BigQuery, WITHIN used a PostgreSQL database to house its data and manual reporting. Not only was the team responsible for managing and maintaining the server, which took focus away from the data analytics, but query latency issues often slowed them down.
BigQuery’s serverless architecture, blazing-fast compute, and rich ecosystem of integrations with other Google Cloud and partner solutions made it possible to rapidly query, automate reporting, and completely get rid of CSV files.
Using BigQuery, WITHIN is able to run Customer Lifetime Value (LTV) analytics and quickly share the insights with their clients in a collaborative Google Sheet. In order to improve the effectiveness of their campaigns across their marketing channels, WITHIN further segments the data into high and low LTV cohorts and shares the predictive insights with their clients for in-platform optimizations.
By distilling these types of LTV insights from BigQuery, WITHIN has been able to use those to empower their campaigns on Google Ads with a few notable success stories.
- WITHIN worked with a pet food company to analyze historical transactional data to model predicted LTV of new customers. They found significant differences between product category and autoship vs single order customers, and they implemented LTV-based optimization. As a result, they saw a 400% increase in average customer LTV.
- WITHIN helped a coffee brand increase their customer base by 560%, with the projected 12-month LTV of newly acquired customers jumping a staggering 1280%.
Through integration with Google AI Platform Notebooks, BigQuery also advanced WITHIN’s ability to use machine learning (ML) models. Today, the team can build and deploy models to predict dedicated campaign impact across channels without moving the data. The integration of clients’ LTV data through Google Ads has also impacted how WITHIN structures their clients’ accounts and how they make performance optimization decisions.
Now, WITHIN can capitalize on the entire data lifecycle: ingesting data from multiple sources into BigQuery, running data analytics, and empowering people with data by automatically visualizing data right in Google Data Studio or Google Sheets.A year ago, we delivered client reporting once a week. Now, it’s daily. Customers can view real-time campaign performance in Data Studio — all they have to do is refresh.
Evan Vaughan
Head of Data Science at WITHIN
Having a consistent nomenclature and being able to stitch together a unified code name has allowed WITHIN to scale their analytics. Today, WITHIN is able to create an internal Media Mix Modeling (MMM) tool with the help of Google Cloud that they’re trialing with their clients.
The overall unseen benefit of BigQuery was that it put WITHIN in a position to remain nimble and spot trends before other agencies when COVID-19 hit. This aggregated view of data allowed WITHIN to provide unique insights to serve their customers better and advise them on rapidly evolving conditions.
Ready to modernize your data analytics? Learn more about how Google BigQuery unlocks the insights hidden in your data.
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What is Google Cloud SQL?
Cloud SQL is a fully managed relational database for MySQL, PostgreSQL, and SQL Server.
It reduces maintenance cost and automates database provisioning, storage capacity management, replication, and backups. It offers quick setup, with standard connection drivers and built-in migration tools.
How Do You Set It Up?
Cloud SQL is easy to setup. You select the region and zone where you would like the instance to be, and it gets created there.
You also have a lot of configuration options, where you can select the machine type with the right number of CPU and amount of memory you need.
Choose storage each type between solid state and hard disk drives, depending on latency queries per second and cost requirements and set storage capacity.
Higher storage capacity leads to better performance.
What About Back Up?
Cloud SQL also offers automated backups and recovery options.
You can set time slots and locations for backups. For production applications, it is recommended to enable high availability, or HA.
By enabling this feature, the database instancewill automatically failover to another zone in your selected region in case of an outage.
You can also create cross-regional replicas to protect from regional failures.
In addition, you can enable automatic storage increase to add more storage when nearing capacity.
How Do You Migrate an Existing MySQL Database to Cloud SQL?
Cloud console makes it very easy by providing a migrate data button, which guides you through easy steps.
First, you provide your data source details, things like public IP address, port number,
and your replication credentials.
Second, you create a Cloud SQL read replica, just like we discussed in the creation process, using a SQL dump file.
Third, you sync the read replica with source. And, finally, you promote the read replica to primary instance with very low downtime.
Is Data Safe in Cloud SQL?
Like anything else in Google Cloud,the data in Cloud SQL is encrypted at rest and in transit.
External connections can be encrypted using SSL or Cloud SQL Proxy, which is a tool to help you connect to your Cloud SQL instance from your local machines.
You can use Cloud SQL as a relational database for your applications that are hosted within Google Cloud, like App Engine, Cloud Run, Compute Engine, Kubernetes Engine, or Cloud Functions.
You can also connect your Cloud SQL database with applications that are hosted outside of Google Cloud.
How Much Does It Cost and What Are Some Uses Cases?
Cloud SQL pricing varies depending on MySQL, PostgreSQL,or SQL Server.
Broadly speaking, though, it’s the combination of the type of instance, storage, or network you use. SQL Server also has some licensing costs.
Since Cloud SQL is a relational database, you can use it with any online transaction processing apps, such as order or payment processing apps, where you need to handle frequent queries with fast response times.
The Divercity Story: Using Google Cloud to Achieve a More Inclusive and Sustainable Workforce

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Despite a growing number of diversity, equity, and inclusion (DEI) initiatives, Black and Latinx people remain highly underrepresented in tech. Although comprising 12.6% and 18% of the U.S. labor force respectively, Black professionals hold only 5% of tech positions, while Latinx professionals fill just 6% of tech roles.
Long-standing biases in hiring practices and non-inclusive work environments are the primary contributors to this lack of diversity. Even when underrepresented professionals are successfully recruited, invisible barriers to promotion and layoffs that disproportionally impact Black and Latinx employees make it extremely challenging for tech firms to retain top talent.
We founded Divercity to help employers build diverse workforces that are more inclusive and sustainable. With our comprehensive recruiting and retention platform, tech companies can accurately measure employee diversity and gender parity, seamlessly connect with underrepresented talent, and significantly reduce turnover.
As Divercity continues to grow, we’ll introduce new services and solutions that empower the tech world to build inclusive companies while improving compliance with state and federal equal opportunity laws. We also hope to expand the reach of Divercity to support DEI initiatives in non-tech industries and bolster recruiting underrepresented professionals in other countries as well.

Scaling Divercity with the help of the Google for Startups Black Founders Fund
Shortly after founding Divercity, we participated in the 2021 Techstars Workforce Development Accelerator. The incredible support and guidance we received during and after the program highlighted the importance of long-term collaboration with reliable technology partners who actively champion diversity and inclusion.
That’s why we became part of the Google for Startups Cloud Program. After completing the program, we used Google Cloud credits and Google for Startups Black Founders Fund funding to cost-effectively trial, deploy, and scale key Google Cloud solutions. In just months, we rolled out new inclusion tracking and recruiting tools on the highly secure-by-design infrastructure of Google Cloud to expedite the sourcing and hiring of underrepresented talent in the tech industry.
With the support and mentorship of the Google for Startups Cloud Program and the Black Founders Fund, Divercity is well on its way to becoming one of the industry’s most trusted sites for DEI measurement, recruitment, and retention.
Delivering predictive diversity analyses with a 99% accuracy rate
We rely on the expansive Google Cloud ecosystem to power all the services offered on the Divercity platform. Specifically, we leverage Colab to write and execute the sophisticated TensorFlow machine learning (ML) models that deliver our predictive diversity analyses with a 99% accuracy rate.
We also use BigQuery to democratize insights and run analytics at scale with 27% lower three-year TCO than cloud data warehouse alternatives. BigQuery seamlessly integrates with Looker and Data Studio to display company diversity and recruitment data on interactive dashboards—and automatically populate reports with detailed demographic information.
We also accelerate the development, launch, and management of new Divercity tools with Firebase, while taking advantage of key features such as A/B testing and messaging campaigns to boost user engagement.
In the future, we plan to explore how Google Cloud AI and machine learning products such as Vertex AI and AutoML can further refine our diversity score analyses and applicant recruiting pipeline. We’ll also continue leveraging the many resources provided by the Google Black Founders Fund, including opportunities for technical project partnerships, early access to new Google Cloud products and tools, and collaboration with dedicated Google experts.
The Google for Startups Cloud Program and Google Black Founders Fund have been invaluable to our success. Since completing the Black Founders Accelerator program, we’ve been named a top 10 HR tech product by HR Tech Outlook, significantly increased our subscriber base, and received positive feedback from investors. We can’t wait to see what we accomplish next as we empower tech companies to build more diverse, inclusive, and sustainable workforces.

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.

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IDC recently examined the benefits of implementing BigQuery for SAP data. The findings reveal massive improvements to the SAP customers’ overall business results due to faster access to data insights, lower data warehouse operation cost, and increased productivity among the data warehouse and development teams. Download the report now!
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.
How Google Cloud Solutions Help Retail Firms to ABP(Always Be Pivoting)

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For years, retailers have been told that they must embrace a litany of new technologies, trends, and imperatives like online shopping, mobile apps, omnichannel, and digital transformation. In search of growth and stability, retailers adopted many of these, only to realize that for every box they ticked, there was another one waiting.
And then the pandemic hit, along with rising social movements and increasingly harsh weather. Some retailers were more prepared to take on these disruptions than others, which crystallized a new universal truth across the industry: the ability to adapt on the fly became the most important trait to survive and thrive.
Today’s retail landscape has surfaced both existing and new challenges for specialty and department store retailers. Approximately 88% of purchases previously occurred within a store environment. Now, it’s closer to 59%, with the remainder done online or through other omni methods.
With such constant change and upheaval, it can feel like the mantra now is ABP: always be pivoting.
The big question isn’t just how to maintain constant momentum and agility—it’s how to do it without sapping your workforce, your inventory, or your profits in the process. The pivot is now a given. What matters is how you do it.
Adapting requires a flexible base of technology that allows retailers to shift and scale seamlessly with the needs of the moment.
They need to be able to leverage real-time insights and enhance customer experiences rapidly, online and in the real world (not to mention the growing hybridization that’s AR and VR). They need to modernize their stores to power engaging consumer and associate experiences. They need to enhance operations for rapid scaling between full operations and digital-only offerings.
To help retailers achieve these goals and more, Google Cloud is honing a trio of essential innovations: demand forecasting that harnesses the power of data analytics and artificial intelligence; enhanced product discovery to improve conversion across channels; and the tools to help create the modern store experience.
In other words, here’s some of the biggest ways we’re ready to help you pivot.
Pivot point 1: Harnessing data and AI for demand forecasting with Vertex AI
One of the greatest challenges for retailers when building organizational flexibility is managing inventory and the supply chain.
We are in the midst of one of the worst global supply chain crises, stemming from soaring demand and logistics issues brought on by the pandemic. This crisis has only heightened the challenge retailers face when assessing demand and product availability. Even in normal times, mismanagement of inventory can add up to a trillion-dollar problem, according to IHL Group (costing $634 billion in lost sales worldwide each year, while overstocks result in $472 billion in lost revenues due to markdowns).
On the flipside, optimizing your supply chain can lead to greater profits. For instance, McKinsey predicts that a 10% to 20% improvement in retail supply chain forecasting accuracy is likely to produce a 5% reduction in inventory costs and a 2% to 3% increase in revenues.
Some of the challenges related to demand forecasting include:
- Low accuracy leads to excess inventory, missed sales, and pressure on fragile supply chains.
- Real drivers of product demand are not included, because large datasets are hard to model using traditional methods.
- Poor accuracy for new product launches and products that have sparse or intermittent demand.
- Complex models are hard to understand, leading to poor product allocation and low return on investment on promotions.
- Different departments use different methods, leading to miscommunication and costly reconciliation errors.
AI-based demand forecasting techniques can help. Vertex AI Forecast supports retailers in maintaining greater inventory flexibility by infusing machine learning into their existing systems. Machine learning and AI-based forecasting models like Vertex AI are able to digest large sets of disparate data, drive analytics and automatically adjust when provided with new information.
With these machine learning models, retailers can not only incorporate historical sales data, but also use close to real-time data such as marketing campaigns, web actions like a customer clicking the “add to cart” button on a website, local weather forecasts, and much more.
Pivot point 2: Enhanced product discovery through AI-powered search and recommendations
If customers can’t easily find what they are looking for, whether online or at the store, they will turn to someone else. That’s a simple statement, but one with profound impacts.
In research conducted by The Harris Poll and Google Cloud, we found that over a six month period, 95% of consumers received search results that were not relevant to what they were searching for on a retail website. And roughly 85% of consumers view a brand differently after an unsuccessful search, while 74% say they avoid websites where they’ve experienced search difficulties in the past.
Each year, retailers lose more than $300 billion dollars from search abandonment, or when a consumer searches for a product on a retailer’s website but does not find what they are looking for. Our product discovery solutions help you surface the right products, to the right customers, at the right time. These solutions include:
- Vision Product Search, which is like bringing the augmented reality of Google Lens to a retailer’s own branded mobile app experience. Both shoppers and retail store associates can search for products using an image they’ve photographed or found online and receive a ranked list of similar items.
- Recommendations AI, which enables retailers to deliver highly personalized recommendations at scale across channels.
- Retail Search, which provides Google-quality search results on a retailer’s own website and mobile applications.
All three are powered by Google Cloud, leveraging Google’s advanced understanding of user context and intent, utilizing technology to deliver a seamless experience to every shopper. With these combined capabilities, retailers are able to reduce search abandonment and improve conversions across their digital properties.
Pivot point 3: Building the modern store
Stores are no longer places for just browsing and buying. They must be flexible operation centers, ready to pivot to address changing circumstances. The modern store must be multiple things at once: a mini-fulfillment and return center, a recommendation engine, a shopping destination, a fun place to work, and more.
Just as retail companies had to embrace omnichannel, stores are now becoming omnichannel centers on their own, mixing the digital and physical into a single location. Retailers can use physical stores as a vehicle to deliver superior customer experiences. This will demand heightened levels of collaboration and cooperation between stores, digital, and tech infrastructure teams, building on the agile ways they have worked together.
In many ways, it’s about allowing our physical spaces to function more like digital ones. Google Cloud can help by bringing the scalability, security, and reliability of the cloud to the store, allowing physical locations to upgrade infrastructure and modernize their internal and customer-facing applications.
Think of it as when a new OS gets released for your phone. It’s the same small, hard box, but the experience can feel radically different. Now, extend that same idea to a digitally enabled store. With the right displays, interfaces, and tools at a given retail location, the team only needs to send an over-the-air update to create radically fresh experiences, ranging from sales displays to fulfillment or employee engagement.
Such an approach can enable streamlined experiences for both customers and store associates. For instance, when it comes to the modern store’s evolving role as a fulfillment or return center, cloud solutions can help drive efficiency in stores through automation of ordering, replenishment, and fulfillment of omnichannel order selection.
Similar tools for personalized product discovery online can be applied to customers in the store, helping them to browse and explore, or even create a tailored shopping experience.
The impact of store associates can be maximized by equipping them with technology to provide expertise that drives value-added customer service, as well as increasing productivity in stores by streamlining operations, thus lowering overhead cost. At the register, customers should be able to enjoy frictionless checkout while ensuring reliable, accurate, secure transactions.
Google Cloud can help retailers transform
The ability to adapt and pivot to meet today’s changing consumer needs requires that retailers rely on modern tools to obtain operational flexibility. We believe that every company can be a tech company. That every decision is data driven. That every store is physical and digital all at once. That every worker is a tech worker.
Google Cloud works with retailers to help them solve their most challenging problems. We have the unique ability to handle massive amounts of unstructured data, in addition to advanced capabilities in AI and ML. Our products and solutions help retailers focus on what’s most important—from improving operations to capturing digital and omnichannel revenue.
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